Overcoming Barriers: Adolescents’ Experiences Using a Mobile Phone Dietary Assessment App
Bibliographic record
Abstract
BACKGROUND: The use of new technology has the potential to increase participation rates in dietary studies and improve the validity of collected dietary data. However, to evaluate the usability of developed dietary methods, qualitative studies of participants' experiences and perceptions are needed. OBJECTIVE: To explore adolescents' experiences using a newly developed mobile phone dietary assessment app, with a focus on factors that could affect their recording of dietary intake. METHODS: Focus group interviews were conducted with 75 participants who had used a newly developed mobile phone dietary assessment app in a quantitative evaluation study. The interviews were analyzed using qualitative content analysis and the theoretical framework of Self Determination Theory was applied. RESULTS: The adolescents' use of the mobile phone dietary assessment app was characterized by their struggle to overcome several perceived barriers. Facilitators that helped adolescents complete the method were also identified. Motivation was found to be an important facilitator, and intrinsically motivated participants completed the method because they found it fun to use. The autonomous extrinsically motivated participants completed the method for the greater good, in order to contribute to the study. The controlled extrinsically motivated participants completed the method to get a reward or avoid punishment. Amotivated participants did not complete the method. More motivated participants were assumed to be more able to overcome barriers and needed less facilitators. CONCLUSIONS: Future studies that examine the recording of food intake should include systematic efforts that aim to minimize identified barriers and promote identified facilitators. Further research should specifically aim at studying methods for (and effects of) increasing intrinsic motivation by supporting autonomy, competence, and relatedness among adolescents asked to participate in dietary studies.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".