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      Incentive preferences for community health volunteers in Kenya: findings from a discrete choice experiment

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          Abstract

          Background

          Community health volunteers (CHVs) play crucial roles in enabling access to healthcare at the community levels. Although CHVs are considered volunteers, programmes provide financial and non-financial incentives. However, there is limited evidence on which bundle of financial and non-financial incentives are most effective for their improved performance.

          Methods

          We used a discrete choice experiment (DCE) to understand incentive preferences of CHVs with the aim to improve their motivation, performance and retention. Relevant incentive attributes were identified through qualitative interviews with CHVs and with their supervisors. We then deployed a nominal group technique to generate and rank preferred attributes among CHVs. We developed a DCE based on the five attributes and administered it to 211 CHVs in Kilifi and Bungoma counties in Kenya. We used mixed multinomial logit models to estimate the utility of each incentive attribute and calculated the trade-offs the CHWs were willing to make for a change in stipend.

          Results

          Transport was considered the incentive attribute with most relative importance followed by tools of trade then monthly stipend. CHVs preferred job incentives that offered higher monthly stipends even though it was not the most important. They had negative preference for job incentives that provided award mechanisms for the best performing CHVs as compared with jobs that provided recognition at the community level and preferred job incentives that provided more tools of trade compared with those that provided limited tools.

          Conclusion

          A bundled incentive of both financial and non-financial packages is necessary to provide a conducive working environment for CHVs. The menu of options relevant for CHVs in Kenya include transport, tools of trade and monthly stipend. Policy decisions should be contextualised to include these attributes to facilitate CHW satisfaction and performance.

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          Most cited references44

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          Mixed MNL models for discrete response

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            Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force.

            The application of conjoint analysis (including discrete-choice experiments and other multiattribute stated-preference methods) in health has increased rapidly over the past decade. A wider acceptance of these methods is limited by an absence of consensus-based methodological standards. The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for Conjoint Analysis Task Force was established to identify good research practices for conjoint-analysis applications in health. The task force met regularly to identify the important steps in a conjoint analysis, to discuss good research practices for conjoint analysis, and to develop and refine the key criteria for identifying good research practices. ISPOR members contributed to this process through an extensive consultation process. A final consensus meeting was held to revise the article using these comments, and those of a number of international reviewers. Task force findings are presented as a 10-item checklist covering: 1) research question; 2) attributes and levels; 3) construction of tasks; 4) experimental design; 5) preference elicitation; 6) instrument design; 7) data-collection plan; 8) statistical analyses; 9) results and conclusions; and 10) study presentation. A primary question relating to each of the 10 items is posed, and three sub-questions examine finer issues within items. Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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              Which intervention design factors influence performance of community health workers in low- and middle-income countries? A systematic review

              Community health workers (CHWs) are increasingly recognized as an integral component of the health workforce needed to achieve public health goals in low- and middle-income countries (LMICs). Many factors influence CHW performance. A systematic review was conducted to identify intervention design related factors influencing performance of CHWs. We systematically searched six databases for quantitative and qualitative studies that included CHWs working in promotional, preventive or curative primary health services in LMICs. One hundred and forty studies met the inclusion criteria, were quality assessed and double read to extract data relevant to the design of CHW programmes. A preliminary framework containing factors influencing CHW performance and characteristics of CHW performance (such as motivation and competencies) guided the literature search and review. A mix of financial and non-financial incentives, predictable for the CHWs, was found to be an effective strategy to enhance performance, especially of those CHWs with multiple tasks. Performance-based financial incentives sometimes resulted in neglect of unpaid tasks. Intervention designs which involved frequent supervision and continuous training led to better CHW performance in certain settings. Supervision and training were often mentioned as facilitating factors, but few studies tested which approach worked best or how these were best implemented. Embedment of CHWs in community and health systems was found to diminish workload and increase CHW credibility. Clearly defined CHW roles and introduction of clear processes for communication among different levels of the health system could strengthen CHW performance. When designing community-based health programmes, factors that increased CHW performance in comparable settings should be taken into account. Additional intervention research to develop a better evidence base for the most effective training and supervision mechanisms and qualitative research to inform policymakers in development of CHW interventions are needed.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2021
                5 July 2021
                : 11
                : 7
                : e048059
                Affiliations
                [1 ]departmentReproductive Health , Population Council , Nairobi, Kenya
                [2 ]departmentHealth Economics Research Centre, Nuffield Department of Population Health , University of Oxford , Oxford, UK
                [3 ]departmentHealth Economics Research Unit , KEMRI-Wellcome Trust Research Programme , Nairobi, Kenya
                [4 ]departmentDivision of Community Health Services , Minsitry of Health , Nairobi, Kenya
                [5 ]Population Council , Washington, DC, USA
                [6 ]departmentDepartment of International Health , Johns Hopkins Bloomberg School of Public Health , Baltimore, Maryland, USA
                Author notes
                [Correspondence to ] Dr Timothy Abuya; tabuya@ 123456popcouncil.org
                Author information
                http://orcid.org/0000-0001-8815-8299
                http://orcid.org/0000-0002-5330-2366
                Article
                bmjopen-2020-048059
                10.1136/bmjopen-2020-048059
                8258597
                34226227
                7988080b-9435-4dfb-8dd9-c523d2b5a098
                © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/.

                History
                : 20 December 2020
                : 26 May 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;
                Award ID: ID OPP1174594
                Categories
                Health Policy
                1506
                1703
                Original research
                Custom metadata
                unlocked

                Medicine
                health policy,international health services,organisation of health services,human resource management

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