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Technology × Therapy: Forms of Organizing Work With Telehealth Within an Academic Health Center

Gordon C Shen & Lokesh Shahani

The Journal of Applied Behavioral Science2025https://doi.org/10.1177/00218863251315953article
AJG 2ABDC B
Weight
0.37

What the paper says

Social constructivists have significantly advanced our understanding of how digital technologies give rise to different forms of organizing between organizations but less is known about similar dynamics within the organizations. Therefore, we investigated the implementation of telehealth within an academic health center during the COVID-19 pandemic. We developed a grounded model of the integration of work with technology based on 54 interviews with 27 healthcare professionals. The model comprises two moments. During the moment of enactment, four connected themes—material affordances, material constraints, embodiment, and relationality—emerged. In the subsequent moment of variation, two themes—stabilization and closure—determined the bifurcation into technology-adjacent and technology-distant organizing. Technology-adjacent organizing involves a telemedicine team continuing to treat patients with serious mental illness admitted to remote state hospitals. Technology-distant organizing entails the redeployment of telehealth in the focal psychiatric hospital for future disasters. The model contributes to scholarship at the intersection of institutional theory and information studies.

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https://doi.org/https://doi.org/10.1177/00218863251315953

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@article{gordon2025,
  title        = {{Technology × Therapy: Forms of Organizing Work With Telehealth Within an Academic Health Center}},
  author       = {Gordon C Shen & Lokesh Shahani},
  journal      = {The Journal of Applied Behavioral Science},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/00218863251315953},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.