Digital fatigue and computerised health technologies: a rapid review
Digital fatigue and computerised health technologies: a rapid review
Background: artificial intelligence (AI) is increasingly integrated into computerised health technologies. While these promise improved diagnostic accuracy, efficiency, and clinical outcomes, concerns are emerging regarding digital fatigue. Prolonged or poorly designed interactions with digitised tools such as decision support systems or self-management applications can contribute to disengagement and cognitive exhaustion in both patients and healthcare professionals, potentially resulting in mental health symptoms.
Objective: to conduct a rapid review of studies utilising computerised health technologies, with a focus on how digital fatigue is defined and measured, and its impact on patients and healthcare professionals.
Methods: this work followed a standardised framework in line with PRISMA-ScR guidelines. PubMed, Web of Science, and Scopus were systematically searched from inception to 2025. Eligible studies reported digital fatigue or similar constructs related to computerised health technologies. Two reviewers independently screened studies, extracted data using a piloted standardised form, and synthesised findings.
Results: six studies met inclusion criteria. Across settings, digital fatigue was linked to techno-overload, system complexity and burnout, yet terminology and measurement lacked consistency. Proposed mitigation strategies included refining alert specificity, aligning system design with workflow demands, and enhancing user-centred support. However, details on the computerised technologies used in included studies and the role of AI therein are largely missing, as are details on the conditions and participant demographics to which these are applied.
Conclusions: digital fatigue is an under-recognised mental barrier to sustained use of computerised health technologies. Standardised definition and measurement of digital fatigue is needed to clarify its impact and guide the design of interventions that support long-term adoption and well-being among patients and healthcare professionals.
Michels, Lysanne Veerle
d3d32d1b-0543-4654-9ed8-0b73b2b49256
Ghannam, Suzan
1ad4a5f0-6b9e-4ddc-9887-08931d445d72
Smith, Lucy
835f8b9b-b6e0-4f5f-b6b4-a48c7913b463
Simpson, Glenn
802b50d9-aa00-4cca-9eaf-238385f8481c
Dambha-Miller, Hajira
58961db5-31aa-460e-9394-08590c4b7ba1
15 October 2025
Michels, Lysanne Veerle
d3d32d1b-0543-4654-9ed8-0b73b2b49256
Ghannam, Suzan
1ad4a5f0-6b9e-4ddc-9887-08931d445d72
Smith, Lucy
835f8b9b-b6e0-4f5f-b6b4-a48c7913b463
Simpson, Glenn
802b50d9-aa00-4cca-9eaf-238385f8481c
Dambha-Miller, Hajira
58961db5-31aa-460e-9394-08590c4b7ba1
[Unknown type: UNSPECIFIED]
Abstract
Background: artificial intelligence (AI) is increasingly integrated into computerised health technologies. While these promise improved diagnostic accuracy, efficiency, and clinical outcomes, concerns are emerging regarding digital fatigue. Prolonged or poorly designed interactions with digitised tools such as decision support systems or self-management applications can contribute to disengagement and cognitive exhaustion in both patients and healthcare professionals, potentially resulting in mental health symptoms.
Objective: to conduct a rapid review of studies utilising computerised health technologies, with a focus on how digital fatigue is defined and measured, and its impact on patients and healthcare professionals.
Methods: this work followed a standardised framework in line with PRISMA-ScR guidelines. PubMed, Web of Science, and Scopus were systematically searched from inception to 2025. Eligible studies reported digital fatigue or similar constructs related to computerised health technologies. Two reviewers independently screened studies, extracted data using a piloted standardised form, and synthesised findings.
Results: six studies met inclusion criteria. Across settings, digital fatigue was linked to techno-overload, system complexity and burnout, yet terminology and measurement lacked consistency. Proposed mitigation strategies included refining alert specificity, aligning system design with workflow demands, and enhancing user-centred support. However, details on the computerised technologies used in included studies and the role of AI therein are largely missing, as are details on the conditions and participant demographics to which these are applied.
Conclusions: digital fatigue is an under-recognised mental barrier to sustained use of computerised health technologies. Standardised definition and measurement of digital fatigue is needed to clarify its impact and guide the design of interventions that support long-term adoption and well-being among patients and healthcare professionals.
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Published date: 15 October 2025
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Local EPrints ID: 506962
URI: http://eprints.soton.ac.uk/id/eprint/506962
PURE UUID: 057ecaac-8975-400d-be1b-d5185a05fbb4
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Date deposited: 24 Nov 2025 17:38
Last modified: 25 Nov 2025 03:05
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Author:
Suzan Ghannam
Author:
Lucy Smith
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