MétaCan
Menu
Back to cohort
Record W1484916377

Psychiatric training in rural and remote areas: increasing skills and building partnerships.

2005· article· en· W1484916377 on OpenAlexaffabout
Andrea Berntson, Elliot M. Goldner, John Leverette, Pippa Moss, Mark Tapper, Brian Hodges

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsGeneral partnershipCurriculumRural areaMedical educationPsychologyMedicineSociologyPolitical sciencePedagogy
DOInot available

Abstract

fetched live from OpenAlex

Andrea Berntson, MD1, Elliot Goldner, MD, MHSc, FRCPC2, John Leverette, MD, FRCPC3, Pippa Moss, MBBS, FRCPC4, Mark Tapper, MD, FRCPC5, Brian Hodges, MD, MEd, FRCPC6 This paper was developed in collaboration with the Canadian Psychiatric Association's Standing Committee on Education and was approved by the Canadian Psychiatric Association's Board of Directors on April 10, 2005. Rural or remote communities may be ideal locations to rain residents in general psychiatry. In addition, evidence from the rural medical education literature suggests that developing educational experiences in these communities may also improve recruitment and retention. University departments of psychiatry, in partnership with national organizations and underserved communities themselves, are beginning to develop training sites in small Canadian communities. This paper examines the educational opportunities for these sites and explores the necessary adaptation of existing curricula to provide optimal learning in rural and remote environments. Introduction Most Canadian provinces have a dramatic imbalance between the number of psychiatrists serving large urban centres and those serving rural and remote communities. Statistics on physician supply in Canada consistently reveal ratios as high as 1 psychiatrist for every 30 000 or more people in rural and remote regions (1). This contrasts sharply with ratios as low as 1 psychiatrist for every 5 000 to 12 000 people in the urban regions. Most studies recommend at least 1 psychiatrist for every 8 000 to 10 000 people (2,3). Until recently, despite long-standing recognition of this problem, academic health sciences centres seemed scarcely interested in addressing the issue. As Dongier noted in 1988, So far, professional associations have only produced sporadic efforts, and very few academics working in isolation have attempted to establish links with peripheral areas, with various degrees of cooperation and little lasting success (4, p 338). This is unfortunate because there is ample evidence that some of the main solutions to the problem are under the control of the academic centres. For example, many studies show that physicians are more likely to settle in areas with which they have had a prior personal contact during training (5,6). Curran and Rourke indicate that psychiatry residents who are not born or raised in a rural or underserviced area are more likely to practise in a rural area if they received early training exposure to rural practice (6). As well, the literature suggests that training psychiatric residents in rural and remote areas has clear benefits in regard to producing well-rounded general psychiatric graduates. After defining the parameters of rural, urban, and remote communities, this paper examines the CanMEDS competencies in this context. Next, the paper examines the barriers to developing programs in rural and remote psychiatry. These include the characteristics of rural psychiatrists, the unique demands of rural practice, and resident attitudes to such training. The attitudes of academic programs are examined, as well as their readiness (which includes appropriate supervision and funding) to provide such training. Also examined is the readiness of communities to be partners in the training element of decentralized psychiatry programs. Adjunct training issues such as the use of distance education and other technologies are reviewed. The impact of distributed training networks on recruitment and retention is considered, and the paper concludes with recommendations for practice. Definitions Rural communities are variously defined in Canada; no single, commonly accepted definition exists (7). The Organization for Economic Co-operation and Development considers a region to be rural if more than one-half the people live in communities with a population density of fewer than 150 persons per square kilometre (see www.hc-sc-gc. …

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0000.000

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 head0.057
GPT teacher head0.378
Teacher spread0.320 · 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 designObservational
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

Citations19
Published2005
Admission routes2
Has abstractyes

Explore more

Same venuePubMedSame topicGlobal Health Workforce IssuesFrench-language works237,207