A Content Analysis of Free, Popular Plant-Based Mobile Health Apps
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There has been an increased emphasis on plant-based foods and diets in numerous dietary guidelines worldwide. Although mobile technology has the potential to be a convenient and cost-effective tool to aid adherence to dietary guidelines, little is known about the content and the quality of available mobile Apps on plant-based diets. Therefore, the objective of the study was to assess free, popular mobile health (mHealth) Apps supporting plant-based diets for Canadians. Using pre-defined search terms, Apple iTunes and GooglePlay App stores were searched on December 22, 2020; the top 100 returns for each search term were screened for eligibility. Free and popular (≥3 out of 5 ratings; ≥100 total reviews) mHealth Apps available in English, primarily marketed to help users follow plant-based diets were included. Included Apps were downloaded and assessed for quality by three research assistants/dietitians using the Mobile App Rating Scale (MARS) and the App Quality Evaluation (AQEL) tool. Of the 998 Apps screened, 16 Apps (mean ratings ± SEM = 4.5 ± 0.08) met the eligibility criteria for assessment, comprising 10 recipe manager and meal planners, 2 food scanners, 2 vegan community builders, 1 restaurant identifier, and 1 sustainability-focused App. All included Apps targeted the general population and focused on changing behaviours using education (14 Apps), skills training (14 Apps), and/or goal setting (5 Apps). Vegan, vegetarian or other plant-based (e.g., pescatarian, flexitarian) settings were available in 13 Apps, while 3 Apps offered no plant-based diet settings. The MARS (rated out of 5) revealed a high overall App quality score (3.84 ± 0.66) and subjective quality score (3.63 ± 0.62), but low credibility score (2.09 ± 0.36). The AQEL (rated out of 10) revealed high scores in App function (8.29 ± 0.47), purpose (8.11 ± 0.39), and behavioral change potential (8.35 ± 0.45), but a low score in support of knowledge acquisition (4.82 ± 0.43). Although a variety of free plant-based Apps with different focuses and behavioural change techniques are available to help Canadians follow plant-based diets, our findings suggest a need for credible Apps and other resources to complement the low support of knowledge acquisition in plant-based Apps. Banting & Best Diabetes Centre.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it