ArticleFrontiers in public health2024
Can technology be good for health? Investigating health-promoting strategies in the private sector.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
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Abstract
Introduction: This research investigates what might motivate tech companies and impact-driven investors to adopt a health-promoting strategy in their product development and capital allocation strategies. Methods: Participants were recruited for semi-structured interviews through purposive and snowball sampling. From 83 outreach attempts, thematic saturation required 19 completed interviews out of the 46 consumer technology executives and impact-focused investors who responded. Interviews were analyzed using grounded theory-based content analysis. Results: Seven coding categories resulted from inductive coding, with 83 sub-codes. The primary themes were: product-based health impact is magnified when matched to user demographics (making an equity mindset important); stakeholders are eager for reliable health metrics, especially those that hold across industry verticals; when capturing health impact, it is critical to include positive (i.e., economically beneficial) externalities. These results allowed for the creation of a logic model with a recommended theory of change for the private sector to develop health strategy. Discussion: Intentional integration of impact strategy with business priorities will allow teams to design products that promote health, driving buy-in and resource allocation while attracting investment and double returns. For policymakers, it is clear that tech policy and regulation for corporate reporting need to keep pace. These findings are limited by the purposive recruitment of participants, introducing potential bias and risk to generalizability.
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