The study set out with a specific aim: to investigate how wives operate as leaders in alcohol-affected households in the Alappad coastal region. Rather than measuring drinking prevalence or economic loss in numerical terms, the researchers chose a multi-method qualitative design that privileges lived experience. Twenty married women from households impacted by alcoholism participated in the research. Participation in in-depth interviews was determined through data saturation, the methodological principle that recruitment continues until new interviews stop yielding new themes, while convenience sampling was used to assemble participants for a focus group discussion. This dual approach allowed the team to capture both the intimate, individual texture of each woman’s situation and the shared, collective patterns that emerged when women spoke together.

Data collection relied on semi-structured interview guides and focus group questions covering five interlocking domains: marital relationships, family roles, decision-making, emotional experiences, and coping mechanisms. The semi-structured format is a deliberate methodological choice in qualitative research; it provides enough consistency across interviews to allow systematic comparison, while leaving space for participants to raise concerns the researchers had not anticipated. The gathered material was then examined through thematic analysis conducted in accordance with Naeem’s methodology, a structured procedure for coding qualitative data, grouping codes into candidate themes, and refining those themes until they form a coherent account of the phenomenon under study.

The in-depth interviews produced a set of themes that trace an arc from disruption to reorganization. The first and most fundamental theme was the disruption of family roles brought on by alcohol addiction. When a husband’s drinking becomes chronic, the responsibilities he was expected to carry, providing income, making major household decisions, representing the family in the community, do not simply disappear. They migrate. The interviews showed women absorbing financial management, childcare, negotiations with creditors and neighbours, and the emotional labour of holding a household together, often while managing the unpredictable behaviour that accompanies alcohol dependence.

From that disruption, the researchers identified a second theme: the shift into functional leadership. This concept is central to the study’s contribution. Functional leadership, in this context, does not mean formal authority or ceremonial headship of the family. It means the practical, day-to-day stewardship of the household, deciding how scarce money is spent, when children go to school, how conflicts are defused, and how the family presents itself to the outside world. The women in the study had not campaigned for this role; it was thrust upon them by circumstance. Yet over time, the interviews suggest, they came to operate as the effective centres of household decision-making, even when the formal structure of the family continued to recognize the husband as its nominal head.

The third theme, managing societal expectations and gender norms, reveals the tightrope these women walk. In Kerala’s coastal communities, as in many patriarchal settings, the ideal of the male breadwinner and the subordinate wife remains culturally powerful. Women who take over household leadership must do so without openly claiming the authority they exercise, because an overt challenge to gender norms invites social judgment. The study found that women negotiated this tension constantly, performing deference in public while exercising control in private, and absorbing stigma both for their husbands’ drinking and for any visible departure from expected feminine roles. The focus group discussion sharpened this picture, surfacing themes of the breakdown of traditional male family roles, the normalization of women’s functional leadership, and the negotiation of gender norms and social judgment.

Emotionally, the burden is not carried alone, and this is where the focus group data proved especially revealing. The discussion yielded themes of shared emotional burden and collective coping, and of collective resilience and empowerment. When women who live through similar circumstances come together, the researchers found, individual suffering becomes a shared experience that can be named, compared, and managed collectively. Coping strategies described across the study ranged from practical adaptation, restructuring household routines to accommodate a husband’s drinking, to emotional strategies that protect children from the worst effects of the situation. The interviews also captured a theme of rethinking authority and family structure, suggesting that prolonged exposure to alcohol-related disruption leads some women to fundamentally reconsider what a family is and who should hold power within it.

The methodological rigour of the study is worth noting for readers assessing how much weight these findings can bear. The combination of data saturation for interview recruitment and convenience sampling for the focus group is a pragmatic hybrid: saturation ensures that the interview corpus is thematically complete, while the focus group adds a deliberative setting in which participants can react to one another’s accounts, often surfacing norms and shared understandings that one-on-one interviews miss. Thematic analysis following Naeem’s procedure provides a transparent, replicable pathway from raw transcripts to reported themes. The study received ethical approval from the Institutional Human Ethics Committee of Amrita Vishwa Vidyapeetham under reference number IHEC/2025/151, and all participants gave informed consent, were assured of confidentiality, and retained the right to withdraw at any time without consequence. The authors declare no competing interests and received no financial support for the research.

What makes the findings resonate beyond Alappad is their conceptual implication: alcoholism is often studied as an individual clinical condition, but this study reframes it as a force that reorganizes entire family systems and, in doing so, quietly rewrites gender relations. The women described here are not passive victims of a husband’s addiction, nor are they simply surviving it. They are functioning as leaders, absorbing responsibilities, negotiating social expectations, and building networks of collective coping that sustain their households over years. The normalization of women’s functional leadership that the focus group identified suggests a durable shift, one that persists even as the underlying alcohol problem remains unresolved.

The authors conclude that the study emphasizes how gender roles and family structures are altered in alcohol-affected families, and they draw direct practical implications from that conclusion. The results highlight the need for psychological support for women carrying these hidden leadership burdens, for family-centred therapies that treat the household rather than only the individual drinker as the unit of intervention, and for greater formal acknowledgement of women’s resilience and leadership in families affected by alcohol. In coastal Kerala, as in alcohol-affected communities worldwide, the research suggests that effective policy must recognize the women who are already holding families together, and support them in roles they never chose but have come to master.

Subject of Research: Women's functional leadership and family role reorganization in alcohol-affected households in coastal Kerala

Article Title: Women as functional leaders in alcohol affected families in coastal Kerala

Article References: Harikrishnan, U., Nair, D. R., Sania, P. S., Fathima, A., Namitha, M. R., Nath, A. S., Athira, R., John, A. E., Ali, A., & Savarimalai, R. (2026). Women as functional leaders in alcohol affected families in coastal Kerala. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00462-y

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00462-y

Keywords: alcoholism, functional leadership, women, family dynamics, coping, resilience, Kerala, qualitative study, gender norms, household decision-making, Alappad, family-centred interventions

The research team conducted individual semi-structured interviews with thirty-four clinicians spanning the entire training continuum, from medical students to postgraduate year one through five residents in internal medicine, and on to attending physicians in internal medicine and critical care medicine at McGill University-affiliated academic hospitals. The interviews were interpreted using applied thematic analysis, a rigorous qualitative method that allows researchers to identify recurring patterns in how participants describe their experiences. What emerged was a developmental arc, a story of how understanding of goals-of-care discussions transforms as clinicians gain experience and seniority.

The analysis organized its findings into four central themes that map the trajectory from novice to expert. The first traces a shift from concrete to abstract conceptualizations of what a goals-of-care discussion actually is. Less experienced trainees frequently conflated goals-of-care conversations with code status discussions, reducing a rich, patient-centered dialogue to a narrow question about resuscitation preferences. For these novices, the task was often perceived as a form to be completed, a checkbox in the admission paperwork rather than an exploration of what matters most to a patient facing serious illness. More senior clinicians, by contrast, described goals of care in abstract and contextual terms, framing these conversations as ongoing negotiations that integrate prognosis, patient values, family dynamics, and clinical uncertainty.

The second theme captures a parallel movement from performative to organic approaches. Early trainees described following scripted frameworks, reciting standardized phrases, and treating the conversation as a performance to be evaluated by a supervising attending. This performative orientation, while a reasonable starting point, left them rigid and easily thrown when a patient or family member deviated from the expected script. Experienced physicians described something fundamentally different: an organic, responsive conversation that flexes to the emotional and informational needs of the moment. They spoke of reading the room, pacing the disclosure of difficult information, and weaving goals-of-care discussions naturally into the fabric of clinical care rather than isolating them as discrete, formulaic events.

The third theme, from follower to leader in shared decision-making, addresses one of the most consequential differences between junior and senior clinicians. Novices were markedly less comfortable offering guidance and tended to position themselves as passive facilitators, presenting options without direction and hoping the patient would choose. This hesitation, the researchers suggest, may reflect both a lack of clinical confidence and an incomplete understanding of prognosis. Attending physicians, drawing on years of accumulated judgment, demonstrated a greater willingness to make recommendations, to share their expert opinion while still honoring patient autonomy, and to steer the conversation toward medically appropriate and patient-aligned decisions. This evolution from deference to directed guidance represents a core component of what experts mean by clinical judgment in serious illness communication.

The fourth theme concerns how learning itself happens, described as scaffolding between formal and informal development. Participants agreed almost universally that goals-of-care skills develop as a career-long endeavor, shaped far more by observation, feedback, and lived clinical experience than by structured instruction. Formal training on this topic was described as limited, fragmented, and often arriving too late. Trainees reported watching senior colleagues conduct these conversations, debriefing afterward with attendings when circumstances allowed, and gradually building competence through repetition and reflection. Yet the study found that many trainees were expected to lead goals-of-care discussions independently early in their training, before adequate scaffolding had been established, raising pointed concerns about patient care and trainee distress.

The implications of this developmental mismatch are significant. Internal medicine is, by the nature of its patient population, a specialty where goals-of-care conversations are frequently required. Hospitalized patients with advanced illness, uncertain prognoses, and complex family situations present these dilemmas daily. If junior physicians are being sent into these encounters with a conceptualization limited to code status and a performative, script-dependent approach, both patients and trainees are being underserved. Prior research cited by the authors, including studies of residents’ code status discussion skills and randomized trials of simulation-based communication training, has shown that these skills can be taught, but the new findings suggest that isolated interventions may not be enough. What is needed, the authors argue, is a structured, stage-specific, longitudinal curriculum that meets learners where they are in their development.

Such a curriculum would look markedly different at each stage. For medical students and early residents, the priority would be building accurate conceptual foundations, decoupling goals of care from code status, and introducing frameworks that emphasize eliciting patient values before discussing interventions. For mid-level residents, deliberate practice with simulated patients and observed conversations with structured feedback could accelerate the shift from performative to organic approaches. For senior residents and early attendings, coaching on recommendation-giving and prognostic communication would support the transition to leadership in shared decision-making. The study’s participants themselves called for exactly this kind of sequenced, longitudinal design, echoing broader movements in medical education such as competency-based frameworks and longitudinal coaching programs that have been adopted in Canada and elsewhere.

The study also carries a broader message about the nature of expertise in medicine. Communication skills are often treated as soft skills, assumed to be absorbed along the way rather than rigorously taught. This research demonstrates that the growth from novice to expert in goals-of-care discussions follows a describable, predictable developmental progression, one that can be anticipated and supported rather than left to chance. The differences in conceptualization, approach, and decision-making role between junior and senior clinicians are not merely matters of personality or confidence. They reflect distinct cognitive and professional stages, each with its own learning needs. Recognizing this progression allows educators to design training that is developmentally attuned, rather than one-size-fits-all lectures delivered at a single point in training.

As populations age and chronic serious illness becomes an ever-larger share of medical practice, the ability to conduct skillful, compassionate goals-of-care conversations will only grow in importance. This study, funded by the Fédération des Médecins Résidents du Québec Research Grant and presented in preliminary form at the International Conference on Residency Education in Ottawa, provides a roadmap for how the medical education community might respond. By treating goals-of-care communication as a career-long developmental arc with structured support at every stage, training programs can ensure that physicians arrive at these pivotal bedside moments not as anxious novices clutching a script, but as confident, nuanced clinicians capable of guiding patients and families through the most consequential decisions of their lives.

Subject of Research: How internal medicine physicians develop goals-of-care discussion skills across the training continuum

Article Title: How Internal Medicine Physicians Learn to Conduct Goals-of-Care Discussions: A Qualitative Study Across the Training Continuum

Article References: Lee, C. B., Snell, L., Li, K. X., Jayaraman, D., & Nugus, P. (2026). How Internal Medicine Physicians Learn to Conduct Goals-of-Care Discussions: A Qualitative Study Across the Training Continuum. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10696-w

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10696-w

Keywords: goals of care, internal medicine, medical education, communication skills, qualitative study, shared decision-making, code status, residency training, palliative care, clinical judgment, longitudinal curriculum, physician development

The study was conducted as the second, qualitative phase of a sequential explanatory mixed-methods project. Twenty-one experts were recruited through snowball sampling from eleven Type I medical universities, the highest tier of Iran’s medical education system. The participant pool deliberately spanned the organizational hierarchy: faculty members who produce research, senior administrators who allocate resources and set strategy, and knowledge translation specialists who sit at the interface between the two worlds. Between February and August 2023, the researchers conducted semistructured interviews lasting between forty-five and ninety minutes, allowing participants to describe in their own words what helps and what hinders the movement of evidence into policy and practice within their institutions.

Analysis followed the inductive content analysis framework of Elo and Kyngäs, proceeding through open coding, categorization, and abstraction with the qualitative analysis software ATLAS.ti. Rigor was addressed through several established safeguards: member checking, in which participants reviewed the researchers’ interpretations; peer debriefing among the analytic team; and audit trails documenting how codes and categories evolved. Inter-coder reliability was quantified using Cohen’s Kappa, reaching a value of 0.82, which is conventionally interpreted as almost perfect agreement between independent coders. The study was conducted in accordance with the Declaration of Helsinki, with ethics approval from the Kerman University of Medical Sciences Ethics Committee and written informed consent from all participants.

From this analysis, five overarching dimensions of organizational readiness for knowledge translation emerged. The first is organizational culture and research climate, encompassing the norms, values, and informal expectations that determine whether evidence is genuinely valued or merely tolerated. The second is human resource development and training, the formal and informal structures through which staff acquire the skills to find, appraise, summarize, and communicate research findings. The third is knowledge production and sharing, the pipelines through which new evidence is generated, stored, and circulated inside and beyond the institution. The fourth is evidence-based policy and strategy, the extent to which institutional decision-making processes are explicitly designed around research findings. The fifth, and for the authors the most consequential, is monitoring and evaluation mechanisms, the systems that track whether knowledge translation efforts are actually functioning.

What elevates this study beyond a conventional checklist of readiness factors is its second-order analysis of how these five dimensions relate to one another. Rather than treating monitoring and evaluation as the final step of an implementation sequence, the researchers found that feedback loops function as the connective tissue of the entire system. In their formulation, feedback mechanisms act as the nervous system of knowledge translation readiness, continuously sensing what is happening across culture, training, production, and policy, and transmitting signals that allow the organization to learn and adapt. Without those loops, the other four dimensions operate in isolation; with them, the organization develops the dynamic capacity to correct course, reinforce what works, and abandon what does not.

This reframing carries real theoretical weight. Many existing knowledge translation frameworks, inherited from linear models of research uptake, position monitoring as a subsequent and largely administrative stage that occurs after the substantive work of translation is complete. The Iranian findings invert that logic: the feedback apparatus is not downstream of implementation but upstream of it, because organizations that cannot perceive the consequences of their own actions cannot become ready for anything. In systems terms, feedback converts a static bundle of resources into a learning system, and it is precisely that learning capacity, the authors argue, that distinguishes institutions where evidence routinely shapes decisions from institutions where reports accumulate unread.

The expert interviews also yielded a sobering catalogue of the barriers currently undermining this capacity in Iranian medical universities. Participants described siloed communication, in which departments, faculties, and administrative units exchange information poorly or not at all, fragmenting the very loops that the readiness model depends upon. They reported limited incentives for the use of evidence, meaning that career advancement, recognition, and reward structures do not encourage either researchers to engage with practice or managers to engage with research. They cited a lack of managerial commitment, insufficient capacity-building structures for developing the specialized skills that knowledge translation demands, and weak linkages between research units and the practice environments, such as hospitals and public health programs, that the evidence is meant to inform.

The authors conclude that enhancing organizational readiness for knowledge translation in this setting requires a multifaceted approach that strengthens cultural, structural, and leadership capacities simultaneously, rather than addressing any single factor in isolation. Most pointedly, they argue that establishing structured feedback mechanisms must be viewed as the core driver, not an afterthought, of sustainable knowledge translation implementation. In practical terms, that would mean designing deliberate channels through which evidence use is observed, questioned, and evaluated: routine forums where researchers and decision-makers exchange information, evaluation systems that generate usable information about how evidence flows, and leadership practices that treat feedback as a resource rather than a threat.

The study’s authors are careful to specify the limits of their claims. The findings identify enabling conditions for knowledge translation rather than providing direct evidence that strengthening these conditions improves health outcomes, a distinction that matters for anyone tempted to treat the five-dimension model as a guaranteed prescription. The research is also confined to Type I medical universities in one national context, and organizational readiness in smaller institutions or different health systems may depend on a different balance of factors. Nevertheless, the implications travel beyond Iran. Knowledge translation challenges are well documented across low- and middle-income countries, where research production has often expanded faster than the organizational machinery needed to apply it. By proposing feedback as the organizing principle of readiness, the study offers a testable hypothesis for implementation science: that the first question any research institution should ask is not how much evidence it produces, but how effectively it hears the signal of its own experience. By addressing these readiness factors, the authors suggest, medical universities can strengthen their role in evidence-informed policy and practice, turning the institutional pyramid of training, production, and strategy into a genuinely self-correcting system.

Subject of Research: Organizational readiness for knowledge translation and feedback loops in Iranian medical universities

Article Title: Feedback loops as a core driver: rethinking organizational readiness for knowledge translation in Iranian medical universities

Article References: Rezaei, F., Saberian, M., Ghasemi, S., Gharibi, Z., & Hosseinzadeh, H. (2026). Feedback loops as a core driver: rethinking organizational readiness for knowledge translation in Iranian medical universities. Health Research Policy and Systems. https://doi.org/10.1186/s12961-026-01537-7

Image Credits: AI Generated

DOI: 10.1186/s12961-026-01537-7

Keywords: knowledge translation, organizational readiness, feedback loops, implementation science, medical universities, Iran, qualitative study, evidence-based policy, monitoring and evaluation, organizational learning, health policy, Feedback

The study was carried out between September 2025 and January 2026 in government-run shelters located in a low-resource region of eastern Iran. Researchers recruited thirteen homeless women through a combination of convenience and purposive sampling, a strategy that allowed them to capture both readily accessible participants and women with particular experiences relevant to the research question. Each participant took part in a semi-structured, in-depth interview that was audio-recorded and later transcribed verbatim. The interviews explored how the women perceived the conditions, circumstances, and structural forces that influenced their day-to-day health, from the availability of food and shelter to their interactions with health services and the communities around them.

To analyze the transcripts, the team applied a manual thematic analysis following Boyatzis’s methodological approach, a well-established technique in qualitative health research that involves systematically coding data and clustering codes into themes. The researchers used the Healthy People 2030 framework, developed by the United States Department of Health and Human Services, as their conceptual guide. This framework organizes social determinants of health, sometimes called social drivers of health, into five domains: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context. Anchoring the analysis in this framework allowed the Iranian findings to be compared with a global body of research on how social conditions shape health outcomes.

The analysis revealed twenty-four social determinants of health distributed across the five framework themes. Two domains stood out for their weight in the women’s lives: Economic Stability and Social and Community Context. These two themes encompassed the highest number of determinants, underscoring, the authors argue, their influential role in the ultimate health outcomes of homeless women. In practical terms, this means that the women’s health was shaped less by individual clinical risk factors alone and more by the grinding arithmetic of poverty, income insecurity, and the presence or absence of supportive relationships and community ties. For a population with no stable housing, economic shocks translate directly into skipped meals, untreated illness, and exposure to unsafe environments.

The emphasis on Economic Stability reflects conditions specific to the border region studied. Eastern Iran’s provinces adjacent to Afghanistan are characterized by pronounced socioeconomic and healthcare disparities, and they host communities affected by migration flows, unemployment, and limited public infrastructure. Homeless women in this setting face a compounding set of disadvantages: they are women in a context of gendered economic exclusion, they are homeless in a region with thin social services, and many are affected by the broader instability associated with the Afghan border. The study’s findings suggest that any intervention aimed at improving these women’s health must begin with economic levers, including income support, employment pathways, and reliable access to basic material needs.

The second dominant domain, Social and Community Context, points to the relational side of health that is often overlooked in clinical settings. For homeless women, social isolation, stigma, family breakdown, and the absence of trusted support networks can be as damaging to health as any pathogen. The interviews captured how the women navigated relationships with shelter staff, other residents, family members, and the wider community, and how the quality of those relationships influenced their willingness to seek care, their mental wellbeing, and their sense of dignity. The researchers note that these findings hold particular value for low-resource settings, where formal health systems cannot alone compensate for the absence of social support structures.

The remaining three themes of the Healthy People 2030 framework also yielded concrete determinants. Education Access and Quality captured how limited literacy and schooling constrained the women’s ability to find work, understand health information, and advocate for themselves. Health Care Access and Quality encompassed barriers such as cost, distance, documentation status, and experiences of discrimination when seeking treatment. Neighborhood and Built Environment covered the physical conditions of shelters and streets, including safety, sanitation, and exposure to environmental hazards. Together, the twenty-four determinants form what the authors describe as a comprehensive list of social determinants of health for homeless women, one of the most granular portraits assembled for this population in the region.

Methodologically, the study demonstrates the value of qualitative inquiry in settings where quantitative data on homeless populations are scarce or unreliable. Homeless women are frequently missed by censuses, surveys, and routine health information systems, meaning their needs remain statistically invisible even as their suffering accumulates. By sitting down with thirteen women and systematically coding their accounts, the research team surfaced determinants that would never appear in administrative datasets. The use of a recognized international framework strengthens the study’s utility, allowing local findings to inform global conversations about housing, health equity, and the social drivers of disease, while remaining grounded in the specific realities of Iran’s eastern borderlands.

The authors conclude that the study highlights the pivotal role of governments in addressing the health of homeless women. Because the determinants identified span income, education, healthcare, housing, and community life, no single ministry or program can tackle them in isolation. Effective responses, the findings imply, require coordinated policy action: social protection schemes that reach women without fixed addresses, shelters that connect residents to healthcare and education, anti-discrimination measures in health facilities, and investment in the infrastructure of neglected border regions. The research was funded by Birjand University of Medical Sciences and approved by the university’s ethics committee, with informed consent obtained from all participants and their anonymity strictly protected throughout collection and analysis.

Beyond its immediate regional significance, the study offers a template for understanding homelessness as a public health issue rather than merely a social welfare problem. The twenty-four determinants mapped by the researchers illustrate how health is produced, or eroded, long before a patient reaches a clinic, in the labor market, the classroom, the neighborhood, and the family. For the homeless women of Iran’s Afghan border regions, the path to better health runs through economic security and human connection as much as through medicine. The study’s comprehensive inventory gives policymakers, clinicians, and advocates a concrete starting point, and it gives a long-invisible population something it has rarely been granted: a documented, systematic account of the forces shaping their lives.

Subject of Research: Social determinants of health among homeless women in Iran's border regions with Afghanistan

Article Title: Social determinants of health among homeless women in border regions of Iran with Afghanistan: a qualitative study

Article References: Khosravi, M., Khosravi, F., Mohammadi, F., Rezaei Qazravan, Z., & Hajiaghaye, Z. (2026). Social determinants of health among homeless women in border regions of Iran with Afghanistan: a qualitative study. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00470-y

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00470-y

Keywords: social determinants of health, homeless women, Iran, Afghanistan border, qualitative study, Healthy People 2030, economic stability, healthcare access, shelters, health equity, Birjand University of Medical Sciences, public health

The research, led by Antita Kanjanakaew and colleagues at Mahidol University’s Faculty of Nursing together with nurse educators at Siriraj Hospital, emerged from a pressing global problem. Health systems worldwide face a shortage of qualified nurse-midwifery educators, the specialized faculty members who traditionally supervise students during clinical placements. When there are not enough educators to go around, students can find themselves watching from the sidelines rather than learning by doing. The buddy model was developed as a collaborative response, pairing students with experienced bedside nurse-midwives who act as day-to-day guides within authentic clinical settings, allowing experiential learning to continue even when formal educator supervision is stretched thin.

To understand whether the model works, the researchers turned to the people at its center. Twenty-six nurse-midwifery students participated in online focus group discussions, while fifteen nurse-midwives took part in in-depth individual interviews. Participants were recruited through purposive sampling, a technique that deliberately selects individuals with direct experience of the phenomenon under study. The team then applied qualitative content analysis, a systematic method for identifying patterns and themes within textual data, to distill hundreds of pages of conversation into a coherent account of what the buddy model delivers, and what it demands.

Four major themes emerged from the students’ side of the relationship. The first was apprehension toward interacting with unfamiliar nurses, a reminder that stepping onto a busy maternity ward as a student is an inherently vulnerable act. Students described initial anxiety about approaching nurses they did not know, worrying about being judged or turned away. Yet this apprehension typically gave way to the second theme: hands-on learning. Once relationships formed, students reported that working alongside buddy nurses enhanced their confidence, accelerated their professional identity formation, and helped them integrate classroom theory with the messy, unpredictable realities of patient care. There is a qualitative difference, the students suggested, between reading about labor management and standing beside a woman in labor with a trusted mentor at your shoulder.

The third and fourth themes revealed the model’s internal complexity. Students described a dichotomy between two types of buddies, and correspondingly different challenges of learning from each. Some buddy nurses were engaged, generous teachers who actively created learning opportunities; others were passive, offering little direction and leaving students to fend for themselves. Busy clinical environments compounded the problem, reducing learning engagement when workloads overwhelmed even the most willing mentors. In other words, the buddy model is not a self-executing mechanism. Its educational value depends heavily on the disposition, availability, and teaching capacity of the individual nurse to whom a student is assigned.

The nurse-midwives’ perspective, captured in the individual interviews, added a second, equally textured layer. Four themes again emerged. The nurse-midwives saw the buddy nurse role as multifaceted, encompassing mentor, emotional supporter, and professional role model simultaneously. They described holding the line between teaching and care, a delicate balancing act in which patient safety must always take priority even as students need room to practice. They also spoke of growth, from self to system, suggesting that serving as buddies prompted reflection not only on their own practice but on the broader structures of the clinical environment. Finally, they identified barriers to effective teaching, including heavy workloads, the constant demands of patient safety, and limited opportunities to carve out genuine learning moments within packed shifts.

When the researchers integrated both sets of perspectives, a striking picture emerged. The buddy model, they concluded, functions as a reciprocal relational learning process rather than a simple one-way transfer of knowledge. The relationship begins with approach and engagement, as students overcome initial apprehension and nurses open their practice to observation and participation. It progresses through support and professional role modeling, as buddies demonstrate not just technical skills but the emotional and ethical dimensions of midwifery. And it culminates in shared learning and professional outcomes, with students gaining competence and confidence while nurse-midwives themselves report renewed professional growth. Learning, in this framing, is not delivered but co-constructed.

That reciprocity may explain why the model appears to support psychological safety, a concept that has attracted growing attention in health professions education. Students who feel emotionally secure are more likely to ask questions, admit uncertainty, and attempt challenging procedures, all of which are essential to developing clinical judgment. The buddy relationship, built on repeated daily contact with a consistent mentor, seems to create precisely the conditions under which such vulnerability becomes productive. The study’s authors suggest this supportive relational quality is central to the model’s perceived benefits for both experiential learning and professional development.

Yet the findings come with candid caveats. The study’s participants perceived the buddy model as valuable, but its successful implementation depended on adequate engagement of buddy nurses, manageable workloads, and sufficient clinical learning opportunities. Where any of these conditions failed, the model’s benefits eroded quickly. Passive buddies and overwhelmed wards turned a potentially rich learning relationship into a hollow formality. The authors are careful to note that their findings offer preliminary, context-specific support, drawn from a single hospital and a particular academic-practice partnership, rather than a universal prescription. Generalizing to other institutions will require further research in different settings and health systems.

Even so, the implications are significant at a moment when midwifery education faces mounting pressure. Shortages of clinical educators are not unique to Thailand; they are a structural feature of nursing and midwifery training in many countries, and they threaten the pipeline of skilled birth attendants precisely when maternal health services need reinforcement. The buddy model offers a pragmatic pathway: it mobilizes the clinical workforce already in place, transforms routine care into a teaching platform, and does so without requiring large new investments in faculty. The Bangkok study suggests the approach can work, but only if institutions treat buddy nurses as educators in their own right, protecting their time, recognizing their teaching role, and selecting for the engaged, supportive disposition that students so clearly valued. The alternative, the study quietly warns, is a buddy system in name only, in which students stand beside nurses too busy to teach and learn far less than they might.

Subject of Research: Experiences of nurse-midwifery students and nurse-midwives with the buddy model of clinical education in Thailand

Article Title: Experiences of the buddy model in midwifery clinical practice: a qualitative exploration of students and nurse-midwives

Article References: Experiences of the buddy model in midwifery clinical practice: a qualitative exploration of students and nurse-midwives. (n.d.). https://doi.org/10.1186/s12912-026-05378-1

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05378-1

Keywords: buddy model, midwifery education, clinical learning, nurse-midwifery students, nurse-midwives, qualitative study, experiential learning, clinical teaching, professional identity, psychological safety, Thailand, nursing education

The study adopted an exploratory qualitative descriptive design, a method chosen precisely because the researchers wanted rich, contextualized accounts rather than numeric satisfaction scores. Through purposive and snowball sampling, the team recruited twelve frontline clinical nurses from multiple tertiary hospitals in Zhejiang Province. Crucially, every participant had hands-on experience with both clinical research and generative AI applications, ensuring that the interviews captured informed users rather than curious outsiders. To maximize diversity, the sample deliberately spanned different hospital departments, professional titles, years of clinical work, levels of research experience, and habitual patterns of AI use, a design decision that strengthens the credibility of the themes that ultimately emerged.

Data collection took the form of semi-structured online interviews, a format that allowed participants to speak freely while ensuring that key domains such as role perception, workflow impact, and support needs were consistently explored. The researchers analyzed transcripts inductively using thematic content analysis supported by NVivo 15.0 software, and the study followed the COREQ checklist, the widely accepted reporting standard for qualitative research. Saturation was assessed dynamically during repeated coding cycles: no new codes or themes appeared after the tenth interview, and two additional interviews confirmed that the dataset had reached its interpretive limits. That kind of methodological transparency matters, because qualitative findings live or die on the rigor with which themes are derived from raw testimony.

From this analysis, five interrelated themes emerged, which the authors summarize as an interpretive model of a collaborative practice ecology. The first theme describes a spectrum of attitudes stretching from efficiency-driven acceptance to ethical skepticism. Some nurses had embraced generative AI enthusiastically, praising its ability to accelerate literature review, questionnaire drafting, and the mundane mechanical work that often bogs down research projects. Others viewed the same capabilities through a more cautious lens, questioning whether speed obtained at the cost of verification and accountability is genuinely a gain for science. The study’s refusal to flatten this diversity into a single sentiment is one of its most valuable contributions, since most prior work has either focused on nursing education or treated nurse researchers as a homogeneous block.

The second theme concerns dual application scenarios. Participants reported that generative AI genuinely empowers data-oriented tasks, from cleaning and structuring datasets to generating code snippets and summarizing text. Yet the tools proved conspicuously limited when it came to understanding clinical context. Nurses described situations in which AI outputs were technically fluent but clinically naive, missing the subtleties of patient populations, departmental workflows, and the lived realities behind a data point. This gap between statistical plausibility and clinical validity is a recurring concern in health AI, and the study documents how frontline staff, who occupy the interface between data and patients, feel it most acutely.

The third theme identifies what the authors call the core challenges: technical reliability, data security, and ambiguities around academic integrity. Reliability worries centered on hallucinations and subtle errors that could propagate into research outputs if unchecked. Data security loomed even larger, given that clinical research often involves identifiable patient information subject to strict confidentiality obligations. Nurses questioned whether entering study-related content into third-party AI platforms could expose sensitive data. Meanwhile, academic integrity emerged as a gray zone: participants were uncertain about when AI assistance crosses the line from acceptable support into misconduct, noting the absence of clear institutional rules to guide them. The paradox is striking: nurses are using tools faster than the norms governing their use can be written.

The fourth theme tracks evolving role perceptions. Over time, participants began to reconceptualize generative AI from a basic tool, something akin to an advanced search engine or spell-checker, into a potential intelligent data-analysis assistant capable of more substantive collaboration. This perceptual shift carries practical consequences. A tool framing invites casual, unexamined use; an assistant framing invites delegation, oversight, and questions about responsibility. As nurses reposition AI within their professional hierarchy of collaborators, institutions will need to decide what levels of autonomy are appropriate and who bears accountability when an AI-assisted analysis goes wrong.

The fifth and final theme captures expectations for the future. Nurses in the study want three things: profession-adapted technology that understands nursing-specific terminology and contexts, targeted AI literacy training that goes beyond generic tutorials, and clear institutional norms that define acceptable use, protect patient data, and resolve integrity questions. The authors argue that collaboration between nurses and generative AI requires a deliberate balancing of efficiency against risk, and they call for a systematic strategy encompassing context-adapted tools, enhanced AI literacy, and explicit ethical and organizational guidelines. In other words, the responsibility for safe and effective adoption does not rest on individual nurses alone; it belongs to hospitals, educators, and technology developers as well.

The significance of this research extends well beyond Zhejiang Province. Clinical nurses are increasingly expected to contribute to research output as part of professional advancement, yet they typically juggle research with demanding clinical schedules, making efficiency tools especially attractive. At the same time, nursing research deals with some of the most sensitive data in medicine. The tension the study documents, between the productivity that generative AI promises and the vigilance that patient privacy and scientific rigor demand, is likely to play out in every health system adopting these technologies. By grounding the debate in the concrete experiences of actual users, the study offers policymakers a template for what guidance must address: verification practices, data-handling boundaries, integrity definitions, and training curricula.

The authors are candid about their limitations. The sample comprised only twelve GenAI-experienced nurses drawn from tertiary hospitals in a single Chinese province, so the findings should be applied cautiously to other settings, particularly primary care environments or institutions at earlier stages of AI adoption. Still, the interpretive model they propose, a collaborative practice ecology in which attitudes, applications, challenges, roles, and expectations interlock, provides a framework that future quantitative and intervention studies can test and refine. As generative AI continues its rapid diffusion into healthcare, this study stands as an early, careful record of how the people closest to patients are negotiating the technology’s promise and peril, and a reminder that the success of AI in medicine will be determined not by the sophistication of the algorithms but by the trust, competence, and protections afforded to the professionals who use them.

Beyond its substantive findings, the study offers a useful illustration of how qualitative evidence can complement the growing body of quantitative surveys on AI adoption in healthcare. Numbers can reveal how many nurses use generative AI or how frequently, but they cannot explain why a nurse hesitates to paste a patient dataset into a chatbot, or how professional identity shifts when a machine becomes a working partner. By following the COREQ reporting standard and documenting saturation explicitly, the authors provide a level of procedural detail that allows other researchers to appraise the trustworthiness of the themes and to replicate the approach in different health systems.

The institutional setting of the research is also worth noting. Tertiary hospitals in China are typically academic medical centers where research participation is woven into professional expectations for nursing staff, and where ethics oversight structures such as the institutional review board that approved this study are well established. That environment helps explain why participants were both experienced users of AI and acutely aware of governance gaps: they work in organizations that simultaneously demand research productivity and enforce strict data confidentiality, leaving them to navigate the tension largely on their own.

The study’s transparency extends to its own relationship with the technology it examines. The authors disclose that a generative AI tool was used solely to improve the readability and language of the manuscript, with full human review and accountability, and that no AI was involved in the design, data collection, analysis, or interpretation of the research. This kind of declaration is becoming an expected feature of credible publications, and its presence here models the very norm clarity that participants said they wanted from their own institutions.

For readers considering how such findings might translate into practice, the most actionable thread is the call for AI literacy training tailored to nursing. Generic digital skills courses rarely address the specific failure modes of generative models, such as fabricated citations or plausible but incorrect clinical reasoning, and they seldom cover the data-protection calculus nurses must perform before using a third-party platform. Profession-specific curricula, paired with written institutional policies defining acceptable use, would directly address the ambiguities participants described.

Finally, the interpretive model of a collaborative practice ecology invites empirical testing. Future work could quantify the attitude spectrum, compare nurses across hospital tiers and regions, or evaluate whether targeted training and clear guidelines measurably reduce the risks participants identified while preserving the efficiency gains they value.

Subject of Research: Frontline clinical nurses' experiences and challenges using generative AI to support clinical research

Article Title: Experiences and challenges of clinical nursing staff using generative AI to support clinical research: a qualitative study

Article References: Qiao, W., & Xiang, X. (2026). Experiences and challenges of clinical nursing staff using generative AI to support clinical research: a qualitative study. BMC Nursing. https://doi.org/10.1186/s12912-026-05167-w

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05167-w

Keywords: generative artificial intelligence, clinical nursing, clinical research, qualitative study, nursing research, data security, academic integrity, AI literacy, frontline nurses, thematic content analysis, tertiary hospitals, China