Reframing Person-Centered Fundamental Care in the Age of Artificial Intelligence, Robotics and Posthumanization: A Theory-Informed Narrative Review

Abstract

Population aging, chronic illness, workforce shortages, and rapid adoption of artificial intelligence (AI), robotics, virtual nursing, remote monitoring, and digital platforms are reshaping fundamental care. Yet existing literature focuses mainly on technical performance, implementation, and ethical risk, with limited attention to how technology alters the relational conditions of person-centered care. This theory-informed narrative review synthesized multidisciplinary literature identified through PubMed, CINAHL, Scopus, and Web of Science, supplemented by reference-list screening and purposive inclusion of seminal works. Seventy-eight empirical, review, conceptual, ethical, policy, and methodological sources informed the synthesis. The review reconceptualizes person-centered fundamental care through posthumanization in nursing—a socio-technical condition in which care practices, judgment, and relationships are increasingly co-produced by human and technological actors—and proposes relational augmentation as an evaluative framework. The synthesis indicates that task substitution is inadequate because it privileges efficiency, standardization, and replacement over interpretation, dignity, and relationship. Relational augmentation instead asks whether technologies strengthen relationship support, integrated recognition of need, and a supportive care context. Across monitoring and prediction, documentation and workflow, communication and education, social robotics, and virtual nursing, the framework identifies both functional benefits and relational risks. It provides a practical basis for evaluating whether technological innovation preserves trust, dignity, equity, contextual understanding, and professional judgment in person-centered fundamental care.

Introduction

Health systems face sustained pressure from population aging, chronic illness, multimorbidity, functional decline, and workforce shortages.^1–5 Longer survival has not simply extended healthy life; it has increased the number of people requiring complex medical, social, and functional support from services already constrained by uneven staffing and retention difficulties.

Technological mediation is now part of ordinary care. AI-enabled systems, robotic platforms, virtual nursing, remote monitoring, social robots, and clinical decision-support tools are being introduced across acute, long-term, community, and home-based settings.^6–10 They support monitoring, documentation, education, communication, companionship, and workflow redesign. Adoption is not always clinician-led or experienced as optional; staffing constraints, procurement priorities, and productivity pressures may embed technology before its effects on care relationships and professional work are understood.^9,10

The deeper issue is not simply the number of technologies entering care, but the redistribution of care agency. Observation, prompting, triage, prioritization, documentation, and elements of judgment are increasingly shared among clinicians, patients, algorithms, sensors, robotic systems, and digital platforms.^11–13 Posthumanization, as used here, does not imply the replacement of clinicians or the disappearance of human agency. It denotes a socio-technical condition in which care practices, knowledge, decisions, and relationships are co-produced through human–technology interaction.

Existing reviews of AI in nursing emphasize technical applications, ethical and social risks, literacy, acceptance, decision support, bias, transparency, data governance, and implementation barriers.^7,14–16 This work clarifies the challenges of responsible adoption, but remains centered on operational fit. Less attention has been given to fundamental care as a conceptual core of nursing or to how technology changes the relational and contextual conditions under which care remains person-centered.

This gap matters for three reasons. First, many early points of technological entry—monitoring, communication, comfort, mobility, hygiene, and daily support—are integral to fundamental care.^6,17 Second, discussions of trust, transparency, and bias rarely examine how nurse–patient relationships change when observation, documentation, companionship, and selected decisions are distributed across human and nonhuman actors.^11,13 Third, few reviews distinguish efficiency gains from relational gains: technologies may accelerate tasks without strengthening person-centered care.

The Fundamentals of Care (FoC) framework provides a suitable anchor because it defines care through three interdependent dimensions: a trusting therapeutic relationship; integrated attention to physical, psychosocial, and relational needs; and a supportive care context.^18–21 Accordingly, this review reconceptualizes person-centered fundamental care in the age of AI, robotics, and posthumanization and proposes relational augmentation as an evaluative standard. Although grounded in nursing theory, the framework is relevant to clinicians, informaticians, engineers, healthcare leaders, ethicists, and developers involved in technology-mediated care.

Review Approach

Design and Rationale

This theory-informed narrative review used a critical interpretive synthesis orientation. The literature is multidisciplinary, conceptually heterogeneous, and distributed across nursing, medicine, ethics, policy, robotics, digital health, and philosophy of care.^22,23 The review did not estimate pooled effects or grade individual technologies. It integrated conceptual, empirical, and ethical literature to identify convergence, tensions, and gaps and to develop a line-of-argument synthesis. Relevant principles from PRISMA-ScR and ENTREQ informed reporting, but the review was not conducted as a systematic or scoping review.^24,25

Search Strategy and Evidence Sources

PubMed, CINAHL, Scopus, and Web of Science were searched, with the final update completed in April 2026. Search concepts were adapted by database and covered care, technology, posthumanization, and ethics; database-specific strings are provided in Supplementary Table S1. Reference-list screening, citation chaining, and purposive theoretical sampling were used to identify conceptually important works that standardized terminology might miss.

Eligible sources included empirical studies, evidence syntheses, conceptual and ethical analyses, professional or policy statements, and seminal theoretical works relevant to nursing or health care. Sources were excluded when they addressed engineering alone without care implications, lacked conceptual or empirical relevance to the review questions, or were unavailable in English. Because records were not managed prospectively as a closed screening cohort, retrospective PRISMA record counts would misrepresent the iterative process. Figure 1 presents the review pathway, and Table 1 summarizes the search and selection strategy. The final manuscript drew on 78 sources across empirical, review, conceptual, ethical, policy, and methodological literature.

Figure 1.

Review and critical interpretive synthesis process. The review combined database searching with reference-list screening, citation chaining, and purposive theoretical sampling. Sources were charted by technology domain, care setting, relevance to the Fundamentals of Care framework, relational implications, ethics or governance, and practice or policy relevance. Comparison of conceptual convergence, divergence, and gaps informed the line-of-argument synthesis.

Table 1.

Search and Conceptual Selection Strategy

Element	Approach
Databases	PubMed, CINAHL, Scopus, and Web of Science.
Temporal coverage	No publication-year restriction; final update completed in April 2026.
Search concepts	Database-adapted concepts covering care, technology, posthumanization, and ethics. Full strings are provided in Supplementary Table S1.
Eligible sources	Empirical studies, evidence syntheses, conceptual and ethical analyses, professional or policy statements, and seminal theoretical works relevant to nursing or health care.
Selection logic	Conceptual relevance to the three guiding questions, considered alongside methodological credibility, currency, and contribution to the line-of-argument synthesis.
Iterative identification	Database searching supplemented by reference-list screening, citation chaining, and purposive theoretical sampling.
Reporting boundary	Records were not managed prospectively as a closed screening cohort; a retrospective PRISMA record count was therefore not generated. Figure 2 presents the review pathway.
Review corpus	The final manuscript drew on 78 empirical, review, conceptual, ethical, policy, and methodological sources.

Selection Logic, Appraisal, and Reflexivity

Selection was guided by three questions: How do AI, robotics, virtual care, and related technologies alter the delivery, organization, or interpretation of fundamental care? How do they reshape relational work, interpretive judgment, and professional responsibility? Which ethical, organizational, and implementation conditions influence whether technology-mediated care remains person-centered? The author team reviewed potentially relevant sources, charted conceptual material, and resolved differences in eligibility or interpretation by consensus.

No single critical appraisal instrument was suitable for the heterogeneous source types. Sources were instead considered for methodological credibility, conceptual relevance, currency, and contribution to the review questions. A data-charting matrix captured source type, technology domain, care setting, FoC relevance, relational implications, ethics or governance, and practice or policy relevance. The synthesis proceeded in three stages: clarification of person-centered care, fundamental care, and posthumanization; comparison of the strengths and limits of task-substitution logic; and development of relational augmentation as a line-of-argument synthesis. Evidence-supported findings were distinguished from interpretive claims and normative proposals.

The synthesis generated five interrelated themes: person-centered fundamental care is relational rather than merely personalized; posthumanization redistributes care agency, knowledge, and accountability; task substitution incompletely captures relational work; relational augmentation offers an alternative evaluative framework; and common care technologies generate both functional benefits and relational risks. Because the evidence included empirical, conceptual, ethical, policy, and methodological sources, these themes should be read as a conceptual synthesis rather than graded evidence of intervention effectiveness.

Results: Conceptual Synthesis

Key concepts and working definitions used throughout this review are summarized in Table 2.

Table 2.

Key Concepts and Working Definitions

Concept	Working Definition in This Review	Analytic Implication
Person-centered care	An approach that treats the individual not merely as a patient, diagnosis, or service recipient, but as a person whose care is shaped by biography, identity, values, vulnerability, and relationships.	Care cannot be judged only by technical correctness or personalization, but by whether the person is recognized and responded to as a whole person.
Fundamental care	Integrated care required to meet essential physical, psychosocial, and relational needs through a trusting therapeutic relationship and within a supportive care context.	Positions basic care as core professional work and provides the primary theoretical anchor for this review.
Posthumanization	A socio-technical condition in which care practices, knowledge, decisions, and relationships are increasingly co-produced through interactions among people, algorithms, sensors, robotic systems, and platforms.	Reframes technology adoption as a transformation of care agency, knowledge, relationships, and responsibility.
Task substitution	A logic in which care is decomposed into standardized, measurable, and automatable units, with technology valued primarily for replacing or accelerating functions.	Serves as the dominant but insufficient evaluative model critiqued in this review.
Relational augmentation	The capacity of technology to strengthen, rather than erode, the relational, interpretive, and contextual conditions of person-centered fundamental care.	Provides the alternative evaluative framework proposed in this review.
Virtual nursing	A model in which selected nursing activities are delivered remotely through digital or audiovisual systems, often in coordination with bedside care.	Illustrates how hybrid delivery may support or fragment care depending on continuity, workload, and relational complementarity.
Social robotics	Robotic systems designed to interact socially and provide companionship, orientation, engagement, reassurance, or emotional support.	Illustrates affective contributions while raising questions about authenticity, dignity, equity, and displacement of human presence.

Person-Centered Fundamental Care is Relational Rather Than Merely Personalized

Person-centered care is not reducible to accommodating preferences, tailoring information, or completing tasks courteously. It requires approaching the individual as a person whose care is shaped by biography, identity, values, vulnerability, relationships, and lived experience.^26–29 Digital personalization is therefore not synonymous with relational understanding: an adaptive system may deliver appropriate content while remaining unable to grasp fear, shame, grief, uncertainty, or the meaning that an act of care holds for a particular person.^27,29

The FoC framework clarifies that fundamental care is not a low-status collection of tasks. It is an integrated relational practice in which physical, psychosocial, and relational needs are addressed through a trusting relationship and within a supportive context.¹⁸ Activities such as helping a person eat, wash, eliminate, rest, move, communicate, manage discomfort, and feel safe are where vulnerability becomes visible and trust is built or lost.^19,20,30

Posthumanization Redistributes Care Agency, Knowledge, and Accountability

Posthumanization does not mean that machines replace clinicians or that human responsibility disappears. It describes care activities, monitoring, communication, judgment, and organizational processes increasingly co-produced by human and nonhuman actors.^11,13 Technologies participate in what is seen, prioritized, documented, remembered, and treated as clinically or relationally significant.¹²

Three shifts follow. Care is enacted through hybrid ecologies rather than a nurse–patient dyad alone; clinical knowledge increasingly incorporates algorithmic classifications and system-mediated pattern recognition; and accountability is distributed across clinicians, institutions, manufacturers, software, and workflow design.^11–13 Technology must therefore be evaluated not only by what it does, but by how it alters the relational and contextual conditions of care.

Task Substitution Inadequately Captures the Relational Work of Fundamental Care

AI and robotic systems enter nursing practice readily because many activities can be rendered discrete, codifiable, and repeatable Documentation, monitoring, medication processes, reminders, and routine support are frequently identified as amenable to automation.^6,17,31 Standardization and efficiency are not inherently opposed to person-centered care: locally validated and appropriately governed systems may reduce unwarranted variation, improve routine safeguards, extend scarce expertise, and lessen clerical or coordination burdens.³¹ The relevant distinction is whether efficiency is achieved with contextual judgment, human oversight, and fair distribution of benefits and burdens—and whether released resources are reinvested in responsive care.

Some of the most consequential elements of fundamental care are also the least amenable to encoding. What matters is not only whether an act occurs, but whether it is performed with attention, explanation, dignity, and responsiveness.^32,33 Technological systems may detect deviations or risk, yet translate lived experience into signals that are more legible to systems than to human situations.³⁴ Refusal to eat, reluctance to turn, withdrawal from communication, or resistance during intimate care may reflect pain, depression, trauma, cultural discomfort, fear of humiliation, or an effort to preserve agency.³⁵ Technology may detect a pattern; clinicians must still interpret its meaning.

Dependence on predictive models, scripted communication, automated documentation, and recommendation engines may also narrow moral and interpretive agency.^34,35 The risk is not simply technical deskilling, but reduced confidence in noticing nuance, questioning a recommendation, or acting when system outputs conflict with relational knowledge.^7,15 A task-substitution logic can also hide relational labor—emotional containment, explanation under uncertainty, dignity during dependence, and continuity of self—that is necessary but often unrecorded.³² Functional success therefore does not establish relational adequacy.

Relational Augmentation Offers an Alternative Evaluative Framework

Relational augmentation refers to the capacity of technology to strengthen, rather than undermine, the relational, interpretive, and contextual conditions of person-centered fundamental care. It is not synonymous with workflow optimization, simulated empathy, patient satisfaction, or generic technological enhancement. Technology is relationally augmentative only when it improves clinicians’ ability to perceive needs, integrate context, sustain continuity, and respond without displacing the relational core of care.

The first dimension, relationship support, concerns continuity, expression of need, early recognition of distress, and timely human response.^16,36,37 The second, integrated need recognition, concerns whether monitoring, warning systems, prompts, and symptom trajectories improve detection without confusing recognition with understanding.^38,39 The third, supportive context creation, asks whether technology releases time, reduces duplication, and strengthens continuity—or instead adds alarms, training, documentation, and coordination burden.^36,37,40

Five cross-cutting criteria make the framework more operational: relational visibility, context sensitivity, dignity preservation, professional amplification, and equity and accountability.^41–43 Relational visibility may be reflected by continuity and timely human review; dignity preservation by privacy, autonomy, and control over monitoring; and professional amplification by clinicians’ ability to contextualize, explain, and override outputs. Relational augmentation is a continuum: lower augmentation emphasizes task completion with weak contextual integration, whereas higher augmentation combines reliable function with relational understanding, dignity, equity, and accountable judgment. Table 3 provides illustrative indicators and interpretive anchors. These proposals require empirical validation and do not constitute a validated measurement instrument. The expanded model is shown in Figure 2.

Table 3.

Operationalizing Relational Augmentation: Proposed Indicators and Interpretive Anchors

Criterion	Illustrative Indicators for Future Research	Lower Relational Augmentation	Higher Relational Augmentation
Relational visibility	Feeling seen; continuity of contact; detection of unspoken or delayed needs; proportion of alerts followed by timely human review.	Tasks or alerts are completed, but tacit needs remain difficult to express or are not acted upon.	The system improves recognition of overlooked needs and prompts timely, accountable human response.
Context sensitivity	Adaptation to biography, culture, language, vulnerability, preference, and local workflow; ability to revise generalized outputs.	Outputs are applied uniformly with limited allowance for individual or local context.	Outputs are interpreted and adapted within the person’s clinical, cultural, and relational situation.
Dignity preservation	Perceived respect, privacy, autonomy, control over monitoring, bodily boundaries, and avoidance of embarrassment or depersonalization.	Efficiency is gained through intrusive, nontransparent, or dignity-eroding processes.	The person retains meaningful control, privacy, and recognition of personhood during technology-mediated care.
Professional amplification	Ability to contextualize, explain, question, override, and integrate outputs; effects on clinical and moral judgment.	Professionals mainly validate outputs or manage alerts, with reduced interpretive agency.	Technology broadens situational awareness while preserving professional authority and responsibility.
Equity and accountability	Performance across populations; accessibility; explainability; appeal and escalation pathways; assigned responsibility for error or harm.	Benefits and burdens are uneven, exclusions are opaque, or responsibility is unclear.	Access and performance are equitable, decisions are contestable, and responsibility is explicit.

Figure 2.

Conceptual model linking technology and implementation characteristics to relational augmentation and person-centered fundamental care outcomes. The model distinguishes task-oriented and relationally enabling implementation pathways. The Fundamentals of Care framework provides the theoretical anchor; relationship support, integrated need recognition, and supportive context creation describe the proposed mechanisms; and trust, continuity, dignity, autonomy, contextual responsiveness, professional judgment, equity, and accountability represent relevant outcomes. The five cross-cutting criteria—relational visibility, context sensitivity, dignity preservation, professional amplification, and equity and accountability—are interpreted along a continuum. This is a conceptual synthesis, not a validated causal or quantitative model.

Remapping Common Care Technologies Through the FoC Lens

When mapped through the FoC lens, monitoring and prediction technologies may support earlier recognition of deterioration, falls, delirium, pain, or activity decline, but can also intensify surveillance and datafication when monitoring is poorly explained or unconnected to human response.^31,44

Documentation and workflow tools may improve handoffs, organize longitudinal information, and reduce repetitive clerical work, yet compress patients’ narratives into templates or generated summaries.^45–47 Communication and education tools may improve access, self-management, and continuity, but information can be delivered successfully without relational understanding.^48–50

Social and companion robots may reduce loneliness, support orientation, and encourage engagement, particularly in older adult and dementia care.^51–53 Their ethical significance depends on whether they complement or displace human presence.^42,54,55 Virtual nursing and hybrid models may extend nursing reach and redistribute selected tasks, but poorly integrated models can create fragmentation, duplication, or workload transfer rather than relational gain.^36,37,40 Table 4 summarizes the principal contributions and relational risks across the three FoC dimensions.

Table 4.

Potential Contributions and Relational Risks of Common Care Technologies Mapped Through the Fundamentals of Care Framework

Technology Domain	Trusting Therapeutic Relationship	Integrated Physical, Psychosocial, and Relational Needs	Supportive Care Context
Monitoring and prediction	+ Timely recognition and response − Surveillance, reduced privacy, datafication	+ Detection of deterioration, pain, falls, delirium, or activity change − Signals without contextual meaning	+ Preventive action and continuity of observation − Alarm burden and monitoring without response capacity
Documentation and workflow	+ Better handoffs and continuity − Loss of patient narrative	+ Organized longitudinal information − Subjective experience compressed into templates	+ Reduced clerical burden − New digital workload and further standardization
Communication and education	+ Improved access and continuity of contact − Scripted exchange without understanding	+ Education, language support, and self-management − Information without contextual interpretation	+ Scalable support beyond bedside encounters − Reduced opportunity for dialogue
Social and companion robotics	+ Companionship and reassurance − Simulated empathy or substitution for human presence	+ Orientation, engagement, and emotional support − Limited contextual understanding or dependency	+ Additional support where human availability is constrained − Normalization of reduced human contact
Virtual nursing and hybrid care	+ Remote support and continuity − Fragmentation if poorly integrated	+ Admission, discharge, education, and follow-up support − Limited interpretation of nonverbal or relational cues	+ Redistribution of selected tasks − Duplication, coordination burden, or workload transfer

Notes: + indicates a potential contribution; − indicates a relational risk. Entries are illustrative rather than exhaustive and should be interpreted in relation to the person, care setting, implementation model, and available human response.

Patient, Ethical, Political, and Epistemic Tensions

Patients, family caregivers, and consumers experience technology not only as functionality, but as changes in visibility, access, dependence, privacy, voice, and relationship. Monitoring may reassure when it leads to timely response, yet feel intrusive when people do not understand what is observed or how data are used.^39,56–58 Privacy in fundamental care is therefore bodily, spatial, relational, and experiential, not merely informational.

Algorithmic bias and digital exclusion may shape who is noticed, prioritized, or misread.⁵⁹ Technologies that depend on digital access, language proficiency, sensory capacity, or caregiver support can amplify existing inequities among older adults, people with cognitive impairment, culturally minoritized groups, and those with limited digital or language resources.^60,61 Equity cannot be inferred from technical availability alone.

Simulated empathy raises a different concern. Social robots or conversational systems may provide comfort, but reassuring language does not assume the moral responsibility of caring.^41,42,54,55 Their ethical value depends on whether they supplement human care, translate concern into appropriate action, and preserve accountable human availability.

Accountability becomes more complex when decision support, surveillance, reminders, and task allocation are co-produced by clinicians and systems. Professionals may retain final moral and clinical responsibility while lacking authority to inspect, modify, or contest the technologies shaping care.⁶² Responsibility may remain at the bedside even when agency is distributed across software, devices, organizations, and workflow architectures.

The synthesis reframes technology evaluation as a question of care quality rather than technical performance alone. Its implications extend beyond nursing because technology-mediated fundamental care is produced through multidisciplinary teams that include physicians, allied health professionals, informaticians, engineers, ethicists, service managers, and policymakers. The framework is therefore intended to support shared decisions about design, procurement, implementation, and evaluation while retaining nursing’s close attention to everyday care relationships.

Discussion

The synthesis reframes technology evaluation as a question of care quality rather than technical performance alone. Its implications extend across nursing, medicine, allied health, informatics, engineering, ethics, management, and policy because these disciplines jointly design, procure, implement, and oversee technology-mediated care. Relational augmentation offers a common language for multidisciplinary decisions while retaining close attention to everyday care relationships.

Emerging AI and Cross-Cultural Implementation

Generative, conversational, and affective AI extend the framework beyond monitoring and documentation because they produce language, explanations, and apparently empathic responses. An integrative review identifies potential gains in documentation, education, decision support, and workflow, alongside concerns about reliability, bias, accountability, and professional judgment.⁶³ A meta-analysis found that written AI responses were often rated as more empathic than responses from health professionals; however, proxy ratings of text do not establish embodied attentiveness, moral responsibility, or longitudinal accountability.⁶⁴ Relational augmentation therefore asks what follows an apparently empathic response: whether the person is understood in context, concern leads to appropriate action, and a responsible human remains available.

Personhood, autonomy, dignity, privacy, and family involvement are culturally situated.^65,66 In low-resource settings, standardization and wider access must be considered alongside infrastructure, local data quality, workforce capacity, financing, and governance.⁶⁷ Technology may extend scarce expertise only when it is locally adapted, understandable, maintainable, and accountable A model developed in one health system cannot be assumed relationally neutral elsewhere.

Implications for Practice, Education, Leadership, and Policy

Before implementation, organizations should undertake an explicit FoC mapping exercise: which dimension of fundamental care is affected, which relational touchpoints may change, what new work is created, and whether time released from routine tasks is reinvested in direct care.⁶⁸ We propose that lower-risk initial applications are those that improve visibility, continuity, or coordination without replacing intimate or morally charged encounters. Technologies used in bathing, toileting, cognitive impairment, end-of-life care, or emotional containment require a higher threshold of justification, meaningful consent, human oversight, and clear accountability.

AI literacy is necessary but insufficient. Education should also develop ethical, interpretive, relational, and implementation literacy so clinicians can judge when a system should be used, limited, questioned, or overridden.^7,69 Healthcare leaders should define non-negotiable care outcomes and relational harms before procurement and implementation.⁷⁰ Service redesign should move beyond workflow optimization toward relationship-sensitive redesign that preserves attentiveness, continuity, and trust.⁷¹

Governance should include transparency, human oversight, appeal and escalation pathways, patient information, assigned responsibility for harm, equity review, privacy protection, and data minimization.⁷² Co-design with patients, family caregivers, frontline clinicians, and communities should be treated as a condition of responsible implementation rather than an optional consultation exercise.^73–76

Future Research Priorities

Future research should move beyond acceptability, feasibility, and efficiency to test whether technologies preserve or deepen relational conditions. Priorities include validated measures of trust, dignity, continuity, feeling seen, and relational safety; FoC-informed implementation studies in real settings; and longitudinal examination of professional identity and moral agency.^35,77

Evaluations should distinguish workload reduction from workload transfer, coordination burden, and cognitive overload.^37,78 Cross-cultural and participatory studies should also examine how privacy, bodily boundaries, autonomy, family involvement, and acceptable machine roles vary across settings. Table 5 summarizes the research agenda.^73–76

Table 5.

Future Research Priorities for Posthuman Fundamental Care

Research Priority	Key Focus
Develop relational outcome measures	Measure trust, dignity, continuity, feeling seen, and relational safety—not only efficiency, accuracy, adoption, or satisfaction.
Build FoC-informed implementation studies	Examine how technologies change fundamental care in real settings, including effects on relationships, integrated need recognition, and care context.
Examine long-term effects on professional identity	Assess whether technology alters clinicians’ roles as relational practitioners, interpreters, and moral agents over time.
Compare cultural meanings of technological care	Examine how privacy, bodily boundaries, family involvement, companionship, autonomy, and acceptable machine roles vary across settings and populations.
Study workload redistribution, not only workload reduction	Distinguish workload reduction, workload transfer, coordination burden, and cognitive overload.
Advance participatory and transdisciplinary methods	Use co-design, participatory implementation research, realist evaluation, and multidisciplinary collaboration rather than allowing technical teams alone to define care problems.

Strengths and Limitations

This review integrates nursing theory, digital health, robotics, ethics, implementation science, and policy and distinguishes functional performance from relational adequacy. Its purpose was conceptual integration rather than exhaustive evidence mapping. The broad, iterative search may have missed relevant sources, and the retained literature is weighted toward Western health systems. Evidence is uneven across technology domains, and long-term data on relational outcomes, professional identity, cost, and unintended workload remain limited. Publication and innovation bias are possible because favorable prototypes and vendor-supported implementations may be more visible than failed or abandoned technologies. The synthesis also required interpretive judgment; the search strings, selection logic, analytic pathway, and evidentiary limits are therefore reported explicitly.

Conclusions

Posthumanization does not make person-centered fundamental care obsolete; it makes its meaning more urgent to define. Technologies should be judged not only by accuracy, efficiency, or the tasks they replace, but by whether they sustain trust, integrate need, protect dignity, distribute benefits fairly, and strengthen professional judgment. Relational augmentation offers clinicians, organizations, and developers a framework for evaluation before, during, and after implementation. The next step is empirical: validate relational outcomes across cultures and care settings and determine whether technological gains produce more responsive care rather than simply more automated work. Future care systems will increasingly be hybrid; their quality will depend on whether technology keeps care accountable to human vulnerability, relationship, and dignity.

Funding Statement

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Use of Generative Artificial Intelligence

The authors used Chatgpt during the preparation of this work to improve readability and language structure. After using this tool, the authors reviewed and edited the content and take full responsibility for the integrity of the manuscript.

Patient and Public Involvement

No patient or public contribution was undertaken because this was a review of published literature.

Abbreviations

AI, artificial intelligence; FoC, Fundamentals of Care.

Data Sharing Statement

No new data were generated or analyzed. All sources are publicly available and cited in the reference list.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no conflicts of interest.