Mobile technology intervention for weight loss in rural men: protocol for a pilot pragmatic randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Men who are overweight or obese in the rural Midwestern USA are an unrepresented, at-risk group exhibiting rising rates of cardiovascular disease, poor access to preventive care and poor lifestyle behaviours that contribute to sedentary lifestyle and unhealthy diet. Self-monitoring of eating and activity has demonstrated efficacy for weight loss. Use of mobile technologies for self-monitoring eating and activity may address rural men's access disparities to preventive health resources and support weight loss. Our pilot trial will assess the feasibility and acceptability of two mobile applications for weight loss in rural men to inform a future, full-scale trial. METHODS AND ANALYSIS: A 6-month randomised controlled trial with contextual evaluation will randomise 80 men using a 1:1 ratio to either a Mobile Technology Plus (MT+) intervention or a basic Mobile Technology (MT) intervention in rural, midlife men (aged 40-69 years). The MT+ intervention consists of a smartphone self-monitoring application enhanced with discussion group (Lose-It premium), short message service text-based support and Wi-Fi scale. The MT group will receive only a self-monitoring application (Lose-It basic). Feasibility and acceptability will be evaluated using number of men recruited and retained, and evaluative focus group feedback. We seek to determine point estimates and variability of outcome measures of weight loss (kg and % body weight) and improved dietary and physical activity behaviours (Behavioral Risk Factor Surveillance System (BRFSS) physical activity and fruit and vegetable consumption surveys, data from Lose-It! application (kcal/day, steps/day)). Community capacity will be assessed using standard best practice methods. Descriptive content analysis will evaluate intervention acceptability and contextual sensitivity. ETHICS AND DISSEMINATION: This protocol was approved by the University of Nebraska Medical Center Institutional Review Board (IRB# 594-17-EP). Dissemination of findings will occur through ClinicalTrials.gov and publish pilot data to inform the design of a larger clinical trial. TRIAL REGISTRATION NUMBER: NCT03329079; preresults. Protocol V.10, study completion date 31 August 2020. Roles and responsibilities funder: NIH/NINR Health Disparities Section 1R15NR017522-01.
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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 | 0.035 | 0.030 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.095 | 0.014 |
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".