Capacity-building and continuing professional development in healthcare and rehabilitation in low- and middle-income countries—a scoping review protocol
Bibliographic record
Abstract
A recent world health report suggests that there is a growing rehabilitation human resource crisis. This review focuses on the capacity-building needed to meet present and future rehabilitation challenges in low- and middle-income countries (LMICs). Capacity-building is the process by which individuals and organizations obtain, improve, and retain the skills, knowledge, tools, equipment, and other resources needed to do their jobs competently. The objectives of this review are (1) to determine how capacity-building has been defined, implemented, and evaluated in LMICs and (2) to provide an overview of the effectiveness of capacity-building initiatives.In the first of seven stages, we will refine and delimit the research. Then, we will identify relevant studies by searching five biomedical databases, two rehabilitation databases, three regional databases, and three databases of gray literature. Two independent reviewers will then select the studies using a priori selection criteria. We will exclude incomplete records, records published prior to 2000 for databases and 2010 for gray literature, and records written in languages other than English or Spanish. We will also exclude records focusing on entry-to-practice programs in academic settings. For Objective 1, using qualitative analysis software, we will extract and analyze text from included records that define or explains capacity building. For Objective 2, using an online file-sharing platform, one reviewer will extract data describing the effectiveness of capacity-building interventions and a second reviewer will verify the accuracy, with disagreements resolved by consensus. The results will be collated using tables and charts. After synthesizing the results, we will discuss the practicality and applicability of the findings with partners from Honduras and Colombia. We will use several formats and venues including presentations and publications in English and Spanish to present our results.To our knowledge, this will be the first attempt to systematically identify knowledge of capacity-building and rehabilitation in LMICs. This scoping review results will offer unique insights concerning the breadth and depth of literature in the area. It is anticipated that results from this scoping review will guide efforts in future capacity-building efforts in rehabilitation in LMICs.Busch AJ, Deprez D, Bidonde J, Ramírez PA, Araque EP. Capacity building and continuing professional development in healthcare and rehabilitation in low- and middle-income countries-a scoping review. 2021. https://doi.org/10.17605/OSF.IO/7VGXU .INTRODUCCIóN: La literatura mundial sugiere que existe una creciente crisis de recursos humanos en el área de rehabilitación. Esta Revisión Sistemática Exploratoria se centra en el desarrollo de capacidades en el área de rehabilitación en países de ingresos bajos y medianos (PIBM). El desarrollo de capacidades es el proceso mediante el cual las personas y las organizaciones obtienen, mejoran y retienen las habilidades, el conocimiento, las herramientas, el equipo y otros recursos necesarios para realizar su trabajo de manera competente.Determinar cómo se ha definido, implementado y evaluado el desarrollo de capacidades en rehabilitación en los PIBM; y proporcionar una síntesis sobre la eficacia de las iniciativas de desarrollo de capacidades en rehabilitación en los PIBM. MéTODOS: En la primera de siete etapas, refinaremos las preguntas de la investigación. Luego, identificaremos estudios relevantes mediante la búsqueda de cinco bases de datos y tres bases de datos de literatura gris. Dos revisores en forma independiente seleccionarán los estudios utilizando criterios definidos a priori. Excluiremos registros (artículos y otra literatura) incompletos, publicados antes de 2000 para bases de datos y 2010 para literatura gris, y escritos en idiomas que no sean inglés o español. También excluiremos registros que sobre programas de ingreso a la práctica profesional (académicos). Para el Objetivo 1, extraeremos y analizaremos el texto que define las estrategias/iniciativas de desarrollo de capacidades en rehabilitación utilizando un software de análisis cualitativo. Para el Objetivo 2, un revisor extraerá datos que describen la efectividad de las intervenciones y un segundo revisor verificará la precisión de los datos utilizando una plataforma electrónica. Los desacuerdos entre revisores se resolverán por consenso. Los resultados se presentarán usando tablas y gráficos. Consultaremos con colegas de PIBM sobre la aplicabilidad de los hallazgos. Para la diseminación de resultados, usaremos presentaciones y publicaciones en inglés y español. DISCUSIóN: Hasta donde sabemos, esta será la primera revisión exploratoria para identificar el desarrollo de capacidades en rehabilitación en los PIBM. Se prevé que los resultados de esta revisión guiarán los esfuerzos futuros de desarrollo de capacidades en la rehabilitación de los PIBM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.151 | 0.131 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.022 | 0.021 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.052 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".