Outreach Worker (ORW) daily diary is a primary source of a lot of data. The guidelines given by the donor agency for ORW daily diary is sufficient. However, in absence of analysis and feedback the data remains hidden, and crude. While interacting with ORW during Technical Support (TS) visits it was shared that they need inputs and guidance to write the ORW diary. ORW daily diary were analyzed with the following objectives-
a) To make the data in the ORW diary more visible
b) To evolve a daily diary format in Marathi ( local language )
c) To enhance the quality of data at grass root level
The report presents the detail analysis of ORW diary and recommends a revised format to be made in the local language so that it can be computerized at a later stage and analyzed using software packages like NVIVO or Atlas TI.
This brief report also aimed at making documentation work by outreach worker very simple , and uniform across the program so that district wise field reality can be compared and outreach strategy can become area specific.
It was decided to use following protocol in content analysis of daily diary.
1) Sample Selection – photocopies of sample pages of ORW diary from the districts – Pune,Solapur,Satara,Miraj from five ORW zone were selected after preliminary reading
2) Arranging the data for content analysis- All the text data was arranged district wise and ORW zone wise for analysis/
3) Deciding coding units – example – word, concept, sentence, paragraph, theme, entire. We used daily report entire text as coding unit.
4) Deciding Categories- categories evolved after immersing oneself in the data instead of deriving from existing theories or previous related studies. The categories that immerged from intensive reading were – Home visits, Events Report, Office work, Networking visit, Accompanied referral, Awareness work done, Training received, Information giving. Each category was further coded with Nodes as shown in the following table.
5) Coding the text - All the selected sample text ( 10 ORW zone, Period Oct-Dec 07 – 20 days x 3 months x 5 zone x 3 districts. However the numbers of report were 300 daily text reports. ) were coded as per the above table. Test coding was done and the same method was followed for the entire sample size.
6) Checking coding consistency – for the time being the codes were limited in number so coding instructions and rules were listed in one page. As the data size increases the instruction dictionary will be prepared which will consist of categories names, definitions or rules for assigning codes. Human coders are subject to fatigue and are likely to make more mistakes as the coding proceeds. However, in the current study the sample size being very small these challenges were not seen.
7) Drawing conclusion from coded data - involved exploring properties and dimensions of categories, identifying relationships between categories, uncovering patterns and testing categories against full range of data. At this stage the findings are presented in this report. Conclusions can be drawn after analyzing the daily diary of all 9 districts.