Development, implementation and evaluation of the online Movement, Interaction and Nutrition for Greater Lifestyles in the Elderly (MINGLE) program: The protocol for a pilot trial
Bibliographic record
Abstract
INTRODUCTION: People with age-related macular degeneration (AMD) are more likely to experience loneliness, have poorer diets and be less physically active than people without AMD. The online Movement, Interaction and Nutrition for Greater Lifestyles in the Elderly (MINGLE) program is a holistic evidence-based intervention aiming to support people with AMD by incorporating physical activity, social interaction and nutrition education components all delivered via a COVID-19-safe Zoom platform. This study will involve two phases: 1) a formative qualitative study with AMD patients to identify the barriers and facilitators to participating in the proposed MINGLE program; and 2) a 10-week pilot study to evaluate the feasibility, acceptability and preliminary efficacy of MINGLE. METHODS AND ANALYSIS: Phase 1 involves AMD patients who will be recruited from an eye clinic in Western Sydney, Australia to participate in audio-recorded semi-structured interviews. Verbatim interview transcripts will be coded using the Capability, Opportunity, Motivation and Behaviour (COM-B) model and themes established. These themes will be used as a guide to specifically tailor the proposed MINGLE program to people with AMD. Phase 2 involves 52 AMD patients who will then be recruited from the same clinic to participate in the MINGLE program. Pre-post questionnaires will be administered to intervention participants to collect information on the following variables: demographics, socioeconomic status, vision function, loneliness, quality of life (including depression), falls risk, physical activity (level), and dietary intake. The acceptability and feasibility of the MINGLE program will also be evaluated using descriptive statistics. TRIAL REGISTRATION NUMBER: ACTRN12621000939897p.
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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 | 0.045 | 0.036 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.048 | 0.010 |
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".