PSYCHOLOGICAL PROFILE OF FRESHMAN PHARMACY STUDENTS
Bibliographic record
Abstract
In the last decades, the role of pharmacists has changed, and new tasks are required for the care of patients. Good communication skills, rapid adjustment to new techniques and research abilities must be developed during academic formation. Aim: the goal of the study is to shape the psychological profile of freshman pharmacy students. Material and methods: 106 freshman pharmacy students were asked to fill in a socio-demographic data sheet and to answer the items of four instruments: Maslach Burnout Inventory (measuring burnout), Toronto Alexithymia Scale (measuring the level of alexithymia), Big Five Inventory (identifying personality traits) and Beck Depression Inventory (evaluating depression). The statistical analysis of data was done using SPSS Statistics 23.0.0 for MAC.OSX. Results: the results identified an average level of emotional exhaustion, a low level of depersonalization and a high level of personal achievement. The scores for alexithymia prove that a possible alexithymia and a mild level of depression was identified for freshman pharmacy students. Comparative results and correlation analysis are presented. Conclusions: the results are important for the pharmacy students to identify their personality traits and for the academic staff to adjust the educational curricula to cover the needs for professional development.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".