| 1. Establish community partnerships |
Participatory mapping and broader community-based participatory research initiatives are ideally supported by community-level partnerships between organizations that 1) have the capacity to generate resident participation, 2) have the requisite insight to point out the nuanced layers of community context and issues, and 3) are well positioned to collaboratively implement public health advocacy and promotion initiatives (27). |
| 2. Establish a community-driven research agenda and identify geographic scope |
Because community residents are central to the participatory mapping process, the research agenda should be driven by resident interests and needs specific to an identifiable geographic area (22). |
| 3. Recruit mapping participants |
Participatory mapping is effectively driven by resident knowledge of place. Therefore, it will benefit communities of practice using this methodology to develop a recruitment strategy that 1) is informed by the available literature, and 2) engages participants possessing a grounded knowledge of the research site (12). |
| 4. Conduct participatory mapping sessions |
In this central phase of the participatory mapping process, facilitators should engage participants with mapping tools that are ideally suited to organizational capacity and familiar to participants, such as paper maps and online mapping resources. |
| 5. Digitize maps and document resident interests |
Digitizing maps to create an overview of resident interests and concerns, and documenting resident identified place-based determinants of health will be beneficial for participant review and informing ensuing analyses. |
| 6. Reconvene residents for map review |
Residents review data and provide additional data points when deemed necessary. |
| 7. Scale maps to larger geographic area |
Participatory mapping is typically conducted at a small scale (eg, within a 1-mile buffer). Therefore, to examine convergent validity, communities of practice may further examine relationships between variables (eg, tobacco shops and crime) on a larger scale via GIS. |
