Action research is a research comprising of a stepwise development which begins with an assessment to identify initial ideas, implementation, and feedback for improving the ideas. The steps after the improved ideas are improved implementation, more feedback and subsequent steps are repeating so forth. In this case, the initial ideas need to fit with the needs of certain community to prepare an implementation/intervention to help the CHWs in making report of Posyandu data. The information is important to develop a plan to design an intervention starting from the initial blueprint and should be presented to the community in order to create an improvement such as the intervention design and further action steps in delivering the intervention. The ideas and intervention are also required to prepare for the advocacy to relevant stakeholders e.g. government and or private sectors. The combination of action research principles, qualitative and quantitative (hybrid approach) methods are synergistically applied for end users, in this case, the CHWs and mothers, in 8 phases: (1) Analysing and understanding users’ activities which refer to a process of exploring their activities in Posyandu, (2) Making a prototype design on paper, (3) Evaluating the design with the users by presenting and discussing it. Any feedback is correction for step 2, then proceed to step 3, (4) Designing the prototype, (5) Creating a dynamic design prototype or a dynamic design that is a programmed with planned features but still not in the executed form, (6) Evaluating design with the users to decrease miscommunication, (7) Evaluating the executed prototype and the coded version, and (8) implementing the final version of the user interface. User interface design is an activity to ensure that good user interface program design is complimented with good quality of program. The initial action research is conducted in qualitative approach because the community insights have to be developed after the observation of information. Thus, the intervention can fulfil the needs in the community. In phases 1 to 3 the qualitative design was used for phase 4-5. Then in phase 6 to 8, the mixed-method (embedded quantitative-qualitative approaches) design was employed to identify the end users’ knowledge and skills including their feedback in using the application (Figure 1).
In the qualitative research method, a focus group discussions (FGDs) of 6-15 informants which included the CHWs and mothers in 2017, the CHWs in 2018, and the CHW and Midwives from each village in 2019 were established. This method was implemented because these population were considered as a higher response group who were able to use smartphone mobile application technology, and midwives’ role as supervisor of Posyandu in every village. The research was conducted in Pasawahan sub-district, Purwakarta district, West Java province, Indonesia. We interviewed the informants of focus group discussion (FGD) by using open questions about the problems that arose when running the Posyandu to understand their solution. Inputs were given for the solution, followed by feedbacks when the solution was implemented. Sample qualitative was chosen using a purposive sample technique according to their activity and ability to use smartphone. Illustration for this explanation is provided in Figure 2.
In order to enable the cadres to operate Posyandu mobile application, an instruction/user guide training is required. The qualitative data was acquired by implementing the FGD with Posyandu cadres to explore their opinion on the Posyandu mobile application instruction. The FGD was conducted with 12 Posyandu cadres representing each village in Pasawahan sub-district. The information acquired was used to establish a Posyandu mobile application guide needed by the cadres. After the user guide creation process was completed, it was then given to the cadres as an application use reference during the training.
After that, a quantitative data was collected to assess the cadres’ knowledge and skills in using Posyandu mobile application during the training. The knowledge assessment was conducted using questionnaires, while the skill assessment was conducted through a quantitative observation using a checklist. During the observation process, the researchers were assisted by selected 10 cadres (those who were most active and trained) to be facilitators.
The facilitators were trained in using Posyandu mobile application based on the instruction book. Each facilitator should be able to operate Posyandu mobile application and to guide the cadres on how to use Posyandu mobile application. Each facilitator was provided with an android/tablet and in charge of 8-10 cadres. The facilitators organized a visit schedule to the cadres under their responsibility. For a month, Posyandu cadres were guided by Posyandu mobile application implementation trainer using the provided tablet/handphone in rotation.
The treatment group consisted of the cadres who fulfilled the inclusion criteria (active cadre) and participated in the Posyandu mobile application training for one day with an instruction book and guided by a trained cadre facilitator. The control group comprising cadres with the inclusion criteria and only participated in the one-day training. The knowledge and skill assessments were conducted one month after the training (2018) and during the implementation of Posyandu (2019)
The quantitative research sample size was counted based on the objective to test the significance between groups and between two points of time (training time and implementation at Posyandu time). We used per group sample equation from Hulley SB, et al, 2007 using α 0.05 (two-tailed hypothesis), β 0.10, effect size from previous research 0,56 (Park, Han, & Kaid, 2013)(15), resulted in a number of 72 to 86 respondents(16).
To see the impact from the local use to national use, we published the application on Google Play in December 2018. We analysed the distribution of registered Posyandu on the mobile application in the country. We used our admin website to download the excel file comprising all Posyandu that have registered to the Posyandu mobile application and stored the data in one database server. Firstly, we checked the data quality using STATA version 15.1 Special Edition License, and then secondly, to make a distribution map, we employed QGIS version 2.6 (open source) shapefile of 34 provinces in Indonesia to map the registered Posyandu until 31 December 2019.
Analysis
In qualitative analysis, we coded and categorized the answers of mothers and CHWs into problems when running Posyandu mobile application and solution suggestions to sustain its operations to improve efficiency. We dragged and grouped similar answers quote to a node/code and use the grouping’s insight to name the node. We wished to build and understand the important connection between the needs and solution suggestions to be used as inputs to the mobile health application design. The analysis used content analysis nodes in NVivo 12 Pro License. The context of diagram and entity relationship diagram were extracted from the application program maker software. Subsequently, the results were exported and therefore can be displayed as a report. As for the quantitative data analysis, we used STATA version 15.1 Special Edition License to observe the significance of implementing T Test dependent or Wilcoxon Test as an alternative if data is not normally distributed. We also analysed effect by looking at Z score (Standardized test statistic, which is produced by STATA) divided by √N (N is number of all respondents) for time difference (training time, 2018, and implementation time, 2019)(17).