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Board #101 - Research Abstract Simulation in Undergraduate Psychiatry Education

2014· article· en· W2321049831 on OpenAlexaff
Petal S. Abdool, Latika Nirula

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2014
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsCurriculumMedical educationMEDLINEPsychologyComputer scienceMedicinePedagogy

Abstract

fetched live from OpenAlex

Hypothesis Undergraduate medical education is increasing the use of simulation-based methodologies to expand students’ exposure to complex clinical scenarios.1-2 While a review of the literature was conducted in 2008 looking at the role of simulation within psychiatric education, emphasis on this review was placed more broadly on all areas of psychiatric education and primarily the role of standardized patients and role play.3 The hypothesis of this paper was to see if additional and potentially more promising approaches to simulation were influencing curriculum development within undergraduate psychiatric education. This paper will review the existing literature on simulation methodologies used specifically within undergraduate psychiatry education and provide an overview of most commonly used approaches to date. The goal is to identify innovative and useful simulations and potential gaps in the use of simulation within the undergraduate psychiatry curriculum. Methods The authors searched the MEDLINE, ERIC, and PsychINFO databases to 2014 using multiple search terms, including simulation, standardized patients, psychiatry, undergraduate education and medical student. A manual refined search of the yielded results specifically including medical students, a range of simulation methodologies (e.g., use of standardized patients, virtual reality, and e-learning simulation modules) was conducted. Literature that indirectly related to the defined search parameters was also included. The authors reviewed each paper manually to determine the type of simulation used and to determine the appropriateness of the use of simulation as a learning modality to enhance teaching, medical student learning and/or assessment. The psychiatry area of focus for the simulation learning was also ascertained. Results The refined search criteria yielded a total of 352 articles examining the use of simulation-based methodologies within undergraduate psychiatry education. Areas of focus included the use of simulation to support learning, assessment, changing attitudes about psychiatry, decreasing stigma, and building empathy among medical students. Of the 352 articles generated, 85 dealt specifically with the use of simulation in undergraduate medical education and spanned a period from 1977 to 2013. Seventy-three percent of the papers looked at the use of standardized patients and 19% utilized an online or web based simulation intervention. Five papers looked at virtual patients in enhancing education. The vast majority of the papers reviewed used simulation in teaching or skill building while seventeen percent discussed its value in assessment or Objective Structured Clinical Examination. Two papers discussed the value of simulation in building cultural competency among medical students.4-5 Conclusion Despite the varied uses of simulation across many health disciplines, little has changed in undergraduate psychiatric education since the 2008 review.3 Some papers focused on skills such as communication skills, empathy and decreasing stigma in psychiatry.6-10 Expanding on these is essential since they are relevant to all facets of the practice of medicine. While a small percentage of papers used simulation-based e-learning models or virtual patients, given the significant resource required for SPs and the challenges in accommodating such learning experiences within an already dense curriculum, these modalities show promise.11 Virtual patients, are reflective of the emergence of the field of telepsychiatry and enable more opportunities for simulation-based learning across a diverse set of contexts.2 Future directions include evaluating the efficacy of these interventions using models of learning to inform future curriculum development in undergraduate psychiatry.12 References 1. Humphrey HJ. Marcangelo M. Rodriguez ER. Spitz D. Assessing competencies during education in psychiatry. International Review of Psychiatry. 25(3):291–300, 2013 Jun. 2. Srinivasan M, Hwang JC, West D, Yellowlees PM. Assessment of clinical skills using simulator technologies. Acad Psychiatry. 2006;30:505–515 3. McNaughton N, Ravitz P, Waddell A, et al: Psychiatric education and simulation: a review of the literature. Can J Psychiatry 2008; 55:3–11 4. Smith BD, Silk K. Cultural competence clinic: an online, interactive, simulation for working effectively with Arab American Muslim patients. Acad Psychiatry, 2011; 35:312–6. 5. Ekblad S, Manicavasagar V, Silove D, Baarnhielm S, Reczycki M, Mollica R, et al. The use of international videoconferencing as a strategy for teaching medical students about transcultural psychiatry. Transcultural Psychiatry 2004; 41, 120–129. 6. Cohen DS, Colliver JA, Marcy MS, Fried ED, Swartz MH. Psychometric properties of a standardized-patient checklist and rating-scale form used to assess interpersonal and communication skills. Acad Med. 1996 Jan;71(1 Suppl):S87–9. 7. Sack S. Drabant B. Perrin E. Communicating about sexuality: an initiative across the core clerkships. Academic Medicine 2002 Nov; 77(11):1159–60, 8. Krahn LE, Bostwick JM, Sutor B, et al: The challenge of empathy: a pilot study of the use of standardized patients to teach introductory psychopathology to medical students. Acad Psychiatry 2002; 26:26–30 9. Bunn W, Terpstra J. Cultivating empathy for the mentally ill using simulated auditory hallucinations. Acad Psychiatry. 2009;33:457–460 10. Galletly C, Burton C. Improving medical student attitudes towards people with schizophrenia. Aust N Z J Psychiatry. 2011 Jun;45(6):473–6. 11. Hasle JL1, Anderson DS, Szerlip HM. Analysis of the costs and benefits of using standardized patients to help teach physical diagnosis. Acad Med. 1994 Jul;69(7):567-70. 12. Kolb D: Kolb D Experiential Learning: Experiences as the Source of Learning and Development. 1984 Englewood Cliff, NJ Prentice-Hall. Disclosures None

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)0.030
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.104
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.108
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1040.015

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 head0.076
GPT teacher head0.479
Teacher spread0.404 · 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 designSimulation or modeling
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
Published2014
Admission routes1
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