Table · dataset · 2026
Supplementary file 1_Digital compassion fatigue and digital empathy in healthcare: mapping the evidence and informing a human-centered clinical framework.docx
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Background<p>Digital transformation has fundamentally reshaped healthcare delivery, creating new opportunities for communication, care coordination, and clinical decision-making while introducing emotional and relational challenges for healthcare professionals.
Description
Among these challenges, Digital Compassion Fatigue (DCF) and Digital Empathy have emerged as closely related but conceptually distinct constructs. Despite increasing interest in both concepts, their theoretical relationship, defining characteristics, and implications for healthcare practice have not previously been synthesized within a unified framework.</p>Objective<p>To synthesize the emerging literature on Digital Compassion Fatigue and Digital Empathy, map the current evidence base, identify conceptual and measurement gaps, and develop an evidence-informed Human-Centered Clinical Framework to guide research, education, leadership, and digitally mediated healthcare practice.</p>Methods<p>This scoping review followed the Joanna Briggs Institute methodology and was reported according to the PRISMA Extension for Scoping Reviews (PRISMA-ScR).
Eligibility criteria were based on the Population–Concept–Context (PCC) framework. Evidence sources were identified through comprehensive searches of six electronic databases, supplemented by Google Scholar, backward reference-list screening, and forward citation tracking. Eligible evidence sources were charted and synthesized using descriptive and narrative approaches.</p>Results<p>The review included 41 evidence sources spanning concept analyses, empirical studies, qualitative studies, scoping reviews, systematic reviews, meta-analyses, and theoretical or framework papers.
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Digital Compassion Fatigue (DCF) remained at an early conceptual stage, with no validated DCF-specific instrument identified, whereas Digital Empathy was supported by a broader conceptual and empirical literature. Because the evidence was heterogeneous and largely observational, conceptual, or secondary, the synthesis supports associations and conceptual propositions rather than causal pathways. The mapped evidence informed a testable Human-Centered Clinical conceptual model integrating digital demands, adaptive resources, organizational support, Digital Empathy, DCF, and patient, professional, and system outcomes.</p>Conclusion<p>This review integrates two previously separate bodies of literature and clarifies Digital Empathy and DCF as related but non-oppositional constructs within digitally mediated healthcare.
The proposed Human-Centered Clinical model is evidence-informed rather than empirically validated and should be tested across professions, healthcare systems, and cultural contexts before it is used to support causal or clinical claims.</p>
Links
Where it is published
- DOI doi.org/10.3389/fpsyg.2026.1959352.s001 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
- From keywords
- Applied and developmental psychology · Artificial intelligence · Astronomy & Astrophysics · Chemistry · Computer Science & AI · Digital health · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Psychology & Behavioral Science · Social Science
Related
Provenance · 1 source records, 20 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| figshare | oai:figshare.com:article/33718981 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].anzsrc:field:420302 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['digital health'] |
| concepts[field].anzsrc:group:4602 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['artificial intelligence'] |
| concepts[field].anzsrc:group:5201 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Applied Psychology'] |
| concepts[field].local:field:astronomy | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:chemistry | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:engineering | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:humanities | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:psychology-behavioral | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:social-science | mapping · figshare com | connector:figshare_com@1.0.0 | |
| description | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/description |
| license | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/rights |
| publication_date | source · figshare com | connector:figshare_com@1.0.0 | |
| title | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/title |