For the full explanation and questions see the user guide.
To effectively utilise the questionnaire, researchers and practitioners should follow a systematic data-collection approach, to ensure its effective administration and interpretation. This approach follows the following steps:
- Preparation
- Train the enumerators about the P-CCQ, interview techniques and research ethics. Together with the enumerators the P-CCQ can be reviewed to understand well its structure, items and answering categories.
- As the Arabic version of the P-CCQ has been psychometrically tested, items of the P-CCQ cannot be adapted content-wise except for some wording to make it contextually valid. However, items can be added to the demographic questions, and additional tools may be added as well to the questionnaire.
- Set-up the questionnaire in a digital data-collection tool into the appropriate software (e.g. KoboToolbox, Monkey Survey etc.). Ensure that all items of the P-CCQ are set as mandatory.
- Questionnaire administration
- Select the appropriate method for administering the questionnaire, such as in-person interviews, online distribution or hard-copy distribution for respondents to fill in the P-CCQ themselves.
- In case respondents fill in the questionnaires themselves, clear instructions should be provided, and confidentiality measures will be explained.
- Data-collection
- Monitor the data-collection process to address any issues or challenges that may arise, such as confusion among participants or enumerators.
- In case the P-CCQ is used in a baseline- and endline study, it is important that respondents receive codes that are linked to their identification details (in a separate file, to ensure confidentiality), so the same respondents can be traced back for the endline study and paired t-tests can be done to measure whether there is any significant change.
- Data-analysis
- Once data-collection is complete, the responses will be inside the larger dataset for analysis.
- Data-cleaning will be conducted before starting the analysis.
- Use appropriate statistical techniques to analyse the dataset. As the P-CCQ uses items that are all scored on a numeric Likert scale (1-7), the summation of scores across all items can be done to calculate the score for each respondent.
- Cross-analysis can be conducted using demographic data like gender, age, religion, etc.
- Paired t-test compares paired data from the baseline and endline dataset, to assess the effectiveness of interventions. With a paired t-test a statistical significance can be measured.
- Interpretation
- Interpret the results of the questionnaire analysis in the context of the research objectives and the specific characteristics of the target community.
- Identify patterns or trends in the data that may indicate strengths or gaps in community cohesion.
- Potentially conduct a sub-analysis per dimension (community connectedness, attachment to neighbourhood and tolerance and respect).
The 22-item P-CCQ can be administered in geographically defined communities to measure community cohesion. In case there is a wish to administer it in communities that are defined by characteristics that are non-geographical (e.g. religious community or school community), the wording of the items may be adapted without losing the content of the item.
