Development And Validation Of A Stage-matched Nutrition Lifestyle Intervention For Primary Care Physicians
Bibliographic record
Abstract
PURPOSE Adoption of healthy lifestyles require change of behavior readiness to do so. We report validation of a stage-specific Mediterranean diet algorithm. Methods Subjects included 3 representative groups of individuals varying from low cardiovascular disease risk (healthy adults), moderate risk (newly diagnosed with IGT) and high risk (newly diagnosed T2D). An algorithm adapted from Greene was used to identify stage of readiness to adopt a Mediterranean diet where benchmarks of this behavior change was defined as low saturated fat, use of olive oil/margarine, increased fruits and vegetables, increased fish, reduced red meat and increased fibre. The algorithm was divided into three steps; Step One identified individuals in the Precontemplation (P), Contemplation (C) and Preparation (Pr) stages by answering: Do you currently follow a Mediterranean Style of Eating. Those reporting to be in the Action (A) or Maintenance (M) stages in Step One completed Steps Two and Three. The dietary fat assessment in Step Two included a short Mediterranean Diet Self Assessment (adapted from the Fat and Fibre Barometer) used to measure if the individual is actually practicing Mediterranean-type eating habits. Step Three asked the individual if they met each of the required behaviors for fat reduction. If they are able to answer yes to practicing all of the Mediterranean eating habits, they remained in the original A or M stage (from Step One), if not they were re-staged into P, C or Pr stages. Results The sample consisted of 70.7% females with a mean age of 62.4 (± 14.1). People with Type 2 diabetes represented 34.1% of the sample and those with IGT 19.5%. The initial staging in Step 1 indicated a valid percentage of participants at each stage (P=18.9%; 10.8%; Pr=21.6%; A=13.5%; M=35.1%). The final stage distribution reflecting the use of the Step 2 and 3 behavioral algorithm strategies resulted in the M Stage only 7.7% and 53.8% of participants in the Pr Stage. The percentage of at risk participants in the preparation stage (71.4%) was higher than the well population (33.3%). Alternatively the percentage of Precontemplators in the well population (36.9%) was higher in comparison to that in the at risk group (4.6%). Conclusions This pilot reconfirms previous reports that many people believe they are eating a healthy diet (and place themselves in action or maintenance stages) due to misconceptions regarding the definition of a healthy eating behaviours. The results from the pilot of the Mediterranean Diet Algorithm indicate that the addition of a Mediterranean Diet Self Assessment (MDSA) for those in the A and M stages (Steps 2 and 3) was effective in improving the accuracy of staging.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".