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Ryan GW, Whitmire P, Batten A, Goulding M, Baltich Nelson B, Lemon SC, Pbert L. Adolescent cancer prevention in rural, pediatric primary care settings in the United States: A scoping review. Prev Med Rep 2023; 36:102449. [PMID: 38116252 PMCID: PMC10728324 DOI: 10.1016/j.pmedr.2023.102449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/03/2023] [Accepted: 09/28/2023] [Indexed: 12/21/2023] Open
Abstract
Adolescence is a critical period for establishing habits and engaging in health behaviors to prevent future cancers. Rural areas tend to have higher rates of cancer-related morbidity and mortality as well as higher rates of cancer-risk factors among adolescents. Rural primary care clinicians are well-positioned to address these risk factors. Our goal was to identify existing literature on adolescent cancer prevention in rural primary care and to classify key barriers and facilitators to implementing interventions in such settings. We searched the following databases: Ovid MEDLINE®; Ovid APA PsycInfo; Cochrane Library; CINAHL; and Scopus. Studies were included if they reported on provider and/or clinic-level interventions in rural primary care clinics addressing one of these four behaviors (obesity, tobacco, sun exposure, HPV vaccination) among adolescent populations. We identified 3,403 unique studies and 24 met inclusion criteria for this review. 16 addressed obesity, 6 addressed HPV vaccination, 1 addressed skin cancer, and 1 addressed multiple behaviors including obesity and tobacco use. 10 studies were either non-randomized experimental designs (n = 8) or randomized controlled trials (n = 2). The remaining were observational or descriptive research. We found a dearth of studies addressing implementation of adolescent cancer prevention interventions in rural primary care settings. Priorities to address this should include further research and increased funding to support EBI adaptation and implementation in rural clinics to reduce urban-rural cancer inequities.
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Affiliation(s)
- Grace W. Ryan
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | | | - Melissa Goulding
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | - Stephenie C. Lemon
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Lori Pbert
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
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de Gooijer FJ, Lasschuijt M, Wit RF, Feskens EJM, Brouwer-Brolsma EM, Camps G. Dietary Behavior Assessments in Children-A Mixed-Method Research Exploring the Perspective of Pediatric Dieticians on Innovative Technologies. Curr Dev Nutr 2023; 7:100091. [PMID: 37213716 PMCID: PMC10196961 DOI: 10.1016/j.cdnut.2023.100091] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 03/21/2023] [Accepted: 04/21/2023] [Indexed: 05/23/2023] Open
Abstract
Background Assessing dietary intake and eating behavior in children is challenging, owing to children's undeveloped food knowledge and perception of portion sizes. Additionally, caregivers cannot always provide complete surrogate information. Consequently, validated dietary behavior assessment methods for children are limited, but technological innovations offer opportunities for the development of new tools. One of the first steps in the developmental process of a newly developed pediatric dietary assessment tool includes an alignment of the needs and preferences of pediatric dieticians (PDs) as potential users. Objectives To explore opinions of Dutch PDs about traditional dietary behavior assessment methods for children and potential technological innovations to replace or support traditional methods. Methods Ten PDs participated in semistructured interviews (total of 7.5 h) based on 2 theoretical frameworks, and data saturation was reached after the seventh interview. Interview transcripts were inductively coded in an iterative process, and overarching themes and domains were identified. Interview data were then used as input for an extensive online survey completed by 31 PDs who were not involved in the initial interview rounds. Results PDs discussed their perspective on dietary behavior assessments in 4 domains: traditional methods, technological methods, future methods, and external influences on these methods. Generally, PDs felt that traditional methods supported them in reaching their desired goals. However, the time needed to obtain a comprehensive overview of dietary intake behavior and the reliability of conventional methods were mentioned as limitations. For future technologies, PDs mention the ease of use and engaging in children as opportunities. Conclusions PDs have a positive attitude toward the use of technology for dietary behavior assessments. Further development of assessment technologies should be tailored to the needs of children in different care situations and age categories to increase its usability among children, their caregivers, and dietician. Curr Dev Nutr 2023;xx:xx.
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Affiliation(s)
- Femke J. de Gooijer
- Division of Human Nutrition and Health, Department Agrotechnology and Food Sciences, Wageningen University and Research, Wageningen, The Netherlands
- OnePlanet Research Centre, Wageningen, The Netherlands
- Corresponding author.
| | - Marlou Lasschuijt
- Division of Human Nutrition and Health, Department Agrotechnology and Food Sciences, Wageningen University and Research, Wageningen, The Netherlands
| | - Renate F. Wit
- Division of Human Nutrition and Health, Department Agrotechnology and Food Sciences, Wageningen University and Research, Wageningen, The Netherlands
| | - Edith JM. Feskens
- Division of Human Nutrition and Health, Department Agrotechnology and Food Sciences, Wageningen University and Research, Wageningen, The Netherlands
| | - Elske M. Brouwer-Brolsma
- Division of Human Nutrition and Health, Department Agrotechnology and Food Sciences, Wageningen University and Research, Wageningen, The Netherlands
| | - Guido Camps
- Division of Human Nutrition and Health, Department Agrotechnology and Food Sciences, Wageningen University and Research, Wageningen, The Netherlands
- OnePlanet Research Centre, Wageningen, The Netherlands
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Vidmar AP, Salvy SJ, Wee CP, Pretlow R, Fox DS, Yee JK, Garell C, Glasner S, Mittelman SD. An addiction-based digital weight loss intervention: A multi-centre randomized controlled trial. Pediatr Obes 2023; 18:e12990. [PMID: 36484235 PMCID: PMC9905275 DOI: 10.1111/ijpo.12990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 10/07/2022] [Accepted: 11/02/2022] [Indexed: 12/13/2022]
Abstract
OBJECTIVE This randomized clinical trial tested the effectiveness of an addiction-based digital weight-loss intervention, focusing on withdrawal/abstinence from self-identified problem foods, snacking and excessive amounts at meals, and discomfort displacement, with and without coaching, compared to an in-person, multi-disciplinary, care model among adolescents with obesity. We hypothesized that the digital intervention with coaching would yield greater weight loss and lower delivery burden than the standard clinical arm, and greater participant engagement than the digital arm without coaching. METHODS Adolescents were randomized to app intervention, with or without coaching, or in-person multidisciplinary obesity intervention for 6 months. The primary outcome was change in %BMIp95 at weeks 12 and 24. A mixed-effects linear regression model was used to assess the association between change in %BMIp95 and intervention arm. We were also interested in assessing delivery burden, participant engagement and evaluating the relationships between weight change and demographic characteristics, mood, executive function and eating behaviours. RESULTS All adolescents (n = 161; BMI ≥95th%, age 16 ± 2.5 year; 47% Hispanic, 65% female, 59% publicly insured) lost weight over 24-weeks (-1.29%, [-1.82, -0.76], p < 0.0001), with no significant weight loss difference between groups (p = 0.3). Girls lost more weight than boys, whereas binge eating behaviour at baseline was associated with increase in %BMIp95 when controlling for other covariates. There was no association between ethnicity, mood, timing of intervention in relation to the pandemic, or executive function and change in %BMIp95 . CONCLUSIONS Contrary with our hypothesis, our results showed no difference in the change in BMI status between treatment arms. Since efficacy of this digital intervention was not inferior to in-person, multi-disciplinary care, this could offer a reasonable weight management option for clinicians, based on youth and family specific characteristics, such as accessibility, resources, and communication styles. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT035008353.
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Affiliation(s)
- Alaina P. Vidmar
- Department of Pediatrics, Center for Endocrinology, Diabetes and Metabolism, Children’s Hospital Los Angeles and Keck School of Medicine of USC, Los Angeles, California, USA
| | - Sarah J. Salvy
- Department of Medicine, Cedars-Sinai Medical Center, Research Center for Health Equity Samuel Oschin Comprehensive Cancer Institute, Los Angeles, California, USA
| | - Choo Phei Wee
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Southern California Clinical Science Institute, Los Angeles, California, USA
| | | | - D. Steven Fox
- Department of Pharmaceutical and Health Economics, School of Pharmacy of the University of Southern California, Los Angeles, California, USA
| | - Jennifer K. Yee
- Division of Pediatric Endocrinology, Harbor-UCLA Medical Center, Harbor-UCLA Medical Center, Torrance, California, United States
| | - Cambria Garell
- Department of Pediatrics, Division of General Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Suzette Glasner
- Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, California, USA
| | - Steven D. Mittelman
- Department of Pediatrics, Division of General Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Pediatrics, Division of Endocrinology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
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Wang T, Zheng X, Liang J, An K, He Y, Nuo M, Wang W, Lei J. Use of Machine Learning to Mine User-Generated Content From Mobile Health Apps for Weight Loss to Assess Factors Correlated With User Satisfaction. JAMA Netw Open 2022; 5:e2215014. [PMID: 35639374 DOI: 10.1001/jamanetworkopen.2022.15014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
IMPORTANCE The effectiveness of mobile health (mHealth) apps for reducing obesity is not ideal in daily life. Therefore, it would be useful to explore factors associated with user satisfaction with weight loss apps. Currently, research on these factors from the perspective of user-generated content is lacking. OBJECTIVE To mine the themes and topics frequently discussed in user-generated content in mHealth apps for weight loss, explore correlations of the topics with user satisfaction and dissatisfaction, and assess whether these correlations were asymmetric. DESIGN, SETTING, AND PARTICIPANTS In this population-based cross-sectional study, unsupervised machine learning was used to identify themes and topics in online discussions generated between January 1, 2019, and May 20, 2021, by Chinese users of mHealth apps for weight loss. MAIN OUTCOMES AND MEASURES Based on the 2-factor theory, a tobit regression model was used to explore the correlation of various app discussion topics with user satisfaction and dissatisfaction. Differences of the coefficients in models of positive rating deviation (PD) and negative rating deviation (ND), defined as the difference between the users' rating of the app and the app's comprehensive rating in the app stores, were analyzed by the Wald test. RESULTS In total, 191 619 reviews and ratings from unique usernames were collected for 2139 weight loss apps; 86 423 reviews (45.1%) from 339 apps (15.8%) were included in the study. Most users (65 249 [75.5%]) were satisfied with the mHealth app. Eighteen topics were identified and summarized into 9 themes. Nine topics had significant positive correlations with the PD of user satisfaction, and 6 had significant negative correlations. The factor with the strongest positive correlation with the PD was celebrity effect (β = 0.307; 95% CI, 0.290-0.323), and the factor with the weakest correlation was economic cost (β = -0.426; 95% CI, -0.447 to -0.406). Nine topics had significant positive correlations with the ND of user satisfaction, whereas 7 topics had significant negative correlations. The factor with the strongest positive correlation with the ND was fitness effect (β = 1.369; 95% CI, 1.283-1.455), and the factor with the strongest negative correlation was economic cost (β = -2.813; 95% CI, -2.875 to -2.751). There were significant differences in the PD and ND of user satisfaction. Nine motivation factors (ie, value-added attributes) and 7 hygiene factors (ie, user-expected attributes) for mHealth apps were identified. CONCLUSIONS AND RELEVANCE In this cross-sectional study, 16 factors had asymmetric correlations with user satisfaction and dissatisfaction with weight loss apps; 7 were related to basic expected attributes of the apps and 9 to value-added attributes. By distinguishing between expected and value-added factors, the use of weight loss apps may be improved.
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Affiliation(s)
- Tong Wang
- Department of Medical Informatics, School of Public Health, Jilin University, Chaoyang District, Changchun, Jilin Province, China
| | - Xu Zheng
- Peking University Third Hospital, Haidian District, Beijing, China
| | - Jun Liang
- IT Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Shangcheng District, Hangzhou, Zhejiang Province, China
- School of Public Health, Zhejiang University, Xihu District, Hangzhou City, Zhejiang Province, China
- Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, School of Medicine, Zhejiang University, Xihu District, Hangzhou City, Zhejiang Province, China
| | - Kai An
- Peking University Third Hospital, Haidian District, Beijing, China
| | - Yunfan He
- School of Public Health, Zhejiang University, Xihu District, Hangzhou City, Zhejiang Province, China
| | - Mingfu Nuo
- Institute of Medical Technology, Health Science Center, Peking University, Haidian District, Beijing, China
| | - Wei Wang
- Department of Medical Informatics, School of Public Health, Jilin University, Chaoyang District, Changchun, Jilin Province, China
| | - Jianbo Lei
- Institute of Medical Technology, Health Science Center, Peking University, Haidian District, Beijing, China
- School of Medical Informatics and Engineering, Southwest Medical University, Longmatan District, Luzhou, Sichuan Province, China
- Center for Medical Informatics, Health Science Center, Peking University, Haidian District, Beijing, China
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