Rapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short report
Abstract Background Using opinion leaders to accelerate the dissemination of evidence-based public health practices is a promising strategy for closing the gap between evidence and practice. Network interventions (using social network data to accelerate behavior change or improve organizational perf...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2017-06-01
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| Series: | Implementation Science |
| Online Access: | http://link.springer.com/article/10.1186/s13012-017-0611-y |
| _version_ | 1818853950700388352 |
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| author | Thomas A. Odeny Maya Petersen Charles T. Muga Jayne Lewis-Kulzer Elizabeth A. Bukusi Elvin H. Geng |
| author_facet | Thomas A. Odeny Maya Petersen Charles T. Muga Jayne Lewis-Kulzer Elizabeth A. Bukusi Elvin H. Geng |
| author_sort | Thomas A. Odeny |
| collection | DOAJ |
| description | Abstract Background Using opinion leaders to accelerate the dissemination of evidence-based public health practices is a promising strategy for closing the gap between evidence and practice. Network interventions (using social network data to accelerate behavior change or improve organizational performance) are a promising but under-explored strategy. We aimed to use mobile phone technology to rapidly and inexpensively map a social network and identify opinion leaders among community health workers in a large HIV program in western Kenya. Methods We administered a five-item socio-metric survey to community health workers using a mobile phone short message service (SMS)-based questionnaire. We used the survey results to construct and characterize a social network of opinion leaders among respondents. We calculated the extent to which a particular respondent was a popular point of reference (“degree centrality”) and the influence of a respondent within the network (“eigenvector centrality”). Results Surveys were returned by 38/39 (97%) of peer health workers contacted; 52% were female. The median survey response time was 13.75 min (inter-quartile range, 8.8–38.7). The total cost of relaying survey questions through a secure cloud-based SMS aggregator was $8.46. The most connected individuals (high degree centrality) were also the most influential (high eigenvector centrality). The distribution of influence (eigenvector centrality) was highly skewed in favor of a single influential individual at each site. Conclusions Leveraging increasing access to SMS technology, we mapped the network of influence among community health workers associated with a HIV treatment program in Kenya. Survey uptake was high, response rates were rapid, and the survey identified clear opinion leaders. In sum, we offer proof of concept that a “mobile health” (mHealth) approach can be used in resource-limited settings to efficiently map opinion leadership among health care workers and thus open the door to reproducible, feasible, and efficient empirically based network interventions that seek to spread novel practices and behaviors among health care workers. |
| first_indexed | 2024-12-19T07:44:58Z |
| format | Article |
| id | doaj.art-89384b2609fb45c7a8f421335eb20ba4 |
| institution | Directory Open Access Journal |
| issn | 1748-5908 |
| language | English |
| last_indexed | 2024-12-19T07:44:58Z |
| publishDate | 2017-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Implementation Science |
| spelling | doaj.art-89384b2609fb45c7a8f421335eb20ba42022-12-21T20:30:22ZengBMCImplementation Science1748-59082017-06-011211710.1186/s13012-017-0611-yRapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short reportThomas A. Odeny0Maya Petersen1Charles T. Muga2Jayne Lewis-Kulzer3Elizabeth A. Bukusi4Elvin H. Geng5Center for Microbiology Research, Kenya Medical Research InstituteSchool of Public Health, University of California, BerkeleyCenter for Microbiology Research, Kenya Medical Research InstituteUniversity of California, San FranciscoCenter for Microbiology Research, Kenya Medical Research InstituteDivision of HIV/AIDS, Infectious Diseases and Global Medicine, Department of Medicine, San Francisco General Hospital, University of California, San FranciscoAbstract Background Using opinion leaders to accelerate the dissemination of evidence-based public health practices is a promising strategy for closing the gap between evidence and practice. Network interventions (using social network data to accelerate behavior change or improve organizational performance) are a promising but under-explored strategy. We aimed to use mobile phone technology to rapidly and inexpensively map a social network and identify opinion leaders among community health workers in a large HIV program in western Kenya. Methods We administered a five-item socio-metric survey to community health workers using a mobile phone short message service (SMS)-based questionnaire. We used the survey results to construct and characterize a social network of opinion leaders among respondents. We calculated the extent to which a particular respondent was a popular point of reference (“degree centrality”) and the influence of a respondent within the network (“eigenvector centrality”). Results Surveys were returned by 38/39 (97%) of peer health workers contacted; 52% were female. The median survey response time was 13.75 min (inter-quartile range, 8.8–38.7). The total cost of relaying survey questions through a secure cloud-based SMS aggregator was $8.46. The most connected individuals (high degree centrality) were also the most influential (high eigenvector centrality). The distribution of influence (eigenvector centrality) was highly skewed in favor of a single influential individual at each site. Conclusions Leveraging increasing access to SMS technology, we mapped the network of influence among community health workers associated with a HIV treatment program in Kenya. Survey uptake was high, response rates were rapid, and the survey identified clear opinion leaders. In sum, we offer proof of concept that a “mobile health” (mHealth) approach can be used in resource-limited settings to efficiently map opinion leadership among health care workers and thus open the door to reproducible, feasible, and efficient empirically based network interventions that seek to spread novel practices and behaviors among health care workers.http://link.springer.com/article/10.1186/s13012-017-0611-y |
| spellingShingle | Thomas A. Odeny Maya Petersen Charles T. Muga Jayne Lewis-Kulzer Elizabeth A. Bukusi Elvin H. Geng Rapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short report Implementation Science |
| title | Rapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short report |
| title_full | Rapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short report |
| title_fullStr | Rapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short report |
| title_full_unstemmed | Rapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short report |
| title_short | Rapid sociometric mapping of community health workers to identify opinion leaders using an SMS platform: a short report |
| title_sort | rapid sociometric mapping of community health workers to identify opinion leaders using an sms platform a short report |
| url | http://link.springer.com/article/10.1186/s13012-017-0611-y |
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