Nurturing the next generation of clinician‐scientists in child and adolescent psychiatry: recommendations from a <scp>WPA</scp> Presidential Task Force
Notice bibliographique
Résumé
Clinician-scientists are members of the health care workforce who devote at least half of their time to research1. There is a concern throughout medicine that the number of clinician-scientists is woefully insufficient to meet the needs of the population. For example, the number of clinician-scientists in the US declined by 22% from 1983 to 20031. According to a 2012 report by the US National Institutes of Health2, clinician-scientists comprised only 1.5% of the total physician workforce. We were not able to find data on the proportion of clinician-scientists in child and adolescent psychiatry, but we believe that it is even lower than for other medical specialties. We are also not aware of any discussion of a human resource plan for child and adolescent psychiatry which includes an estimate of the number of clinician-scientists that the field needs and how this might be distributed across high- and low- or middle-income countries. Since the majority of the globe's children and youth live in low- or middle-income countries, the workforce needed to support mental health clinical innovation in these countries is a pressing human resource challenge. Research from other disciplines suggests that the lack of mentors and organized research training programs plays an essential role in determining the scarcity of clinician-scientists3. Key issues in child and adolescent psychiatry appear to be the lack of protected time during training to learn research methodology, read the literature, conduct pilot studies, and participate in mentors’ research. Research training in child and adolescent psychiatry is in a crisis. The solution depends on our determination to focus on the mental health of today's children and youth while simultaneously developing the resources necessary to support the mental health and well-being of children and youth of the future. We can only do this using innovative evidence-based treatments, generated by clinician-scientists working today and in the near future. There is evidence that clinician-scientist training programs are effective, at least in high-income countries, in medicine and surgery4 as well as in adult or general psychiatry5. There is only one report of a successful training program in child and adolescent psychiatry6. Ingredients of successful training programs include a strong synergy between a trainee's clinical and research interests7, an active support from department chairs and national policy makers, and availability of funds for the trainee to carry out initial, independent research separate from the mentor's scientific work. Our field is at a critical juncture. We fear that doing nothing will lead to the gradual “extinction” of clinician-scientists in child and adolescent psychiatry. By neglecting this priority, we will disadvantage the children who will need our services and our science in the decades to come. The time has come to address the mental health needs of future generations of children and youth who will be the beneficiaries of clinical innovation based on the work done today by clinician-scientists. The effectiveness of our clinical interventions in child and adolescent psychiatry can be improved only by supporting and nurturing the next generation of clinician-scientists in this field.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,126 | 0,137 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,005 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,013 | 0,011 |
| Communication savante | 0,022 | 0,028 |
| Science ouverte | 0,014 | 0,024 |
| Intégrité de la recherche | 0,052 | 0,044 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,022 | 0,017 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».