ArticleInternational journal of multiple research approaches2018
Skills Development and Academic Productivity of Scholars in the NIH Mixed Methods Research Training Program for the Health Sciences.
Article in International journal of multiple research approaches, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 22 citations in OpenAlex.
- Going virtual: mixed methods evaluation of online versus in-person learning in the NIH mixed methods research training program retreat.BMC medical education · 2024Article
- Integrating a focus on health equity in implementation science: Case examples from the national cancer institute's implementation science in cancer control centers (ISCJournal of clinical and translational science · 2023Article
- Advancing discussion of ethics in mixed methods health services research.BMC health services research · 2021Article
- PROJECTA: An Art-Based Tool in Trauma Treatment.Frontiers in psychology · 2020Article
- Mixed methods grant applications in the health sciences: An analysis of reviewer comments.PloS one · 2019Article
- Development of a Self-Rated Mixed Methods Skills Assessment: The National Institutes of Health Mixed Methods Research Training Program for the Health Sciences.The Journal of continuing education in the health professions · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
The Mixed Methods Research Training Program (MMRTP) for the Health Sciences is a mentoring-based program to train faculty in mixed methods research. We administered a Mixed Methods Skills Self-Assessment instrument with domains of "research questions," "design/approach," "sampling," "analysis," and "dissemination." For each item (i.e., skill), we requested three ratings on a 5-point Likert-format scale drawn from an educational competency ratings scale: "My ability to define/explain," "My ability to apply to practical problems," and "Extent to which I need to improve my skill." To assess productivity, we administered a survey with questions related to grants funded, grants submitted, publications, presentations, instances of serving as an institutional resource for mixed methods, and other comments. The results showed that 29 scholars in the first two cohorts represented a diverse set of disciplines and research topics. Although scholars expressed a strong interest in learning mixed methods skills, they came into the program with limited professional experiences with mixed methods. Scholars reported statistically significantly increased confidence in ability to define or explain concepts and in ability to apply the concepts to practical problems. Only practical applications of case studies and ethical principles of research did not show statistically significant improvement after the retreat. Scholars reported substantial productivity in mixed methods and described leadership in mixed methods at their institutions. Participation in an interactive program statistically significantly improved the confidence of scholars. The MMRTP holds promise to bridge the gap between complex research questions in the health sciences and investigators suitably trained in mixed methods.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.