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BMC Health Services Research
Published in: BMC Health Services Research 1/2018

Open Access 01-12-2018 | Research article

A new tool to measure approaches to supervision from the perspective of community health workers: a prospective, longitudinal, validation study in seven countries

Authors: Frédérique Vallières, Philip Hyland, Eilish McAuliffe, Ilias Mahmud, Olivia Tulloch, Polly Walker, Miriam Taegtmeyer

Published in: BMC Health Services Research | Issue 1/2018

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Abstract

Background

The global scale-up of community health workers (CHWs) depends on supportive management and supervision of this expanding cadre. Existing tools fail to incorporate the perspective of the CHW (i.e. perceived supervision) in terms of supportive experiences with their supervisor. Aligned to the WHO’s strategy on human resources for health, we developed and validated a simple tool to measure perceived supervision across seven low and middle-income countries.

Methods

Phase 1 was carried out with 327 CHWs in Sierra Leone. Twelve questions, informed by the extant literature on health worker supervision, were reduced to six questions using confirmatory factor analysis. Phase 2 employed structural equation modelling with 741 CHWs in six countries (Bangladesh, Ethiopia, Indonesia, Kenya, Malawi, Mozambique), to assess the factorial validity, predictive validity, and internal reliability of the questions at three time-points, over 8-months.

Results

We developed a robust, 6-item measure of perceived supervision (PSS), capturing regular contact, two-way communication, and joint problem-solving elements as being critical from the perspective of CHWs. When assessed across the six countries, over time, the PSS was also found to have good validity and internal reliability. PSS scores at baseline positively and significantly predicted a range of performance-related outcomes at follow-up.

Conclusion

The PSS is the first validated tool that measures supervisory experience from the perspective of CHWs and is applicable across multiple, culturally-distinct global health contexts with a wide range of CHW typologies. Simple, quick to administer, and freely available in 11 languages, the PSS could assist practitioners in the management of community health programmes.
Appendix
Available only for authorised users
Footnotes
1
Depicted as λpre in Additional file 1: Table S2, factor loadings indicate what proportion of the variance in each item on the questionnaire can be explained by the underlying latent construct.
 
2
A unidimensional model indicates that the PSS should be scored by summing questions PSS1-PSS6 to produce a total PSS score.
 
Literature
1.
Gilmore B, McAuliffe E. Effectiveness of community health workers delivering preventive interventions for maternal and child health in low- and middle-income countries: a systematic review. BMC Public Health. 2013;13:847.CrossRef
2.
McPake B, Edoka I, Witter S, Kielmann K, Taegtmeyer M, Dieleman M, Vaughan K, Gama E, Kok M, Datiko D, et al. Cost-effectiveness of community-based practitioner programmes in Ethiopia, Indonesia and Kenya. Bull World Health Organ. 2015;93(9):631–639a.CrossRef
3.
Tulenko K, Mogedal S, Afzal MM, Frymus D, Oshin A, Pate M, Quain E, Pinel A, Wynd S, Zodpey S. Community health workers for universal health-care coverage: from fragmentation to synergy. Bull World Health Organ. 2013;91(11):847–52.CrossRef
4.
World Health Organization. Global strategy on human resources for health: workforce 2030. Geneva: World Health Organization; 2016.
5.
Maher D, Cometto G. Research on community-based health workers is needed to achieve the sustainable development goals. Bull World Health Organ. 2016;94(11):786.CrossRef
6.
Kok MC, Dieleman M, Taegtmeyer M, Broerse JE, Kane SS, Ormel H, Tijm MM, de Koning KA. Which intervention design factors influence performance of community health workers in low- and middle-income countries? A systematic review. Health Policy Plan. 2014;30(9):1207–27.CrossRef
7.
Hill Z, Dumbaugh M, Benton L, Kallander K, Strachan D, ten Asbroek A, Tibenderana J, Kirkwood B, Meek S. Supervising community health workers in low-income countries—a review of impact and implementation issues. Glob Health Action. 2014;7:24085.CrossRef
8.
Bosch-Capblanch X, Garner P. Primary health care supervision in developing countries. Tropical Med Int Health. 2008;13(3):369–83.CrossRef
9.
Crigler L, Gergen J, Perry H. Supervision of community health workers. In: Developing and strengthening community health worker programs at scale: a reference guide for Progam managers and policy makers. Baltimore: USAID and MCHIP; 2014. p. 10.11–26.
10.
Hernandez AR, Hurtig AK, Dahlblom K, San Sebastian M. More than a checklist: a realist evaluation of supervision of mid-level health workers in rural Guatemala. BMC Health Serv Res. 2014;14:112.CrossRef
11.
Marquez L, Kean L. Making supervision supportive and sustainable: new approaches to old problems. Washington DC: USAID: Maximizing Access and Quality (MAQ) Initiative; 2002.
12.
Kok M, Muula A. Motivation and job satisfaction of health surveillance assistants in Mwanza, Malawi: an explorative study. Malawi Med J. 2013;25:5–11.PubMedPubMedCentral
13.
Jaskiewicz W, Tulenko K. Increasing community health worker productivity and effectiveness: a review of the influence of the work environment. Hum Resour Health. 2012;10(1):38.CrossRef
14.
Ndima SD, Sidat M, Give C, Ormel H, Kok MC, Taegtmeyer M. Supervision of community health workers in Mozambique: a qualitative study of factors influencing motivation and programme implementation. Hum Resour Health. 2015;13:63.CrossRef
15.
Frimpong JA, Helleringer S, Awoonor-Williams JK, Yeji F, Phillips JF. Does supervision improve health worker productivity? Evidence from the upper east region of Ghana. Tropical Med Int Health. 2011;16(10):1225–33.CrossRef
16.
Willis-Shattuck M, Bidwell P, Thomas S, Wyness L, Blaauw D, Ditlopo P. Motivation and retention of health workers in developing countries: a systematic review. BMC Health Serv Res. 2008;8(1):247.CrossRef
17.
McAuliffe E, Daly M, Kamwendo F, Masanja H, Sidat M, de Pinho H. The critical role of supervision in retaining staff in obstetric services: a three country study. PLoS One. 2013;8(3):e58415.CrossRef
18.
19.
Deci EL, Flaste R. Why we do what we do: understanding self-motivation. New York: Penguin Group; 1995.
20.
Crigler L, Furth R, Bjerregaard D. Communith health worker assessment and improvement matrix (CHW AIM): a toolkit for improving community health worker programs and services. Bethesda: University Reserach Co., LLC; 2011.
21.
Mathauer I, Imhoff I. Health worker motivation in Africa: the role of non-financial incentives and human resource management tools. Hum Resour Health. 2006;4:24.CrossRef
22.
May DR, Gilson RL, Harter LM. The psychological conditions of meaningfulness, safety and availability and the engagement of the human spirit at work. J Occup Organ Psychol. 2004;77:11–37.CrossRef
23.
Mbindyo PM, Blaauw D, Gilson L, English M. Developing a tool to measure health worker motivation in district hospitals in Kenya. Hum Resour Health. 2009;7:40.CrossRef
24.
Thompson B. Exploratory and confirmatory factor analysis. Washington, DC: American Psychological Association; 2004.
25.
Comrey AL, Lee HB. A first course in factor analysis. Hillsdale: Erlbaum Associates; 1992.
26.
Byrne BM. Structural equation modeling with Mplus: basic concepts, applications, and programming. Hove, East Sussex: Routledge Taylor & Francis Group; 2012.
27.
Raykov T. Behavioral scale reliability and measurement invariance evaluation using latent variable modeling. Behav Ther. 2004;35:299–331.CrossRef
28.
Muthen LK, Muthen BO. MPlus statistical analysis with latent variables. 7.4 ed. Los Angeles: Muthen and Muthen; 2013.
29.
Flora DB, Curran PJ. An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychol Methods. 2004;9(4):466–91.CrossRef
30.
Hu L, Bentler PM. Cutoff criteria for fit indices in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6:1–55.CrossRef
31.
Kenny DA, Kaniskan B, McCoach DB. The performance of RMSEA in models with small degrees of freedom. Sociol Methods Res. 2015;44:486–507.CrossRef
32.
Lehmann U, Sanders D. Community health workers: what do we know about them? The state of the evidence on programmes, activities, costs and impact on health outcomes of using community health workers. Geneva: World Health Organization; 2007.
33.
Strachan DL, Kallander K, Ten Asbroek AH, Kirkwood B, Meek SR, Benton L, Conteh L, Tibenderana J, Hill Z. Interventions to improve motivation and retention of community health workers delivering integrated community case management (iCCM): stakeholder perceptions and priorities. Am J Trop Med Hyg. 2012;87(5 Suppl):111–9.CrossRef
34.
Borghi J, Lohmann J, Dale E, Meheus F, Goudge J, Oboirien K, Kuwawenaruwa A. How to do (or not to do). Measuring health worker motivation in surveys in low- and middle-income countries. Health Policy Plan. 2018;33(2):192–203.CrossRef
35.
Wolf EJ, Harrington KM, Clark SL, Miller MW. Sample size requirements for structural equation models: an evaluation of power, Bias, and solution propriety. Educ Psychol Meas. 2013;76(6):913–34.CrossRef
Metadata
Title
A new tool to measure approaches to supervision from the perspective of community health workers: a prospective, longitudinal, validation study in seven countries
Authors
Frédérique Vallières
Philip Hyland
Eilish McAuliffe
Ilias Mahmud
Olivia Tulloch
Polly Walker
Miriam Taegtmeyer
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2018
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-018-3595-7

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