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Journal of Medical Internet Research
Article . 2022 . Peer-reviewed
Data sources: Crossref
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Jyväskylä University Digital Archive
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Developing the "Choosing Health" Digital Weight Loss and Maintenance Intervention: Intervention Mapping Study

Intervention Mapping Study
Authors: Palacz-Poborczyk, Iga; Idziak, Paulina; Januszewicz, Anna; Luszczynska, Aleksandra; Quested, Eleanor; Naughton, Felix; Hagger, Martin S; +5 Authors

Developing the "Choosing Health" Digital Weight Loss and Maintenance Intervention: Intervention Mapping Study

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

Countries
Finland, United Kingdom, Netherlands
Keywords

Obesity/therapy, behavior change, obesity, behavior maintenance, Computer applications to medicine. Medical informatics, digital health, R858-859.7, 610, Health Promotion, Weight Gain, Health Promotion/methods, terveyden edistäminen, painonhallinta, käyttäytymismallit, Weight Loss, Liikuntapsykologia, overweight, Humans, within-person design, Obesity, teleterveydenhuolto, Intervention Mapping, Exercise, Sport and Exercise Psychology, ta515, interventio, behavioral theory, Original Paper, intervention Mapping, laihdutus, ta3141, ylipaino, interventiotutkimus, Overweight, satunnaistetut vertailukokeet, terveyskäyttäytyminen, randomized controlled trial, lihavuus, weight loss, Public aspects of medicine, RA1-1270

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green
gold