Evidence map›Paper›PMID 32467769›Full record

ArticlePilot and feasibility studies2020

The TDR MOOC training in implementation research: evaluation of feasibility and lessons learned in Rwanda.

Cole Hooley, Ana A Baumann, Vincent Mutabazi, Angela Brown, Dominic Reeds, W Todd Cade, Lisa de las Fuentes, Enola K Proctor, Stephen Karengera, Kenneth Schecthman and 4 more

Open access · goldAbstract read
In one paragraph

Article in Pilot and feasibility studies, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 4 countries.

Cole Hooley *1Brown School of Social Work, WUSTL, St. Louis, MO USA.
Ana A Baumann *1Brown School of Social Work, WUSTL, St. Louis, MO USA.
Vincent Mutabazi2Regional Alliance for Sustainable Development (RASD) Rwanda, Kigali, Rwanda.ORCID 0000-0003-3100-6862
Angela Brown3Cardiovascular Division, WUSTL, St. Louis, MO USA.
Dominic Reeds4Division of Geriatrics and Nutritional Science, WUSTL, St. Louis, MO USA.
W Todd Cade5Program in Physical Therapy, WUSTL, St. Louis, MO USA.
Lisa de las Fuentes3Cardiovascular Division, WUSTL, St. Louis, MO USA.
Enola K Proctor1Brown School of Social Work, WUSTL, St. Louis, MO USA.
Stephen Karengera2Regional Alliance for Sustainable Development (RASD) Rwanda, Kigali, Rwanda.
Kenneth Schecthman6Division of Biostatistics, WUSTL, St. Louis, MO USA.
Charles Goss6Division of Biostatistics, WUSTL, St. Louis, MO USA.
Pascal Launois7Special Programme for Research and Training in Tropical Diseases, WHO, Geneva, Switzerland.
Victor G Davila-Roman3Cardiovascular Division, WUSTL, St. Louis, MO USA.
Eugene Mutimura2Regional Alliance for Sustainable Development (RASD) Rwanda, Kigali, Rwanda.
Washington University in St. Louis · USRwanda Development Board · RWDr. Lisbeth Hurni Coaching & Consulting · CHNutrition Sciences (Belgium) · BE

Funding

Washington University Implementation Science Center for Cancer Control (WU-ISCCC)P50CA244431 · NCI · WASHINGTON UNIVERSITY · PI BROWNSON, ROSS C, COLDITZ, GRAHAM A. · 2019 to 2023
$8.0M
NCI NIH HHS P50 CA244431
6 · The paper itself

Abstract

backgroundHypertension (HTN) affects nearly 1 billion people globally and is a major cause of morbidity and mortality. In low- and middle-income countries (LMICs), HTN represents an unmet health care gap that can be addressed by strengthening national health care systems. The National Heart, Lung, and Blood Institute recently funded the T4 Translation Research Capacity Building Initiative in Low Income Countries (TREIN) program to build capacity in dissemination and implementation (D&I) research in HTN in LMICs. The Special Programme for Research and Training in Tropical Diseases (TDR) at the World Health Organization (WHO) recently developed a massive open online course (MOOC) to train in D&I. Herein, we report on the use of the TDR WHO MOOC in D&I for the TREIN program in Rwanda, assessing feasibility of the MOOC and D&I competencies after MOOC training.

methodsParticipants in one-group MOOC training completed pre- and post-training questionnaires to assess dissemination and implementation (D&I) competency outcomes and feasibility. D&I competencies were measured by use of a scale developed for a US-based training program, with the change in competency scores assessed by paired

resultsOf the 92 trainees enrolled, 35 (38%) completed all MOOC components. D&I competency scores showed strong evidence of improvements from pre- to post-test. The full-scale average score improved by an average of 1.09 points, representing an effect size of 1.25 (CI 0.48-2.00); all four subscales also showed strong evidence of improvements. Trainees reported challenges to MOOC course completion that included technological issues (i.e., limited internet access) and competing demands (i.e., work, family).

conclusionsIn the context of LMIC training, the MOOC course was feasible and course completion showed improvement in D&I competency scores. While the program was designed with a focus on training for tropical diseases, there is potential for scalability to a wider audience of health care researchers, workers, administrators, and policymakers in LMIC interested in D&I research in non-communicable diseases.

Indexed as

D&I competenciesHypertensionLow-middle-income countriesTraining

Identifiers

PMID32467769
PMCPMC7229620
OpenAlexW3032142045

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.