From Passive Recipient to Digital Co-Creator: Introducing the e-Patient in the Digital Health Era

Digital transformation is changing not only how healthcare is delivered but also who holds information, interprets data, participates in decisions, and produces healthcare solutions. The article “The e-Patient in the Digital Health Era: A Concept Analysis Using Rodgers’ Evolutionary Method” examines this transformation by clarifying the meaning of the e-patient concept. Rather than treating the e-patient as someone who merely searches for symptoms online, the authors conceptualize this individual as an active, digitally equipped, self-directed, and increasingly innovative participant in healthcare. This is the article’s central contribution: it moves the e-patient from the margins of digital health technology to the center of contemporary patient–professional relationships (Hosseinabadi-Farahani & Dinmohammadi, 2026).

The study uses Rodgers’ evolutionary concept analysis method and analyzes 38 publications. Its conceptual structure is organized around antecedents, defining attributes, types, and consequences. The antecedents include the development of technological infrastructure, the transition from paternalistic medicine to patient-centered care, and increasing public access to health information. The defining attributes are proactivity, empowerment, digital health literacy, communication and collaboration, self-management, demand for access to medical records, and innovation. The consequences are examined at the patient, patient–provider relationship, and healthcare-system levels. This structure makes the article accessible to readers from nursing, health management, health informatics, patient safety, and health policy (Hosseinabadi-Farahani & Dinmohammadi, 2026).

What the Article Does Well

The strongest aspect of the article is its rejection of a technologically reductionist definition. The authors do not equate an e-patient with a person who owns a smartphone, uses a health application, or searches the internet. Instead, they emphasize what the patient does with digital information and how this activity changes the patient’s position in the healthcare system. Technology is therefore presented as an enabling infrastructure rather than the defining feature of the concept. The defining transformation is behavioral and relational: the patient progresses from receiving information to evaluating it, generating personal health data, participating in decisions, collaborating with peers and professionals, and occasionally developing new solutions (Hosseinabadi-Farahani & Dinmohammadi, 2026).

The distinction between first-generation and second-generation e-patients is particularly valuable. First-generation e-patients predominantly seek information, whereas second-generation e-patients produce, analyze, and share data and may contribute to research or technological innovation. The inclusion of patient-led initiatives such as the #WeAreNotWaiting movement illustrates why contemporary patients cannot always be understood as passive consumers of professionally designed services. Some patients identify unmet needs, build solutions, organize peer communities, and generate experiential knowledge before healthcare institutions respond. This observation gives the article relevance beyond nursing because it connects the e-patient concept with participatory medicine, open innovation, co-production, and patient-led healthcare design (Hosseinabadi-Farahani & Dinmohammadi, 2026).

Another important strength is the balanced treatment of consequences. The article avoids presenting patient empowerment as automatically beneficial. At the patient level, digital engagement may improve knowledge, control, adherence, and self-management, but it may also increase confusion, anxiety, exposure to misinformation, privacy risks, and cyberchondria. At the relational level, informed patients can enrich consultations and support shared decision-making, but they may also encounter professional resistance when online or experiential knowledge challenges clinical authority. At the system level, digital participation may improve efficiency and reduce service utilization, while simultaneously reproducing inequalities through differences in access, literacy, skills, and trust. This balanced interpretation prevents the concept from becoming a promotional slogan for digital health (Hosseinabadi-Farahani & Dinmohammadi, 2026).

The article also correctly recognizes that the digital divide is multidimensional. Possession of a device or internet connection does not guarantee meaningful participation. Patients must be able to locate information, assess credibility, understand clinical uncertainty, interpret personal data, protect privacy, and communicate their findings in clinical encounters. Consequently, digital health literacy is treated as an integrated capacity rather than a narrow technical skill. This conceptualization is especially important for older adults, people with low educational attainment, patients with disabilities, rural populations, migrants, and individuals living with complex chronic diseases. For these groups, digitalization can either expand autonomy or create a new layer of exclusion.

The analysis of the patient–provider relationship is another substantive contribution. The article demonstrates that access to information does not automatically create an equal partnership. Patients may possess information but avoid discussing it because they anticipate dismissal or confrontation. Professionals may interpret patient-generated information as a challenge to authority rather than as a resource for safer and more individualized care. By highlighting this tension, the article identifies communication climate and professional receptiveness as critical conditions separating genuine empowerment from symbolic participation. The e-patient is therefore not produced by technology alone; the concept also depends on whether healthcare institutions permit patients to act as knowledgeable participants.

The implications for nursing are clearly articulated. Nurses are repositioned as coaches, facilitators, interpreters, and digital-health guides rather than exclusive providers of information. This is a realistic response to an environment in which patients may arrive with online research, wearable-device data, application-generated reports, and peer-community experiences. The proposed educational implications are also relevant: nursing curricula should include source appraisal, digital communication, interpretation of patient-generated data, ethical use of social media and portals, and constructive communication with informed patients. The article thus translates conceptual clarification into implications for clinical practice, education, and research (Hosseinabadi-Farahani & Dinmohammadi, 2026).

The model case involving a patient with hypertension is useful because it converts an abstract concept into an observable clinical sequence. Internet and smartphone access represent antecedent conditions; searching credible sources, recording blood pressure, monitoring medication, and discussing possible adverse effects represent attributes; improved control, collaborative treatment adjustment, and a stronger therapeutic relationship represent consequences. This example helps readers distinguish the e-patient from a person whose digital engagement consists only of occasional internet searching.

Methodological Limitations and Their Value as Future Research Opportunities

The article’s most important methodological limitation is insufficient search reproducibility. The abstract and methods state that five primary databases were searched, but only four are named: PubMed, CINAHL, Web of Science, and Scopus. This discrepancy should have been corrected before publication because it creates uncertainty about the evidence base. The article also provides general keywords but does not report complete database-specific search strings, search fields, filters, exact search dates, duplicate-removal procedures, or the number of records at each screening stage. Future research can address this weakness by publishing a fully reproducible search protocol and a transparent study-selection flow diagram. A registered protocol would further reduce the risk of post hoc decisions.

The sampling frame is also insufficiently explained. Although the authors report that 38 articles were included, readers cannot determine the initial number of retrieved records, how many duplicates were removed, how many full texts were assessed, or why individual publications were excluded. In concept analysis, transparency is essential because the final definition depends directly on the literature selected for analysis. A future updated analysis could use systematic-review reporting standards adapted to concept analysis, provide a complete exclusion log, and include a supplementary extraction matrix linking every conceptual claim to its source.

The restriction to English-language literature is acknowledged, but its conceptual significance deserves greater attention. Concepts such as autonomy, empowerment, partnership, trust, professional authority, and access to records are culturally sensitive. A definition constructed predominantly from English-language literature may reflect digitally advanced, individualistic, and relatively well-resourced health systems. Future studies should investigate whether the same attributes appear in collectivist societies, low-resource settings, authoritarian clinical cultures, and healthcare systems with limited patient access to records. Comparative concept analyses across countries could reveal whether the e-patient is a universal concept or a family of context-dependent roles.

The analytical process requires greater methodological detail. The authors state that two researchers conducted screening and that thematic analysis was used, but they do not adequately explain how coding disagreements were resolved, whether a codebook was developed, how themes were revised, or whether inter-coder agreement was assessed. The reported frequencies in the thematic table create an impression of quantitative precision, but the procedures used to count conceptual elements are not sufficiently described. Future research should provide a coding framework, examples of coded passages, coder training procedures, disagreement-resolution rules, and an audit trail. Inter-coder agreement may be reported as supporting evidence, although agreement statistics should complement rather than replace interpretive discussion.

The study identifies attributes, antecedents, and consequences, but the boundaries between these categories are sometimes permeable. Digital health literacy may be an attribute of the e-patient, but it can also function as an antecedent enabling participation. Empowerment may be a defining attribute, a process, or an outcome. Collaboration may be both a behavioral attribute and a relational consequence. This ambiguity is not necessarily a conceptual failure; it may indicate that the e-patient is a dynamic developmental process rather than a static category. Future research could test a longitudinal model in which access and literacy operate as enabling conditions, engagement and self-management represent behaviors, empowerment functions as a mediating psychological mechanism, and health or relational outcomes emerge over time.

The proposed classifications also require empirical validation. Categorizing patients as accepting, informed, involved, or in control is intuitively useful, but the categories may incorrectly imply a linear progression toward complete autonomy. Not every patient wants full decision-making responsibility, and preferences may change according to disease severity, uncertainty, age, emotional state, treatment risk, or trust in the professional. A person can be highly autonomous in diabetes self-management but deliberately defer decisions during cancer treatment. Future research should therefore treat e-patient status as multidimensional and context-specific rather than as a fixed personal identity.

The article does not sufficiently distinguish beneficial engagement from unsafe self-direction. Active participation may improve care, but patient-generated solutions and online advice can also bypass evidence standards, regulatory oversight, or clinical safeguards. The brief reference to “co-destruction” is important but underdeveloped. Future studies should investigate the conditions under which co-creation improves safety and when it produces misinformation, treatment delay, inappropriate self-medication, device misuse, or fragmented responsibility. This would connect the e-patient literature more directly with patient safety, clinical risk management, and digital governance.

The treatment of professional resistance could also be expanded. The article tends to frame tension as a conflict between empowered patients and traditional professional authority. However, clinicians’ concerns may sometimes be legitimate, particularly when patient-generated data are incomplete, devices are not clinically validated, applications use opaque algorithms, or online information lacks contextual relevance. Future research should move beyond the simple opposition between enlightened patients and resistant professionals. It should examine data quality, interoperability, clinical workload, liability, uncertainty communication, and the evidentiary status of patient-generated information.

The positive system-level consequences are presented somewhat broadly. Claims regarding efficiency, cost-effectiveness, reduced visits, and improved outcomes are plausible, but the e-patient concept itself should not be treated as equivalent to the effectiveness of all eHealth interventions. Digitally active patients may generate additional messages, data streams, clarification requests, and monitoring responsibilities. These activities can reduce some forms of utilization while increasing professional workload elsewhere. Future economic evaluations should therefore capture transferred workload, infrastructure costs, cybersecurity requirements, training needs, unequal uptake, and the opportunity costs of reviewing patient-generated data.

The article acknowledges the digital divide but does not fully integrate structural inequality into the core definition. Digital participation is shaped by income, education, disability, age, language, health status, device quality, internet stability, algorithmic bias, portal accessibility, and institutional trust. Future research could develop the concept of the “structurally enabled e-patient,” emphasizing that empowerment is jointly produced by individual capability and system design. Such a framework would prevent healthcare organizations from blaming patients for low digital participation when the underlying problem is inaccessible technology or inadequate institutional support.

The use of generative artificial intelligence during data synthesis, content enrichment, language editing, and formatting is disclosed, which is commendable. Nevertheless, “content enrichment” and “data synthesis” are substantive activities, and the article does not explain how AI-generated contributions were verified, documented, or separated from the authors’ analytical judgments. Future concept analyses using generative AI should report the model and version, dates of use, task-specific prompts, verification procedures, human oversight, confidentiality safeguards, and measures taken to detect fabricated or distorted interpretations. Transparent disclosure should evolve from simply naming the tool to documenting its epistemic role in the research process.

The article is also a time-bound snapshot of a rapidly changing phenomenon. Developments in artificial intelligence, wearable sensors, digital therapeutics, patient-controlled records, remote monitoring, and conversational health agents may quickly change what an e-patient can do. Future concept analyses should therefore be planned as periodic updates rather than definitive classifications. Longitudinal conceptual surveillance could track how patients move from information consumers to data producers, algorithm users, citizen scientists, and co-designers of healthcare systems.

A Future Research Agenda

The next phase should be empirical concept validation. Researchers could convert the proposed attributes into a multidimensional measurement instrument covering digital health literacy, proactive information seeking, self-management, access to records, collaboration, data production, and innovation. Content validity should be established with patients, nurses, physicians, informaticians, and health-service managers. Construct validity could then be tested across age groups, diseases, cultures, and healthcare systems. Such a scale would make it possible to examine whether e-patient characteristics predict adherence, shared decision-making, patient safety outcomes, service utilization, trust, satisfaction, or health inequalities.

Qualitative research should examine patients who do not fit the idealized empowered profile. Particularly valuable groups include reluctant digital users, digitally excluded patients, people who delegate technology use to relatives, patients who distrust portals, individuals overwhelmed by health information, and patients whose online knowledge has been dismissed by professionals. These cases would reveal the boundaries of the concept and prevent the e-patient from becoming a normative label that divides patients into “active” and “deficient” groups.

Dyadic and team-based studies are equally necessary. The consequences of e-patient behavior cannot be understood by studying patients alone because collaboration is jointly produced. Observational studies of clinical encounters could examine how professionals respond to online information, wearable data, patient-generated hypotheses, and requests for record access. Such work could identify communication practices that transform potential conflict into shared learning and practices that create silence, distrust, or safety risks.

Intervention studies should evaluate educational programs for both patients and professionals. Patient interventions could focus on source appraisal, uncertainty, privacy, algorithmic limitations, and effective communication with clinicians. Professional interventions could focus on receiving patient-generated information without dismissal, verifying evidence efficiently, discussing misinformation respectfully, and integrating useful patient data into clinical decisions. Outcomes should include not only satisfaction and knowledge but also diagnostic delay, medication safety, treatment adherence, decisional conflict, workload, and equity.

Overall Assessment

The article makes a timely and conceptually useful contribution by defining the e-patient as an active, digitally literate, collaborative, self-managing, and potentially innovative actor. Its principal achievement is to show that the e-patient is not a technology user but a transformed participant in healthcare. The analysis is balanced, clinically relevant, and especially valuable for nursing education and practice. Its main weaknesses concern search reproducibility, coding transparency, category overlap, cultural generalizability, empirical validation, and insufficiently developed safety and governance dimensions.

These limitations do not invalidate the article’s contribution. They reveal that the paper should be read as a conceptual foundation rather than a completed theory or validated classification. Its greatest value lies in opening a research program: determining who can become an e-patient, under what structural conditions, with what degree of autonomy, through which professional relationships, and with what consequences for safety, equity, workload, and health outcomes. The future of the e-patient will depend not merely on whether patients gain access to technology, but on whether healthcare systems are prepared to recognize, evaluate, and responsibly integrate the knowledge that digitally engaged patients bring into care.

Reference

Hosseinabadi-Farahani, M., & Dinmohammadi, M. (2026). The e-patient in the digital health era: A concept analysis using Rodgers’ evolutionary method. Nursing Forum, 2026, Article 1227765. https://doi.org/10.1155/nuf/1227765