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Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence
INTRODUCTION: This paper maps the evidence published between 2000 and 2018 on the use of mobile technologies to train community health workers (CHWs) in low- and middle-income countries (LMICs) across nine areas of global healthcare, including the neglected areas of disability and mental health. MET...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6673767/ https://www.ncbi.nlm.nih.gov/pubmed/31413872 http://dx.doi.org/10.1136/bmjgh-2019-001421 |
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author | Winters, Niall Langer, Laurenz Nduku, Promise Robson, James O'Donovan, James Maulik, Pallab Paton, Chris Geniets, Anne Peiris, David Nagraj, Shobhana |
author_facet | Winters, Niall Langer, Laurenz Nduku, Promise Robson, James O'Donovan, James Maulik, Pallab Paton, Chris Geniets, Anne Peiris, David Nagraj, Shobhana |
author_sort | Winters, Niall |
collection | PubMed |
description | INTRODUCTION: This paper maps the evidence published between 2000 and 2018 on the use of mobile technologies to train community health workers (CHWs) in low- and middle-income countries (LMICs) across nine areas of global healthcare, including the neglected areas of disability and mental health. METHODS: We used an evidence mapping methodology, based on systematic review guidelines, to systematically and transparently assess the available evidence-base. We searched eight scientific databases and 54 grey literature sources, developed explicit inclusion criteria, and coded all included studies at full text for key variables. The included evidence-base was visualised and made accessible through heat mapping and the development of an online interactive evidence interface. RESULTS: The systematic search for evidence identified a total of 2530 citations of which 88 met the full inclusion criteria. Results illustrate overall gaps and clusters of evidence. While the evidence map shows a positive shift away from information dissemination towards approaches that use more interactive learner-centred pedagogies, including supervision and peer learning, this was not seen across all areas of global health. Areas of neglect remain; no studies of trauma, disability, nutrition or mental health that use information dissemination, peer learning or supervision for training CHWs in LMICs were found. CONCLUSION: The evidence map shows significant gaps in the use of mobile technologies for training, particularly in the currently neglected areas of global health. Significant work will be needed to improve the evidence-base, including assessing the quality of mobile-based training programmes. |
format | Online Article Text |
id | pubmed-6673767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-66737672019-08-14 Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence Winters, Niall Langer, Laurenz Nduku, Promise Robson, James O'Donovan, James Maulik, Pallab Paton, Chris Geniets, Anne Peiris, David Nagraj, Shobhana BMJ Glob Health Research INTRODUCTION: This paper maps the evidence published between 2000 and 2018 on the use of mobile technologies to train community health workers (CHWs) in low- and middle-income countries (LMICs) across nine areas of global healthcare, including the neglected areas of disability and mental health. METHODS: We used an evidence mapping methodology, based on systematic review guidelines, to systematically and transparently assess the available evidence-base. We searched eight scientific databases and 54 grey literature sources, developed explicit inclusion criteria, and coded all included studies at full text for key variables. The included evidence-base was visualised and made accessible through heat mapping and the development of an online interactive evidence interface. RESULTS: The systematic search for evidence identified a total of 2530 citations of which 88 met the full inclusion criteria. Results illustrate overall gaps and clusters of evidence. While the evidence map shows a positive shift away from information dissemination towards approaches that use more interactive learner-centred pedagogies, including supervision and peer learning, this was not seen across all areas of global health. Areas of neglect remain; no studies of trauma, disability, nutrition or mental health that use information dissemination, peer learning or supervision for training CHWs in LMICs were found. CONCLUSION: The evidence map shows significant gaps in the use of mobile technologies for training, particularly in the currently neglected areas of global health. Significant work will be needed to improve the evidence-base, including assessing the quality of mobile-based training programmes. BMJ Publishing Group 2019-07-30 /pmc/articles/PMC6673767/ /pubmed/31413872 http://dx.doi.org/10.1136/bmjgh-2019-001421 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Research Winters, Niall Langer, Laurenz Nduku, Promise Robson, James O'Donovan, James Maulik, Pallab Paton, Chris Geniets, Anne Peiris, David Nagraj, Shobhana Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence |
title | Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence |
title_full | Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence |
title_fullStr | Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence |
title_full_unstemmed | Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence |
title_short | Using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence |
title_sort | using mobile technologies to support the training of community health workers in low-income and middle-income countries: mapping the evidence |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6673767/ https://www.ncbi.nlm.nih.gov/pubmed/31413872 http://dx.doi.org/10.1136/bmjgh-2019-001421 |
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