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Szeto K, Arnold J, Maher C. The Wearable Activity Tracker Checklist for Healthcare (WATCH): a 12-point guide for the implementation of wearable activity trackers in healthcare. Int J Behav Nutr Phys Act 2024; 21:30. [PMID: 38481238 PMCID: PMC10938760 DOI: 10.1186/s12966-024-01567-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/27/2024] [Indexed: 03/17/2024] Open
Abstract
Increasing physical activity in patients offers dual benefits, fostering improved patient health and recovery, while also bolstering healthcare system efficiency by minimizing costs related to extended hospital stays, complications, and readmissions. Wearable activity trackers offer valuable opportunities to enhance physical activity across various healthcare settings and among different patient groups. However, their integration into healthcare faces multiple implementation challenges related to the devices themselves, patients, clinicians, and systemic factors. This article presents the Wearable Activity Tracker Checklist for Healthcare (WATCH), which was recently developed through an international Delphi study. The WATCH provides a comprehensive framework for implementation and evaluation of wearable activity trackers in healthcare. It covers the purpose and setting for usage; patient, provider, and support personnel roles; selection of relevant metrics; device specifications; procedural steps for issuance and maintenance; data management; timelines; necessary adaptations for specific scenarios; and essential resources (such as education and training) for effective implementation. The WATCH is designed to support the implementation of wearable activity trackers across a wide range of healthcare populations and settings, and in those with varied levels of experience. The overarching goal is to support broader, sustained, and systematic use of wearable activity trackers in healthcare, therefore fostering enhanced physical activity promotion and improved patient outcomes.
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Affiliation(s)
- Kimberley Szeto
- Alliance for Research in Exercise Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, North Terrace, GPO Box 2471, 5001, Adelaide, SA, Australia
| | - John Arnold
- Alliance for Research in Exercise Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, North Terrace, GPO Box 2471, 5001, Adelaide, SA, Australia
| | - Carol Maher
- Alliance for Research in Exercise Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, North Terrace, GPO Box 2471, 5001, Adelaide, SA, Australia.
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Ferguson T, Curtis R, Fraysse F, Olds T, Dumuid D, Brown W, Esterman A, Maher C. The Annual Rhythms in Sleep, Sedentary Behavior, and Physical Activity of Australian Adults: A Prospective Cohort Study. Ann Behav Med 2024; 58:286-295. [PMID: 38394346 DOI: 10.1093/abm/kaae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Sleep, sedentary behavior, and physical activity have fundamental impacts on health and well-being. Little is known about how these behaviors vary across the year. PURPOSE To investigate how movement-related behaviors change across days of the week and seasons, and describe movement patterns across a full year and around specific temporal events. METHODS This cohort study included 368 adults (mean age = 40.2 years [SD = 5.9]) who wore Fitbit activity trackers for 12 months to collect minute-by-minute data on sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data were analyzed descriptively, as well as through multilevel mixed-effects linear regression to explore associations with specific temporal cycles (day-of-the-week, season) and events. RESULTS Movement patterns varied significantly by day-of-the-week and season, as well as during annual events like Christmas-New Year and daylight saving time (DST) transitions. For example, sleep was longer on weekends (+32 min/day), during autumn and winter relative to summer (+4 and +11 min/day), and over Christmas-New Year (+24 min/day). Sedentary behavior was longer on weekdays, during winter, after Christmas-New Year, and after DST ended (+45, +7, +12, and +8 min/day, respectively). LPA was shorter in autumn, winter, and during and after Christmas-New Year (-6, -15, -17, and -31 min/day, respectively). Finally, there was less MVPA on weekdays and during winter (-5 min/day and -2 min/day, respectively). CONCLUSIONS Across the year, there were notable variations in movement behaviors. Identifying high-risk periods for unfavorable behavior changes may inform time-targeted interventions and health messaging.
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Affiliation(s)
- Ty Ferguson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, Frome Road, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Rachel Curtis
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, Frome Road, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - François Fraysse
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, Frome Road, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Timothy Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, Frome Road, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, Frome Road, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Wendy Brown
- School of Human Movement and Nutrition Sciences, University of Queensland, Brisbane, Queensland 4072, Australia
| | - Adrian Esterman
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, Frome Road, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, Frome Road, GPO Box 2471, Adelaide, SA, 5001, Australia
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Maher C, Singh B. Editorial: Insights in digital health communication: 2023. Front Digit Health 2024; 6:1368666. [PMID: 38495378 PMCID: PMC10940536 DOI: 10.3389/fdgth.2024.1368666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 02/20/2024] [Indexed: 03/19/2024] Open
Affiliation(s)
| | - Ben Singh
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
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Matricciani L, Dumuid D, Stanford T, Maher C, Bennett P, Bobrovskaya L, Murphy A, Olds T. Time use and dimensions of healthy sleep: A cross-sectional study of Australian children and adults. Sleep Health 2024:S2352-7218(23)00250-4. [PMID: 38199899 DOI: 10.1016/j.sleh.2023.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 09/12/2023] [Accepted: 10/24/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Sleep is increasingly recognized as a multidimensional construct that occurs within the 24-hour day. Despite advances in our understanding, studies continue to consider the relationship between sleep, sedentary time and physical activity separately, and not as part of the 24-hour day. AIMS To determine the association between the 24-hour activity composition and dimensions of healthy sleep. METHODS This study examined data on 1168 children (mean age 12years; 49% female) and 1360 adults (mean age 44years; 87% female) collected as part of the Child Health CheckPoint study. Participants were asked to wear a GENEActiv monitor (Activinsights, Cambs, UK) on their nondominant wrist for eight consecutive days to measure 24-hour time-use. Compositional data analysis was used to examine the association between time use (actigraphy-derived sleep duration, sedentary time, light physical activity and moderate-vigorous physical activity) and dimensions of healthy sleep. Healthy sleep was conceptualized in terms of continuity/efficiency, timing, alertness/sleepiness, satisfaction/quality, and regularity. Time allocations were also examined. RESULTS The 24-hour activity composition was significantly associated with all objectively measured and self-report dimensions of healthy sleep in both children and adults. Allocating more time to sleep was associated with earlier sleep onsets, later sleep offsets, less efficient and more consistent sleep patterns for both children and adults. CONCLUSION This study highlights the integral relationship between daily activities and dimensions of sleep. Considering sleep within the 24-hour day activity composition framework may help inform lifestyle decisions to improve sleep health.
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Affiliation(s)
- Lisa Matricciani
- Clinical & Health Sciences, University of South Australia, Adelaide, South Australia, Australia; Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Rosemary Bryant AO Research Centre, University of South Australia, Adelaide, South Australia, Australia.
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Allied Health and Human Performance (AHHP), University of South Australia, Adelaide, South Australia, Australia; Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Ty Stanford
- Clinical & Health Sciences, University of South Australia, Adelaide, South Australia, Australia; Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Allied Health and Human Performance (AHHP), University of South Australia, Adelaide, South Australia, Australia
| | - Paul Bennett
- School of Nursing and Midwifery, Griffith Health, Griffith University, Brisbane, Queensland, Australia
| | - Larisa Bobrovskaya
- Health and Biomedical Innovation, Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Andrew Murphy
- Allied Health and Human Performance (AHHP), University of South Australia, Adelaide, South Australia, Australia
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Allied Health and Human Performance (AHHP), University of South Australia, Adelaide, South Australia, Australia; Murdoch Children's Research Institute, Parkville, Victoria, Australia
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Olds T, Singh B, Miatke A, Eglitis E, Maher C, Dumuid D. The Association Between Socioeconomic Status and Use of Time in Australian Children and Adolescents. J Adolesc Health 2023; 73:1068-1076. [PMID: 37665307 DOI: 10.1016/j.jadohealth.2023.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 06/26/2023] [Accepted: 07/03/2023] [Indexed: 09/05/2023]
Abstract
PURPOSE There are well-known socioeconomic status (SES) gradients in children and adolescents' health which may be associated with time use. Our aim was to evaluate the association between Australian children's 24-hour time use and SES using four separate surveys from 2005 to 2021. METHODS Time use was assessed in 4526 8-19-year-olds from the 2005 Health of Young Victorians, 2007 National Children's Nutrition and Physical Activity, 2015 Child Health CheckPoint, and 2019-21 Life on Holidays study. Each survey used the same reliable, valid, 24-hour recall instrument. SES was quantified using tertiles of household income, education, and postcode-level measures. Compositional data analysis was used to compare 24-hour time use between SES categories, adjusting for age, sex, and puberty. RESULTS Time-use compositions differed significantly by SES in each survey. Relative to the lowest SES, children from the highest SES accumulated on average 31 min/day more School-related time, 6 min/day more Passive Transport and 6 min/day more Self-care. Conversely, they accumulated 30 min/day less Screen Time (which included computer time), 11 min/day less sleep, and spent 7 min/day less in Domestic/Social activities. There were only small differences in Quiet Time and Physical Activity. DISCUSSION SES-related differences in time use were robust across ages 8-19, a 16-year timespan, diverse Australian geographical regions, and using different SES metrics. The exchange of about 30 min/day between School-related activities and Screen Time amounts to >180 hours extra exposure to School-related activities annually in the highest SES category relative to the lowest, equivalent to >6 weeks of school time per year.
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Affiliation(s)
- Timothy Olds
- Allied Health & Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Centre for Adolescent Health, Murdoch Children's Research Centre, Royal Children's Hospital, Parkville, Melbourne, Victoria, Australia
| | - Ben Singh
- Allied Health & Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia.
| | - Aaron Miatke
- Allied Health & Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Centre for Adolescent Health, Murdoch Children's Research Centre, Royal Children's Hospital, Parkville, Melbourne, Victoria, Australia
| | - Emily Eglitis
- Allied Health & Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Carol Maher
- Allied Health & Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Dorothea Dumuid
- Allied Health & Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Centre for Adolescent Health, Murdoch Children's Research Centre, Royal Children's Hospital, Parkville, Melbourne, Victoria, Australia
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Olds T, Dumuid D, Eglitis E, Golley R, Fraysse F, Miatke A, Tomkinson GR, Watson A, Munzberg M, Maher C. Changes in fitness and fatness in Australian schoolchildren during the summer holidays: fitness lost, fatness regained? A cohort study. BMC Public Health 2023; 23:2094. [PMID: 37880621 PMCID: PMC10601165 DOI: 10.1186/s12889-023-17009-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 10/17/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND Emerging evidence suggests that children's fatness increases and fitness declines at a greater rate during the summer holiday period, compared with the school year. The aim of this study was to compare rates of change in fitness and fatness over the in-term and summer holiday periods among Australian schoolchildren. A secondary aim was to explore whether rates of change differed according to the child's sex, socio-economic status (SES), pubertal status and weight status. METHODS Children (n = 381) initially in Grade 4 (age 9) were recruited for this 2-year longitudinal study. Fatness (% body fat, BMI z-score, waist-to-height ratio) and fitness (20-m shuttle run and standing broad jump) were measured at the start and end of two consecutive years. Rates of change were calculated for the two in-school periods (Grades 4 and 5) and for the summer holiday period. Rates of change in fatness and fitness between in-school and holiday periods were compared, and differences in rates of change according to sex, socio-economic status, and weight status were explored. RESULTS During the holidays, percentage body fat increased at a greater rate (annualised rate of change [RoC]: +3.9 vs. Grade 4 and + 4.7 vs. Grade 5), and aerobic fitness declined at a greater rate (RoC - 4.7 vs. Grade 4 and - 4.4 vs. Grade 5), than during the in-school periods. There were no differences in rates of change for BMI z-score, waist-to-height ratio or standing broad jump. Body fatness increased faster in the holidays (relative to the in-school period) in children who are overweight and from low-SES families. Aerobic fitness declined more rapidly in the holidays in children who are overweight. CONCLUSION This study highlights that during the summer holiday period, children experience greater increases in fatness and declines in fitness, with children who live with low-SES families and are overweight being more affected. The findings suggest the need for targeted interventions during this period to address these negative health trends. TRIAL REGISTRATION Australia New Zealand Clinical Trials Registry, identifier ACTRN12618002008202. Retrospectively registered on 14 December 2018.
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Affiliation(s)
- Tim Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
- Murdoch Children's Research Institute, Parkville, 3052, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
- Murdoch Children's Research Institute, Parkville, 3052, Australia
| | - Emily Eglitis
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
| | - Rebecca Golley
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Bedford Park, 5042, Australia
| | - François Fraysse
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
| | - Aaron Miatke
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
- Murdoch Children's Research Institute, Parkville, 3052, Australia
| | - Grant R Tomkinson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
| | - Amanda Watson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
| | - Mason Munzberg
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, 5000, Australia.
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Miatke A, Olds T, Maher C, Fraysse F, Mellow ML, Smith AE, Pedisic Z, Grgic J, Dumuid D. The association between reallocations of time and health using compositional data analysis: a systematic scoping review with an interactive data exploration interface. Int J Behav Nutr Phys Act 2023; 20:127. [PMID: 37858243 PMCID: PMC10588100 DOI: 10.1186/s12966-023-01526-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/02/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND How time is allocated influences health. However, any increase in time allocated to one behaviour must be offset by a decrease in others. Recently, studies have used compositional data analysis (CoDA) to estimate the associations with health when reallocating time between different behaviours. The aim of this scoping review was to provide an overview of studies that have used CoDA to model how reallocating time between different time-use components is associated with health. METHODS A systematic search of four electronic databases (MEDLINE, Embase, Scopus, SPORTDiscus) was conducted in October 2022. Studies were eligible if they used CoDA to examine the associations of time reallocations and health. Reallocations were considered between movement behaviours (sedentary behaviour (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA)) or various activities of daily living (screen time, work, household chores etc.). The review considered all populations, including clinical populations, as well as all health-related outcomes. RESULTS One hundred and three studies were included. Adiposity was the most commonly studied health outcome (n = 41). Most studies (n = 75) reported reallocations amongst daily sleep, SB, LPA and MVPA. While other studies reported reallocations amongst sub-compositions of these (work MVPA vs. leisure MVPA), activity types determined by recall (screen time, household chores, passive transport etc.) or bouted behaviours (short vs. long bouts of SB). In general, when considering cross-sectional results, reallocating time to MVPA from any behaviour(s) was favourably associated with health and reallocating time away from MVPA to any behaviour(s) was unfavourably associated with health. Some beneficial associations were seen when reallocating time from SB to both LPA and sleep; however, the strength of the association was much lower than for any reallocations involving MVPA. However, there were many null findings. Notably, most of the longitudinal studies found no associations between reallocations of time and health. Some evidence also suggested the context of behaviours was important, with reallocations of leisure time toward MVPA having a stronger favourable association for health than reallocating work time towards MVPA. CONCLUSIONS Evidence suggests that reallocating time towards MVPA from any behaviour(s) has the strongest favourable association with health, and reallocating time away from MVPA toward any behaviour(s) has the strongest unfavourable association with health. Future studies should use longitudinal and experimental study designs, and for a wider range of outcomes.
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Affiliation(s)
- Aaron Miatke
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO box, Adelaide, S.A, 2471, 5001, Australia.
- Centre for Adolescent Health, Murdoch Children's Research Institute, Melbourne, Australia.
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO box, Adelaide, S.A, 2471, 5001, Australia
- Centre for Adolescent Health, Murdoch Children's Research Institute, Melbourne, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO box, Adelaide, S.A, 2471, 5001, Australia
| | - Francois Fraysse
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO box, Adelaide, S.A, 2471, 5001, Australia
| | - Maddison L Mellow
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO box, Adelaide, S.A, 2471, 5001, Australia
| | - Ashleigh E Smith
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO box, Adelaide, S.A, 2471, 5001, Australia
| | - Zeljko Pedisic
- Institute for Health and Sport, Victoria University, Melbourne, Australia
| | - Jozo Grgic
- Institute for Health and Sport, Victoria University, Melbourne, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO box, Adelaide, S.A, 2471, 5001, Australia
- Centre for Adolescent Health, Murdoch Children's Research Institute, Melbourne, Australia
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Sanchez-Trigo H, Maher C, Godino JG, Sañudo B. Effects of an mHealth physical activity intervention to prevent osteoporosis in premenopausal women. A randomized controlled trial. J Sci Med Sport 2023; 26:545-552. [PMID: 37739855 DOI: 10.1016/j.jsams.2023.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 07/31/2023] [Accepted: 09/02/2023] [Indexed: 09/24/2023]
Abstract
OBJECTIVES It is critical to develop prevention strategies for osteoporosis that reduce the burden fractures place on individuals and health systems. This study evaluated the effects of an mHealth intervention that delivered and monitored a non-supervised exercise program on bone mineral density (BMD). DESIGN Randomized controlled trial. METHODS 60 premenopausal women aged 35-50 years were divided into an intervention group (IG) and a control group (CG). The IG followed a 6-month intervention aimed at increasing osteogenic physical activity, guided by two daily goals: walking at least 10,000 steps and completing 60 impacts over 4 g of acceleration. These goals were monitored using a wearable accelerometer linked to an mHealth app. The CG maintained their regular lifestyle and wore the accelerometer without feedback. BMD was estimated using dual-energy X-ray absorptiometry (DXA) scans at baseline and after 6 months, with group-by-time analyses conducted using ANCOVA. The intervention's impact on physical fitness and activity habits was also evaluated. RESULTS 46 participants completed the study (IG = 24; CG = 22). The IG showed significant improvements compared to the CG in femoral neck BMD (IG: +0.003 ± 0.029 g/cm2 vs CG: -0.027 ± 0.031 g/cm2), trochanter BMD (IG: +0.004 ± 0.023 g/cm2 vs CG: -0.026 ± 0.030 g/cm2), and total hip BMD (IG: +0.006 ± 0.043 g/cm2 vs CG: -0.040 ± 0.048 g/cm2). The IG also demonstrated significant improvements in physical fitness measures, including peak torque and power at various speeds and positions. No adverse events related to the intervention were reported. CONCLUSIONS This non-supervised physical activity intervention delivered by wearable-technology and an mHealth app was effective in improving BMD, suggesting its potential for osteoporosis prevention.
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Affiliation(s)
| | - Carol Maher
- Allied Health and Human Performance, University of South Australia, Australia; Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Australia
| | - Job G Godino
- Herbert Wertheim School of Public Health and Longevity Science, University of California, USA; Exercise and Physical Activity Resource Center, University of California, USA; Laura Rodriguez Research Institute, Family Health Centers of San Diego, USA
| | - Borja Sañudo
- Physical Education and Sports Department, University of Seville, Spain
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Singh B, Olds T, Curtis R, Dumuid D, Virgara R, Watson A, Szeto K, O'Connor E, Ferguson T, Eglitis E, Miatke A, Simpson CE, Maher C. Effectiveness of physical activity interventions for improving depression, anxiety and distress: an overview of systematic reviews. Br J Sports Med 2023; 57:1203-1209. [PMID: 36796860 PMCID: PMC10579187 DOI: 10.1136/bjsports-2022-106195] [Citation(s) in RCA: 74] [Impact Index Per Article: 74.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/03/2023] [Indexed: 02/18/2023]
Abstract
OBJECTIVE To synthesise the evidence on the effects of physical activity on symptoms of depression, anxiety and psychological distress in adult populations. DESIGN Umbrella review. DATA SOURCES Twelve electronic databases were searched for eligible studies published from inception to 1 January 2022. ELIGIBILITY CRITERIA FOR SELECTING STUDIES Systematic reviews with meta-analyses of randomised controlled trials designed to increase physical activity in an adult population and that assessed depression, anxiety or psychological distress were eligible. Study selection was undertaken in duplicate by two independent reviewers. RESULTS Ninety-seven reviews (1039 trials and 128 119 participants) were included. Populations included healthy adults, people with mental health disorders and people with various chronic diseases. Most reviews (n=77) had a critically low A MeaSurement Tool to Assess systematic Reviews score. Physical activity had medium effects on depression (median effect size=-0.43, IQR=-0.66 to -0.27), anxiety (median effect size=-0.42, IQR=-0.66 to -0.26) and psychological distress (effect size=-0.60, 95% CI -0.78 to -0.42), compared with usual care across all populations. The largest benefits were seen in people with depression, HIV and kidney disease, in pregnant and postpartum women, and in healthy individuals. Higher intensity physical activity was associated with greater improvements in symptoms. Effectiveness of physical activity interventions diminished with longer duration interventions. CONCLUSION AND RELEVANCE Physical activity is highly beneficial for improving symptoms of depression, anxiety and distress across a wide range of adult populations, including the general population, people with diagnosed mental health disorders and people with chronic disease. Physical activity should be a mainstay approach in the management of depression, anxiety and psychological distress. PROSPERO REGISTRATION NUMBER CRD42021292710.
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Affiliation(s)
- Ben Singh
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Timothy Olds
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Rachel Curtis
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Dorothea Dumuid
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Rosa Virgara
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Amanda Watson
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Kimberley Szeto
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Edward O'Connor
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Ty Ferguson
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Emily Eglitis
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Aaron Miatke
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Catherine Em Simpson
- Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Carol Maher
- Health and Use of Time (HUT) Group, University of South Australia, Adelaide, South Australia, Australia
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Vandelanotte C, Trost S, Hodgetts D, Imam T, Rashid M, To QG, Maher C. Increasing physical activity using an just-in-time adaptive digital assistant supported by machine learning: A novel approach for hyper-personalised mHealth interventions. J Biomed Inform 2023; 144:104435. [PMID: 37394024 DOI: 10.1016/j.jbi.2023.104435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 06/26/2023] [Accepted: 06/28/2023] [Indexed: 07/04/2023]
Abstract
OBJECTIVE Physical inactivity is a leading modifiable cause of death and disease worldwide. Population-based interventions to increase physical activity are needed. Existing automated expert systems (e.g., computer-tailored interventions) have significant limitations that result in low long-term effectiveness. Therefore, innovative approaches are needed. This special communication aims to describe and discuss a novel mHealth intervention approach that proactively offers participants with hyper-personalised intervention content adjusted in real-time. METHODS Using machine learning approaches, we propose a novel physical activity intervention approach that can learn and adapt in real-time to achieve high levels of personalisation and user engagement, underpinned by a likeable digital assistant. It will consist of three major components: (1) conversations: to increase user's knowledge on a wide range of activity-related topics underpinned by Natural Language Processing; (2) nudge engine: to provide users with hyper-personalised cues to action underpinned by reinforcement learning (i.e., contextual bandit) and integrating real-time data from activity tracking, GPS, GIS, weather, and user provided data; (3) Q&A: to facilitate users asking any physical activity related questions underpinned by generative AI (e.g., ChatGPT, Bard) for content generation. RESULTS The detailed concept of the proposed physical activity intervention platform demonstrates the practical application of a just-in-time adaptive intervention applying various machine learning techniques to deliver a hyper-personalised physical activity intervention in an engaging way. Compared to traditional interventions, the novel platform is expected to show potential for increased user engagement and long-term effectiveness due to: (1) using new variables to personalise content (e.g., GPS, weather), (2) providing behavioural support at the right time in real-time, (3) implementing an engaging digital assistant and (4) improving the relevance of content through applying machine learning algorithms. CONCLUSION The use of machine learning is on the rise in every aspect of today's society, however few attempts have been undertaken to harness its potential to achieve health behaviour change. By sharing our intervention concept, we contribute to the ongoing dialogue on creating effective methods for promoting health and well-being in the informatics research community. Future research should focus on refining these techniques and evaluating their effectiveness in controlled and real-world circumstances.
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Affiliation(s)
- Corneel Vandelanotte
- Appleton Institute, Central Queensland University, Bruce Highway, Rockhampton, Queensland 4702, Australia.
| | - Stewart Trost
- School of Human Movement and Nutrition Science, The University of Queensland, St Lucia, Queensland 4072, Australia.
| | - Danya Hodgetts
- Appleton Institute, Central Queensland University, Bruce Highway, Rockhampton, Queensland 4702, Australia.
| | - Tasadduq Imam
- School of Business and Law, Central Queensland University, 120 Spencer Street, Melbourne, Victoria 3000, Australia.
| | - Mamunur Rashid
- School of Engineering and Technology, Central Queensland University, 120 Spencer Street, Melbourne, Victoria 3000, Australia.
| | - Quyen G To
- Appleton Institute, Central Queensland University, Bruce Highway, Rockhampton, Queensland 4702, Australia.
| | - Carol Maher
- Allied Health and Human Performance, University of South Australia, City East Campus, Adelaide, South Australia 5001, Australia.
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Singh B, Olds T, Curtis R, Ferguson T, Matricciani L, Brown WJ, Dumuid D, Esterman A, Maher C. Association between the use of weight management strategies and weight change among Australian adults over 12 months: an observational study. BMC Public Health 2023; 23:1461. [PMID: 37525173 PMCID: PMC10391811 DOI: 10.1186/s12889-023-16277-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Obesity is a growing, global public health issue. This study aimed to describe the weight management strategies used by a sample of Australian adults; examine the socio-demographic characteristics of using each strategy; and examine whether use of each strategy was associated with 12-month weight change. METHODS This observational study involved a community-based sample of 375 healthy adults (mean age: 40.1 ± 5.8 years, 56.8% female). Participants wore a Fitbit activity monitor, weighed themselves daily, and completed eight online surveys on socio-demographic characteristics. Participants also recalled their use of weight management strategies over the past month, at 8 timepoints during the 12-month study period. RESULTS Most participants (81%) reported using at least one weight management strategy, with exercise/physical activity being the most common strategy at each timepoint (40-54%). Those who accepted their current bodyweight were less likely to use at least one weight management strategy (Odds ratio = 0.38, 95% CI = 0.22-0.64, p < 0.01) and those who reported being physically active for weight maintenance had a greater reduction in bodyweight, than those who did not (between group difference: -1.2 kg, p < 0.01). The use of supplements and fasting were associated with poorer mental health and quality of life outcomes (p < 0.01). CONCLUSIONS The use of weight management strategies appears to be common. Being physically active was associated with greater weight loss. Individuals who accepted their current body weight were less likely to use weight management strategies. Fasting and the use of supplements were associated with poorer mental health. Promoting physical activity as a weight management strategy appears important, particularly considering its multiple health benefits.
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Affiliation(s)
- Ben Singh
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Timothy Olds
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Rachel Curtis
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Ty Ferguson
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Lisa Matricciani
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Wendy J Brown
- University of Queensland, St Lucia, Brisbane, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Adrian Esterman
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Carol Maher
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia.
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12
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Wilhite K, Del Pozo Cruz B, Noetel M, Lonsdale C, Ridgers ND, Maher C, Bradshaw E, Sanders T. Socioeconomic position as a predictor of youth's movement trajectory profiles between ages 10 and 14 years. Int J Behav Nutr Phys Act 2023; 20:88. [PMID: 37481648 PMCID: PMC10363305 DOI: 10.1186/s12966-023-01491-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 07/10/2023] [Indexed: 07/24/2023] Open
Abstract
BACKGROUND Combinations of movement behaviors (i.e., physical activity, sedentary behavior, sleep) are associated with health and developmental outcomes in youth. Youth vary in how they accumulate these behaviors, both in volume and specific domains (e.g., sedentary time spent on recreational screen activities vs homework). The aim of this study was to examine how youth's combined general and domain-specific movement trajectories differ by socioeconomic position. METHODS We conducted a longitudinal, group-based multi-trajectory analysis to identify general and domain-specific movement trajectory profiles for 2457 youth from age 10 to 14 years from the Longitudinal Study of Australian Children from 2014-2018. We used multinomial logistic regression to test if socioeconomic position predicted profile membership. RESULTS We identified three general movement trajectory profiles for both sexes, four domain-specific profiles for males, and five for females. For general movement trajectories, females from lower socioeconomic positions were more likely to be a combination of less active and more sedentary than females from higher socioeconomic positions. Males across socioeconomic positions spend similar amounts of time in physical activity, sedentary time, and sleep. For domain-specific movement trajectories, youth from lower socioeconomic positions were likely to spend a combination of less time in education-based sedentary behavior and more time in recreational screen activities than their higher socioeconomic position peers. CONCLUSION Our results indicate that socioeconomic position predicted in which domains youth accumulate their movements. Future observational research and interventions targeting different socioeconomic groups should therefore consider domain-specific movement trajectories.
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Affiliation(s)
- Katrina Wilhite
- Institute for Positive Psychology and Education, Australian Catholic University, 33 Berry Street, Sydney, NSW, 2060, Australia
| | - Borja Del Pozo Cruz
- Center for Active and Healthy Ageing, Department of Sport Sciences and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Michael Noetel
- School of Behavioural and Health Sciences, Australian Catholic University, Brisbane, Australia
| | - Chris Lonsdale
- Institute for Positive Psychology and Education, Australian Catholic University, 33 Berry Street, Sydney, NSW, 2060, Australia
| | - Nicola D Ridgers
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia
| | - Emma Bradshaw
- Institute for Positive Psychology and Education, Australian Catholic University, 33 Berry Street, Sydney, NSW, 2060, Australia
| | - Taren Sanders
- Institute for Positive Psychology and Education, Australian Catholic University, 33 Berry Street, Sydney, NSW, 2060, Australia.
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13
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Thøgersen-Ntoumani C, Kritz M, Grunseit A, Chau J, Ahmadi M, Holtermann A, Koster A, Tudor-Locke C, Johnson N, Sherrington C, Paudel S, Maher C, Stamatakis E. Barriers and enablers of vigorous intermittent lifestyle physical activity (VILPA) in physically inactive adults: a focus group study. Int J Behav Nutr Phys Act 2023; 20:78. [PMID: 37403160 DOI: 10.1186/s12966-023-01480-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/20/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUND Vigorous Intermittent Lifestyle Physical Activity (VILPA) refers to brief bouts of vigorous intensity physical activity performed as part of daily living. VILPA has been proposed as a novel concept to expand physical activity options among the least active. As a nascent area of research, factors which impede or encourage VILPA in physically inactive adults are yet to be explored. Such information is pertinent in the design of future interventions. We examined the barriers and enablers of VILPA among physically inactive adults using the Capability, Opportunity, Motivation, Behavior (COM-B) model as a conceptual framework. METHODS We recruited a sample of self-identified physically inactive middle-aged and older adults (N = 78) based in Australia to take part in 19 online focus groups across three age groups: young-middle (age 35-44), middle (age 45-59) and old (age 60-76). We analyzed interviews using a critical realist approach to thematic analysis. Identified barriers and enablers were subsequently mapped onto the COM-B model components. RESULTS The data generated 6 barriers and 10 enablers of VILPA that corresponded to COM-B concepts. Barriers included physical limitations (physical capability), perceptions of aging, need for knowledge (psychological capability), environmental constraints (physical opportunity), perceptions of effort and energy, and fear (automatic motivation). Enablers included convenience, reframing physical activity as purposeful movement, use of prompts and reminders (physical opportunity), normalization of taking the active option, gamification (social opportunity), sense of achievement, health improvements, personally salient rewards (reflective motivation), identity fit, and changing from effortful deliberation to habitual action (automatic motivation). CONCLUSION The barriers and enablers of VILPA span capability, opportunity, and motivation beliefs. Promoting the time-efficient nature and simplicity of VILPA requiring no equipment or special gym sessions, the use of prompts and reminders at opportune times, and habit formation strategies could capitalize on the enablers. Addressing the suitability of the small bouts, the development of specific guidelines, addressing safety concerns, and explicating the potential benefits of, and opportunities to do, VILPA could ameliorate some of the barriers identified. Future VILPA interventions may require limited age customization, speaking to the potential for such interventions to be delivered at scale.
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Affiliation(s)
- C Thøgersen-Ntoumani
- Danish Center for Motivation and Behavior Science (DRIVEN), Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
| | - M Kritz
- Curtin School of Population Health, Curtin University, Perth, Australia
| | - A Grunseit
- School of Public Health, University of Technology Sydney, Sydney, Australia
| | - J Chau
- Department of Health Sciences, Macquarie University, Sydney, Australia
| | - M Ahmadi
- Mackenzie Wearables Research Hub, Charles Perkins Centre, University of Sydney, Sydney, Australia
| | - A Holtermann
- National Research Centre for the Working Environment, Copenhagen, Denmark
| | - A Koster
- School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
| | - C Tudor-Locke
- College of Health and Human Services, University of North Carolina Charlotte, Charlotte, USA
| | - N Johnson
- Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - C Sherrington
- School of Public Health, University of Sydney, Sydney, Australia
| | - S Paudel
- School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia
| | - C Maher
- Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - E Stamatakis
- Mackenzie Wearables Research Hub, Charles Perkins Centre, University of Sydney, Sydney, Australia
- School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
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14
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Maher C, Ferguson T, Curtis R, Brown W, Dumuid D, Fraysse F, Hendrie GA, Singh B, Esterman A, Olds T. Weekly, Seasonal, and Festive Period Weight Gain Among Australian Adults. JAMA Netw Open 2023; 6:e2326038. [PMID: 37498598 PMCID: PMC10375309 DOI: 10.1001/jamanetworkopen.2023.26038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/28/2023] Open
Abstract
Importance Obesity is a major global health concern. A better understanding of temporal patterns of weight gain will enable the design and implementation of interventions with potential to alter obesity trajectories. Objective To describe changes in daily weight across 12 months among Australian adults. Design, Setting, and Participants This cohort study conducted between December 1, 2019, and December 31, 2021 in Adelaide, South Australia, involved 375 community-dwelling adults aged 18 to 65 years. Participants wore a fitness tracker and were encouraged to weigh themselves, preferably daily but at least weekly, using a body weight scale. Data were remotely gathered using custom-developed software. Exposure Time assessed weekly, seasonally, and at Christmas/New Year and Easter. Main Outcomes and Measures Data were visually inspected to assess the overall yearly pattern in weight change. Data were detrended (to remove systematic bias from intraindividual gradual increases or decreases in weight) by calculating a line of best fit for each individual's annual weight change relative to baseline and subtracting this from each participant's weight data. Multilevel mixed-effects linear regression analysis was used to compare weight across days of the week and seasons and at Christmas/New Year and Easter. Results Of 375 participants recruited, 368 (mean [SD] age, 40.2 [5.9] years; 209 [56.8%] female; mean [SD] baseline weight, 84.0 [20.5] kg) provided at least 7 days of weight data for inclusion in analyses. Across the 12-month period, participants gained a median of 0.26% body weight (218 g) (range, -29.4% to 24.0%). Weight fluctuated by approximately 0.3% (252 g) each week, with Mondays and Tuesdays being the heaviest days of the week. Relative to Monday, participants' weight gradually decreased from Tuesday, although not significantly so (mean [SE] weight change, 0.01% [0.03%]; P = .83), to Friday (mean [SE] weight change, -0.18% [0.03%]; P < .001) and increased across the weekend to Monday (mean [SE] weight change for Saturday, -0.16% [0.03%]; P < .001; mean [SE] weight change for Sunday, -0.10% [0.03%]; P < .001). Participants' weight increased sharply at Christmas/New Year (mean [SE] increase, 0.65% [0.03%]; z score, 25.30; P < .001) and Easter (mean [SE] weight change, 0.29% [0.02%], z score, 11.51; P < .001). Overall, participants were heaviest in summer (significantly heavier than in all other seasons), were lightest in autumn (mean [SE] weight change relative to summer, -0.47% [0.07%]; P < .001), regained some weight in winter (mean [SE] weight change relative to summer, -0.23% [0.07%]; P = .001), and became lighter in spring (mean [SE] weight change relative to summer, -0.27% [0.07%]; P < .001). Conclusions and Relevance In this cohort study of Australian adults with weekly and yearly patterns in weight gain observed across 12 months, high-risk times for weight gain were Christmas/New Year, weekends, and winter, suggesting that temporally targeted weight gain prevention interventions may be warranted.
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Affiliation(s)
- Carol Maher
- UniSA Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Ty Ferguson
- UniSA Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Rachel Curtis
- UniSA Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Wendy Brown
- School of Human Movement and Nutrition Sciences, University of Queensland, St Lucia, Brisbane, Australia
| | - Dorothea Dumuid
- UniSA Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Francois Fraysse
- UniSA Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Gilly A Hendrie
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| | - Ben Singh
- UniSA Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Adrian Esterman
- UniSA Clinical and Health Sciences, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Timothy Olds
- UniSA Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
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15
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Watson A, Maher C, Golley R, Dumuid D, Manson A, Tomkinson G, Fraysse F, Olds T. Children's activity and diet behaviours in the summer holidays versus school year. Pediatr Obes 2023; 18:e13029. [PMID: 36945145 PMCID: PMC10909460 DOI: 10.1111/ijpo.13029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/20/2023] [Accepted: 03/06/2023] [Indexed: 03/23/2023]
Abstract
BACKGROUND Evidence shows children gain more weight during the summer holidays versus the school year. OBJECTIVES To examine within-child differences in activity and diet behaviours during the summer holidays versus the school year. METHODS Children (mean age 9.4 years; 37% male) wore accelerometers (GENEActiv; n = 133), reported activities (Multimedia Activity Recall for Children and Adolescents; n = 133) and parents reported child diet (n = 133) at five timepoints over 2 years capturing school and summer holiday values. Mixed-effects models were used to compare school and summer holiday behaviours. RESULTS Children spent less time in moderate- to vigorous-physical activity (-12 min/day; p = 0.001) and sleep (-12 min/day; p < 0.001) and more time sedentary (+27 min/day; p < 0.001) during summer holidays versus the school year. Screentime (+70 min/day; p < 0.001), domestic/social activities (+43 min/day; p = <0.001), self-care (+24 min/day; p < 0.001), passive transport (+22 min/day; p = 0.001) and quiet time (+16 min/day; p = 0.012) were higher during the summer holidays, compensating for less time in school-related activities (-164 min/day; p < 0.001). Diet quality was lower (-4 points; p < 0.001) and children consumed fewer serves of fruit (-0.4 serves; p < 0.001) during the summer holidays versus the school year. CONCLUSIONS Children are displaying poorer activity and diet behaviours during the summer holidays, which may contribute to accelerated weight gain over the holiday period.
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Affiliation(s)
- Amanda Watson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South AustraliaAdelaideSouth AustraliaAustralia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South AustraliaAdelaideSouth AustraliaAustralia
| | - Rebecca Golley
- College of Nursing and Health Sciences, Flinders UniversityAdelaideSouth AustraliaAustralia
| | - Dot Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South AustraliaAdelaideSouth AustraliaAustralia
| | - Alexandra Manson
- College of Nursing and Health Sciences, Flinders UniversityAdelaideSouth AustraliaAustralia
| | - Grant Tomkinson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South AustraliaAdelaideSouth AustraliaAustralia
| | - Francois Fraysse
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South AustraliaAdelaideSouth AustraliaAustralia
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South AustraliaAdelaideSouth AustraliaAustralia
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Singh B, Olds T, Brinsley J, Dumuid D, Virgara R, Matricciani L, Watson A, Szeto K, Eglitis E, Miatke A, Simpson CEM, Vandelanotte C, Maher C. Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours. NPJ Digit Med 2023; 6:118. [PMID: 37353578 DOI: 10.1038/s41746-023-00856-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 06/01/2023] [Indexed: 06/25/2023] Open
Abstract
Chatbots (also known as conversational agents and virtual assistants) offer the potential to deliver healthcare in an efficient, appealing and personalised manner. The purpose of this systematic review and meta-analysis was to evaluate the efficacy of chatbot interventions designed to improve physical activity, diet and sleep. Electronic databases were searched for randomised and non-randomised controlled trials, and pre-post trials that evaluated chatbot interventions targeting physical activity, diet and/or sleep, published before 1 September 2022. Outcomes were total physical activity, steps, moderate-to-vigorous physical activity (MVPA), fruit and vegetable consumption, sleep quality and sleep duration. Standardised mean differences (SMD) were calculated to compare intervention effects. Subgroup analyses were conducted to assess chatbot type, intervention type, duration, output and use of artificial intelligence. Risk of bias was assessed using the Effective Public Health Practice Project Quality Assessment tool. Nineteen trials were included. Sample sizes ranged between 25-958, and mean participant age ranged between 9-71 years. Most interventions (n = 15, 79%) targeted physical activity, and most trials had a low-quality rating (n = 14, 74%). Meta-analysis results showed significant effects (all p < 0.05) of chatbots for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40]), daily steps (SMD = 0.28 [95% CI = 0.17, 0.39]), MVPA (SMD = 0.53 [95% CI = 0.24, 0.83]), fruit and vegetable consumption (SMD = 0.59 [95% CI = 0.25, 0.93]), sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55]) and sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90]). Subgroup analyses showed that text-based, and artificial intelligence chatbots were more efficacious than speech/voice chatbots for fruit and vegetable consumption, and multicomponent interventions were more efficacious than chatbot-only interventions for sleep duration and sleep quality (all p < 0.05). Findings from this systematic review and meta-analysis indicate that chatbot interventions are efficacious for increasing physical activity, fruit and vegetable consumption, sleep duration and sleep quality. Chatbot interventions were efficacious across a range of populations and age groups, with both short- and longer-term interventions, and chatbot only and multicomponent interventions being efficacious.
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Affiliation(s)
- Ben Singh
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
| | - Timothy Olds
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Jacinta Brinsley
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Dot Dumuid
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Rosa Virgara
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Lisa Matricciani
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Amanda Watson
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Kimberley Szeto
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Emily Eglitis
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Aaron Miatke
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Catherine E M Simpson
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Corneel Vandelanotte
- School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, QLD, Australia
| | - Carol Maher
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
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Giraud S, Zamora JC, Zegers RGT, Bazin D, Ayyad Y, Bacca S, Beceiro-Novo S, Brown BA, Carls A, Chen J, Cortesi M, DeNudt M, Hagen G, Hultquist C, Maher C, Mittig W, Ndayisabye F, Noji S, Novario SJ, Pereira J, Rahman Z, Schmitt J, Serikow M, Sun LJ, Surbrook J, Watwood N, Wheeler T. β^{+} Gamow-Teller Strengths from Unstable ^{14}O via the (d,^{2}He) Reaction in Inverse Kinematics. Phys Rev Lett 2023; 130:232301. [PMID: 37354417 DOI: 10.1103/physrevlett.130.232301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 04/14/2023] [Accepted: 05/05/2023] [Indexed: 06/26/2023]
Abstract
For the first time, the (d,^{2}He) reaction was successfully used in inverse kinematics to extract the Gamow-Teller transition strength in the β^{+} direction from an unstable nucleus. The new technique was made possible by the use of an active-target time-projection chamber and a magnetic spectrometer, and opens a path to addressing a range of scientific challenges, including in astrophysics and neutrino physics. In this Letter, the nucleus studied was ^{14}O, and the Gamow-Teller transition strength to ^{14}N was extracted up to an excitation energy of 22 MeV. The data were compared to shell-model and state-of-the-art coupled-cluster calculations. Shell-model calculations reproduce the measured Gamow-Teller strength distribution up to about 15 MeV reasonably well, after the application of a phenomenological quenching factor. In a significant step forward to better understand this quenching, the coupled-cluster calculation reproduces the full strength distribution well without such quenching, owing to the large model space, the inclusion of strong correlations, and the coupling of the weak interaction to two nucleons through two-body currents.
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Affiliation(s)
- S Giraud
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - J C Zamora
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
| | - R G T Zegers
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - D Bazin
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - Y Ayyad
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- IGFAE, Universidade de Santiago de Compostela, E-15782 Santiago de Compostela, Spain
| | - S Bacca
- Institut für Kernphysik and PRISMA+ Cluster of Excellence, Johannes Gutenberg-Universität, 55128 Mainz, Germany
- Helmholtz-Institut Mainz, Johannes Gutenberg-Universität Mainz, D-55099 Mainz, Germany
| | - S Beceiro-Novo
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
- CITENI, Campus Industrial de Ferrol, Universidade da Coruña, Campus de Esteiro, 15403 Ferrol, Spain
| | - B A Brown
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - A Carls
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - J Chen
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Physics Division, Argonne National Laboratory, Lemont, Illinois 60439, USA
| | - M Cortesi
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
| | - M DeNudt
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - G Hagen
- Physics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
- Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - C Hultquist
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - C Maher
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - W Mittig
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - F Ndayisabye
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - S Noji
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
| | - S J Novario
- Physics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
- Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - J Pereira
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
| | - Z Rahman
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - J Schmitt
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - M Serikow
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - L J Sun
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
| | - J Surbrook
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - N Watwood
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - T Wheeler
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics: Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
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Szeto K, Arnold J, Singh B, Gower B, Simpson CEM, Maher C. Interventions Using Wearable Activity Trackers to Improve Patient Physical Activity and Other Outcomes in Adults Who Are Hospitalized: A Systematic Review and Meta-analysis. JAMA Netw Open 2023; 6:e2318478. [PMID: 37318806 PMCID: PMC10273021 DOI: 10.1001/jamanetworkopen.2023.18478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 04/28/2023] [Indexed: 06/16/2023] Open
Abstract
Importance Low levels of physical activity during hospitalization are thought to contribute to a range of poor outcomes for patients. Using wearable activity trackers during hospitalization may help improve patient activity, sedentary behavior, and other outcomes. Objective To evaluate the association of interventions that use wearable activity trackers during hospitalization with patient physical activity, sedentary behavior, clinical outcomes, and hospital efficiency outcomes. Data Sources OVID MEDLINE, CINAHL, Embase, EmCare, PEDro, SportDiscuss, and Scopus databases were searched from inception to March 2022. The Cochrane Central Register for Controlled trials, ClinicalTrials.gov, and World Health Organization Clinical Trials Registry were also searched for registered protocols. No language restrictions were imposed. Study Selection Randomized clinical trials and nonrandomized clinical trials of interventions that used wearable activity trackers to increase physical activity or reduce sedentary behavior in adults (aged 18 years or older) who were hospitalized were included. Data Extraction and Synthesis Study selection, data extraction, and critical appraisal were conducted in duplicate. Data were pooled for meta-analysis using random-effects models. The Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline was followed. Main Outcomes and Measures The primary outcomes were objectively measured physical activity or sedentary behavior. Secondary outcomes included clinical outcomes (eg, physical function, pain, mental health), and hospital efficiency outcomes (eg, length of stay, readmission). Results Fifteen studies with a total of 1911 participants were included, representing various surgical cohorts (4 studies), stroke rehabilitation (3 studies), orthopedic rehabilitation (3 studies), mixed rehabilitation (3 studies), and mixed medical (2 studies). All studies were included in meta-analyses. There was a significant association between wearable activity tracker interventions with higher overall physical activity (standardized mean difference, 0.35; 95% CI, 0.15 to 0.54; I2 = 72%; P < .002) and less sedentary behavior (mean difference, -35.46 min/d; 95% CI, -57.43 to -13.48 min/d; I2 = 0; P = .002), and a significant association between wearable activity tracker interventions with improvements in physical function (standardized mean difference, 0.27; 95% CI, 0.08 to 0.46; I2 = 0; P = .006) compared with usual care. There was no significant association between wearable activity tracker interventions with pain, mental health, length of stay, or readmission risk. Conclusions and Relevance In this systematic review and meta-analysis, interventions that used wearable activity trackers with patients who are hospitalized were associated with higher physical activity levels, less sedentary behavior, and better physical functioning compared with usual care.
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Affiliation(s)
- Kimberley Szeto
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - John Arnold
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Ben Singh
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Bethany Gower
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Catherine E. M. Simpson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
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19
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Singh B, Palmer S, Maher C. Evaluation of a supportive care app for coordinating caring networks: an analysis of the first 19,000 users. Front Digit Health 2023; 5:1063277. [PMID: 37266027 PMCID: PMC10229897 DOI: 10.3389/fdgth.2023.1063277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 04/26/2023] [Indexed: 06/03/2023] Open
Abstract
Background Major illnesses such as cancer, and other traumatic life events, can lead to sudden increases in supportive care needs. This study aimed to describe engagement, acceptability and satisfaction with a supportive care networking app under real-world conditions. Methods A total of 10,952 individuals used the app during the study period (2018-2022). The app is designed to enable "captains" to assemble a network of friends and family members to provide timely, and individually tailored, supportive care (including assistance with tasks such as taking children to school, cooking meals, grocery shopping, and transport to appointments). Engagement was determined from server data, whilst acceptability and satisfaction were captured using purposed-designed surveys. Results Users were mostly female (76%) and aged between 30 and 49 years (61%). The most common reason for using the app was sudden illness (web: 81%; mobile: 64%). An average of 42 tasks were requested per network, with a 32% acceptance rate. Significantly more tasks were requested (web: 52.2 tasks per network; mobile: 31.7 tasks per network; p < 0.001) and accepted (web: 43.2%; mobile: 20.2%; p < 0.001) in the web app vs. the mobile app. Task requests in the web app most commonly related to food (43% of requested tasks), social (15% of requested tasks) and children (13% of requested tasks). The task acceptance rate differed by task categories (p < 0.001), with tasks relating to transport, medical appointments and children accepted at the highest rates (56%, 52% and 49%, respectively). Acceptability and satisfaction data suggested that the app was well received and overall, participants were satisfied with the app. Conclusion Findings suggested that this support care networking app achieved widespread uptake for a wide variety of supportive care tasks. Future research focused on optimizing engagement with the mobile app and examining the effectiveness of the app for improving patient and hospital outcomes is warranted.
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Affiliation(s)
- Ben Singh
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
| | - Susan Palmer
- Research and Development Department, The Gather Group Co, Gather Group, Elsternwick VIC, Australia
| | - Carol Maher
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
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20
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Jennings C, Singh B, Oni H, Mazzacano A, Maher C. A needs assessment for self-management services for adults awaiting community-based mental health services. BMC Public Health 2023; 23:570. [PMID: 36973724 PMCID: PMC10041506 DOI: 10.1186/s12889-023-15382-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/06/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND High demand for services has resulted in lengthy waiting times being experienced across mental health services, both across Australia and internationally. Timely access to services is necessary to optimise the effectiveness of treatment, and prevent further mental health decline, risk of suicidality and hospitalisation for clients waiting for services to commence. The present study aims to better understand the experiences of individuals who are waiting for ongoing mental health services to commence and their preferences for additional support whilst on the waitlist, as a means to recommend alternative supports. METHODS A link to the cross-sectional, anonymous survey was sent via text message to 2,147 clients of a mental health service, with a reminder text message sent approximately one week subsequent to those who did not opt out of the communication. Eligibility criteria included having been a client of the service in the previous 12 months, having spent time on the waiting list, being aged 16 or over and having sufficient English proficiency. RESULTS A total of 334 participants responded to the needs assessment survey, 277 (82.9%) of which resided in the metropolitan region and 57 (17.1%) residing in the country region. Of the respondents, the majority presented with generalised anxiety/panic attacks (n = 205, 61.4%), followed by life stressors (e.g., financial concerns, relationships, n = 196, 58.7%) and lack of motivation/loss of interest (n = 196, 58.7%). Most respondents (52.7%) waited 4-12 months for ongoing services to commence and almost half (47%) reported that their mental health deteriorated during this time. Of the additional support options, most participants expressed interest in additional mental health supports (78.4%, n = 262), such as telephone support and access to online materials. There was significant interest in other supports such as exercise support (57.4%, n = 192), sleep education (56.6%, n = 190) and healthy eating support (41%, n = 137). CONCLUSION Mental health services are experiencing significant waiting times, increasing the risk of mental health deterioration for persons waiting for services to commence. However, the findings demonstrate that there is interest for alternative support options, such as lifestyle interventions, in the interim. Desire for lifestyle support services, particularly in-person exercise programs and self-directed sleep, was especially high amongst the population of respondents within this study. Future work to rigorously develop and evaluate such lifestyle support services for mental health clients is warranted.
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Affiliation(s)
- Cally Jennings
- Sonder Mental Health Services, Adelaide, South Australia, Australia
| | - Ben Singh
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, GPO Box 2471, Adelaide, South Australia, SA 5001, Australia
| | - Helen Oni
- Sonder Mental Health Services, Adelaide, South Australia, Australia
| | - Anna Mazzacano
- Sonder Mental Health Services, Adelaide, South Australia, Australia
| | - Carol Maher
- Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, GPO Box 2471, Adelaide, South Australia, SA 5001, Australia.
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21
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Ferguson T, Curtis R, Fraysse F, Olds T, Dumuid D, Brown W, Esterman A, Maher C. How do 24-h movement behaviours change during and after vacation? A cohort study. Int J Behav Nutr Phys Act 2023; 20:24. [PMID: 36859292 PMCID: PMC9976678 DOI: 10.1186/s12966-023-01416-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 01/23/2023] [Indexed: 03/03/2023] Open
Abstract
BACKGROUND For adults, vacations represent a break from daily responsibilities of work - offering the opportunity to re-distribute time between sleep, sedentary behaviour, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) across the 24-h day. To date, there has been minimal research into how activity behaviour patterns change on vacation, and whether any changes linger after the vacation. This study examined how daily movement behaviours change from before, to during and after vacations, and whether these varied based on the type of vacation and vacation duration. METHODS Data collected during the Annual Rhythms In Adults' lifestyle and health (ARIA) study were used. 308 adults (mean age 40.4 years, SD 5.6) wore Fitbit Charge 3 fitness trackers 24 h a day for 13 months. Minute-by-minute movement behaviour data were aggregated into daily totals. Multi-level mixed-effects linear regressions were used to compare movement behaviours during and post-vacation (4 weeks) to pre-vacation levels (14 days), and to examine the associations with vacation type and duration. RESULTS Participants took an average of 2.6 (SD = 1.7) vacations of 12 (SD = 14) days' (N = 9778 days) duration. The most common vacation type was outdoor recreation (35%) followed by family/social events (31%), rest (17%) and non-leisure (17%). Daily sleep, LPA and MVPA all increased (+ 21 min [95% CI = 19,24] p < 0.001, + 3 min [95% CI = 0.4,5] p < 0.02, and + 5 min [95% CI = 3,6] p < 0.001 respectively) and sedentary behaviour decreased (-29 min [95% CI = -32,-25] p < 0.001) during vacation. Post-vacation, sleep remained elevated for two weeks; MVPA returned to pre-vacation levels; and LPA and sedentary behaviour over-corrected, with LPA significantly lower for 4 weeks, and sedentary behaviour significantly higher for one week. The largest changes were seen for "rest" and "outdoor" vacations. The magnitude of changes was smallest for short vacations (< 3 days). CONCLUSIONS Vacations are associated with favourable changes in daily movement behaviours. These data provide preliminary evidence of the health benefits of vacations. TRIAL REGISTRATION The study was prospectively registered on the Australian New Zealand Clinical Trial Registry (Trial ID: ACTRN12619001430123).
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Affiliation(s)
- Ty Ferguson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA) of the University of South Australia, Adelaide, SA, Australia.
| | - Rachel Curtis
- Alliance for Research in Exercise, Nutrition and Activity (ARENA) of the University of South Australia, Adelaide, SA, Australia
| | - Francois Fraysse
- Alliance for Research in Exercise, Nutrition and Activity (ARENA) of the University of South Australia, Adelaide, SA, Australia
| | - Timothy Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA) of the University of South Australia, Adelaide, SA, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA) of the University of South Australia, Adelaide, SA, Australia
| | - Wendy Brown
- School of Human Movement and Nutrition Sciences of the University of Queensland, Brisbane, QLD, Australia
| | - Adrian Esterman
- Alliance for Research in Exercise, Nutrition and Activity (ARENA) of the University of South Australia, Adelaide, SA, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA) of the University of South Australia, Adelaide, SA, Australia
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22
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Cogliati Dezza I, Maher C, Sharot T. People adaptively use information to improve their internal states and external outcomes. Cognition 2022; 228:105224. [PMID: 35850045 PMCID: PMC10510028 DOI: 10.1016/j.cognition.2022.105224] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 07/05/2022] [Accepted: 07/06/2022] [Indexed: 11/23/2022]
Abstract
Information can strongly impact people's affect, their level of uncertainty and their decisions. It is assumed that people seek information with the goal of improving all three. But are they successful at achieving this goal? Answering this question is important for assessing the impact of self-driven information consumption on people's well-being. Here, over five experiments (total N = 727) we show that participants accurately predict the impact of information on their internal states (e.g., affect and cognition) and external outcomes (e.g., material rewards), and use these predictions to guide information-seeking choices. A model incorporating participants' subjective expectations regarding the impact of information on their affective, cognitive, and material outcomes accounted for information-seeking choices better than a model that included only objective proxies of those measures. This model also accounted for individual differences in information-seeking choices. By balancing considerations of the impact of information on affective, cognitive and material outcomes when seeking knowledge, participants became happier, more certain and made better decisions when they sought information relative to when they did not, suggesting that the actual consequences of receiving information aligned with their subjective expectations.
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Affiliation(s)
- I Cogliati Dezza
- Department of Experimental Psychology, Faculty of Brain Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK; Department of Experimental Psychology, Ghent University, Henri Dunantlaan 2, Ghent, BE, Belgium; The Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, 10-12 Russell Square, London, WC1B 5EH, UK.
| | - C Maher
- Department of Experimental Psychology, Faculty of Brain Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK; The Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, 10-12 Russell Square, London, WC1B 5EH, UK
| | - T Sharot
- Department of Experimental Psychology, Faculty of Brain Sciences, University College London, 26 Bedford Way, London WC1H 0AP, UK; The Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, 10-12 Russell Square, London, WC1B 5EH, UK; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, MA 02139, USA.
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23
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Chen Q, Machado G, Ferreira G, Maher C. Comment on the article by Singh et al.: The 2019 GBD study provided very limited primary data to estimate the burden of osteoarthritis in India over 30 years. Osteoarthritis Cartilage 2022; 30:1411-1412. [PMID: 35970255 DOI: 10.1016/j.joca.2022.06.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 06/26/2022] [Accepted: 06/30/2022] [Indexed: 02/02/2023]
Affiliation(s)
- Q Chen
- Institute for Musculoskeletal Health, The University of Sydney and Sydney Local Health District, Sydney, NSW, Australia.
| | - G Machado
- Institute for Musculoskeletal Health, The University of Sydney and Sydney Local Health District, Sydney, NSW, Australia
| | - G Ferreira
- Institute for Musculoskeletal Health, The University of Sydney and Sydney Local Health District, Sydney, NSW, Australia
| | - C Maher
- Institute for Musculoskeletal Health, The University of Sydney and Sydney Local Health District, Sydney, NSW, Australia
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24
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Wilson LM, Potter A, Maher C, Ellis MJ, Lane RL, Wilson JW, Keating DT, Jaberzadeh S, Button BM. Feasibility of the A-STEP for the assessment of exercise capacity in people with cystic fibrosis. Pediatr Pulmonol 2022; 57:2524-2532. [PMID: 35811327 PMCID: PMC9796135 DOI: 10.1002/ppul.26069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/04/2022] [Accepted: 07/06/2022] [Indexed: 01/01/2023]
Abstract
OBJECTIVES To evaluate feasibility of the Alfred Step Test Exercise Protocol (A-STEP) for the assessment of exercise capacity in adults and children with cystic fibrosis (CF); in adults to test whether demographics and/or lung function correlated with exercise capacity. METHODS Adults and children with stable CF from two centres completed the A-STEP (a recently developed incremental maximal-effort step test). Feasibility was evaluated by: usefulness for exercise capacity assessment (measures of exercise capacity were: level reached, exercise-induced desaturation, and achievement of at least one maximal effort criteria); safety; operational factors; time to complete; floor and/or ceiling effects. We used multiple linear regression to test whether demographics and/or lung function correlated with exercise capacity. RESULTS A total of 49 participants: 38 adults (18 male), percent predicted (pp) forced expiration in one second (FEV1 ) 29-109, aged 22-48 years and 11 children (6 male), ppFEV1 68-107, aged 10-15 years were included. Levels reached (mean (SD) [range]) were 10.2 (2.4) [6-15] (adults), 10.1 (2.5) [7-14] (children); desaturation (change between baseline and peak-exercise SpO2 ): was 8.4 (3.8 [0-15]% (adults), 2.0 (2.0) [0-7]% (children). A total of 8 (21%) adults and no children desaturated <90% SpO2 . At least one criterion for maximal effort was reached by 33 (84%) adults and 10 (91%) children. There were no adverse events. The A-STEP was straightforward to use and carried out by one operator. A total of 26 (68.4%) adults and 7 (63.6%) children completed the test within the recommended 8-12 min. All participants completed a minimum of 6 levels, and completed the test before the final 16th level. In adults, ppFEV1 and ppFVC correlated with the level reached (r = 0.55; p = <0.001 and r = 0.66, p = <0.0001) and desaturation (r = 0.55, p = <0.001 and r = 0.45, p = <0.005). CONCLUSION In adults and children with stable CF, the A-STEP was feasible, safe, and operationally easy to use for the assessment of exercise capacity, without floor or ceiling effects. In adults, lung function correlated with exercise capacity.
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Affiliation(s)
- Lisa M Wilson
- Department of Physiotherapy, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia.,Department of Physiotherapy, Alfred Health, Melbourne, Victoria, Australia.,Department of Respiratory Medicine, Alfred Health, Melbourne, Victoria, Australia
| | - Angela Potter
- Department of Physiotherapy, Women's and Children's Hospital, Adelaide, South Australia, Australia
| | - Carol Maher
- Department of Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity (ARENA) Research Centre, University of South Australia, Adelaide, Australia
| | - Matthew J Ellis
- Department of Respiratory Medicine, Alfred Health, Melbourne, Victoria, Australia
| | - Rebecca L Lane
- Department of Physiotherapy, Victoria University, Melbourne, Victoria, Australia
| | - John W Wilson
- Department of Respiratory Medicine, Alfred Health, Melbourne, Victoria, Australia.,Department of Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Dominic T Keating
- Department of Respiratory Medicine, Alfred Health, Melbourne, Victoria, Australia.,Department of Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Shapour Jaberzadeh
- Department of Physiotherapy, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Brenda M Button
- Department of Physiotherapy, Alfred Health, Melbourne, Victoria, Australia.,Department of Respiratory Medicine, Alfred Health, Melbourne, Victoria, Australia.,Department of Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
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25
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Potter A, Singh B, Scutter E, Maher C. The feasibility of collecting the physiotherapy outcomes airway clearance, physical activity and fitness for the Australian Cystic Fibrosis Data Registry. BMC Pulm Med 2022; 22:342. [PMID: 36088311 PMCID: PMC9463726 DOI: 10.1186/s12890-022-02141-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 09/06/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Physiotherapy-related data, such as airway clearance techniques (ACTS), physical activity and aerobic fitness are not consistently included in international cystic fibrosis (CF) data registries. This study aimed to pilot the collection of ACTS, physical activity and fitness in a hospital CF clinic, as a step towards informing future national implementation.
Methods
This study was undertaken in a CF clinic within a major tertiary hospital. Patients and families were invited to participate. Participants completed self-report questionnaires on ACT use and those aged ≥ 10 years completed a physical activity questionnaire (Core Indicators and Measures of Youth Health Survey) and aerobic fitness test (the A-STEP test). Participants also completed a survey to explore the tolerance and acceptability of the fitness test, and the perceived accuracy of the self-reported data collection.
Results
Forty patients agreed to participate in the study (mean age = 9.8, SD = 4.1 years old; 52.5% female). All patients and/or families that were approached agreed to participate and completion rate for the ACTs and physical activity surveys was 98% and 100% (respectively). Completion rate for the fitness test was 55%, due to time constraints. Most participants agreed (≥ 90%) they could accurately provide ACT and physical activity data, and the assessments were tolerable and acceptable.
Conclusions
Patients with CF and their families are able to and can acceptably provide physiotherapy-related data, and collecting self-report ACTs and physical activity data is highly feasibly during routine CF clinic visits. However, aerobic fitness testing using the A-STEP test may be less feasible in clinic environments, due to time constraints.
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Watson A, Dumuid D, Maher C, Fraysse F, Mauch C, Tomkinson GR, Ferguson T, Olds T. Parenting Styles and Their Associations with Children's Body Composition, Activity Patterns, Fitness, Diet, Health, and Academic Achievement. Child Obes 2022. [PMID: 35950961 DOI: 10.1089/chi.2022.0054] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Background: Evidence regarding the impact of parenting style on health and other outcomes is inconsistent and limited by measurement quality and type. This study will examine associations between parenting style and children's objectively assessed activity patterns, body composition, fitness, diet, health, and academic achievement. Methods: Two hundred fifty-five children (mean age: 9.4 years) from Adelaide, Australia, were included. Parenting style (items from Child Rearing Questionnaire and National Longitudinal Survey of Children and Youth to assess Authoritative, Authoritarian, Permissive, Disengaged parenting), diet, and health were proxy-reported by parents. Body composition, fitness, and 24 hour activity patterns were objectively measured, and children reported screen-time. Academic achievement was measured using standardized tests in reading and mathematics. Mixed models were used to regress parenting style against activity patterns, body composition, fitness, diet, health, and academic achievement, adjusted for age, sex, socioeconomic position, and pubertal stage. Results: Children with Disengaged parents had poorer activity patterns: less moderate to vigorous physical activity (standard mean difference [SMD] relative to grand mean = -0.23), light physical activity (SMD = -0.13) and sleep (SMD = -0.18), more sitting (SMD = 0.45), later bedtime (SMD = 0.18), lower overall energy expenditure (SMD = -0.23), and poorer overall self-reported health (SMD = -0.30). Children with Permissive parents had generally better activity patterns (SMD = 0.25-0.32). Children with Authoritative parents were more likely to meet dietary guidelines for fruit intake (SMD = 0.12). There were no associations for Authoritarian parenting style or for academic achievement, body composition, or fitness. Conclusions: Disengaged parenting was detrimental, while Permissive parenting was beneficial for activity patterns. As parenting styles may be malleable, future interventions may target Permissive parenting to improve children's activity patterns. Trial registration: Australia New Zealand Clinical Trials Registry, identifier ACTRN12618002008202. Retrospectively registered on 14 December 2018.
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Affiliation(s)
- Amanda Watson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Francois Fraysse
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Chelsea Mauch
- College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Grant R Tomkinson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
- Department of Education, Health and Behavior Studies, University of North Dakota, Grand Forks, USA
| | - Ty Ferguson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
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Tong HL, Maher C, Parker K, Pham TD, Neves AL, Riordan B, Chow CK, Laranjo L, Quiroz JC. The use of mobile apps and fitness trackers to promote healthy behaviors during COVID-19: A cross-sectional survey. PLOS Digit Health 2022; 1:e0000087. [PMID: 36812578 PMCID: PMC9931267 DOI: 10.1371/journal.pdig.0000087] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Accepted: 07/14/2022] [Indexed: 06/18/2023]
Abstract
OBJECTIVES To examine i) the use of mobile apps and fitness trackers in adults during the COVID-19 pandemic to support health behaviors; ii) the use of COVID-19 apps; iii) associations between using mobile apps and fitness trackers, and health behaviors; iv) differences in usage amongst population subgroups. METHODS An online cross-sectional survey was conducted during June-September 2020. The survey was developed and reviewed independently by co-authors to establish face validity. Associations between using mobile apps and fitness trackers and health behaviors were examined using multivariate logistic regression models. Subgroup analyses were conducted using Chi-square and Fisher's exact tests. Three open-ended questions were included to elicit participants' views; thematic analysis was conducted. RESULTS Participants included 552 adults (76.7% women; mean age: 38±13.6 years); 59.9% used mobile apps for health, 38.2% used fitness trackers, and 46.3% used COVID-19 apps. Users of mobile apps or fitness trackers had almost two times the odds of meeting aerobic physical activity guidelines compared to non-users (odds ratio = 1.91, 95% confidence interval 1.07 to 3.46, P = .03). More women used health apps than men (64.0% vs 46.8%, P = .004). Compared to people aged 18-44 (46.1%), more people aged 60+ (74.5%) and more people aged 45-60 (57.6%) used a COVID-19 related app (P < .001). Qualitative data suggest people viewed technologies (especially social media) as a 'double-edged sword': helping with maintaining a sense of normalcy and staying active and socially connected, but also having a negative emotional effect stemming from seeing COVID-related news. People also found that mobile apps did not adapt quickly enough to the circumstances caused by COVID-19. CONCLUSIONS Use of mobile apps and fitness trackers during the pandemic was associated with higher levels of physical activity, in a sample of educated and likely health-conscious individuals. Future research is needed to understand whether the association between using mobile devices and physical activity is maintained in the long-term.
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Affiliation(s)
- Huong Ly Tong
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Kate Parker
- Deakin University, Geelong, Australia, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences
| | - Tien Dung Pham
- Royal Melbourne Hospital, School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia
| | - Ana Luisa Neves
- NIHR Imperial Patient Safety Translational Research Centre, Imperial College of London, London, United Kingdom
- Centre for Health Technology and Services Research, Department of Community Medicine, Information and Decision in Health, Faculty of Medicine, University of Porto, Porto, Portugal
| | - Benjamin Riordan
- Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia
| | - Clara K. Chow
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
- Department of Cardiology, Westmead Hospital, Sydney, Australia
| | - Liliana Laranjo
- Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
- Western Sydney Primary Health Network, Sydney, Australia
| | - Juan C. Quiroz
- Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
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Luo J, Wu S, Rizvi H, Zhang Q, Egger JV, Osorio JC, Schoenfeld AJ, Plodkowski AJ, Ginsberg MS, Callahan MK, Maher C, Shoushtari AN, Postow MA, Voss MH, Kotecha RR, Gupta A, Raja R, Kris MG, Hellmann MD. Deciphering radiological stable disease to immune checkpoint inhibitors. Ann Oncol 2022; 33:824-835. [PMID: 35533926 PMCID: PMC10001430 DOI: 10.1016/j.annonc.2022.04.450] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND 'Stable disease (SD)' as per RECIST is a common but ambiguous outcome in patients receiving immune checkpoint inhibitors (ICIs). This study aimed to characterize SD and identify the subset of patients with SD who are benefiting from treatment. Understanding SD would facilitate drug development and improve precision in correlative research. PATIENTS AND METHODS A systematic review was carried out to characterize SD in ICI trials. SD and objective response were compared to proliferation index using The Cancer Genome Atlas gene expression data. To identify a subgroup of SD with outcomes mirroring responders, we examined a discovery cohort of non-small-cell lung cancer (NSCLC). Serial cutpoints of two variables, % best overall response and progression-free survival (PFS), were tested to define a subgroup of patients with SD with similar survival as responders. Results were then tested in external validation cohorts. RESULTS Among trials of ICIs (59 studies, 14 280 patients), SD ranged from 16% to 42% in different tumor types and was associated with disease-specific proliferation index (ρ = -0.75, P = 0.03), a proxy of tumor kinetics, rather than relative response to ICIs. In a discovery cohort of NSCLC [1220 patients, 313 (26%) with SD to ICIs], PFS ranged widely in SD (0.2-49 months, median 4.9 months). The subset with PFS >6 months and no tumor growth mirrored partial response (PR) minor (overall survival hazard ratio 1.0) and was proposed as the definition of SD responder. This definition was confirmed in two validation cohorts from trials of NSCLC treated with durvalumab and found to apply in tumor types treated with immunotherapy in which depth and duration of benefit were correlated. CONCLUSIONS RECIST-defined SD to immunotherapy is common, heterogeneous, and may largely reflect tumor growth rate rather than ICI response. In patients with NSCLC and SD to ICIs, PFS >6 months and no tumor growth may be considered 'SD responders'. This definition may improve the efficiency of and insight derivable from clinical and translational research.
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Affiliation(s)
- J Luo
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA
| | - S Wu
- Translational Medicine Oncology, AstraZeneca, Gaithersburg, USA
| | - H Rizvi
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Q Zhang
- Translational Medicine Oncology, AstraZeneca, Gaithersburg, USA
| | - J V Egger
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, USA
| | - J C Osorio
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - A J Schoenfeld
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Department of Medicine, Weill Cornell Medical Center, New York, USA
| | - A J Plodkowski
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M S Ginsberg
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M K Callahan
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Parker Institute for Cancer Immunotherapy at Memorial Sloan Kettering Cancer Center, New York, USA; Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - C Maher
- Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - A N Shoushtari
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M A Postow
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M H Voss
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - R R Kotecha
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - A Gupta
- Global Medicines Development, AstraZeneca, Gaithersburg, USA
| | - R Raja
- Translational Medicine Oncology, AstraZeneca, Gaithersburg, USA
| | - M G Kris
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Department of Medicine, Weill Cornell Medical Center, New York, USA
| | - M D Hellmann
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Department of Medicine, Weill Cornell Medical Center, New York, USA; Parker Institute for Cancer Immunotherapy at Memorial Sloan Kettering Cancer Center, New York, USA.
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Ferguson T, Olds T, Curtis R, Blake H, Crozier AJ, Dankiw K, Dumuid D, Kasai D, O'Connor E, Virgara R, Maher C. Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses. Lancet Digit Health 2022; 4:e615-e626. [PMID: 35868813 DOI: 10.1016/s2589-7500(22)00111-x] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/22/2022] [Accepted: 05/27/2022] [Indexed: 05/27/2023]
Abstract
Wearable activity trackers offer an appealing, low-cost tool to address physical inactivity. This systematic review of systematic reviews and meta-analyses (umbrella review) aimed to examine the effectiveness of activity trackers for improving physical activity and related physiological and psychosocial outcomes in clinical and non-clinical populations. Seven databases (Embase, MEDLINE, Ovid Emcare, Scopus, SPORTDiscus, the Cochrane Library, and Web of Science) were searched from database inception to April 8, 2021. Systematic reviews of primary studies using activity trackers as interventions and reporting physical activity, physiological, or psychosocial outcomes were eligible for inclusion. In total, 39 systematic reviews and meta-analyses were identified, reporting results from 163 992 participants spanning all age groups, from both healthy and clinical populations. Taken together, the meta-analyses suggested activity trackers improved physical activity (standardised mean difference [SMD] 0·3-0·6), body composition (SMD 0·7-2·0), and fitness (SMD 0·3), equating to approximately 1800 extra steps per day, 40 min per day more walking, and reductions of approximately 1 kg in bodyweight. Effects for other physiological (blood pressure, cholesterol, and glycosylated haemoglobin) and psychosocial (quality of life and pain) outcomes were typically small and often non-significant. Activity trackers appear to be effective at increasing physical activity in a variety of age groups and clinical and non-clinical populations. The benefit is clinically important and is sustained over time. Based on the studies evaluated, there is sufficient evidence to recommend the use of activity trackers.
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Affiliation(s)
- Ty Ferguson
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Timothy Olds
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Rachel Curtis
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Henry Blake
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Alyson J Crozier
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Kylie Dankiw
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Daiki Kasai
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Edward O'Connor
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Rosa Virgara
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, SA, Australia.
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Watson A, Dumuid D, Maher C, Olds T. Associations between meeting 24-hour movement guidelines and academic achievement in Australian primary school-aged children. J Sport Health Sci 2022; 11:521-529. [PMID: 33359235 PMCID: PMC9338336 DOI: 10.1016/j.jshs.2020.12.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/21/2020] [Accepted: 10/20/2020] [Indexed: 05/12/2023]
Abstract
BACKGROUND Few studies have investigated associations between academic achievement and meeting recommendations from the 24-hour (24-h) movement guidelines. The specific guidelines associated with the most benefit academic achievement are unknown. Utilizing both self-report and objective movement data, this study examined associations between academic achievement and meeting individual recommendations and combinations of recommendations from the 24-h movement guidelines (sleep, physical activity, and screen time). METHODS Data from CheckPoint, a cross-sectional study nested between Waves 6 and 7 of the Longitudinal Study of Australian Children, were used. Movement behaviors were measured using 24-h wrist-worn accelerometry (GENEActiv (Activinsights, Kimbolton, UK)) and were self-reported by children using the Multimedia Activity Recall for Children and Adolescents. Academic achievement was measured using a nationally administered standardized test in literacy and numeracy. Analysis of covariance, with t tests with sequential Bonferroni adjustments, was used to compare academic achievement with all possible combinations of meeting recommendations, adjusting for demographic confounders. Two models were considered: guideline compliance assessed by self-report (n = 1270, mean age = 11.99 years, 52% males) and by accelerometry (for moderate-to-vigorous intensity physical activity (MVPA) and sleep)) and self-report (screen time) in combination (n = 927, mean age = 11.97 years, 52% males). RESULTS Literacy achievement significantly differed based on self-report (F(7, 1258) = 3.08, p = 0.003) and accelerometer derived (F(7, 915) = 2.40, p = 0.02) guideline compliance. Numeracy achievement significantly differed based on self-report (F(7, 1258) = 2.92, p = 0.005) but not accelerometer derived guideline compliance (F(7, 915) = 0.80, p = 0.58). When assessed by self-report, children who met all guidelines (t(334) = -4.05, p = 0.0001) or met the screen time and sleep guidelines in combination (t(125) = -5.02, p < 0.001) had superior literacy achievement. Meeting the self-report MVPA guideline in any combination was associated with higher numeracy scores (p < 0.05). Post-hoc analyses showed no differences in academic achievement for any category of accelerometer derived guideline compliance. CONCLUSION The findings suggest that limiting recreational screen time is important for literacy achievement and that encouraging compliance with the MVPA guideline is important for numeracy achievement.
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Affiliation(s)
- Amanda Watson
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, SA5001, Australia.
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, SA5001, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, SA5001, Australia
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, SA5001, Australia
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Kennewell E, Curtis RG, Maher C, Luddy S, Virgara R. The relationships between school children's wellbeing, socio-economic disadvantage and after-school activities: a cross-sectional study. BMC Pediatr 2022; 22:297. [PMID: 35597918 PMCID: PMC9123778 DOI: 10.1186/s12887-022-03322-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 04/29/2022] [Indexed: 11/12/2022] Open
Abstract
Background Lower socioeconomic status is associated with poorer wellbeing among children. Identifying how children participate in after-school activities and how after-school activities are associated with wellbeing may inform interventions to improve wellbeing among children from low socioeconomic backgrounds. This study explored whether children’s after-school activities varied by socioeconomic status and examined the associations between after-school activities and wellbeing in low socioeconomic status children. Methods This study analysed cross-sectional data from 61,759 school students in years 4 to 9 who completed the 2018 South Australian Wellbeing and Engagement Collection. Students reported the number of days per week they participated in 12 activities (after-school care, homework, music lessons or practice, youth organisations, sports, television, videogames, social media, reading, chores, arts and crafts, and socialising with friends) during the after-school period (3-6 pm) and their wellbeing (happiness, sadness, worry, engagement, perseverance, optimism, emotion regulation, and life satisfaction). Socioeconomic status was measured by parents' highest education level obtained from school enrolment data. Linear multilevel models were used to examine whether frequency of after-school activities varied by socioeconomic status. Multilevel ordered logit models were used to analyse the association between after-school activities and wellbeing amongst participants in the low socioeconomic status category. Results After-school activities differed according to socioeconomic status; high socioeconomic status children did more frequent sport, homework, and reading and low socioeconomic status children did more frequent screen-based activities (TV, videogames and social media). Among children from low socioeconomic status backgrounds, higher wellbeing was associated most consistently with more frequent sports participation, homework, reading and spending time with friends and less frequent videogames, social media and after-school care. Conclusions Children's wellbeing is positively associated with socioeconomic status. Amongst children from disadvantaged backgrounds, participating in sport, spending time with friends and getting less screen time may be protective for wellbeing. The results suggest that programming targeted at increasing sports participation and reducing screen time amongst children from low socioeconomic status backgrounds may support their wellbeing. Supplementary Information The online version contains supplementary material available at 10.1186/s12887-022-03322-1.
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Affiliation(s)
- Eliza Kennewell
- Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia
| | - Rachel G Curtis
- Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia.
| | - Samuel Luddy
- System Performance Division, Government of South Australia Department for Education, 31 Flinders St Adelaide, Adelaide, South Australia, 5001, Australia
| | - Rosa Virgara
- Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia
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Beleigoli A, Nicholls SJ, Brown A, Chew DP, Beltrame J, Maeder A, Maher C, Versace VL, Hendriks JM, Tideman P, Kaambwa B, Zeitz C, Prichard IJ, Tavella R, Tirimacco R, Keech W, Astley C, Govin K, Nesbitt K, Du H, Champion S, Pinero de Plaza MA, Lynch I, Poulsen V, Ludlow M, Wanguhu K, Meyer H, Krollig A, Gebremichael L, Green C, Clark RA. Implementation and prospective evaluation of the Country Heart Attack Prevention model of care to improve attendance and completion of cardiac rehabilitation for patients with cardiovascular diseases living in rural Australia: a study protocol. BMJ Open 2022; 12:e054558. [PMID: 35173003 PMCID: PMC8852732 DOI: 10.1136/bmjopen-2021-054558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
INTRODUCTION Despite extensive evidence of its benefits and recommendation by guidelines, cardiac rehabilitation (CR) remains highly underused with only 20%-50% of eligible patients participating. We aim to implement and evaluate the Country Heart Attack Prevention (CHAP) model of care to improve CR attendance and completion for rural and remote participants. METHODS AND ANALYSIS CHAP will apply the model for large-scale knowledge translation to develop and implement a model of care to CR in rural Australia. Partnering with patients, clinicians and health service managers, we will codevelop new approaches and refine/expand existing ones to address known barriers to CR attendance. CHAP will codesign a web-based CR programme with patients expanding their choices to CR attendance. To increase referral rates, CHAP will promote endorsement of CR among clinicians and develop an electronic system that automatises referrals of in-hospital eligible patients to CR. A business model that includes reimbursement of CR delivered in primary care by Medicare will enable sustainable access to CR. To promote CR quality improvement, professional development interventions and an accreditation programme of CR services and programmes will be developed. To evaluate 12-month CR attendance/completion (primary outcome), clinical and cost-effectiveness (secondary outcomes) between patients exposed (n=1223) and not exposed (n=3669) to CHAP, we will apply a multidesign approach that encompasses a prospective cohort study, a pre-post study and a comprehensive economic evaluation. ETHICS AND DISSEMINATION This study was approved by the Southern Adelaide Clinical Human Research Ethics Committee (HREC/20/SAC/78) and by the Department for Health and Wellbeing Human Research Ethics Committee (2021/HRE00270), which approved a waiver of informed consent. Findings and dissemination to patients and clinicians will be through a public website, online educational sessions and scientific publications. Deidentified data will be available from the corresponding author on reasonable request. TRIAL REGISTRATION NUMBER ACTRN12621000222842.
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Affiliation(s)
- Alline Beleigoli
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Stephen J Nicholls
- Monash Cardiovascular Research Centre, Victorian Heart Institute, Monash University, Melbourne, Victoria, Australia
| | - Alex Brown
- Indigenous Health, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Derek P Chew
- College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - John Beltrame
- The Queen Elizabeth Hospital, Central Adelaide Local Health Network, Adelaide, South Australia, Australia
- Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Anthony Maeder
- Flinders Digital Health Research Centre, Flinders University, Adelaide, South Australia, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Vincent L Versace
- Deakin Rural Health, School of Medicine, Deakin University, Melbourne, Victoria, Australia
| | - Jeroen M Hendriks
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Philip Tideman
- College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
- Integrated Cardiovascular Clinical Network, Rural Support Service, Adelaide, South Australia, Australia
| | - Billingsley Kaambwa
- College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Christopher Zeitz
- Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Ivanka J Prichard
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Rosanna Tavella
- The Queen Elizabeth Hospital, Central Adelaide Local Health Network, Adelaide, South Australia, Australia
- Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Rosy Tirimacco
- Integrated Cardiovascular Clinical Network, Rural Support Service, Adelaide, South Australia, Australia
| | - Wendy Keech
- Health Translation SA, Adelaide, South Australia, Australia
| | - Carolyn Astley
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Kay Govin
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Katie Nesbitt
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Huiyun Du
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Stephanie Champion
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | | | - Imelda Lynch
- National Heart Foundation of Australia, Mawson, Australia Central Territory, Australia
| | - Vanessa Poulsen
- National Heart Foundation of Australia, Mawson, Australia Central Territory, Australia
| | - Marie Ludlow
- National Heart Foundation of Australia, Mawson, Australia Central Territory, Australia
| | - Ken Wanguhu
- Royal Australian College of General Practitioners, Waikerie, Victoria, Australia
| | - Hendrika Meyer
- Rural Support Service, SA Health, Adelaide, South Australia, Australia
| | - Ali Krollig
- Rural Support Service, SA Health, Adelaide, South Australia, Australia
| | - Lemlem Gebremichael
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Chloe Green
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | - Robyn A Clark
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
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Maher C, Szeto K, Arnold J. The use of accelerometer-based wearable activity monitors in clinical settings: current practice, barriers, enablers, and future opportunities. BMC Health Serv Res 2021; 21:1064. [PMID: 34625076 PMCID: PMC8501528 DOI: 10.1186/s12913-021-07096-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/13/2021] [Indexed: 11/10/2022] Open
Abstract
Background Wearable activity monitors (WAMs, e.g. Fitbits and research accelerometers) show promise for helping health care professionals (HCPs) measure and intervene on patients’ activity patterns. This study aimed to describe the clinical use of WAMs within South Australia, barriers and enablers, and future opportunities for large-scale clinical use. Methods A descriptive qualitative study was undertaken using semi-structured interviews. Participants were HCPs with experience using WAMs in South Australian clinical settings. Commencing with participants identified through the research team’s professional networks, snowball recruitment continued until all identified eligible HCPs had been invited. Semi-structured interviews were used to explore the research aims, with quantitative data analysed descriptively, and qualitative data analysed thematically. Results 18 participants (physiotherapists n = 8, exercise physiologists n = 6, medical consultants n = 2, and research personnel recommended by medical consultants n = 2), represented 12 discrete “hubs” of WAM use in clinical practice, spanning rehabilitation, orthopaedics, geriatrics, intensive care, and various inpatient-, outpatient-, community-based hospital and private-practice settings. Across the 12 hubs, five primarily used Fitbits® (various models), four used research-grade accelerometers (e.g. GENEActiv, ActivPAL and StepWatch accelerometers), one used Whoop Bands® and another used smartphone-based step counters. In three hubs, WAMs were used to observe natural activity levels without intervention, while in nine they were used to increase (i.e. intervene on) activity. Device selection was typically based on ease of availability (e.g. devices borrowed from another department) and cost-economy (e.g. Fitbits® are relatively affordable compared with research-grade devices). Enablers included device characteristics (e.g. accuracy, long battery life, simple metrics such as step count) and patient characteristics (e.g. motivation, rehabilitation population, tech-savvy), whilst barriers included the HCPs’ time to download and interpret the data, multidisciplinary team attitudes and lack of protocols for managing the devices. Conclusions At present, the use of WAMs in clinical practice appears to be fragmented and ad hoc, though holds promise for understanding patient outcomes and enhancing therapy. Future work may focus on developing protocols for optimal use, system-level approaches, and generating cost-benefit data to underpin continued health service funding for ongoing/wide-spread WAM use. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-021-07096-7.
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Affiliation(s)
- Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health & Human Performance, University of South Australia, GPO Box 2471, SA, 5001, Adelaide, Australia.
| | - Kimberley Szeto
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health & Human Performance, University of South Australia, GPO Box 2471, SA, 5001, Adelaide, Australia
| | - John Arnold
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health & Human Performance, University of South Australia, GPO Box 2471, SA, 5001, Adelaide, Australia.,Innovation, Implementation and Clinical Translation in Health (IIMPACT in Health), Allied Health & Human Performance, University of South Australia, SA, Adelaide, Australia
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Hutchesson MJ, Gough C, Müller AM, Short CE, Whatnall MC, Ahmed M, Pearson N, Yin Z, Ashton LM, Maher C, Staiano AE, Mauch CE, DeSmet A, Vandelanotte C. eHealth interventions targeting nutrition, physical activity, sedentary behavior, or obesity in adults: A scoping review of systematic reviews. Obes Rev 2021; 22:e13295. [PMID: 34159684 DOI: 10.1111/obr.13295] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 04/28/2021] [Accepted: 05/05/2021] [Indexed: 12/11/2022]
Abstract
A vast body of evidence regarding eHealth interventions for nutrition, physical activity, sedentary behavior, and obesity exists. This scoping review of systematic reviews aimed to evaluate the current level of evidence in this growing field. Seven electronic databases were searched for systematic reviews published until October 27, 2019. The systematic reviews must have included adult participants only and have evaluated eHealth behavioral interventions with the primary aim of changing nutrition, physical activity, and sedentary behavior or treating or preventing overweight and obesity. One hundred and six systematic reviews, published from 2006 to 2019, were included. Almost all (n = 98) reviews evaluated the efficacy of interventions. Over half (n = 61) included interventions focused on physical activity, followed by treatment of obesity (n = 28), nutrition (n = 22), prevention of obesity (n = 18), and sedentary behavior (n = 6). Many reviews (n = 46) evaluated one type of eHealth intervention only, while 60 included two or more types. Most reviews (n = 67) were rated as being of critically low methodological quality. This scoping review identified an increasing volume of systematic reviews evaluating eHealth interventions. It highlights several evidence gaps (e.g., evaluation of other outcomes, such as reach, engagement, or cost effectiveness), guiding future research efforts in this area.
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Affiliation(s)
- Melinda J Hutchesson
- School of Health Sciences, College of Health, Medicine and Wellbeing, and Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, New South Wales, Australia
| | - Claire Gough
- Flinders Digital Health Research Centre, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia.,Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia
| | | | - Camille E Short
- Melbourne School of Psychological Sciences and Melbourne School of Health Sciences, Faculty of Dentistry, Medicine and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Megan C Whatnall
- School of Health Sciences, College of Health, Medicine and Wellbeing, and Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, New South Wales, Australia
| | - Mavra Ahmed
- Department of Nutritional Sciences and Joannah and Brian Lawson Centre for Child Nutrition, University of Toronto, Toronto, Ontario, Canada
| | - Nicole Pearson
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia
| | - Zenong Yin
- UT Health San Antonio Graduate School of Biomedical Sciences, University of Texas, San Antonio, Texas, USA
| | - Lee M Ashton
- School of Health Sciences, College of Health, Medicine and Wellbeing, and Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, New South Wales, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Amanda E Staiano
- Population and Public Health, Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
| | - Chelsea E Mauch
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia.,Nutrition and Health Program, Health & Biosecurity Business Unit, CSIRO, Canberra, ACT, Australia
| | - Ann DeSmet
- Faculty of Psychology and Educational Sciences, Université Libre de Bruxelles, Brussels, Belgium.,Department of Communication Studies, University of Antwerp, Antwerp, Belgium
| | - Corneel Vandelanotte
- Physical Activity Research Group, Appleton Institute, Central Queensland University, Rockhampton, Queensland, Australia
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Virgara R, Phillips A, Lewis LK, Baldock K, Wolfenden L, Ferguson T, Richardson M, Okely A, Beets M, Maher C. Interventions in outside-school hours childcare settings for promoting physical activity amongst schoolchildren aged 4 to 12 years. Cochrane Database Syst Rev 2021; 9:CD013380. [PMID: 34694005 PMCID: PMC8543676 DOI: 10.1002/14651858.cd013380.pub2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
BACKGROUND Insufficient physical activity is one of four primary risk factors for non-communicable diseases such as stroke, heart disease, type 2 diabetes, cancer and chronic lung disease. As few as one in five children aged 5 to 17 years have the physical activity recommended for health benefits. The outside-school hours period contributes around 30% of children's daily physical activity and presents a key opportunity for children to increase their physical activity. Testing the effects of interventions in outside-school hours childcare settings is required to assess the potential to increase physical activity and reduce disease burden. OBJECTIVES To assess the effectiveness, cost-effectiveness and associated adverse events of interventions designed to increase physical activity in children aged 4 to 12 years in outside-school hours childcare settings. SEARCH METHODS We searched CENTRAL, MEDLINE, Embase, ERIC and SportsDISCUS to identify eligible trials on 18 August 2020. We searched two databases, three trial registries, reference lists of included trials and handsearched two physical activity journals in August 2020. We contacted first and senior authors on articles identified for inclusion for ongoing or unpublished potentially relevant trials in August 2020. SELECTION CRITERIA We included randomised controlled trials, including cluster-randomised controlled trials, of any intervention primarily aimed at increasing physical activity in children aged 4 to 12 years in outside-school hours childcare settings compared to usual care. To be eligible, the interventions must have been delivered in the context of an existing outside-school hours childcare setting (i.e. childcare that was available consistently throughout the school week/year), and not set up in the after-school period for the purpose of research. Two review authors independently screened titles and abstracts of identified papers with discrepancies resolved via a consensus discussion. A third review author was not required to resolve disagreements. DATA COLLECTION AND ANALYSIS Two review authors independently extracted data and assessed the risk of bias of included trials with discrepancies resolved via a consensus discussion; a third review author was not required to resolve disagreements. For continuous measures of physical activity, we reported the mean difference (MD) with 95% confidence intervals (CIs) in random-effects models using the generic inverse variance method for each outcome. For continuous measures, when studies used different scales to measure the same outcome, we used standardised mean differences (SMDs). We conducted assessments of risk of bias of all outcomes and evaluated the certainty of evidence (GRADE approach) using standard Cochrane procedures. MAIN RESULTS We included nine trials with 4458 participants. Five trials examined the effectiveness of staff-based interventions to change practice in the outside-school hours childcare setting (e.g. change in programming, activities offered by staff, staff facilitation/training). Two trials examined the effectiveness of staff- and parent-based interventions (e.g. parent newsletters/telephone calls/messages or parent tool-kits in addition to staff-based interventions), one trial assessed staff- and child-based intervention (e.g. children had home activities to emphasise physical activity education learnt during outside-school hours childcare sessions in addition to staff-based interventions) and one trial assessed child-only based intervention (i.e. only children were targeted). We judged two trials as free from high risk of bias across all domains. Of those studies at high risk of bias, it was across domains of randomisation process, missing outcome data and measurement of the outcome. There was low-certainty evidence that physical activity interventions may have little to no effect on total daily moderate-to-vigorous physical activity compared to no intervention (MD 1.7 minutes, 95% CI -0.42 to 3.82; P = 0.12; 6 trials; 3042 children). We were unable to pool data on proportion of the OSHC session spent in moderate-to-vigorous physical activity in a meta-analysis. Both trials showed an increase in proportion of session spent in moderate-to-vigorous physical activity (moderate-certainty evidence) from 4% to 7.3% of session time; however, only one trial was statistically significant. There was low-certainty evidence that physical activity interventions may lead to little to no reduction in body mass index (BMI) as a measure of cardiovascular health, compared to no intervention (SMD -0.17, 95% CI -0.44 to 0.10; P = 0.22; 4 trials, 1684 children). Physical activity interventions that were delivered online were more cost-effective than in person. Combined results suggest that staff-and-parent and staff-and-child-based interventions may lead to a small increase in overall daily physical activity and a small reduction or no difference in BMI. Process evaluation was assessed differently by four of the included studies, with two studies reporting improvements in physical activity practices, one reporting high programme satisfaction and one high programme fidelity. The certainty of the evidence for these outcomes was low to moderate. Finally, there was very low-certainty evidence that physical activity interventions in outside-school hours childcare settings may increase cardiovascular fitness. No trials reported on quality of life or adverse outcomes. Trials reported funding from local government health grants or charitable funds; no trials reported industry funding. AUTHORS' CONCLUSIONS Although the review included nine trials, the evidence for how to increase children's physical activity in outside-school hours care settings remains limited, both in terms of certainty of evidence and magnitude of the effect. Of the types of interventions identified, when assessed using GRADE there was low-certainty evidence that multi-component interventions, with a specific physical activity goal may have a small increase in daily moderate-to-vigorous physical activity and a slight reduction in BMI. There was very low-certainty evidence that interventions increase cardiovascular fitness. By contrast there was moderate-certainty evidence that interventions were effective for increasing proportion of time spent in moderate-to-vigorous physical activity, and online training is cost-effective.
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Affiliation(s)
- Rosa Virgara
- Allied Health and Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia
| | - Anna Phillips
- Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Lucy K Lewis
- College of Nursing and Health Sciences, Flinders University, Bedford Park, Australia
| | - Katherine Baldock
- Allied Health and Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia
| | - Luke Wolfenden
- School of Medicine and Public Health, The University of Newcastle, Callaghan, Australia
| | - Ty Ferguson
- Allied Health and Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia
| | - Mandy Richardson
- Outside School Hours Care (OSHC) Service, St Pius X School, Windsor Gardens, Australia
| | - Anthony Okely
- Early Start Research Institute, University of Wollongong, Wollongong, Australia
| | - Michael Beets
- Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Carol Maher
- Allied Health and Human Performance, Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia
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Potter A, Pancholi B, Smith L, Maher C. Should the physiotherapy outcomes airway clearance, physical activity and fitness be recorded on the Australian Cystic Fibrosis Data Registry? A consensus approach. BMC Pulm Med 2021; 21:298. [PMID: 34548053 PMCID: PMC8456641 DOI: 10.1186/s12890-021-01669-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 09/01/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Physiotherapy is a cornerstone of cystic fibrosis (CF) management, yet the Australian CF Data Registry (ACFDR) currently does not record physiotherapy-related data. This study aimed to gather opinions from lead Australian CF physiotherapists regarding the importance and feasibility of collecting physiotherapy-related data on the ACFDR. METHODS A three-round online Delphi survey was conducted to gather expert stakeholder opinion and consensus agreement. Lead physiotherapists from all 23 Australian CF centres were invited to participate. Round one explored the potential benefits, barriers and importance of recording three physiotherapy-related domains on the ACFDR: airway clearance, physical activity and fitness. Subsequent rounds were developed based on the findings from the previous round and sought consensus (80% agreement) for the inclusion of physiotherapy-related data on the ACFDR and for the most appropriate methods of collecting such data. RESULTS The response rate was > 80% for all rounds. Participants agreed that collection of airway clearance, physical activity and fitness data on the ACFDR was important and feasible. Findings suggested that airway clearance and physical activity should be collected using self-reported questionnaires, while fitness should be measured using a field-based test. CONCLUSIONS Australian lead CF physiotherapists believe that collection of airway clearance, physical activity and fitness on the ACFDR is important and feasible. Future work is needed to pilot the data collection procedure to examine its feasibility in real-world clinical settings. This study demonstrates how Delphi methodology can provide a contemporary summary of expert clinicians' opinion that may underpin nation-wide health service improvement.
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Affiliation(s)
- Angela Potter
- Physiotherapy Department, Women's and Children's Hospital, SA Health, 72 King William Rd, North Adelaide, SA, 5006, Australia
| | - Bhavita Pancholi
- Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Lahni Smith
- Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Carol Maher
- Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia. .,Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
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Stanton TR, Braithwaite FA, Butler D, Moseley GL, Hill C, Milte R, Ratcliffe J, Maher C, Tomkins-Lane C, Pulling BW, MacIntyre E, Esterman A, Stanford T, Lee H, Fraysse F, Metcalf B, Mouatt B, Bennell K. The EPIPHA-KNEE trial: Explaining Pain to target unhelpful pain beliefs to Increase PHysical Activity in KNEE osteoarthritis - a protocol for a multicentre, randomised controlled trial with clinical- and cost-effectiveness analysis. BMC Musculoskelet Disord 2021; 22:738. [PMID: 34454458 PMCID: PMC8401372 DOI: 10.1186/s12891-021-04561-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 07/12/2021] [Indexed: 12/29/2022] Open
Abstract
Background Despite well-established benefits of physical activity for knee osteoarthritis (OA), nine of ten people with knee OA are inactive. People with knee OA who are inactive often believe that physical activity is dangerous, fearing that it will further damage their joint(s). Such unhelpful beliefs can negatively influence physical activity levels. We aim to evaluate the clinical- and cost-effectiveness of integrating physiotherapist-delivered pain science education (PSE), an evidence-based conceptual change intervention targeting unhelpful pain beliefs by increasing pain knowledge, with an individualised walking, strengthening, and general education program. Methods Two-arm, parallel-design, multicentre randomised controlled trial involving 198 people aged ≥50 years with painful knee OA who do not meet physical activity guideline recommendations or walk regularly for exercise. Both groups receive an individualised physiotherapist-led walking, strengthening, and OA/activity education program via 4x weekly in-person treatment sessions, followed by 4 weeks of at-home activities (weekly check-in via telehealth), with follow-up sessions at 3 months (telehealth) and 5 and 9 months (in-person). The EPIPHA-KNEE group also receives contemporary PSE about OA/pain and activity, embedded into all aspects of the intervention. Outcomes are assessed at baseline, 12 weeks, 6 and 12 months. Primary outcomes are physical activity level (step count; wrist-based accelerometry) and self-reported knee symptoms (WOMAC Total score) at 12 months. Secondary outcomes are quality of life, pain intensity, global rating of change, self-efficacy, pain catastrophising, depression, anxiety, stress, fear of movement, knee awareness, OA/activity conceptualisation, and self-regulated learning ability. Additional measures include adherence, adverse events, blinding success, COVID-19 impact on activity, intention to exercise, treatment expectancy/perceived credibility, implicit movement/environmental bias, implicit motor imagery, two-point discrimination, and pain sensitivity to activity. Cost-utility analysis of the EPIPHA-KNEE intervention will be undertaken, in addition to evaluation of cost-effectiveness in the context of primary trial outcomes. Discussion We will determine whether the integration of PSE into an individualised OA education, walking, and strengthening program is more effective than receiving the individualised program alone. Findings will inform the development and implementation of future delivery of PSE as part of best practice for people with knee OA. Trial registration Australian New Zealand Clinical Trials Registry: ACTRN12620001041943 (13/10/2020). Supplementary Information The online version contains supplementary material available at 10.1186/s12891-021-04561-6.
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Affiliation(s)
- Tasha R Stanton
- IIMPACT in Health, Allied Health and Human Performance, University of South Australia, G.P.O. Box 2471, Adelaide, 5001, Australia.
| | - Felicity A Braithwaite
- IIMPACT in Health, Allied Health and Human Performance, University of South Australia, G.P.O. Box 2471, Adelaide, 5001, Australia
| | - David Butler
- IIMPACT in Health, Allied Health and Human Performance, University of South Australia, G.P.O. Box 2471, Adelaide, 5001, Australia.,NOIgroup Pty Ltd, Adelaide, South Australia
| | - G Lorimer Moseley
- IIMPACT in Health, Allied Health and Human Performance, University of South Australia, G.P.O. Box 2471, Adelaide, 5001, Australia
| | - Catherine Hill
- Rheumatology Department, The Queen Elizabeth Hospital, Adelaide, Australia.,Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, Australia
| | - Rachel Milte
- Caring Futures Institute, Flinders University, Adelaide, Australia
| | - Julie Ratcliffe
- Caring Futures Institute, Flinders University, Adelaide, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Christy Tomkins-Lane
- Department of Health and Physical Education, Mount Royal University, Calgary, Canada
| | - Brian W Pulling
- IIMPACT in Health, Allied Health and Human Performance, University of South Australia, G.P.O. Box 2471, Adelaide, 5001, Australia
| | - Erin MacIntyre
- IIMPACT in Health, Allied Health and Human Performance, University of South Australia, G.P.O. Box 2471, Adelaide, 5001, Australia
| | - Adrian Esterman
- Clinical & Health Sciences, University of South Australia, Adelaide, Australia
| | - Ty Stanford
- Clinical & Health Sciences, University of South Australia, Adelaide, Australia
| | - Hopin Lee
- Centre for Statistics in Medicine, Rehabilitation Research in Oxford (RRIO), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK.,School of Medicine and Public Health, University of Newcastle, Newcastle, Australia
| | - Francois Fraysse
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Ben Metcalf
- Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, The University of Melbourne, Victoria, Australia
| | - Brendan Mouatt
- IIMPACT in Health, Allied Health and Human Performance, University of South Australia, G.P.O. Box 2471, Adelaide, 5001, Australia
| | - Kim Bennell
- Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, The University of Melbourne, Victoria, Australia
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Northcott C, Curtis R, Bogomolova S, Olds T, Vandelanotte C, Plotnikoff R, Maher C. Should Facebook advertisements promoting a physical activity smartphone app be image or video-based, and should they promote benefits of being active or the app attributes? Transl Behav Med 2021; 11:2136-2143. [PMID: 34398963 DOI: 10.1093/tbm/ibab101] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Social media provides a convenient platform for health campaigns. However, practitioners designing such campaigns are faced with a number of decisions regarding advertising formats and appeals. This study set out to compare the effectiveness of two advertising formats (image vs. video) and two advertising appeals (benefits of being active vs. app attributes and features) for promoting a physical-activity smartphone app. The advertising experiment was conducted on Facebook and employed a 2 × 2 full-factorial experimental design, examining two advertising formats: image versus video and two advertising appeals: benefit versus attribute. Outcome measures were advertisement cost (number of viewers reached according to the amount spent) and consumer engagement (rates of advertisement click-through and app downloads). Chi-Square analysis revealed that advertisement cost was found to differ according to the type of advertising format used, with image advertisements achieving a greater audience reach than video advertisements (χ 2(1) = 905.292, p < .001). Consumer engagement also differed according to advertising format and appeal: images achieved high rates of advertisement click-through (2.7% vs. 1.9%; χ 2(1) = 196.9, p < .001) and app downloads (0.6% vs. 0.5%; χ 2(1) = 4.0, p = .044) compared with videos. Furthermore, benefit appeal advertisements were more effective than attribute appeals, yielding a greater rate of advertisement click-through (2.8% vs. 1.8%; χ 2(1) = 282.2, p < .001) and app downloads (0.7% vs. 0.4%; χ 2(1) =106.0, p < .001). Overall, image advertisements were seen to be the most cost-effective and engaging. Advertisements employing a benefit appeal achieved greater consumer engagement than and attribute appeal advertisements.
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Affiliation(s)
- Celine Northcott
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Rachel Curtis
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Svetlana Bogomolova
- Ehrenberg-Bass Institute for Marketing Science, UniSA Business, University of South Australia, Adelaide, Australia
| | - Timothy Olds
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Corneel Vandelanotte
- Physical Activity Research Group, Appleton Institute, Central Queensland University, Rockhampton, Australia
| | - Ronald Plotnikoff
- School of Medicine & Public Health; Faculty of Health and Medicine, Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Callaghan, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, Australia
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Northcott C, Curtis R, Bogomolova S, Olds T, Vandelanotte C, Plotnikoff R, Maher C. Evaluating the effectiveness of a physical activity social media advertising campaign using Facebook, Facebook Messenger, and Instagram. Transl Behav Med 2021; 11:870-881. [PMID: 33484152 DOI: 10.1093/tbm/ibaa139] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Technology-based physical activity programs are a novel solution to the major public health issue of physical inactivity. However, to be successful, there must be a large and population-appropriate uptake, which depends heavily on promotion. This study evaluates the effectiveness of an advertising campaign to disseminate a physical activity smartphone app. The experiment used a 3 × 3 × 3 full-factorial design, examining platforms (Facebook; Facebook Messenger; Instagram), selling-techniques (hard-sell-sending viewers directly to (a) Apple Store or (b) Google Play, and soft-sell-sending viewers from an ad to a (c) landing-page, then to an app store) and themes (Health and Wellbeing; Body and Self-Confidence; Social Enjoyment). Outcomes were reach, click-through, and app downloads. Advertisements reached 1,373,273 people, achieving 2,989 clicks and 667 downloads. Instagram and Facebook Messenger had higher reach compared to Facebook (F[2,27] = 27.17, p < .001), whilst Facebook and Facebook Messenger both produced higher click-through (F[2,27] = 8.98, p < .001) and downloads (F[2,27] = 4.649, p = .018). Selling-technique differed, with soft-selling ads producing greater reach (F[2,27] = 4,616.077, p < .001); however, both hard-selling ads (Apple Store and Google Play) had greater click-through (F[2,27] = 10.77, p < .001) and downloads (F[2,27] = 3.791, p < .001). Advertising theme varied, with Social Enjoyment themes producing less click-through (F[2,27] = 5.709, p = .009) and downloads (F[2,27] = 5.480, p = .010). We recommend future studies to consider Facebook and Facebook Messenger, using hard-selling techniques, with themes relating to Health and Wellbeing and Body and Self-Confidence.
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Affiliation(s)
- Celine Northcott
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia
| | - Rachel Curtis
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia
| | - Svetlana Bogomolova
- Ehrenberg-Bass Institute for Marketing Science, University of South Australia, Adelaide, Australia
| | - Timothy Olds
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia
| | - Corneel Vandelanotte
- Physical Activity Research Group, Central Queensland University, Rockhampton, Australia
| | - Ronald Plotnikoff
- Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Callaghan, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia
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Miatke A, Maher C, Fraysse F, Dumuid D, Olds T. Are all MVPA minutes equal? Associations between MVPA characteristics, independent of duration, and childhood adiposity. BMC Public Health 2021; 21:1321. [PMID: 34225692 PMCID: PMC8259325 DOI: 10.1186/s12889-021-11420-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 06/30/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The inverse relationship between moderate-to-vigorous physical activity (MVPA) duration and childhood adiposity is well established. Less is known about how characteristics of MVPA accumulation may be associated with adiposity, independent of MVPA duration. This study aimed to investigate how the MVPA characteristics of children, other than duration (bout length, time of day, day-to-day consistency, intensity), were associated with adiposity. METHODS Cross-sectional study of the Australian arm of the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) (participants: n = 424, age range 9-11, 44% male). Adiposity was determined by percent body fat via bioelectrical impedance. MVPA duration and characteristics (bout length, time of day, consistency, intensity) were derived from 7-day, 24-h accelerometry. Generalised estimating equations were used to examine the individual and multivariate associations between MVPA characteristics and adiposity. RESULTS Univariate analyses showed that higher MVPA duration (β range = - 0.26,-0.15), longer bouts of MVPA (β range = 0.15,0.22) and higher MVPA intensity (β range = - 0.20,-0.13) were all inversely associated with adiposity (all p < 0.05). When models were adjusted for MVPA duration, only MVPA intensity (β range = - 0.16,-0.04) showed consistent significant associations with adiposity. CONCLUSIONS Characteristics of MVPA other than duration and intensity appear to be unrelated to adiposity.
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Affiliation(s)
- Aaron Miatke
- Alliance for Research in Exercise, Nutrition & Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, Australia. .,Present address: Centre for Adolescent Health, Level 5, Murdoch Children's Research Centre, Royal Children's Hospital, 50 Flemington Road, Parkville, 3052, Australia.
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition & Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - François Fraysse
- Alliance for Research in Exercise, Nutrition & Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Dot Dumuid
- Alliance for Research in Exercise, Nutrition & Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition & Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, Australia
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Stamatakis E, Huang BH, Maher C, Thøgersen-Ntoumani C, Stathi A, Dempsey PC, Johnson N, Holtermann A, Chau JY, Sherrington C, Daley AJ, Hamer M, Murphy MH, Tudor-Locke C, Gibala MJ. Untapping the Health Enhancing Potential of Vigorous Intermittent Lifestyle Physical Activity (VILPA): Rationale, Scoping Review, and a 4-Pillar Research Framework. Sports Med 2021; 51:1-10. [PMID: 33108651 PMCID: PMC7806564 DOI: 10.1007/s40279-020-01368-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Recently revised public health guidelines acknowledge the health benefits of regular intermittent bouts of vigorous intensity incidental physical activity done as part of daily living, such as carrying shopping bags, walking uphill, and stair climbing. Despite this recognition and the advantages such lifestyle physical activity has over continuous vigorous intensity structured exercise, a scoping review we conducted revealed that current research in this area is, at best, rudimentary. Key gaps include the absence of an empirically-derived dose specification (e.g., minimum duration of lifestyle physical activity required to achieve absolute or relative vigorous intensity), lack of acceptable measurement standards, limited understanding of acute and chronic (adaptive) effects of intermittent vigorous bouts on health, and paucity of essential information necessary to develop feasible and scalable interventions (e.g., acceptability of this kind of physical activity by the public). To encourage collaboration and research agenda alignment among groups interested in this field, we propose a research framework to further understanding of vigorous intermittent lifestyle physical activity (VILPA). This framework comprises four pillars aimed at the development of: (a) an empirical definition of VILPA, (b) methods to reliably and accurately measure VILPA, (c) approaches to examine the short and long-term dose-response effects of VILPA, and (d) scalable and acceptable behavioural VILPA-promoting interventions.
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Affiliation(s)
- Emmanuel Stamatakis
- School of Health Sciences, Charles Perkins Centre, The University of Sydney, Faculty of Medicine and Health, Hub D17, L6 West, Sydney, NSW, Australia.
| | - Bo-Huei Huang
- School of Health Sciences, Charles Perkins Centre, The University of Sydney, Faculty of Medicine and Health, Hub D17, L6 West, Sydney, NSW, Australia
| | - Carol Maher
- Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Cecilie Thøgersen-Ntoumani
- Physical Activity and Well-Being Research Group, School of Psychology, Curtin University, Perth, Australia
| | - Afroditi Stathi
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK
| | - Paddy C Dempsey
- Physical Activity and Behavioural Epidemiology Laboratories, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Nathan Johnson
- School of Health Sciences, Charles Perkins Centre, The University of Sydney, Faculty of Medicine and Health, Hub D17, L6 West, Sydney, NSW, Australia
| | - Andreas Holtermann
- National Research Centre for the Working Environment (NRCWE), Copenhagen, Denmark
| | - Josephine Y Chau
- Department of Health Systems and Populations, Macquarie University, Sydney, Australia
| | - Catherine Sherrington
- Institute of Musculoskeletal Health, University of Sydney, Sydney School of Public Health, Faculty of Medicine and Health, Sydney, Australia
| | - Amanda J Daley
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Mark Hamer
- Institute Sport Exercise Health, Faculty Medical Sciences, University College London, London, UK
| | - Marie H Murphy
- Doctoral College, Ulster University, Newtownabbey, Co Antrim, BT37 0QB, Northern Ireland, UK
| | - Catrine Tudor-Locke
- Department of Kinesiology, College of Health and Human Services, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Martin J Gibala
- Department of Kinesiology, McMaster University, Hamilton, ON, Canada
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Gao B, Giraud S, Li KA, Sieverding A, Zegers RGT, Tang X, Ash J, Ayyad-Limonge Y, Bazin D, Biswas S, Brown BA, Chen J, DeNudt M, Farris P, Gabler JM, Gade A, Ginter T, Grinder M, Heger A, Hultquist C, Hill AM, Iwasaki H, Kwan E, Li J, Longfellow B, Maher C, Ndayisabye F, Noji S, Pereira J, Qi C, Rebenstock J, Revel A, Rhodes D, Sanchez A, Schmitt J, Sumithrarachchi C, Sun BH, Weisshaar D. New ^{59}Fe Stellar Decay Rate with Implications for the ^{60}Fe Radioactivity in Massive Stars. Phys Rev Lett 2021; 126:152701. [PMID: 33929230 DOI: 10.1103/physrevlett.126.152701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/20/2021] [Accepted: 03/17/2021] [Indexed: 06/12/2023]
Abstract
The discrepancy between observations from γ-ray astronomy of the ^{60}Fe/^{26}Al γ-ray flux ratio and recent calculations is an unresolved puzzle in nuclear astrophysics. The stellar β-decay rate of ^{59}Fe is one of the major nuclear uncertainties impeding us from a precise prediction. The important Gamow-Teller strengths from the low-lying states in ^{59}Fe to the ^{59}Co ground state are measured for the first time using the exclusive measurement of the ^{59}Co(t,^{3}He+γ)^{59}Fe charge-exchange reaction. The new stellar decay rate of ^{59}Fe is a factor of 3.5±1.1 larger than the currently adopted rate at T=1.2 GK. Stellar evolution calculations show that the ^{60}Fe production yield of an 18 solar mass star is decreased significantly by 40% when using the new rate. Our result eliminates one of the major nuclear uncertainties in the predicted yield of ^{60}Fe and alleviates the existing discrepancy of the ^{60}Fe/^{26}Al ratio.
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Affiliation(s)
- B Gao
- CAS Key Laboratory of High Precision Nuclear Spectroscopy, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 73000, People's Republic of China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S Giraud
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - K A Li
- CAS Key Laboratory of High Precision Nuclear Spectroscopy, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 73000, People's Republic of China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - A Sieverding
- School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R G T Zegers
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics-Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - X Tang
- CAS Key Laboratory of High Precision Nuclear Spectroscopy, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 73000, People's Republic of China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J Ash
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - Y Ayyad-Limonge
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - D Bazin
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - S Biswas
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - B A Brown
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics-Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - J Chen
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - M DeNudt
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - P Farris
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - J M Gabler
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - A Gade
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics-Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - T Ginter
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - M Grinder
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - A Heger
- School of Physics and Astronomy, Monash University, Victoria 3800, Australia
| | - C Hultquist
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - A M Hill
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - H Iwasaki
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - E Kwan
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - J Li
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - B Longfellow
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - C Maher
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - F Ndayisabye
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - S Noji
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics-Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
| | - J Pereira
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics-Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
| | - C Qi
- Department of Physics, Royal Institute of Technology, Stockholm 10691, Sweden
| | - J Rebenstock
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - A Revel
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - D Rhodes
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - A Sanchez
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - J Schmitt
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
- Joint Institute for Nuclear Astrophysics-Center for the Evolution of the Elements, Michigan State University, East Lansing, Michigan 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA
| | - C Sumithrarachchi
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
| | - B H Sun
- School of Physics, Beihang University, Beijing 100191, China
- International Research Center for Nuclei and Particles in the Cosmos, Beijing 100191, China
| | - D Weisshaar
- National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, Michigan 48824, USA
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Northcott C, Curtis R, Bogomolova S, Olds T, Vandelanotte C, Plotnikoff R, Maher C. Seasonal Differences in the Cost and Engagement of Facebook Advertisements for a Physical Activity Smartphone App. Am J Health Promot 2021; 35:803-808. [PMID: 33641453 DOI: 10.1177/0890117121997304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
PURPOSE To evaluate the performance of Facebook advertisements for a physical activity smartphone app at different times of the year. DESIGN A repeated cross-sectional study examined the cost and engagement levels of advertisements during 3 time points: Post-Easter April-May 2019, Pre-Summer October 2019, and New Year January 2020 . SETTING Advertisements were delivered on Facebook. SUBJECTS The target population was Australian females aged 25-60 years. MEASURES Cost was evaluated in terms of reach per dollar. Engagement was evaluated in terms of click-through and app downloads per reach. ANALYSIS ANOVA and Chi-square were used to assess differences in reach per dollar, click-through, and app downloads per reach between time points. RESULTS Reach per dollar was highest in Post-Easter, but declined in Pre-Summer and New Year (reach/$ 34.8 vs 31.5 vs 27.5; p = .004). Click-through was highest in New Year followed by Post-Easter, then Pre-Summer (click-through 3.2% vs 1.9% vs 1.2%; p < .001). New Year and Post-Easter advertisements achieved higher app downloads per reach than Pre-Summer (downloads 0.9% vs 0.7% vs 0.3%; p < .001). CONCLUSION Facebook advertisements were cheaper in the first time-point, and appear to be getting more expensive (i.e. declining reach/$). Advertisements in the New Year achieved the highest click-through and app downloads per reach, suggesting a useful time of year to promote physical activity products.
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Affiliation(s)
- Celine Northcott
- Alliance for Research in Exercise, Nutrition and Activity, 1067University of South Australia, Adelaide, Australia
| | - Rachel Curtis
- Alliance for Research in Exercise, Nutrition and Activity, 1067University of South Australia, Adelaide, Australia
| | - Svetlana Bogomolova
- Ehrenberg-Bass Institute for Marketing Science, 1067University of South Australia, Adelaide, Australia
| | - Timothy Olds
- Alliance for Research in Exercise, Nutrition and Activity, 1067University of South Australia, Adelaide, Australia
| | - Corneel Vandelanotte
- Physical Activity Research Group, 6939Central Queensland University, Rockhampton, Australia
| | - Ronald Plotnikoff
- Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Callaghan, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition and Activity, 1067University of South Australia, Adelaide, Australia
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Virgara R, Phillips A, Lewis L, Richardson M, Maher C. Development of Australian physical activity and screen time guidelines for outside school hours care: an international Delphi study. Int J Behav Nutr Phys Act 2021; 18:3. [PMID: 33407628 PMCID: PMC7789289 DOI: 10.1186/s12966-020-01061-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 11/20/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Children's activity patterns in the periods before and after school make a key contribution to achieving 24-h movement guidelines. There are currently no national-level guidelines informing physical activity and screen time practices in Outside School Hours Care (OSHC) programs anywhere in the world. This study aimed to work with industry, government and academic stakeholders to develop draft physical activity and screen time guidelines for use in Australian OSHC. METHODS A 4-round online Delphi survey was conducted from May 2019 to January 2020. The Delphi participants included national and international experts and stakeholders from academia, education, government, health and the OSHC sectors. Round 1 consisted of open-ended questions exploring physical activity, screen time and sedentary behaviour in various periods of OSHC (before school, after school and vacation care). In rounds 2 and 3, participants rated the importance of items generated from the first round for inclusion in national guidelines using a Likert scale (1-9). Consensus was defined a priori as ≥80% of respondents rating an item as "critically important" (score 7-9). Between rounds 3 and 4, the guideline development panel used the consensus items, systematic review evidence, and followed the GRADE process, to draft the guidelines. In round 4, participants were invited to provide feedback on the draft guidelines and comment on barriers and enablers to implementation. RESULTS Sixty-seven stakeholders agreed to participate, with response rates 61, 81, 54 and 72% for the four rounds respectively. Of the 123 items generated across the three rounds, 48 statements achieved consensus agreement as critically important for inclusion in the guidelines. These included offering a variety of physical activities (free play, playground and equipment) and restriction of screen time. The final round provided feedback on the draft guidelines. The wording of the guidelines was found to be appropriate and preliminary enablers and barriers to implementation were identified. CONCLUSIONS This world-first expert and stakeholder consultation has underpinned the development of the draft Australian guidelines for physical activity and screen time in OSHC. Ongoing work is needed to further refine the guidelines, determine current rates of compliance with the guidelines and implement the guidelines into practice.
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Affiliation(s)
- Rosa Virgara
- Allied Health and Human Performance, University of South Australia, c/o GPO Box 2471, SA, 5001, Adelaide, Australia.
| | - Anna Phillips
- Allied Health and Human Performance, University of South Australia, c/o GPO Box 2471, SA, 5001, Adelaide, Australia
| | - Lucy Lewis
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, Australia
| | | | - Carol Maher
- Allied Health and Human Performance, University of South Australia, c/o GPO Box 2471, SA, 5001, Adelaide, Australia
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Kotnik E, Spies N, Miller C, Li T, Inkman M, Zhang J, Guo L, Maher C, McCourt C, Thaker P, Hagemann A, Mutch D, Powell M, Fuh K. Characterization of primary-metastasis pairs in high-grade serous ovarian cancer with short- and long-term survival. Gynecol Oncol 2020. [DOI: 10.1016/j.ygyno.2020.05.458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Kilbane MT, Crowley RK, Twomey PJ, Maher C, McKenna MJ. Anorexia Nervosa with Markedly High Bone Turnover and Hyperphosphatemia During Refeeding Rectified by Denosumab. Osteoporos Int 2020; 31:1395-1398. [PMID: 31975181 DOI: 10.1007/s00198-020-05307-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 01/17/2020] [Indexed: 01/12/2023]
Abstract
We describe a unique case of hyperphosphatemia associated with a very high bone turnover rate in a 51-year-old postmenopausal woman with undiagnosed anorexia nervosa (AN) who presented with a low-trauma hip fracture. In view of her severely malnourished state, she was not fit for surgery. She was treated according to a refeeding protocol that mandated bed rest. Contrary to expectation, she developed sustained hyperphosphatemia and borderline hypercalcemia. Bone remodelling markers, both resorption and formation, were markedly elevated. Parathyroid hormone (PTH) was low-normal at 1.7 pmol/L, C-terminal fibroblast growth factor 23 (FGF23) was high at 293 RU/ml, but tubular maximum reabsorption of phosphate (TmPO4/GFR) was elevated at 1.93 mmol/L. Denosumab 60 mg was administered that was followed by: rapid normalisation of serum phosphate; normalisation of resorption markers, transient hypocalcaemia with secondary hyperparathyroidism, and normalisation of both TmPO4/GFR and C-terminal FGF23. We speculate that prolonged immobilization as part of AN management led to a high remodelling state followed by hyperphosphatemia and high-normal calcium with appropriate suppression of PTH and that marked hyperphosphatemia and high TmP/GFR despite high FGF23 indicates the necessity of PTH adequacy for excess FGF23 to lower TmP/GFR.
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Affiliation(s)
- M T Kilbane
- Department of Clinical Chemistry, St. Vincent's University Hospital, Dublin, Ireland.
| | - R K Crowley
- Department of Endocrinology, St. Vincent's University Hospital, Dublin, Ireland
- UCD School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - P J Twomey
- Department of Clinical Chemistry, St. Vincent's University Hospital, Dublin, Ireland
- UCD School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - C Maher
- Department of Psychiatry, St Vincent's University Hospital, Dublin, Ireland
| | - M J McKenna
- Department of Clinical Chemistry, St. Vincent's University Hospital, Dublin, Ireland
- Department of Endocrinology, St. Vincent's University Hospital, Dublin, Ireland
- UCD School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
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Degroote L, Hamerlinck G, Poels K, Maher C, Crombez G, De Bourdeaudhuij I, Vandendriessche A, Curtis RG, DeSmet A. Low-Cost Consumer-Based Trackers to Measure Physical Activity and Sleep Duration Among Adults in Free-Living Conditions: Validation Study. JMIR Mhealth Uhealth 2020; 8:e16674. [PMID: 32282332 PMCID: PMC7268004 DOI: 10.2196/16674] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 02/24/2020] [Accepted: 02/26/2020] [Indexed: 12/29/2022] Open
Abstract
Background Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption. Objective This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2. Methods A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0. Results Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA. Conclusions This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.
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Affiliation(s)
- Laurent Degroote
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.,Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium.,Research Foundation Flanders, Brussels, Belgium
| | - Gilles Hamerlinck
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
| | - Karolien Poels
- Department of Communication Studies, University of Antwerp, Antwerp, Belgium
| | - Carol Maher
- School of Health Sciences, University of South Australia, Adelaide, Australia
| | - Geert Crombez
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | | | - Ann Vandendriessche
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Rachel G Curtis
- School of Health Sciences, University of South Australia, Adelaide, Australia
| | - Ann DeSmet
- Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.,Research Foundation Flanders, Brussels, Belgium.,Department of Communication Studies, University of Antwerp, Antwerp, Belgium.,Department of Clinical and Health Psychology, Université Libre de Bruxelles, Brussels, Belgium
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Ma J, Qiao Y, Zhao P, Li W, Katzmarzyk PT, Chaput JP, Fogelholm M, Kuriyan R, Lambert EV, Maher C, Maia J, Matsudo V, Olds T, Onywera V, Sarmiento OL, Standage M, Tremblay MS, Tudor-Locke C, Hu G. Breastfeeding and childhood obesity: A 12-country study. Matern Child Nutr 2020; 16:e12984. [PMID: 32141229 PMCID: PMC7296809 DOI: 10.1111/mcn.12984] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 02/11/2020] [Accepted: 02/18/2020] [Indexed: 01/24/2023]
Abstract
This study aimed to examine the association between breastfeeding and childhood obesity. A multinational cross‐sectional study of 4,740 children aged 9–11 years was conducted from 12 countries. Infant breastfeeding was recalled by parents or legal guardians. Height, weight, waist circumference, and body fat were obtained using standardized methods. The overall prevalence of obesity, central obesity, and high body fat were 12.3%, 9.9%, and 8.1%, respectively. After adjustment for maternal age at delivery, body mass index (BMI), highest maternal education, history of gestational diabetes, gestational age, and child's age, sex, birth weight, unhealthy diet pattern scores, moderate‐to‐vigorous physical activity, sleeping, and sedentary time, exclusive breastfeeding was associated with lower odds of obesity (odds ratio [OR] 0.76, 95% confidence interval, CI [0.57, 1.00]) and high body fat (OR 0.60, 95% CI [0.43, 0.84]) compared with exclusive formula feeding. The multivariable‐adjusted ORs based on different breastfeeding durations (none, 1–6, 6–12, and > 12 months) were 1.00, 0.74, 0.70, and 0.60 for obesity (Ptrend = .020) and 1.00, 0.64, 047, and 0.64 for high body fat (Ptrend = .012), respectively. These associations were no longer significant after adjustment for maternal BMI. Breastfeeding may be a protective factor for obesity and high body fat in 9‐ to 11‐year‐old children from 12 countries.
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Affiliation(s)
- Jian Ma
- Tianjin Women's and Children's Health Center, Tianjin, China
| | - Yijuan Qiao
- Tianjin Women's and Children's Health Center, Tianjin, China
| | - Pei Zhao
- Tianjin Women's and Children's Health Center, Tianjin, China
| | - Wei Li
- Tianjin Women's and Children's Health Center, Tianjin, China
| | | | - Jean-Philippe Chaput
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Mikael Fogelholm
- Department of Food and Nutrition, University of Helsinki, Helsinki, Finland
| | | | - Estelle V Lambert
- Division of Exercise Science and Sports Medicine, Department of Human Biology, University of Cape Town, Cape Town, South Africa
| | - Carol Maher
- Alliance for Research In Exercise Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Jose Maia
- CIFI2D, Faculdade de Desporto, University of Porto, Porto, Portugal
| | - Victor Matsudo
- Center of Studies from the Physical Fitness Research Laboratory, de São Caetano do Sul, Sao Paulo, Brazil
| | - Timothy Olds
- Alliance for Research In Exercise Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Vincent Onywera
- Department of Recreation Management and Exercise Science, Kenyatta University, Nairobi, Kenya
| | | | - Martyn Standage
- Centre for Motivation and Health Behaviour Change, Department for Health, University of Bath, Bath, UK
| | - Mark S Tremblay
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Catrine Tudor-Locke
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, Massachusetts, USA
| | - Gang Hu
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
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Curtis RG, Olds T, Plotnikoff R, Vandelanotte C, Edney S, Ryan J, Maher C. Validity and bias on the online active Australia survey: activity level and participant factors associated with self-report bias. BMC Med Res Methodol 2020; 20:6. [PMID: 31924171 PMCID: PMC6954551 DOI: 10.1186/s12874-020-0896-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 12/31/2019] [Indexed: 12/31/2022] Open
Abstract
Background This study examined the criterion validity of the online Active Australia Survey, using accelerometry as the criterion, and whether self-report bias was related to level of activity, age, sex, education, body mass index and health-related quality of life. Methods The online Active Australia Survey was validated against the GENEActiv accelerometer as a direct measure of activity. Participants (n = 344) wore an accelerometer for 7 days, completed the Active Australia Survey, and reported their health and demographic characteristics. A Spearman’s rank coefficient examined the association between minutes of moderate-to-vigorous physical activity recorded on the Active Australia Survey and GENEActiv accelerometer. A Bland-Altman plot illustrated self-report bias (the difference between methods). Linear mixed effects modelling was used to examine whether participant factors predicted self-report bias. Results The association between moderate-to-vigorous physical activity reported on the online Active Australia Survey and accelerometer was significant (rs = .27, p < .001). Participants reported 4 fewer minutes per day on the Active Australia Survey than was recorded by accelerometry (95% limits of agreement −104 – 96 min) but the difference was not significant (t(343) = −1.40, p = .16). Self-report bias was negatively associated with minutes of accelerometer-recorded moderate-to-vigorous physical activity and positively associated with mental health-related quality of life. Conclusions The online Active Australia Survey showed limited criterion validity against accelerometry. Self-report bias was related to activity level and mental health-related quality of life. Caution is recommended when interpreting studies using the online Active Australia Survey.
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Affiliation(s)
- Rachel G Curtis
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
| | - Timothy Olds
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Ronald Plotnikoff
- Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Callaghan, NSW, 2308, Australia
| | - Corneel Vandelanotte
- Physical Activity Research Group, School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, QLD, 4702, Australia
| | - Sarah Edney
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Jillian Ryan
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia
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Ryan J, Curtis R, Olds T, Edney S, Vandelanotte C, Plotnikoff R, Maher C. Psychometric properties of the PERMA Profiler for measuring wellbeing in Australian adults. PLoS One 2019; 14:e0225932. [PMID: 31869336 PMCID: PMC6927648 DOI: 10.1371/journal.pone.0225932] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Accepted: 11/15/2019] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION This study evaluated the psychometric properties of the PERMA Profiler, a 15-item self-report measurement tool designed to measure Seligman's five pillars of wellbeing: Positive emotions, Relationships, Engagement, Meaning, and Accomplishment. METHODS Australian adults (N = 439) completed the PERMA Profiler and measures of physical and mental health (SF-12), depression, anxiety, stress (DASS 21), subjective physical activity (Active Australia Survey), and objective activity and sleep (GENEActiv accelerometer). Internal consistency was examined using Cronbach's alpha and associations between theoretically related constructs examined using Pearson's correlation. Model fit in comparison with theorised models was examined via Confirmatory Factor Analysis. RESULTS Results indicated acceptable internal consistency for overall PERMA Profiler scores and all subscales (α range = 0.80-0.93) except Engagement (α = 0.66). Moderate associations were found between PERMA Profiler wellbeing scores with subjective constructs (e.g. depression, anxiety, stress; r = -0.374 - -0.645, p = <0.001) but not objective physical activity or sleep. Data failed to meet model fit criteria for neither the theorised five-factor nor an alternative single-factor structure. CONCLUSIONS Findings were mixed, providing strong support for the scale's internal consistency and moderate support for congervent and divergent validity, albeit not in comparison to objectively captured activity outcomes. We could not replicate the theorised data structure nor an alternative, single factor structure. Results indicate insufficient psychometric properties of the PERMA Profiler.
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Affiliation(s)
- Jillian Ryan
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Rachel Curtis
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Sarah Edney
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, South Australia, Australia
| | - Corneel Vandelanotte
- Physical Activity Research Group, School of Health Medical and Applied Sciences, Central Queensland University, Norman Gardens, Queensland, Australia
| | - Ronald Plotnikoff
- Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Carol Maher
- Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, Adelaide, South Australia, Australia
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