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Record W2008707710 · doi:10.4236/psych.2013.411a005

Designing Effective CME—Potential Barriers to Practice Change in the Management of Depression: A Qualitative Study

2013· article· en· W2008707710 on OpenAlexaff
Mandana Shirazi, Sagar V. Parikh, Ideh Dadgaran, Charlotte Silén

Bibliographic record

VenuePsychology · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsAttendancePsychologyIntervention (counseling)PerceptionApplied psychologyQualitative researchDepression (economics)Global Positioning SystemMedical educationClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Aim: The main aim of the current study is to explore GPs’ micro level obstacles of behavior change which affects diagnosis and management of Depressive Disorders following attendance at a Depression CME event. Methods: In this qualitative study, semi-structured interviews exploring GPs’ perceptions and experiences regarding the diagnosis and treatment of depression were done. A purposeful sampling to obtain a broad range of views was carried out among GPs that had participated in an educational intervention study three years earlier. Eleven GPs were interviewed and their views were probed in depth to get rich descriptions to ensure trustworthiness of the data. The data were analyzed by using qualitative content analysis. Results: GPs’ beliefs regarding micro level barriers emerged as two important themes individual and workplace factors. The individual themes included: educational and professional, and the contextual themes included: psychological disorders and work place categories. The results showed different perceptions on the barriers between the two groups of GPs, those who did change and had a positive perception of the CME program they participated in three years ago, and some who did not change. Conclusion: The results of this study imply that a number of micro level obstacles were of great importance when managing patients with depression disorders. In order to improve the effectiveness of CME events they should be tailored for the individual and address workplace issues i.e. both individual and contextual factors need attention.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.274
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.110
GPT teacher head0.563
Teacher spread0.452 · 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 teacher head, 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".

Quick stats

Citations6
Published2013
Admission routes1
Has abstractyes

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