Transforming Healthcare: Evaluating a Decade of Postgraduate Training at the Liberia College of Physicians and Surgeons
Notice bibliographique
Résumé
BACKGROUND: Postgraduate training in Liberia was commenced in 2013 under the Liberia College of Physicians and Surgeons (LCPS). Since its inception, 125 medical doctors have specialized in seven disciplines: internal medicine, pediatrics, surgery, obstetrics and gynecology, family medicine, ophthalmology and psychiatry. This study evaluates the outcomes of a decade of postgraduate training in Liberia. METHODS: An online questionnaire was distributed to all graduates, collecting data on demographics, work history, motivation, self-assessed competencies, and training experiences, including examinations, research and feedback. Descriptive analysis was used to calculate response frequency distributions for quantitative outcomes, and thematic analysis was used for open answer responses. RESULTS: Ninety graduates (72.0%) responded to the questionnaire. All respondents worked in Liberia, with 56.3% in Montserrado County. Most (94.4%) were primarily employed in the public sector, whereas 21.1% held additional roles in the private sector or academia. After 3 years of membership-level postgraduate training to become a specialist, 30.0% pursued additional education, including 18.9% fellowship training. Overall, graduates expressed strong confidence in competencies gained during the postgraduate training, particularly medical knowledge, professionalism and teaching, with over 95% of graduates considering themselves competent in these areas. In contrast, only 44.3% felt competent in research. Nearly all graduates reported that the training supported their career growth and would recommend it to colleagues. Suggestions for improvements included increasing faculty numbers and diversity, enhancing training resources, and expanding research opportunities. CONCLUSIONS: The LCPS has contributed substantially to developing a competent specialist health workforce in Liberia. Graduates had a high retention rate and were primarily employed in clinical roles in the public sector. Challenges remain, such as too few specialists and limited healthcare coverage in rural areas. To train well-equipped specialists, it is crucial to strengthen faculty, institutional capacity and training resources, and to build research capacity. Sustained investment and continued collaborations between the government and partners are needed to implement strategies to maintain retention and improve equitable distribution of specialists and to support their career growth. These efforts will ensure the program's impact to meet Liberia's evolving healthcare demands effectively.
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 | 0,015 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».