Evaluation of an infographic: prescription drug misuse among older adults in Saskatchewan
Bibliographic record
Abstract
Misuse of prescription drugs leads to morbidity and mortality. Prescription drug misuse among older adults over the age of 60 years is an understudied area which needs attention and one of the best methods to spread awareness is through infographics. The main objective of this study was to develop and evaluate an infographic on the extent of prescription drug misuse problems among older adults over the age of 60 years in Saskatchewan, Canada. A mixed-method approach was used for this study which involved an online survey and development of an infographic. The survey was administered between October and November 2022. Survey participants were asked about their drug use habits. An infographic was created based on the results. Two focus groups which consisted of seven individuals were carried out to evaluate the infographic over Zoom. Questions were asked based on three themes (content, presentation, and reflection). Data from the focus group was used to revise the infographic. The majority of participants in the focus group indicated that the infographic was useful in getting the message across to the public and would be beneficial in various health care settings.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".