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Enregistrement W1656795713 · doi:10.1002/j.2051-5545.2009.tb00226.x

What makes a good psychiatrist? A survey of clinical tutors responsible for psychiatric training in the UK and Eire

2009· article· en· W1656795713 sur OpenAlexaboutno aff
Dinesh Bhugra, K. Sivakumar, Gareth Holsgrove, Georgia Butler, Morven Leese

Notice bibliographique

RevueWorld Psychiatry · 2009
Typearticle
Langueen
DomaineHealth Professions
ThématiqueChild and Adolescent Health
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychiatryChild and adolescent psychiatryMedicineEmpathyService (business)Medical educationPsychology

Résumé

récupéré en direct d'OpenAlex

The Royal College of Psychiatrists published Good Psychiatric Practice 1 in 2000, with a revised third edition in 2009. Modelled on Good Medical Practice 2 produced by the General Medical Council, core attributes for good psychiatric practice are listed as clinical competency, being a good communicator and listener, basic understanding of group dynamics, ability to work within a team, ability to be decisive and to appraise staff with a basic understanding of the principles of operational management, understanding the role and status of vulnerable patients, and bringing empathy and encouragement to patients and their carers, with critical awareness of emotional responses to clinical situations. Within the National Health Service (NHS), training for psychiatrists is organised in training schemes, with clinical tutors (approved by the Royal College of Psychiatrists) as individuals responsible for training, mentoring and supporting a number of trainees. Tutors have to support the application of a candidate to take the membership examination of the Royal College of Psychiatrists leading to the award of MRCPsych, which is a prerequisite for moving up to higher training leading to specialist status in one of six sub-specialities of psychiatry: adult general and community psychiatry, child and adolescent psychiatry, psychiatry of learning disability, forensic psychiatry, psychotherapy, and old age psychiatry. The role of proving training schemes has been taken over by an overarching Postgraduate Medical Education and Training Board (PMETB). However, PMETB has clearly laid out principles of training and assessment. Although the USA and Canada have had reports of competencies and evolving concepts for clinical practice and training 3,5, these concepts are being focused on in the UK only in recent times. Scheiber and Kramer 6 suggest that competencies can be measured along a sliding scale. Core competencies are the ones central to medical practice and are non-negotiable 4. Mikhael 7 has produced a list of competencies for speciality physicians. These are similar to the ones acknowledged in Good Psychiatric Practice and also include diagnostic capabilities, communication skills, collaborating, managing being a health advocate and a scholar. These competencies can be mapped on to different assessment methods. When trainees attain MRCPsych on the basis of examination, they have an obligation to meet standards of training and practice. Till recently, these standards were monitored by the Royal College of Psychiatrists, but since 30 September 2005 PMETB has taken on this responsibility. The clinical tutors are key individuals responsible for training and are in regular touch with trainees. We decided to approach them to obtain their views on the characteristics of a good psychiatrist. We used a postal survey, and all the tutors on the Royal College of Psychiatrists database were sent the questionnaire. In view of resource difficulties, no follow-up or reminders were arranged. The accompanying letter made it clear that there was no compulsion for response. The competencies from Good Psychiatric Practice were consolidated into ten competencies (see Table 1) and the respondents were asked to rate each competency as positive (by saying “yes”), negative (by saying “no”) or “did not know”. A simple tabular analysis was carried out. Of 163 clinical tutors who were approached, responses were received from 113 (69.3% response). The findings are illustrated in Table 1. There was an overwhelming agreement on the importance of overall clinical competency in diagnosis, investigations and management, being a good communicator and ability to make appropriate clinical decisions. The respondents were unable to say if ability to appraise staff, basic understanding of the principles of operational management, and having a basic understanding of group dynamics are desirable for this group of trainees. This brief survey highlights the typical and desirable characteristics of a good psychiatrist. Although it was a postal survey, the response rate was quite respectable. Although those who responded would be expected to be those with strong opinions, it seems unlikely that specific views of responders would be biased in any particular direction. It is not surprising that the most desirable characteristics are to do with clinical skills and competencies, which is what would be expected from psychiatrists. The surprising finding is that a majority of the respondents were unable to say if a knowledge of group dynamics is essential. This has been one of the requirements of the Royal College of Psychiatrists for training. Low emphasis on group dynamics indicates that there may be a shift away from general psychodynamic principles, as trainees used to be taught these. This may also be a reflection of a shortage of psychoanalytic therapists/trainers. The emphasis on operational management and staff appraisal is understandably low, as trainees will not be expected to participate in these activities although they have started undergoing appraisal. It is also possible that the role of these activities is clearer to organisations and institutions such as the Royal College of Psychiatrists and hospitals but not to trainers or trainees. With recent changes in training and assessment in the UK, further surveys of this kind are indicated to understand the trainers’ views, and should be preferably extended also to trainees. The authors would like to thank all the participants for their responses.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,058
Score d'incertitude au seuil0,987

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0090,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,140
Tête enseignante GPT0,489
Écart entre enseignants0,348 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations11
Publié2009
Routes d'admission1
Résumé présentoui

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