**5. Methods**

## **5.1 Data collection**

## *5.1.1 Popularity*

*Popularity* of the CHC can be measured by the ability of the facilitators to attract many members and retain their attendance for the duration of the intervention. The Membership Cards of all members were collected at the end of the training and this was triangulated with project records to ascertain overall number of members in the

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*Comparative Assessment of Hygiene Behaviour Change and Cost-Effectiveness of Community…*

intervention, percentage of households within a CHC in each village and number of members completing the training i.e. graduating. This enabled us to have exact

Effectiveness was demonstrated by the *community response to the training* as measured by the percentage of members adopting each of the recommended practices. The observation check list, known as the *'Household Inventory',* was used to conduct spot surveys which uses proxy indicators of hygiene behavior change which can be empirically observed first-hand by the enumerator. We did not use self-reported data as we are skeptical of the value of this method given the well-known effect of observer bias. For example: although we can observe the presence of handwashing facility (HWF) and whether soap was present, the calculation of regular usage over time is not observable. To overcome this monitoring challenge, all members are required to place a pot plant beneath their HWF. If the pot plant has been regularly receiving water from the HWF, and is alive, we know the HWF is likely to be in use. Similarly, we do not place much credibility on reported behaviour, as householders when asked this question, are likely to answer that they are in compliance with handwashing methods and use soap. To avoid such interviewer bias, we simply ask a child to demonstrate how they wash their hands and we note whether soap is used. Observations in Rwanda were conducted by Environmental Health Officers (EHOs) and trained enumerators drawn from teachers and students for a random selection of CHC member households. In Zimbabwe CHC facilitators, CHC chairpersons and

Project Records and accounts were used to ascertain field costs. An Analysis of Cost-Effectiveness was done by dividing the field costs by number of direct beneficiaries within a one-year time frame and was calculated, giving a 'cost per direct beneficiary per year' for improved hygiene [31]. Direct beneficiaries are taken to be all those within the household of a CHC Member, estimated at 4.7 people per household in Rwanda, and 4 people per household in Zimbabwe based on local census.

In Rwanda a custom-made digital application for mobile phones was designed for CBEHPP which enabled data to be entered directly online thus eliminating most human error, through instant processing online using Open Development Kit (ODK) a free application for data analysis. This data was downloaded into in excel

In Zimbabwe the data was collected by Project Officers and CHC facilitators and entered into excel computer program manually and analyzed in excel to generate a bar chart of before and after (at least 6 months after training) for each program.

In Rusizi, the results were provided to all stakeholders involved in the training with Ministry of Health and 25 EHOs through Focus Groups Discussions at District Level. The EHOs were asked to identify and discuss reasons for the variation

*DOI: http://dx.doi.org/10.5772/intechopen.89995*

*5.1.2 Effectiveness*

**5.2 Data analysis**

and then analyzed in SPSS.

*5.2.3 Qualitative analysis of value for money*

numbers of *active* members to calculate cost per beneficiary.

Environmental Health Technicians (EHTs) collected data.

*5.2.2 Analysis of community response: hygiene behavior change*

*5.2.1 Quantitative analysis of cost-effectiveness*

intervention, percentage of households within a CHC in each village and number of members completing the training i.e. graduating. This enabled us to have exact numbers of *active* members to calculate cost per beneficiary.
