Identifying factors that underpin student decisions to pursue the Doctor of Pharmacy degree at Atlantic Canadian Universities: Protocol for a mixed methods study
Bibliographic record
Abstract
Several international studies have investigated academic decision-making in higher education, but there is limited research on students' choice to study pharmacy in the Canadian context. While there is some variation across jurisdictions, decisions to enroll in a particular degree program fall into several decision-making domains (e.g., personal, family, institutional, social, and economic). These findings have been theorized in various ways, for example, through social cognitive theory and social reproduction theory. The purpose of this study is to gain a better understanding of the personal, family, institutional, social, and economic factors that underpin student decisions to pursue the Doctor of Pharmacy (PharmD) degree at Atlantic Canadian Universities and to explore barriers to pursuing a pharmacy degree. The proposed study uses an explanatory sequential mixed-methods design consisting of a quantitative survey followed by qualitative interviews. All entry-to-practice PharmD students and graduates in Atlantic Canada are eligible to participate. The survey consists of several Likert scale questions associated with five decision-making domains, as well as several socio-demographic questions. Descriptive statistics and frequency counts will be used to describe the data; differences across decision-making domains, by gender and other demographic groupings, will be analyzed using inferential statistics. Semi-structured interviews with a sample of 12 to 15 participants will be conducted to further understand and explain the quantitative results. We will engage in thematic analysis of qualitative data. The findings of this research will provide insight into the decision-making patterns and socio-demographic characteristics of students who have chosen to pursue a PharmD. Important information will be gathered to inform health professional education and workforce planning, which we believe will contribute to improving healthcare resource capacity and patient outcomes in Atlantic Canada. The results of this project will also inform future recruitment strategies and admission criteria and support educators in the secondary school system in providing evidence-informed career counselling advice for students interested in pursuing a degree in pharmacy. The findings of this study may also be useful to educational leaders and policymakers.
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 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 | 0.076 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.064 | 0.011 |
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".