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Record W7116977344 · doi:10.2196/76599

Medical Students' Reflections on Transitioning to Their First General Practice Placement: Qualitative Descriptive Study

2025· article· en· W7116977344 on OpenAlexaffvenue
Sara Bashar Qasrawi, Maryam Tomerak, Shahad Abdulkhaleq Mamalchi, Fatima Atieh, Hasan Aladraj, Mohamed Abdulla, Salim Fredericks, Ghufran Jassim, Hani Malik, Eric Clarke, Denis W. Harkin, Shaista Salman Guraya

Bibliographic record

VenueJMIR Medical Education · 2025
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeneral practiceDescriptive researchQualitative researchMedical practiceNatural rubber

Abstract

fetched live from OpenAlex

Background: Transitioning from preclinical to clinical training is a critical milestone of "becoming and being" in a medical student's journey. Despite simulation-based learning, real-world clinical exposure remains indispensable in shaping professional identity. The clinical learning environment is a complex interplay of social, cultural, and organizational factors that influence students' development as future health care professionals. Objective: This study explores medical students' reflections on their first clinical placement in general practice, aiming to understand their experiences, challenges, and the clinical learning environment's role in their learning and developing professional identity formation as a step toward establishing a conceptual framework and a common language for educators, which we hope will promote further advances to support beneficial professional identity formation. Methods: We analyzed reflections from fourth-year medical students following their initial general practice placement. A qualitative descriptive approach grounded in naturalism was employed to explain our participants' transitioning encounters in clear, everyday language to ensure their experiences were presented in their own words, without bias. Content thematic analysis was conducted to identify key themes related to their experiences. Results: Students' reflections revealed a startled cohort unprepared for the epistemological, emotional, and practical realities of clinical work. Many assumed that classroom "knowing" would seamlessly translate into clinical "doing" but were met instead with uncertainty, failure, and emotional overwhelm, often manifesting as shame, guilt, and withdrawal. These experiences illuminated a fracture between knowledge and knowing, underscored by students' prereflective epistemological beliefs and varying degrees of supervisory preparedness. While emotional and cognitive struggles were widespread, rare instances of supportive mentorship and feedback significantly bolstered students' confidence and participation. Conclusions: Reflection offered a valuable window into how students think, feel, and act during this critical transition, but it is not a cure-all. Reflection should be positioned as a developmental and communal tool within a broader scaffolding that includes early skills preparation, role clarity, psychological safety, and trained supervisors. Structured shared reflective circles and narrative listening sessions can help normalize uncertainty, support identity formation, and foster resilience during students' entry into clinical practice and can ease the journey of "becoming and being."

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 imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.008
Scholarly communication0.0060.003
Open science0.0030.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.041
GPT teacher head0.512
Teacher spread0.472 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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