An international systematic mapping review of fieldwork education in occupational therapy
Bibliographic record
Abstract
BACKGROUND: Owing to its importance in preparing occupational therapists, fieldwork education has generated numerous studies. These have not been collected and reviewed, leaving researchers without a map for growing a science of fieldwork education. PURPOSE: This study aimed to systematically categorize the topics, research designs, methods, levels of impact, and themes that have and have not been addressed in fieldwork education scholarship. METHOD: Guided by a systematic mapping review design, 124 articles, identified through database searches and inclusion coding, were studied. Data were collected using a data extraction instrument and analyzed using Microsoft Access queries. FINDINGS: Papers primarily addressed curriculum (n = 51) and students (n = 32). Conceptual/descriptive inquiry methods (n = 57) were predominant. Qualitative (n = 48) and quantitative methods (n = 49) were used equally. Research outcomes mainly targeted perceived participation in fieldwork. Recurring themes included student perceptions, external influences, and transition to practice. IMPLICATIONS: Three recommendations were identified: strengthen procedures for studying singular fieldwork experiences, broaden rationales for studying fieldwork, and translate educational concepts for occupational therapy.
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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 | 0.037 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.039 | 0.040 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".