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Palacz-Poborczyk I, Naughton F, Luszczynska A, Januszewicz A, Quested E, Hagger MS, Pagoto S, Verboon P, Robinson S, Kwasnicka D. Choosing Health: acceptability and feasibility of a theory-based, online-delivered, tailored weight loss, and weight loss maintenance intervention. Transl Behav Med 2024:ibae023. [PMID: 38768381 DOI: 10.1093/tbm/ibae023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024] Open
Abstract
Few weight loss and weight loss maintenance interventions are tailored to include factors demonstrated to predict the user's behavior. Establishing the feasibility and acceptability of such interventions is crucial. The aim of this study was to assess the acceptability and feasibility of a theory-based, tailored, online-delivered weight loss and weight loss maintenance intervention (Choosing Health). We conducted a mixed methods process evaluation of the Choosing Health tailored intervention, nested in a randomized controlled trial (N = 288) with an embedded N-of-1 study, investigating participants' and implementers' experiences related to intervention context, implementation, and mechanisms of impact. Measures included: (i) surveys, (ii) data-prompted interviews (DPIs) with study participants, (iii) semi-structured interviews with implementers, and (iv) intervention access and engagement data. Five themes described the acceptability of the intervention to participants: (i) monitoring behavior change and personal progress to better understand the weight management process, (ii) working collaboratively with the intervention implementers to achieve participants' goals, (iii) perceived benefits of non-judgmental and problem-solving tone of the intervention, (iv) changes in personal perception of the weight management process due to intervention tailoring, and (v) insufficient intervention content tailoring. The intervention delivery was feasible, however, emails and text messages differed in terms of accessibility and resources required to deliver the content. The use of Ecological Momentary Assessment as a technique to gather personal data for further tailoring was acceptable, and facilitated behavior change monitoring. Personalization of the intervention content above and beyond domain-specific issues, for example, by addressing participants' social roles may better match their needs. Support from the implementers and feedback on body composition changes may increase participants' engagement.
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Affiliation(s)
- Iga Palacz-Poborczyk
- Faculty of Psychology, SWPS University, Aleksandra Ostrowskiego 30b, 53-238 Wroclaw, Poland
| | - Felix Naughton
- Behavioural and Implementation Science Group, School of Health Sciences, University of East Anglia, Norwich NR4 7UL, UK
| | - Aleksandra Luszczynska
- Faculty of Psychology, SWPS University, Aleksandra Ostrowskiego 30b, 53-238 Wroclaw, Poland
| | - Anna Januszewicz
- Faculty of Psychology, SWPS University, Aleksandra Ostrowskiego 30b, 53-238 Wroclaw, Poland
| | - Eleanor Quested
- Physical Activity and Well-being Research Group, enAble Institute, Curtin University, Perth, Australia
- Curtin School of Population Health, Curtin University, Kent Street, 6102 Perth, Australia
| | - Martin S Hagger
- Department of Psychological Sciences, University of California, Merced, 5200 N. Lake Rd., Merced, CA 95343, USA
- Health Sciences Research Institute, University of California, Merced, 5200 N. Lake Rd., Merced, CA 95343, USA
- Faculty of Sport and Health Sciences, University of Jyväskylä, Seminaarinkatu 15, 40014 Jyväskylä, Finland
- School of Applied Psychology, Griffith University, Mt. Gravatt Campus,176 Messines Ridge Rd, Mount Gravatt QLD 4122, Australia
| | - Sherry Pagoto
- Department of Allied Health Sciences, The UConn Center for mHealth and Social Media, University of Connecticut, Connecticut, USA
| | - Peter Verboon
- Department of Psychology, Open Universiteit Nederland, Heerlen, The Netherlands
| | - Suzanne Robinson
- Curtin School of Population Health, Curtin University, Kent Street, 6102 Perth, Australia
- Deakin Health Economics, Institute for Health Transformation, Deakin University, Victoria, Australia
| | - Dominika Kwasnicka
- Faculty of Psychology, SWPS University, Aleksandra Ostrowskiego 30b, 53-238 Wroclaw, Poland
- Melbourne School of Population and Global Health, University of Melbourne, 333 Exhibition Street, 3000 Melbourne, Australia
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Perski O, Keller J, Kale D, Asare BYA, Schneider V, Powell D, Naughton F, ten Hoor G, Verboon P, Kwasnicka D. Understanding health behaviours in context: A systematic review and meta-analysis of ecological momentary assessment studies of five key health behaviours. Health Psychol Rev 2022; 16:576-601. [PMID: 35975950 PMCID: PMC9704370 DOI: 10.1080/17437199.2022.2112258] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Ecological Momentary Assessment (EMA) involves repeated, real-time sampling of health behaviours in context. We present the state-of-knowledge in EMA research focused on five key health behaviours (physical activity and sedentary behaviour, dietary behaviour, alcohol consumption, tobacco smoking, sexual health), summarising theoretical (e.g., psychological and contextual predictors) and methodological aspects (e.g., study characteristics, EMA adherence). We searched Ovid MEDLINE, Embase, PsycINFO and Web of Science until February 2021. We included studies focused on any of the aforementioned health behaviours in adult, non-clinical populations that assessed ≥1 psychological/contextual predictor and reported a predictor-behaviour association. A narrative synthesis and random-effects meta-analyses of EMA adherence were conducted. We included 633 studies. The median study duration was 14 days. The most frequently assessed predictors were 'negative feeling states' (21%) and 'motivation and goals' (16.5%). The pooled percentage of EMA adherence was high at 81.4% (95% CI = 80.0%, 82.8%, k = 348) and did not differ by target behaviour but was somewhat higher in student (vs. general population) samples, when EMAs were delivered via mobile phones/smartphones (vs. handheld devices), and when event contingent (vs. fixed) sampling was used. This review showcases how the EMA method has been applied to improve understanding and prediction of health behaviours in context.
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Affiliation(s)
- Olga Perski
- Department of Behavioural Science and Health, University College London, London, United Kingdom, Olga Perski
| | - Jan Keller
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - Dimitra Kale
- Department of Behavioural Science and Health, University College London, London, United Kingdom
| | - Bernard Yeboah-Asiamah Asare
- Curtin School of Population Health, Curtin University, Perth, Australia,Health Psychology, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Verena Schneider
- Department of Behavioural Science and Health, University College London, London, United Kingdom
| | - Daniel Powell
- Health Psychology, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom,Rowett Institute, University of Aberdeen, Aberdeen, United Kingdom
| | - Felix Naughton
- Behavioural and Implementation Science Research Group, School of Health Sciences, University of East Anglia, Norwich, United Kingdom
| | - Gill ten Hoor
- Department of Work and Social Psychology, Faculty of Psychology and Neurosciences, Maastricht University, Maastricht, The Netherlands
| | - Peter Verboon
- Faculty of Psychology, Open University, Heerlen, The Netherlands
| | - Dominika Kwasnicka
- Faculty of Psychology, SWPS University of Social Sciences and Humanities, Wroclaw, Poland,NHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
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Richards R, Jones RA, Whittle F, Hughes CA, Hill AJ, Lawlor ER, Bostock J, Bates S, Breeze PR, Brennan A, Thomas CV, Stubbings M, Woolston J, Griffin SJ, Ahern AL. Development of a Web-Based, Guided Self-help, Acceptance and Commitment Therapy-Based Intervention for Weight Loss Maintenance: Evidence-, Theory-, and Person-Based Approach. JMIR Form Res 2022; 6:e31801. [PMID: 34994698 PMCID: PMC8783282 DOI: 10.2196/31801] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 10/25/2021] [Accepted: 10/27/2021] [Indexed: 12/15/2022] Open
Abstract
Background The long-term impact and cost-effectiveness of weight management programs depend on posttreatment weight maintenance. There is growing evidence that interventions based on third-wave cognitive behavioral therapy, particularly acceptance and commitment therapy (ACT), could improve long-term weight management; however, these interventions are typically delivered face-to-face by psychologists, which limits the scalability of these types of intervention. Objective The aim of this study is to use an evidence-, theory-, and person-based approach to develop an ACT-based intervention for weight loss maintenance that uses digital technology and nonspecialist guidance to minimize the resources needed for delivery at scale. Methods Intervention development was guided by the Medical Research Council framework for the development of complex interventions in health care, Intervention Mapping Protocol, and a person-based approach for enhancing the acceptability and feasibility of interventions. Work was conducted in two phases: phase 1 consisted of collating and analyzing existing and new primary evidence and phase 2 consisted of theoretical modeling and intervention development. Phase 1 included a synthesis of existing evidence on weight loss maintenance from previous research, a systematic review and network meta-analysis of third-wave cognitive behavioral therapy interventions for weight management, a qualitative interview study of experiences of weight loss maintenance, and the modeling of a justifiable cost for a weight loss maintenance program. Phase 2 included the iterative development of guiding principles, a logic model, and the intervention design and content. Target user and stakeholder panels were established to inform each phase of development, and user testing of successive iterations of the prototype intervention was conducted. Results This process resulted in a guided self-help ACT-based intervention called SWiM (Supporting Weight Management). SWiM is a 4-month program consisting of weekly web-based sessions for 13 consecutive weeks followed by a 4-week break for participants to reflect and practice their new skills and a final session at week 18. Each session consists of psychoeducational content, reflective exercises, and behavioral experiments. SWiM includes specific sessions on key determinants of weight loss maintenance, including developing skills to manage high-risk situations for lapses, creating new helpful habits, breaking old unhelpful habits, and learning to manage interpersonal relationships and their impact on weight management. A trained, nonspecialist coach provides guidance for the participants through the program with 4 scheduled 30-minute telephone calls and 3 further optional calls. Conclusions This comprehensive approach facilitated the development of an intervention that is based on scientific theory and evidence for supporting people with weight loss maintenance and is grounded in the experiences of the target users and the context in which it is intended to be delivered. The intervention will be refined based on the findings of a planned pilot randomized controlled trial.
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Affiliation(s)
- Rebecca Richards
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Rebecca A Jones
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Fiona Whittle
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | | | - Andrew J Hill
- School of Medicine, University of Leeds, Leeds, United Kingdom
| | - Emma R Lawlor
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jennifer Bostock
- Patient and Public Involvement Representative, Kent, United Kingdom
| | - Sarah Bates
- School of Health and Related Research, The University of Sheffield, Sheffield, United Kingdom
| | - Penny R Breeze
- School of Health and Related Research, The University of Sheffield, Sheffield, United Kingdom
| | - Alan Brennan
- School of Health and Related Research, The University of Sheffield, Sheffield, United Kingdom
| | - Chloe V Thomas
- School of Health and Related Research, The University of Sheffield, Sheffield, United Kingdom
| | - Marie Stubbings
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jennifer Woolston
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Simon J Griffin
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Amy L Ahern
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
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Bromley PA, Müller FO, Malan J, Torres J, Vanderbeke O. An Intervention Mapping Study: Developing the Choosing Health digital weight loss and maintenance intervention (Preprint). J Med Internet Res 2021; 24:e34089. [PMID: 362568 PMCID: PMC9627465 DOI: 10.2196/34089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 05/10/2022] [Accepted: 05/29/2022] [Indexed: 12/01/2022] Open
Abstract
Background Digital health promotion programs tailored to the individual are a potential cost-effective and scalable solution to enable self-management and provide support to people with excess body weight. However, solutions that are widely accessible, personalized, and theory- and evidence-based are still limited. Objective This study aimed to develop a digital behavior change program, Choosing Health, that could identify modifiable predictors of weight loss and maintenance for each individual and use these to provide tailored support. Methods We applied an Intervention Mapping protocol to design the program. This systematic approach to develop theory- and evidence-based health promotion programs consisted of 6 steps: development of a logic model of the problem, a model of change, intervention design and intervention production, the implementation plan, and the evaluation plan. The decisions made during the Intervention Mapping process were guided by theory, existing evidence, and our own research—including 4 focus groups (n=40), expert consultations (n=12), and interviews (n=11). The stakeholders included researchers, public representatives (including individuals with overweight and obesity), and experts from a variety of relevant backgrounds (including nutrition, physical activity, and the health care sector). Results Following a structured process, we developed a tailored intervention that has the potential to reduce excess body weight and support behavior changes in people with overweight and obesity. The Choosing Health intervention consists of tailored, personalized text messages and email support that correspond with theoretical domains potentially predictive of weight outcomes for each participant. The intervention content includes behavior change techniques to support motivation maintenance, self-regulation, habit formation, environmental restructuring, social support, and addressing physical and psychological resources. Conclusions The use of an Intervention Mapping protocol enabled the systematic development of the Choosing Health intervention and guided the implementation and evaluation of the program. Through the involvement of different stakeholders, including representatives of the general public, we were able to map out program facilitators and barriers while increasing the ecological validity of the program to ensure that we build an intervention that is useful, user-friendly, and informative. We also summarized the lessons learned for the Choosing Health intervention development and for other health promotion programs. International Registered Report Identifier (IRRID) RR2-10.1136/bmjopen-2020-040183
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