Health Communication Cards as a Tool for Behaviour Change
Bibliographic record
Abstract
Individuals seeking healthcare treatment in the context of obesity often experience difficulty engaging in discussions around their health and face challenges finding consensus with practitioners on care plans that best suit their lives. The complex set of biological, social, and environmental variables that have contributed to the higher prevalence of obesity are well illustrated in the foresight obesity system map. Effectively understanding and addressing key variables for each individual has proven to be difficult, with clinicians facing barriers and limited resources to help address patients' unique needs. However, productive discussions inspired by patient centered care may be particularly effective in promoting behaviour change. Tools based on systems science that facilitate patient centered care and help identify behaviour change priorities have not been developed to help treat adult obesity. This project created and pilot tested a card based clinical communication tool designed to help facilitate conversations with individuals engaged in health behaviour change. The health communication cards were designed to help direct conversation between patients and healthcare providers toward issues relevant to the individual. Use of the cards to facilitate patient driven conversations in clinical care may help to streamline conversations, set realistic care plan goals, and improve long term rates of compliance.
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.
How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".