Exploiting the emergent nature of mixed methods designs: insights from a mixed methods impact evaluation in Malawi
The application of mixed methods in Health Policy and Systems Research (HPSR) has expanded remarkably. Nevertheless, a recent review has highlighted how many mixed methods studies do not conceptualize the quantitative and the qualitative component as part of a single research effort, failing to make...
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| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2020
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| In: |
Health policy and planning
Year: 2020, Jahrgang: 35, Heft: 1, Pages: 102-106 |
| ISSN: | 1460-2237 |
| DOI: | 10.1093/heapol/czz126 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1093/heapol/czz126
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| Verfasserangaben: | Manuela De Allegri, Stephan Brenner, Christabel Kambala, Jacob Mazalale, Adamson S. Muula, Jobiba Chinkhumba, Danielle Wilhelm and Julia Lohmann |
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| 520 | |a The application of mixed methods in Health Policy and Systems Research (HPSR) has expanded remarkably. Nevertheless, a recent review has highlighted how many mixed methods studies do not conceptualize the quantitative and the qualitative component as part of a single research effort, failing to make use of integrated approaches to data collection and analysis. More specifically, current mixed methods studies rarely rely on emergent designs as a specific feature of this methodological approach. In our work, we postulate that explicitly acknowledging the emergent nature of mixed methods research by building on a continuous exchange between quantitative and qualitative strains of data collection and analysis leads to a richer and more informative application in the field of HPSR. We illustrate our point by reflecting on our own experience conducting the mixed methods impact evaluation of a complex health system intervention in Malawi, the Results Based Financing for Maternal and Newborn Health Initiative. We describe how in the light of a contradiction between the initial set of quantitative and qualitative findings, we modified our design multiple times to include additional sources of quantitative and qualitative data and analytical approaches. To find an answer to the initial riddle, we made use of household survey data, routine health facility data, and multiple rounds of interviews with both healthcare workers and service users. We highlight what contextual factors made it possible for us to maintain the high level of methodological flexibility that ultimately allowed us to solve the riddle. This process of constant reiteration between quantitative and qualitative data allowed us to provide policymakers with a more credible and comprehensive picture of what dynamics the intervention had triggered and with what effects, in a way that we would have never been able to do had we kept faithful to our original mixed methods design. | ||
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