Design, implementation and evaluation of a blended intensive short-term dynamic psychotherapy course
Bibliographic record
Abstract
Purpose: There is a trend towards competency based education in Canada.The Royal College of Physicians and Surgeons of Canada has greatly enhanced and expanded the psychotherapy requirements for postgraduate psychiatry training programs to reflect this trend.However, training programs throughout the country are finding it difficult to meet these expanded requirements.A wide variety of psychotherapy modalities are covered and faculty are voicing concerns about the time and expertise needed to meet the educational needs of learners.The objective of this study is to determine if online learning modules can be an effective mode of delivering competency based education in psychotherapy.Methods: A need analysis was performed to determine the learning needs and preferences of the psychiatry residents at Memorial University of Newfoundland.A blended course (consisting of traditional lectures, online modules and videotape review) was designed and developed based on these perceived needs.Lectures and modules were evaluated by means of pre-tests and post-tests to see if learning had occurred in each modality and between modalities.A learner satisfaction questionnaire was distributed with each online module.Results: Nineteen residents completed either an online module and/or a lecture.There was statistically significant learning in each individual online module and lecture group.There was no difference in learning between online modules and lectures.Overall, residents expressed satisfaction with the online learning module format.Conclusions: Online learning modules may enhance learner satisfaction in psychotherapy education.But there may be no difference in learning compared to traditional classroom-based lectures.The conclusion is that online modules can meet learners' preferences but may not result in more learning as measured by pre-and post-tests.However, the small sample of this study limits the generalizability of these findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".