Protocol for a qualitative study exploring the pharmacist’s role in supporting postsecondary students with psychotropic medication management
Bibliographic record
Abstract
INTRODUCTION: Findings from the National College Health Assessment (2019) stated that anxiety and depression are the most prevalent diagnosed mental illnesses among Canadian postsecondary students with one-fifth of students self-reporting a lifetime diagnosis. Psychotropic medications can be an important component of a multifaceted approach to the management and treatment of mental illness and are the most commonly dispensed via community pharmacies. Community pharmacies provide an opportunity for pharmacists to have a prominent role in supporting patients' psychotropic medication management. However, there has been limited exploration of how pharmacists can address patients' psychotropic medication management needs, experiences and opportunities for improvements especially for emerging adults. METHODS AND ANALYSIS: This qualitative study will incorporate Thorne's approach to interpretative description. Purposeful snowball sampling will be used to identify students (18-25 years) taking psychotropic medication(s) to manage their mental health. Participants will be interviewed one on one using a semistructured interview guide virtually. Inductive thematic analysis is underway with data analysis being iterative and reflexive using NVivo. Information provided from the interviews will be reviewed and summarised into key themes. ETHICS AND DISSEMINATION: This study was approved by the University of Toronto Health Sciences Research Ethics Board (REB #43185). It is expected that there will be a very low risk for mild psychological and social harm for participants as they will have the ability to stop the interview at any time and will be aware of confidentiality. The results from this study will be used to create or adapt healthcare team services including the role of pharmacists within the healthcare ecosystem at the university and contribute to developing the next stage of research to evaluate feasibility and effectiveness of programmes at the university that help postsecondary students to manage psychotropic medication.
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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 | 0.071 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.095 | 0.017 |
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".