2016
DOI: 10.1136/bmjopen-2016-011885
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How do community health committees contribute to capacity building for maternal and child health? A realist evaluation protocol

Abstract: IntroductionThe proposed research is part of ongoing operations research within World Vision's Access: Infant and Maternal Health Programme. This study aims to identify key context features and underlying mechanisms through which community health committees build community capacity within the field of maternal and child health. This may help to improve programme implementation by providing contextually informed and explanatory findings forhowcommunity health committees work,whatworks best and forwhomdo they wo… Show more

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Cited by 24 publications
(28 citation statements)
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“…21 To achieve this, we will analyse qualitative data from interview and document sources, following a coding framework of intervention description, observed outcomes, context conditions and underlying mechanisms. 17 Observational data will be coded according to a framework informed by Spradley’s 20 dimensions. This coding will be conducted with continual reference to potential CMO configurations that either support or refute the working hypothesis.…”
Section: Methods and Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…21 To achieve this, we will analyse qualitative data from interview and document sources, following a coding framework of intervention description, observed outcomes, context conditions and underlying mechanisms. 17 Observational data will be coded according to a framework informed by Spradley’s 20 dimensions. This coding will be conducted with continual reference to potential CMO configurations that either support or refute the working hypothesis.…”
Section: Methods and Analysismentioning
confidence: 99%
“… 15 16 Data collection is pragmatic and method-neutral—selection of data sources and methods is guided by what is needed to test the working hypothesis. 17 …”
Section: Introductionmentioning
confidence: 99%
“…Realist evaluations can include qualitative and quantitative data collection and analysis, but may be purely quantitative or qualitative [ 27 ]. In reality most realist evaluations in health are qualitative in nature and any quantitative analysis focuses on outcomes, tending to either be descriptive or use hypothesis testing to assess statistical significance before and after intervention implementation [ 28 ]. Few use more advanced statistical modelling techniques, such as interrupted time series or regression [ 29 , 30 ].…”
Section: Discussionmentioning
confidence: 99%
“…Realist evaluations are increasingly being employed within low- and middle-income countries by academics, non-governmental organisations (NGOs) and other programme implementers as evidenced by the rapid growth of the number of published realist evaluations from these countries 17–25. There remains, however, little precedent for its use within these countries.…”
Section: Realist Evaluation Within Low- and Middle-income Countries Bmentioning
confidence: 99%