Improving Vitamin D Status and Related Health in Young Women: The Safe-D study – Part B
Bibliographic record
Abstract
BACKGROUND: Vitamin D deficiency is highly prevalent and associated with increased risk of a number of chronic health conditions including cardiovascular disease, poor bone and muscle health, poor mental health, infection, and diabetes. Vitamin D deficiency affects millions of Australians, potentially causing considerable suffering, economic loss, and mortality. OBJECTIVE: To measure the effectiveness of a (1) mobile-based app (behavioral) and (2) pharmacological intervention to increase circulating 25-hydroxyvitamin D (serum 25 OHD) levels and health outcomes over 4 months of intervention compared with usual care in a cohort of young women with suboptimal serum 25 OHD levels (25-75 nmol/L). METHODS: Participants with 25 OHD levels 25 to 75 nmol/L are invited to participate in this study. Participants are randomized to one of three groups in 1:1:1 ratio: a mobile phone-based application, vitamin D supplementation (1000 IU/day), and a control group. Data collection points are at baseline, 4, and 12 months post baseline with the major endpoints being at 4 months. A wide-range of information is collected from participants throughout the course of this study. General health, behavioral and demographic information, medications, smoking, alcohol and other substance use, health risk factors, nutrition, eating patterns and disorders, and mental health data are sourced from self-administered, Web-based surveys. Clinical data include anthropometric measurements, a silicone skin cast of the hand, cutaneous melanin density, bone mineral density, and body composition scans obtained through site visits. Main analyses will be conducted in two ways on an intention-to-treat (ITT) basis using the last observation carried forward approach as an imputation for missing data, and on a per protocol basis to compare the intervention arms against the control group at 4 and 12 months. RESULTS: Publication of trial results is anticipated in 2017. CONCLUSIONS: The study will allow assessment of the effects of a mobile-based app behavioral intervention and vitamin D supplementation on vitamin D status and will evaluate the effects of improving vitamin D levels on several health outcomes.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".