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Gava V, Xavier de Araujo F, Sharma S, Abbott JH, Lamb SE, Ribeiro DC. Insufficient structure and reporting of process evaluations of complex interventions for musculoskeletal conditions in randomized controlled trials: a systematic review. J Clin Epidemiol 2025; 179:111637. [PMID: 39662642 DOI: 10.1016/j.jclinepi.2024.111637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2024] [Revised: 11/12/2024] [Accepted: 12/03/2024] [Indexed: 12/13/2024]
Abstract
OBJECTIVES To explore how process evaluation of complex interventions alongside randomized clinical trials (RCTs) in musculoskeletal conditions are conducted. STUDY DESIGN AND SETTING Systematic review. METHODS We searched the MEDLINE, SCOPUS, CINAHL, PsycINFO, Embase, Web of Science, and Cochrane databases. Studies were included if they reported process evaluation conducted alongside RCTs, within the main report or as separate reports, that assessed process evaluation of RCTs of complex nonsurgical and nonpharmacological interventions for musculoskeletal conditions. We performed a descriptive analysis of the included studies based on process evaluation parameters. RESULTS Data were extracted from 61 studies from 17 countries. Our findings showed studies used qualitative, quantitative, and mixed methods for process evaluations, typically reporting within the main RCT. Most studies were conducted in primary care settings. Only a few studies (16%) included a theoretical model to guide their process evaluation. Studies reported reach (8%), patients' and clinicians' perceptions of the interventions (44% and 8%, respectively), treatment fidelity and adherence (52% and 43%, respectively), training of patients and clinicians (eg, workshops, manuals and additional training) (54%), how the integration of process evaluation and outcome evaluation findings was performed (68%), barriers to perform the process evaluation (2%), and the strengths and weaknesses of the process evaluation (65%). CONCLUSION Reporting of process evaluations within RCTs is insufficiently reported. Researchers rarely adopted a theoretical model or framework to guide their process evaluation. Studies used a variety of methods to conduct process evaluations. We identified barriers, strengths, and weaknesses of methods used for assessing process evaluation as reported by authors from studies included in this review.
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Affiliation(s)
- Vander Gava
- Department of Physical Therapy, Universidade Federal de São Carlos, São Carlos, São Paulo, Brazil; Centre for Health, Activity and Rehabilitation Research, School of Physiotherapy, University of Otago, Dunedin, New Zealand
| | - Francisco Xavier de Araujo
- School of Physical Education and Physiotherapy, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Saurab Sharma
- Michael J. Cousins Pain Management and Research Centre, Royal North Shore Hospital, Northern Sydney Local Health District, Sydney, Australia; Faculty of Medicine and Health, School of Health Sciences, University of New South Wales, Sydney, Australia; Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia
| | - J Haxby Abbott
- Department of Surgical Sciences, University of Otago Medical School, Dunedin, New Zealand
| | - Sarah E Lamb
- Faculty of Health and Life Sciences, University of Exeter Medical School, St Luke's Campus, Exeter, UK
| | - Daniel Cury Ribeiro
- Centre for Health, Activity and Rehabilitation Research, School of Physiotherapy, University of Otago, Dunedin, New Zealand; Faculty of Health Sciences, Curtin School of Allied Health, Curtin University, Perth, Western Australia, Australia.
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Dzeng RJ, Watanabe K, Hsueh HH, Fu CK. A GRU-Based Model for Detecting Common Accidents of Construction Workers. SENSORS (BASEL, SWITZERLAND) 2024; 24:672. [PMID: 38276363 PMCID: PMC10818701 DOI: 10.3390/s24020672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/16/2024] [Accepted: 01/16/2024] [Indexed: 01/27/2024]
Abstract
Fall accidents in the construction industry have been studied over several decades and identified as a common hazard and the leading cause of fatalities. Inertial sensors have recently been used to detect accidents of workers in construction sites, such as falls or trips. IMU-based systems for detecting fall-related accidents have been developed and have yielded satisfactory accuracy in laboratory settings. Nevertheless, the existing systems fail to uphold consistent accuracy and produce a significant number of false alarms when deployed in real-world settings, primarily due to the intricate nature of the working environments and the behaviors of the workers. In this research, the authors redesign the aforementioned laboratory experiment to target situations that are prone to false alarms based on the feedback obtained from workers in real construction sites. In addition, a new algorithm based on recurrent neural networks was developed to reduce the frequencies of various types of false alarms. The proposed model outperforms the existing benchmark model (i.e., hierarchical threshold model) with higher sensitivities and fewer false alarms in detecting stumble (100% sensitivity vs. 40%) and fall (95% sensitivity vs. 65%) events. However, the model did not outperform the hierarchical model in detecting coma events in terms of sensitivity (70% vs. 100%), but it did generate fewer false alarms (5 false alarms vs. 13).
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Affiliation(s)
- Ren-Jye Dzeng
- Department of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
| | - Keisuke Watanabe
- Department of Marine Science and Ocean Engineering, School of Marine Science and Technology, Tokai University, Shizuoka 424–8610, Japan;
| | - Hsien-Hui Hsueh
- Department of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
| | - Chien-Kai Fu
- Department of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
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Hernández-Lázaro H, Mingo-Gómez MT, Jiménez-del-Barrio S, Lahuerta-Martín S, Hernando-Garijo I, Medrano-de-la-Fuente R, Ceballos-Laita L. Researcher's Perspective on Musculoskeletal Conditions in Primary Care Physiotherapy Units through the International Classification of Functioning, Disability, and Health (ICF): A Scoping Review. Biomedicines 2023; 11:290. [PMID: 36830831 PMCID: PMC9953260 DOI: 10.3390/biomedicines11020290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/13/2023] [Accepted: 01/18/2023] [Indexed: 01/26/2023] Open
Abstract
(1) Background: Musculoskeletal disorders are the second cause of disability in the world. The International Classification of Functioning Disability and Health (ICF) is a tool for systematically describing functioning. Outcome measures for musculoskeletal disorders and functioning concepts embedded in them have not been described under the ICF paradigm. The objective of this scoping review was to identify ICF categories representing the researcher's perspective and to compare them with the ICF core set for post-acute musculoskeletal conditions. (2) Methods: This review was conducted as follows: (a) literature search using MEDLINE/PubMed, CINAHL, Web of Science, and Scopus databases; (b) study selection applying inclusion criteria (PICOS): musculoskeletal conditions in primary care, application of physiotherapy as a treatment, outcome measures related to functioning, and experimental or observational studies conducted in Western countries during the last 10 years; (c) extraction of relevant concepts; (d) linkage to the ICF; (e) frequency analysis; and (f) comparison with the ICF core set. (3) Results: From 540 studies identified, a total of 51 were included, and 108 outcome measures were extracted. In the ICF linking process, 147 ICF categories were identified. Analysis of data showed that 84.2% of the categories in the ICF core set for post-acute musculoskeletal conditions can be covered by the outcome measures analyzed. Sixty-eight relevant additional ICF categories were identified. (4) Conclusion: Outcome measures analyzed partially represent the ICF core set taken as a reference. The identification of additional categories calls into question the applicability of this core set in primary care physiotherapy units.
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Affiliation(s)
- Héctor Hernández-Lázaro
- Faculty of Health Sciences, University of Valladolid, 42004 Soria, Spain
- Clinical Research in Health Sciences Group, University of Valladolid, 42004 Soria, Spain
- Ólvega Primary Care Health Center (Soria, Spain), Soria Health Care Management, Castilla y León Regional Health Management (SACYL), 47007 Valladolid, Spain
| | - María Teresa Mingo-Gómez
- Faculty of Health Sciences, University of Valladolid, 42004 Soria, Spain
- Clinical Research in Health Sciences Group, University of Valladolid, 42004 Soria, Spain
| | - Sandra Jiménez-del-Barrio
- Faculty of Health Sciences, University of Valladolid, 42004 Soria, Spain
- Clinical Research in Health Sciences Group, University of Valladolid, 42004 Soria, Spain
| | | | - Ignacio Hernando-Garijo
- Faculty of Health Sciences, University of Valladolid, 42004 Soria, Spain
- Clinical Research in Health Sciences Group, University of Valladolid, 42004 Soria, Spain
| | - Ricardo Medrano-de-la-Fuente
- Faculty of Health Sciences, University of Valladolid, 42004 Soria, Spain
- Clinical Research in Health Sciences Group, University of Valladolid, 42004 Soria, Spain
| | - Luis Ceballos-Laita
- Faculty of Health Sciences, University of Valladolid, 42004 Soria, Spain
- Clinical Research in Health Sciences Group, University of Valladolid, 42004 Soria, Spain
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Grunberg VA, Greenberg J, Mace RA, Bakhshaie J, Choi KW, Vranceanu AM. Fitbit Activity, Quota-Based Pacing, and Physical and Emotional Functioning Among Adults With Chronic Pain. THE JOURNAL OF PAIN 2022; 23:1933-1944. [PMID: 35914640 PMCID: PMC10226285 DOI: 10.1016/j.jpain.2022.07.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/14/2022] [Accepted: 07/11/2022] [Indexed: 11/20/2022]
Abstract
Physical activity can improve function in patients with chronic pain, however, adherence is low, in part due to inconsistent activity patterns. Smart wearable activity trackers, such as Fitbits, may help promote activity. In our program for chronic pain, we examined: 1) Fitbit activity patterns (ie, step count, moderate-to-vigorous physical activity (MVPA), sedentary behavior), and 2) whether achievement of weekly, individualized Fitbit step goals was associated with functional outcomes. We conducted a secondary analysis of Fitbit data from our 10-week mind-body activity program for chronic pain (GetActive-Fitbit arm, N = 41). Participants self-reported emotional and physical function and completed performance-based and accelerometer-based assessments. From week 1 to week 10, 30% of participants increased >800 steps; 32.5% increased MVPA; and 30% decreased sedentary behavior. Only step count significantly changed across time with mean steps peaking at week 8 (M = +1897.60, SD = 467.67). Fitbit step goal achievement was associated with improvements in anxiety (ß = -.35, CI [-2.80, -.43]), self-reported physical function (ß = -.34, CI [-5.17, 8.05]), and performance-based physical function (ß = .29, CI [-71.93, 28.38]), but not accelerometer-based physical function or depression. Adhering to individualized Fitbit step goals in the context of a mind-body activity program may improve anxiety and self-reported and performance-based physical function. PERSPECTIVE: We examine Fitbit activity patterns and the association between quota-based pacing and functional outcomes within a mind-body activity program for adults with chronic pain. Complementing quota-based pacing and coping skills with Fitbits may be a useful approach to promote activity engagement and behavior change in chronic pain populations.
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Affiliation(s)
- Victoria A Grunberg
- Center for Health Outcomes and Interdisciplinary Research, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Division of Newborn Medicine, MassGeneral for Children, Boston, Massachusetts
| | - Jonathan Greenberg
- Center for Health Outcomes and Interdisciplinary Research, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Ryan A Mace
- Center for Health Outcomes and Interdisciplinary Research, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Jafar Bakhshaie
- Center for Health Outcomes and Interdisciplinary Research, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Karmel W Choi
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Ana-Maria Vranceanu
- Center for Health Outcomes and Interdisciplinary Research, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
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Dunphy E, Button K, Hamilton F, Williams J, Spasic I, Murray E. Feasibility randomised controlled trial comparing TRAK-ACL digital rehabilitation intervention plus treatment as usual versus treatment as usual for patients following anterior cruciate ligament reconstruction. BMJ Open Sport Exerc Med 2021; 7:e001002. [PMID: 34035951 PMCID: PMC8103946 DOI: 10.1136/bmjsem-2020-001002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/16/2021] [Indexed: 01/24/2023] Open
Abstract
Objectives To evaluate the feasibility of trialling taxonomy for the rehabilitation of knee conditions—ACL (TRAK-ACL), a digital health intervention that provides health information, personalised exercise plans and remote clinical support combined with treatment as usual (TAU), for people following ACL reconstruction. Methods The study design was a two-arm parallel randomised controlled trial (RCT). Eligible participants were English-speaking adults who had undergone ACL reconstruction within the last 12 weeks, had access to the internet and could provide informed consent. Recruitment took place at three sites in the UK. TRAK-ACL intervention was an interactive website informed by behaviour change technique combined with TAU. The comparator was TAU. Outcomes were: recruitment and retention; completeness of outcome measures at follow-up; fidelity of intervention delivery and engagement with the intervention. Individuals were randomised using a computer-generated random number sequence. Blinded assessors allocated groups and collected outcome measures. Results Fifty-nine people were assessed for eligibility at two of the participating sites, and 51 were randomised; 26 were allocated to TRAK-ACL and 25 to TAU. Follow-up data were collected on 44 and 40 participants at 3 and 6 months, respectively. All outcome measures were completed fully at 6 months except the Client Service Receipt Inventory. Two patients in each arm did not receive the treatment they were randomised to. Engagement with TRAK-ACL intervention was a median of 5 logins (IQR 3–13 logins), over 18 weeks (SD 12.2 weeks). Conclusion TRAK-ACL would be suitable for evaluation of effectiveness in a fully powered RCT.
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Affiliation(s)
- Emma Dunphy
- Research Department of Primary Care and Population Health, University College London, London, UK.,Physiotherapy Department, Homerton University Hospital NHS Foundation Trust, London, UK
| | - Kate Button
- School of Healthcare Sciences, Cardiff University, Cardiff, UK.,Physiotherapy Department, Cardiff and Vale University Local Health Board, Cardiff, UK
| | - Fiona Hamilton
- Research Department of Primary Care and Population Health, University College London, London, UK
| | - Jodie Williams
- Physiotherapy Department, Homerton University Hospital NHS Foundation Trust, London, UK
| | - Irena Spasic
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Elizabeth Murray
- Research Department of Primary Care and Population Health, University College London, London, UK
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