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
Bibliographic record
Abstract
BACKGROUND: Unhealthy dietary patterns and insufficient physical activity (PA) are associated with negative health outcomes, such as cardiovascular diseases, type 2 diabetes, cancer, overweight, and obesity. This makes the promotion of healthy dietary and PA behaviors a public health priority. OBJECTIVE: This paper describes the development, design, and evaluation protocol of a Web-based computer-tailored (CT) dietary and PA promotion intervention, MyLifestyleCoach. A Web-based format was chosen for its accessibility and large-scale reach and low-cost potential. To achieve effective and persistent behavioral change, this innovative intervention is tailored to individual characteristics and is based on the self-determination theory and motivational interviewing (MI). METHODS: The 6 steps of the intervention mapping protocol were used to systematically develop MyLifestyleCoach based on the existing effective CT PA promotion intervention I Move. The MyLifestyleCoach intervention consists of 2 modules: I Move, which is aimed at promoting PA, and I Eat, which is aimed at promoting healthy eating. Development of the I Eat module was informed by the previously developed I Move. Both modules were integrated to form the comprehensive MyLifestyleCoach program. Furthermore, I Move was slightly adapted, for example, the new Dutch PA guidelines were implemented. A randomized controlled trial consisting of an intervention condition and waiting list control group will be used to evaluate the effectiveness of the intervention on diet and PA. RESULTS: Self-reported measures take place at baseline, 6 months, and 12 months after baseline. Enrollment started in October 2018 and will be completed in June 2020. Data analysis is currently under way, and the first results are expected to be submitted for publication in 2020. CONCLUSIONS: MyLifestyleCoach is one of the first interventions to translate and apply self-determination theory and techniques from MI in Web-based computer tailoring for an intervention targeting PA and dietary behavior. Intervention mapping served as a blueprint for the development of this intervention. We will evaluate whether this approach is also successful in promoting eating healthier and increasing PA using an randomized controlled trial by comparing the intervention to a waiting list control condition. The results will provide an insight into the short- and long-term efficacy and will result in recommendations for the implementation and promotion of healthy eating and PA among adults in the Netherlands. TRIAL REGISTRATION: Dutch Trial Register NL7333; https://www.trialregister.nl/trial/7333. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14491.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.028 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.058 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".