Digital compassion fatigue in nurses: an evolutionary concept analysis

Electronic health records, telehealth and home monitoring are changing the psychosocial conditions of nursing work, and digital compassion fatigue in nurses has recently been proposed to describe compassion fatigue that may evolve within technology-mediated care. Direct evidence remains minimal, comprising two concept studies and one commentary, and the boundaries with compassion fatigue, burnout, technostress, moral distress and digital fatigue are unsettled. This study applied Rodgers' evolutionary concept analysis, which, unlike approaches that fix defining attributes at a single point in time, treats concepts as provisional and traces their development across time, disciplines and contexts; to our knowledge it is the first evolutionary analysis of this concept. PubMed, Embase and EBSCOhost (CINAHL Ultimate; Academic Search Premier) were searched to 2 August 2026, identifying 545 records (287 after cross-database de-duplication), supplemented by purposive sampling of adjacent literatures to saturation, citation tracking and hand searching; 38 concept-related papers were included. Five defining attributes are proposed as theoretical propositions rather than established findings: specificity to technology-mediated care; persistent post-encounter emotional exhaustion; compassion withdrawal and relational detachment; cognitive overload during digital interaction; and diminished therapeutic presence and professional efficacy. Each attribute is anchored in the direct conceptual literature and corroborated only by adjacent empirical evidence; proposed antecedents and consequences likewise rest largely on adjacent evidence and are presented as hypotheses rather than causal claims. The principal limitation is the near absence of direct evidence. Digital compassion fatigue is therefore best treated as a provisional working concept, possibly a context-specific subtype of compassion fatigue rather than a new construct, pending tests of discriminant validity. The analysis contributes an attribute-level evidence map, a testable working definition and candidate indicators to guide instrument development and occupational-health-oriented prevention research.