ArticleBMC public health2013
Systematic development of a text-driven and a video-driven web-based computer-tailored obesity prevention intervention.
Article in BMC public health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Employee Perceptions of Workplace Health Promotion Programs: Comparison of a Tailored, Semi-Tailored, and Standardized Approach.International journal of environmental research and public health · 2018Trial
- Effectiveness of a Video-Versus Text-Based Computer-Tailored Intervention for Obesity Prevention after One Year: A Randomized Controlled Trial.International journal of environmental research and public health · 2017Trial
- Comparing a Video and Text Version of a Web-Based Computer-Tailored Intervention for Obesity Prevention: A Randomized Controlled Trial.Journal of medical Internet research · 2015Trial
- Rationale, design and baseline characteristics of a randomized controlled trial of a web-based computer-tailored physical activity intervention for adults from Quebec City.BMC public health · 2015Trial
- Innovative video tailoring for dietary change: final results of the Good for you! cluster randomized trial.The international journal of behavioral nutrition and physical activity · 2015Trial
- Use and Effectiveness of a Video- and Text-Driven Web-Based Computer-Tailored Intervention: Randomized Controlled Trial.Journal of medical Internet research · 2015Trial
- Trial
- Tailoring in eHealth lifestyle interventions targeting people with cardiometabolic conditions and lower socioeconomic position: A scoping review.PLOS digital health · 2026Article
- Parent-implemented early intervention design for improving speech and language skills among Mandarin-speaking infants and toddlers with cleft lip and/or palate.Frontiers in public health · 2025Article
- A Tailored Motivational Messages Library for a Mobile Health Sleep Behavior Change Support System to Promote Continuous Positive Airway Pressure Use Among Patients With Obstructive Sleep Apnea: Development, Content Validation, and Testing.JMIR mHealth and uHealth · 2020Article
- Development and Testing of a Personalized Web-Based Diet and Physical Activity Intervention Based on Motivational Interviewing and the Self-Determination Theory: Protocol for the MyLifestyleCoach Randomized Controlled Trial.JMIR research protocols · 2020Article
- Article
- En_Línea. An online treatment to change lifestyle in overweight and obesity: study protocol for a randomized controlled trial.BMC public health · 2019Article
- User Models for Personalized Physical Activity Interventions: Scoping Review.JMIR mHealth and uHealth · 2019Article
- Development of a computer-tailored nutrition and physical activity intervention for lower-educated women of Dutch, Turkish and Moroccan origin using content matching and ethnic identity tailoring.BMC public health · 2016Article
- A Self-Regulation eHealth Intervention to Increase Healthy Behavior Through General Practice: Protocol and Systematic Development.JMIR research protocols · 2015Article
- Impact of Educational Level on Study Attrition and Evaluation of Web-Based Computer-Tailored Interventions: Results From Seven Randomized Controlled Trials.Journal of medical Internet research · 2015Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis paper describes the systematic development of a text-driven and a video-driven web-based computer-tailored intervention aimed to prevent obesity among normal weight and overweight adults. We hypothesize that the video-driven intervention will be more effective and appealing for individuals with a low level of education. METHODS AND
designThe Intervention Mapping protocol was used to develop the interventions, which have exactly the same educational content but differ in the format in which the information is delivered. One intervention is fully text-based, while in the other intervention in addition to text-based feedback, the core messages are provided by means of videos. The aim of the interventions is to prevent weight gain or achieve modest weight loss by making small changes in dietary intake or physical activity. The content of the interventions is based on the I-Change Model and self-regulation theories and includes behavior change methods such as consciousness raising, tailored feedback on behavior and cognitions, goal setting, action and coping planning, and evaluation of goal pursuit. The interventions consist of six sessions. In the first two sessions, participants will set weight and behavioral change goals and form plans for specific actions to achieve the desired goals. In the remaining four sessions, participants' will evaluate their progress toward achievement of the behavioral and weight goals. They will also receive personalized feedback on how to deal with difficulties they may encounter, including the opportunity to make coping plans and the possibility to learn from experiences of others. The efficacy and appreciation of the interventions will be examined by means of a three-group randomized controlled trial using a waiting list control group. Measurements will take place at baseline and six and twelve months after baseline. Primary outcome measures are body mass index, physical activity, and dietary intake. DISCUSSION: The present paper provides insight into how web-based computer-tailored obesity prevention interventions consisting of self-regulation concepts and text-driven and video-driven messages can be developed systematically. The evaluation of the interventions will provide insight into their efficacy and will result in recommendations for future web-based computer-tailored interventions and the additional value of using video tailoring.
trial registrationNTR3501.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.