Table 3.

Visual and Narrative

Visual and Narrative. This domain includes participatory visual and narrative approaches to data collection, analysis, and interpretation.
	Type/Brief Description	Goals	Participants	Strengths	Challenges
Participatory GIS mapping (Brown et al., 2014; Elwood, 2006; Rouse et al., 2007) Asset mapping (Kramer et al., 2012; Lightfoot et al., 2014; Mosavel et al., 2018) Food mapping (Jacobi et al., 2019; Sweeney et al., 2016)	Spatial data method	-Generate spatially explicit information for multiple decision-making purposes -Disease surveillance	-Stakeholders	-Creates a new perspective on research for local stakeholders -Visual aspect is easily engaging -Adaptable for different social and cultural environments	-Can be difficult to use -Requires specific technical skills -Can be expensive and time consuming
Photovoice (Catalani & Minkler, 2010; Wang et al., 1998; Wang & Burris, 1997) Videovoice (Catalani et al., 2012; Li et al., 2019; Warren et al., 2014)	Visual, arts-based, small group method	-Promotes social action through photography so that participants can document their lives and communities	-Community members -Specialized populations (e.g., youth)	-Works well regardless of language/literacy -Flexible -Accessible	-Logistical support -Ongoing participation required
Storytelling (Digital) (de Jager et al., 2017; Rieger et al., 2018) —also oral histories; theatre-based	Arts-based, qualitative research method	-Create short videos that capture and share participants’ lived experiences as counter-narratives	-Social inequity groups -Vulnerable and marginalized populations	-Participatory approach to making meaning, engaging in decision making, active involvement in research process -Suited to knowledge translation and dissemination	-Limited publication of studies -Stories are usually very brief (3–5 minutes) and may not capture potentially important content and context -Requires skilled researchers to minimize bias, influence, etc. -Not always part of a participatory process
Participatory art-making methods (Carter & Ford, 2013; Coemans & Hannes, 2017; Jones & Leavy, 2014; Van der Vaart et al., 2018) —examples: collage, drawing, tapestry, murals, mandalas	Methods that use art/visual methods to create data	-Provides opportunity for creative expression beyond words -Understand and represent human experience and phenomena of interest	-Community members -Specialized populations (e.g., youth)	-Fun, creative -Engaging -Works well regardless of language/literacy -Taps into lived experience and feelings	-Can be intimidating if the method is perceived to require artistic abilities -Considered by some to be too subjective and non-rigorous