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Hossaini J, Osmani V, Klug SJ. Behavioral weight loss interventions for people with physical disabilities: A systematic review. Obes Rev 2024; 25:e13722. [PMID: 38332472 DOI: 10.1111/obr.13722] [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: 02/03/2023] [Revised: 10/26/2023] [Accepted: 01/17/2024] [Indexed: 02/10/2024]
Abstract
AIM The aim of this study is to examine which interventions lead to clinically significant weight loss among people with physical disabilities. METHODS We systematically searched three electronic databases (PubMed, Scopus, and CENTRAL) including studies until May 2022 to find randomized controlled trials on behavioral interventions and weight-related outcomes in people with physical disabilities. Pharmacological or surgical interventions were excluded. Study quality was evaluated using the Cochrane Risk of Bias Tool. Interventions were grouped as dietary, physical activity, education/coaching, or multi-component. Mean weight changes, standard deviations, confidence intervals, and effect sizes were extracted or calculated for assessment of the intervention effect. RESULTS Sixty studies involving 6,511 participants were included in the qualitative synthesis. Most studies (n = 32) included multi-component interventions, incorporating dietary and physical activity components. Limited evidence suggests that extensive dietary interventions or long-term multi-component interventions might lead to a clinically relevant weight reduction of at least 5% for older individuals (age > 50) with mild-to-moderate mobility impairments. DISCUSSION Due to the high heterogeneity of studies and low study quality, it can be assumed that the range of applicability of the findings is questionable. Further research should examine younger age groups (i.e., children, adolescents, and adults under 40 years) and compare different settings such as schools, clinics, nursing homes, and assisted living facilities.
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Affiliation(s)
- Jihad Hossaini
- Chair of Social Determinants of Health, School of Medicine and Health, Department Health and Sport Sciences, Technical University of Munich, Munich, Germany
| | - Vanesa Osmani
- Chair of Epidemiology, School of Medicine and Health, Department Health and Sport Sciences, Technical University of Munich, Munich, Germany
| | - Stefanie J Klug
- Chair of Epidemiology, School of Medicine and Health, Department Health and Sport Sciences, Technical University of Munich, Munich, Germany
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Gille F, Frei A, Kaufmann M, Lehmann A, Muñoz Laguna J, Papadopoulos K, Spörri A, Stanikić M, Tušl M, Zavattaro F, Puhan MA. A guide for a student-led doctoral-level qualitative methods short course in epidemiology: faculty and student perspectives. Int J Epidemiol 2024; 53:dyae029. [PMID: 38389285 PMCID: PMC10883707 DOI: 10.1093/ije/dyae029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 02/07/2024] [Indexed: 02/24/2024] Open
Abstract
Qualitative research and mixed methods are core competencies for epidemiologists. In response to the shortage of guidance on graduate course development, we wrote a course development guide aimed at faculty and students designing similar courses in epidemiology curricula. The guide combines established educational theory with faculty and student experiences from a recent introductory course for epidemiology and biostatistics doctoral students at the University of Zurich and Swiss Federal Institute of Technology, Zurich. We propose a student-centred course with inverse classroom teaching and practice exercises with faculty input. Integration of student input during the course development process helps align the course syllabus with student needs. The proposed course comprises six sessions that cover learning outcomes in comprehension, knowledge, application, analysis, synthesis and evaluation. Following an introductory session, the students engage in face-to-face interviews, focus group interviews, observational methods, analysis and how qualitative and quantitative methods are integrated in mixed methods. Furthermore, the course covers interviewer safety, research ethics, quality in qualitative research and a practice session focused on the use of interview hardware, including video and audio recorders. The student-led teaching characteristic of the course allows for an immersive and reflective teaching-learning environment. After implementation of the course and learning from faculty and student perspectives, we propose these additional foci: a student project to apply learned knowledge to a case study; integration in mixed-methods; and providing faculty a larger space to cover theory and field anecdotes.
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Affiliation(s)
- Felix Gille
- Institute for Implementation Science in Health Care (IfIS), University of Zurich, Zurich, Switzerland
- Digital Society Initiative (DSI), University of Zurich, Zurich, Switzerland
| | - Anja Frei
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
| | - Marco Kaufmann
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
| | - Anja Lehmann
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
| | - Javier Muñoz Laguna
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
- EBPI-UWZH Musculoskeletal Epidemiology Research Group, University of Zurich and Balgrist University Hospital, Zurich, Switzerland
- University Spine Centre Zurich (UWZH), Balgrist University Hospital and University of Zurich, Zurich, Switzerland
| | - Kimon Papadopoulos
- Institute for Implementation Science in Health Care (IfIS), University of Zurich, Zurich, Switzerland
- Digital Society Initiative (DSI), University of Zurich, Zurich, Switzerland
| | - Angela Spörri
- Central Informatics, Multimedia an E-Learning Services, University of Zurich, Zurich, Switzerland
| | - Mina Stanikić
- Institute for Implementation Science in Health Care (IfIS), University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
| | - Martin Tušl
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
| | - Federica Zavattaro
- Institute for Implementation Science in Health Care (IfIS), University of Zurich, Zurich, Switzerland
- Digital Society Initiative (DSI), University of Zurich, Zurich, Switzerland
| | - Milo Alan Puhan
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
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Salisbury C, Man MS, Chaplin K, Mann C, Bower P, Brookes S, Duncan P, Fitzpatrick B, Gardner C, Gaunt DM, Guthrie B, Hollinghurst S, Kadir B, Lee V, McLeod J, Mercer SW, Moffat KR, Moody E, Rafi I, Robinson R, Shaw A, Thorn J. A patient-centred intervention to improve the management of multimorbidity in general practice: the 3D RCT. HEALTH SERVICES AND DELIVERY RESEARCH 2019. [DOI: 10.3310/hsdr07050] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Background
People with multimorbidity experience impaired quality of life, poor health and a burden from treatment. Their care is often disease-focused rather than patient-centred and tailored to their individual needs.
Objective
To implement and evaluate a patient-centred intervention to improve the management of patients with multimorbidity in general practice.
Design
Pragmatic, cluster randomised controlled trial with parallel process and economic evaluations. Practices were centrally randomised by a statistician blind to practice identifiers, using a computer-generated algorithm.
Setting
Thirty-three general practices in three areas of England and Scotland.
Participants
Practices had at least 4500 patients and two general practitioners (GPs) and used the EMIS (Egton Medical Information Systems) computer system. Patients were aged ≥ 18 years with three or more long-term conditions.
Interventions
The 3D (Dimensions of health, Depression and Drugs) intervention was designed to offer patients continuity of care with a named GP, replacing separate reviews of each long-term condition with comprehensive reviews every 6 months. These focused on individualising care to address patients’ main problems, attention to quality of life, depression and polypharmacy and on disease control and agreeing treatment plans. Control practices provided usual care.
Outcome measures
Primary outcome – health-related quality of life (assessed using the EuroQol-5 Dimensions, five-level version) after 15 months. Secondary outcomes – measures of illness burden, treatment burden and patient-centred care. We assessed cost-effectiveness from a NHS and a social care perspective.
Results
Thirty-three practices (1546 patients) were randomised from May to December 2015 [16 practices (797 patients) to the 3D intervention, 17 practices (749 patients) to usual care]. All participants were included in the primary outcome analysis by imputing missing data. There was no evidence of difference between trial arms in health-related quality of life {adjusted difference in means 0.00 [95% confidence interval (CI) –0.02 to 0.02]; p = 0.93}, illness burden or treatment burden. However, patients reported significant benefits from the 3D intervention in all measures of patient-centred care. Qualitative data suggested that both patients and staff welcomed having more time, continuity of care and the patient-centred approach. The economic analysis found no meaningful differences between the intervention and usual care in either quality-adjusted life-years [(QALYs) adjusted mean QALY difference 0.007, 95% CI –0.009 to 0.023] or costs (adjusted mean difference £126, 95% CI –£739 to £991), with wide uncertainty around point estimates. The cost-effectiveness acceptability curve suggested that the intervention was unlikely to be either more or less cost-effective than usual care. Seventy-eight patients died (46 in the intervention arm and 32 in the usual-care arm), with no evidence of difference between trial arms; no deaths appeared to be associated with the intervention.
Limitations
In this pragmatic trial, the implementation of the intervention was incomplete: 49% of patients received two 3D reviews over 15 months, whereas 75% received at least one review.
Conclusions
The 3D approach reflected international consensus about how to improve care for multimorbidity. Although it achieved the aim of providing more patient-centred care, this was not associated with benefits in quality of life, illness burden or treatment burden. The intervention was no more or less cost-effective than usual care. Modifications to the 3D approach might improve its effectiveness. Evaluation is needed based on whole-system change over a longer period of time.
Trial registration
Current Controlled Trials ISRCTN06180958.
Funding
This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 7, No. 5. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Chris Salisbury
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Mei-See Man
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Randomised Trials Collaboration, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Katherine Chaplin
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Cindy Mann
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Peter Bower
- National Institute for Health Research School for Primary Care Research, Centre for Primary Care, Division of Population of Health, Health Services Research and Primary Care, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Sara Brookes
- Bristol Randomised Trials Collaboration, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Polly Duncan
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Caroline Gardner
- National Institute for Health Research School for Primary Care Research, Centre for Primary Care, Division of Population of Health, Health Services Research and Primary Care, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Daisy M Gaunt
- Bristol Randomised Trials Collaboration, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Bruce Guthrie
- Population Health Sciences Division, School of Medicine, University of Dundee, Dundee, UK
| | - Sandra Hollinghurst
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Bryar Kadir
- Bristol Randomised Trials Collaboration, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Victoria Lee
- National Institute for Health Research School for Primary Care Research, Centre for Primary Care, Division of Population of Health, Health Services Research and Primary Care, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - John McLeod
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Stewart W Mercer
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Keith R Moffat
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Emma Moody
- Bristol Clinical Commissioning Group, Bristol, UK
| | - Imran Rafi
- Royal College of General Practitioners, London, UK
| | | | - Alison Shaw
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Joanna Thorn
- Centre for Academic Primary Care, National Institute for Health Research School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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