aceExplainable AI for resource-aware intervention prioritization of digital burnout in healthcare workplaces
Digital burnout is an emerging workforce risk in digitally intensive healthcare systems, yet existing studies remain largely descriptive and provide limited guidance for prioritizing modifiable risk factors. This study develops an explainable artificial intelligence framework for model-based prioritization of digital burnout drivers among healthcare professionals. Cross-sectional survey data were collected from Malaysian healthcare professionals (N = 400). Digital burnout was modelled as a continuous outcome usi…
A gradient boosting model with SHAP explanations predicted digital burnout in 400 healthcare professionals and pointed to digital minimalism practices and technostress as the main levers for prioritizing interventions.
The counterfactual burnout reductions are simulated, non-causal estimates from cross-sectional data and need longitudinal or experimental validation before being read as real intervention effects.
Evidence
- Peer-reviewedHealth Information Science and Systems2026-10-15
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Truvace Impact Record TRV-2026-1997, v1: “Explainable AI for resource-aware intervention prioritization of digital burnout in healthcare workplaces.” Truvace, 2026-10-20. /record/TRV-2026-1997 (accessed at citation time). sha256 1771dff35fb75eea…
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