A phenomenological study of the self-directed learning habits of rural physicians in a digital age
Bibliographic record
Abstract
Purpose: Physicians need to develop lifelong learning skills to stay abreast of ongoing advances in the medical sciences and to find solutions to everyday problems encountered in clinical practice.Self-directed learning (SDL) is one way in which physicians can plan, manage and evaluate their own learning, with or without the help of others.However, there are numerous barriers reported to SDL, including concerns with access to information and the ability to use systems effectively and efficiently to search and locate information relevant to one's needs.The latter is particularly important given the increasing use of digital, social media and mobile technologies by physicians.The purpose of this study is to explore the SDL experiences, habits, needs and perceptions of rural physicians in NL in a digital age.Methods: A phenomenological study encompassing semi-structured interviews with a purposive sample of rural physicians recruited from across regional health authorities in NL.Interview data was transcribed verbatim and analyzed using NVivo analytical software and thematic analysis.Results: Eleven (N=11) interviews have been completed and preliminary analysis suggests that respondents undertake SDL to obtain information regarding recent trials/research, to assist with challenging cases, or to respond to community needs.Interview respondents report depending on mainly digital technologies for SDL, such as various websites, apps, podcasts, online modules, and YouTube.A minority of respondents report using more traditional methods of CME/CPD to meet their SDL needs, including attending conferences or participating in teleconferences or journal clubs.A majority of respondents report lack of time and access to required resources (i.e.internet) as barriers to managing their SDL.Conclusions: Few studies have explored the unique practice circumstances of rural physicians, their patterns and habits of SDL and the effect of barriers to SDL on feelings of professional isolation.The study findings have important implications for informing potential CPD programming to improve the SDL skills of physicians; informing education/training of medical students and postgraduate residents in SDL skills; informing regulatory/licensing practices around
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".