Table 4.

Benefits of Using Image Capture in Research: Thematic Analysis of Open-Ended Qualitative Responses

		N (%) by Image Collection Category
Theme and Brief Description	Total N (%) (N = 26)	Participant Generated (n = 11)	Researcher Generated (n = 8)	Curated from Third Party (n = 7)
Theme 1: Automates: Automated image processing was of value.	2 (7.7%)	0 (0%)	2 (25.0%)	0 (0%)
Theme 2: Reduces researcher burden/makes feasible: Images reduced the need for in-person observations.	6 (23.1%)	1 (9.1%)	1 (12.5%)	4 (57.1%)
Theme 3: Improves accuracy of measurement; Supports more objective assessment, reduces bias.	9 (34.6%)	1 (9.1%)	7 (87.5%)	1 (14.3%)
Theme 4: Potential for scalability: Involves an existing data source with wide coverage.	1 (3.8%)	0 (0%)	0 (0%)	1 (14.3%)
Theme 5: Provides more data: More settings and time points can be covered feasibly.	9 (34.6%)	2 (18.2%)	2 (25.0%)	5 (71.4%)
Theme 6: Supports evaluation: Provides existing data for evaluating naturalistic interventions.	2 (7.7%)	0 (0%)	1 (12.5%)	1 (14.3%)
Theme 7: Supports participant engagement/intervention: Participants are engaged through image capture.	8 (30.8%)	8 (72.7%)	0 (0%)	0 (0%)
Theme 8: Supports validation/algorithm training: Provides objective ground truth data.	2 (7.7%)	0 (0%)	2 (25.0%)	0 (0%)
Theme 9: Creates real-time or rapid feedback: Is being used to support real-time analyses and actuations.	1 (3.8%)	0 (0%)	1 (12.5%)	0 (0%)
Theme 10: Generates qualitative data to complement quantitative: Supports improved contextual information through imagery and descriptive summaries.	6 (23.1%)	6 (54.5%)	0 (0%)	0 (0%)