Comparing Diet and Exercise Monitoring Using Smartphone App and Paper Diary: A Two-Phase Intervention Study
Bibliographic record
Abstract
BACKGROUND: There is increasing recognition that personalized approaches may be more effective in helping people establish healthier eating patterns and exercise more, and that this approach may be particularly effective in adolescents. OBJECTIVE: The objective of this study was to investigate the use of a smartphone app (FoodWiz2) in supporting healthy lifestyle choices in adolescence. METHODS: Participants (N=34: 11 male, 23 female) aged 16-19 years in full- or part-time education were recruited from sixth form colleges, schools, and other further education establishments in Norfolk and Suffolk, United Kingdom, between February and May 2015. Participants recorded food intake and exercise using a paper diary for 4-5 weeks and then used the app for the same duration. Initial nutrition education and general support were provided during the paper diary use, but the app included personalized messages sent in response to app activity. At the end of each study phase, participants completed an online questionnaire to describe their experience of using the paper diary and app. RESULTS: Record completion declined throughout the study, possibly affected by examination pressure. Food intake data showed increased fruit consumption and significantly reduced consumption of chocolate snacks (P=.01) and fizzy drinks (P=.002) among participants using the app. Questionnaire responses indicated that the app was generally preferred to the paper diary, in particular, the app was seen as less boring to use (P=.03) and more acceptable in social settings (P<.001). CONCLUSIONS: This app-based approach has shown the potential for a more effective approach to improving adolescent diet and exercise levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".