The present work provides both assessment and appreciation of the profound and deeply human contributions of the scientist Mark Hume Chignell. His varying conceptual, methodological, and applied innovations are set within a career chronology that features a focus on his humanity as much as it does on his science. Having assimilated the disparate, yet still coherent scientific disciplines of both psychology and engineering, it is of little surprise that Chignell’s oeuvre featured a Human Factors/Ergonomics emphasis in which he might well be considered the quintessential engineering psychologist. Whilst making crucial contributions to the theoretical formulations concerning adaptative and expert systems, Chignell was never content to be isolated in the experimental laboratory but felt obliged and even mandated to carry progress being made therein out into the world of users. His later work on assistive medical technologies for the elderly typified these concerns and embodied his lifelong dedication to the improvement of humanity. This characteristic, whether expressed through his far-reaching science or in his immediate professional and social presence, ran as a golden thread throughout his lifetime, and now beyond.
Introduction : Community pharmacists play a vital role in ensuring optimum medication safety. The study aim was to measure safety culture in Irish community pharmacies using the validated Community Pharmacy Survey on Patient Safety Culture (PSOPSC). Methods : The survey consisted of 40 questions using a 5-point Likert scale, within 11 dimensions; three demographic questions and a free-text comments section. The online questionnaire was emailed to all 3943 Irish community pharmacists. The positive rate response (PRR), that is the mean percentage of positive Likert scale responses to each item and each dimension of the survey, was calculated. Free-text responses were explored by thematic analysis. Results : The survey was completed by 173 pharmacists, response rate 4.4%. The mean %PRR across the 11 survey dimensions was 72.3%. The statement with highest PRR was “Our pharmacists tell patients important information about their new prescriptions.” The statement with lowest PRR was “Interruptions/distractions in this pharmacy (from phone calls, faxes, customers, etc.) make it difficult for staff to work accurately” (PRR=6.4%). The dimension of “Organizational Learning-Continuous Improvement” demonstrated the highest PRR (81.6%). The dimension of “Staffing, work pressure and pace” demonstrated the lowest PRR (35.6%). Respondents rated overall patient safety in their pharmacy as excellent/very good/good (88.4%). Emergent themes in free-text comments were patient safety culture, impact of distractions, and work environment and staffing. Conclusion : Respondents reported a broadly positive patient safety culture in the pharmacy in which they work. Workplace conditions and staffing issues are considered detrimental to safety culture in Irish community pharmacies.
Objective We aimed to study the experience of using continuous glucose monitoring (CGM) among older Chinese Americans with cognitive impairment (CI) and their care partners. We also explored physicians’ perspectives on using CGM in older adults with cognitive decline. Background CI can heighten the challenges of managing type 2 diabetes (T2D), particularly among older Chinese Americans due to the interplays of cultural, financial, and health-related burdens and older adults with cognitive decline that add additional challenges of diabetes management. The application of CGM in such populations remains understudied. Method Older Chinese American adults with CI and T2D and their care partners were recruited from the New York City (NYC) community. Clinicians who had clinical experience of the application of CGM in individuals with diabetes and cognitive decline were recruited nationally. After brief education, patients used CGM for 10 days and shared the data with their care partners. In-depth interviews were conducted among older Chinese Americans with both T2D and CI (n=11), care partners (n=11), and clinicians (n=8), transcribed, and then thematically analyzed using ATLAS.ti software. Results Older Chinese Americans with both T2D and CI had a mean age of 74.5 ± 5.2 years, and 63.6% were women. They reported CGM helped them assess the influence of various foods on glucose levels in order to choose appropriate foods (n=10) and portion sizes (n=5), gain insight on the role and impact of exercise (n=5), enhance care partner involvement (n=5) and communication (n=4), and promote a positive mindset by improving management confidence or disease understanding (n=9) in diabetes self-management. Care partners echoed similar sentiments but added that the device enhanced diabetes management as it was more persuasive in motivating behavioral changes (n=5), and increased care partner involvement by allowing them to check in more often (n=6) and review data with the patient at anytime and anywhere (n=4). Clinicians emphasized that CGM provided real-time, shareable continuous data, in contrast with occasional A1C results (n=5), improving safety, supporting individualized treatment decisions (n=5), highlighting the importance of strong care partner support systems (n=8), and noting that newer models with automatic data transmission (Dexcom G6/G7) are especially valuable (n=5). Conclusion Our findings indicate that CGM was feasible in easing management burden for older Chinese Americans with CI and T2D, while also enhancing care partner involvement and supporting clinicians in individualized treatment decisions. Application Potential applications of this research include the adaptation of the CGM in older Chinese Americans with CI and T2D to better accommodate their cultural needs in diabetes management.
Background Integration of robotic-assisted surgery (RAS) systems into modern surgical practice requires operating room teams to effectively adapt to a rapidly evolving array of technologies. There are many RAS systems with varied designs and features in clinical use around the world. As healthcare organizations are increasingly integrating new systems into surgical practice, operating room teams must maintain flexibility in their practice and adapt to different systems that require different setups, communication, and coordination strategies. Therefore, the goal of this perspectives paper is to provide recommendations to facilitate effective adaptation to different systems. Method This perspectives paper draws from the wider human factors and teamwork literature to provide actionable, preliminary recommendations to guide clinicians and healthcare organizations as widespread adoption of multiple RAS systems becomes more common. As the extant literature on team adaptation to different RAS systems is limited, this paper is not a formal, systematic review. As the evidence base expands, a systematic review to determine evidence-based best practices will be meaningful, but in the mean time, these recommendations can be used to guide multi-RAS system integration. Results We recommend: (1) engaging in team reflexivity through structured discussions and reflections before, during, and after surgical procedures involving a new system, (2) integrating team process training as a whole team or cross-training alongside technical training for the new system, and (3) studying team adaptation process and outcomes for research and outlining system-specific or multi-system credentialing and continuing professional development by healthcare organizations and governing bodies. Conclusion Integrating the human factors and teamwork literature, we provide recommendations for effective adaptation to different RAS systems. We hope that this paper ignites a discussion and roadmap for practice, research, and policy in using different RAS systems to safely and efficiently deliver the surgery. In the future, when the evidence base allows, a systematic review of best practices is recommended.
Despite being the most commonly used medical imaging technology worldwide, ultrasound probes have undergone few to no changes throughout the past decades. Recent studies have shown that the intensive use and unsuitable design of ultrasound equipment contributes to a high prevalence of wor k-related musculoskeletal disorders (WMSDs) among examiners. This study, therefore, examined means to enhance the ergonomic qualities of abdominal ultrasound probes and the resulting acceptance rates by medical staff. Using feedback from 25 physicians, weight, size and center of mass were identified as key factors for perceived ergonomics during experiments in a simulated environment, whereas the hand size, age and experience of the subjects had no significant impact. Based on these findings, a redesigned probe was developed, offering improved perceived ergonomics while maintaining acceptance comparable to that of established probes. By aligning with existing technical constraints, the proposed design could be readily implemented in clinical practice, reducing WMSDs among healthcare professionals.
Objective This proof-of-concept study sought to explore how data from CGM and exercise can be aggregated and analyzed to capture clinically meaningful glycemic patterns and actionable feedback. To this end, we examined how exercise days were associated with glucose outcomes derived from continuous glucose monitoring (CGM) among adults with type 1 diabetes (T1D) who had low baseline exercise levels. Methods Secondary analyses were conducted on data from a 10-week digital app-based exercise intervention. Participants (N = 17; 52.9% Female; M [SD] age = 43.4 years [13.5]; M [SD] diabetes duration = 23.1 years [15.2]) received an exercise app with videos, text-based exercise coaching, a web-based self-monitoring diary, and a monthly session with personalized integrated feedback of CGM and other psychosocial data (exercise, mood, and sleep). To identify meaningful post-exercise periods, glucose patterns were examined across the 24-hour period, followed by iterative testing of different analytic windows. The final models focused on evening and overnight periods (18:00–06:00) to capture immediate and delayed glycemic effects. CGM-derived outcomes – mean glucose, time in range (TIR; 70–180 mg/dL), time in hyperglycemia (≥250 mg/dL), and time in hypoglycemia (≤70 mg/dL) – were analyzed using generalized linear mixed models. Logistic mixed models estimated odds of hyperglycemia and hypoglycemia, adjusting for age, diabetes duration, BMI, weekday, and HbA1c. Results Relative to non-exercise days, exercise days were associated with lower mean glucose (−3.13 mg/dL, p = .001) and higher TIR (3.36%, p < .001), corresponding to ∼25 additional minutes per night in range. Exercise days were associated with reduced time in hyperglycemia (−2.16%, p < .001) and lower odds of hyperglycemia (OR = 0.68 [0.58–0.78], p < .001). Exercise was associated with a small but statistically significant increase in percent time below 70 mg/dL (0.81%, p = .002); however, the interval-level odds model did not show a statistically significant increase in hypoglycemia risk (OR = 0.85 [0.71–1.00], p = .057). Conclusions In this exploratory study, exercise was associated with greater evening and overnight glucose stability among adults with T1D who were physically inactive at baseline (i.e., 0 min of recorded exercise per week). These preliminary findings suggest the analytic feasibility of linking CGM and exercise data to identify clinically meaningful glycemic patterns. This lays the groundwork for an integrated behavioral support system that provides interpretable, actionable feedback to support patients’ diabetes self-management.
Objective Explore multi-level drivers of effective teamwork in colorectal cancer screening (CRCS) at institutions that serve persistently impoverished patients. Background Teamwork is vital to quality care in outpatient settings, including routine cancer screenings. In recent years, CRCS guidelines have changed, decreasing the screening age from 50 to 45 years. Institutions that serve individuals who live in persistent poverty have lower CRCS rates. Teamwork, and other institutional characteristics that facilitate or hinder success of care coordination, test ordering, and results communication have been underexplored in this area. Method We collected qualitative and quantitative data through surveys and interviews of providers at seven Federally Qualified Health Centers located in the Midwest region of the United States. Data were gathered concordantly, analyzed separately, and merged for mixed method integration according to a scientifically-based heuristic for teamwork, the 7 Cs of teamwork. Results Fourteen providers participated, including primary care providers and staff. Organizational-level conditions, such as time, staff availability, and materials appeared to bar successful CRCS. Interestingly, several team-level factors, such as communication and coordination, reportedly served to facilitate CRCS when staffing was sufficient. Cognitions within clinic teams were good; however, several barriers to shared cognition were noted when clinicians interfaced with patients. Additionally, patient-level characteristics were noted to impede collaborative work in CRCS completion. Discussion Teamwork facilitates CRCS; however, several organizational conditions impede CRCS completion. Needs arose for including the patient in shared decision making as well as the pros and cons of coordination via EHR. Conclusions Multi-level drivers to successful CRCS were identified at the individual, team, and organizational level. Interventions seeking to improve CRCS should target identified levels in clinics serving persistently impoverished patient populations.
Background Perfusionists manage critical physiological parameters of cardiac surgery patients during cardiopulmonary bypass (CPB), requiring rapid, high-stakes decision-making under uncertainty. While artificial intelligence (AI) has the potential to enhance perfusionists’ decision-making and improve patient safety, there is limited understanding of how future AI-enabled clinical decision support systems (CDSS) should be designed to align with perfusionists’ workflows and cognitive demands. Objective This study aims to identify human-centered design requirements for CDSS in cardiac perfusion and to conduct a formative evaluation of a prototype interface presenting simulated decision-support recommendations. Methods A three-phase, multiple-method qualitative study was conducted with eight practicing perfusionists. Phase 1 involved semi-structured interviews to characterize workflow challenges and design requirements. Phase 2 engaged participants in structured prototype-feedback sessions to refine an interface concept for future AI-enabled decision support. Phase 3 assessed interface usability using scenario-based tasks with simulated AI recommendations designed by clinical experts and measured task success and exploratory self-reported perceptions. Results Overall, perfusionists expressed positive perceptions of future AI-enabled CDSS concepts but emphasized the need to retain human control and receive contextually relevant explanations. Among three explanation formats evaluated, decision trees emerged as the most preferred explanation format across the study participants. In usability testing, participants achieved an 84% task success rate, reported positive perceptions of the prototype and perceived compatibility with perfusion workflows. Conclusion This work contributes empirically grounded design requirements for future AI-enabled CDSS in safety-critical intraoperative settings. Key design considerations include: (1) prioritizing interpretable explanations (such as decision trees), (2) ensuring system recommendations align with perfusionists’ reported monitoring strategies, and (3) preserving clinician oversight through human-in-the-loop design frameworks.
Objective To demonstrate a novel application of macroergonomic theory to guide qualitative naturalistic observation for examining complex healthcare work systems. Background Community pharmacies have evolved from strictly dispensing sites to multifaceted healthcare environments with growing integration of clinical services. Despite this shift, pharmacy workflows are often conceptualized as standardized linear processes. Prior research has frequently relied on pharmacy staff retrospective self-reporting of their daily tasks, which may overlook real-time workflow dynamics such as interruptions, multitasking, and environmental constraints. Macroergonomics offers a systems-oriented framework for examining interactions among people, tasks, and organizational factors that can assist in structuring qualitative observational research in community pharmacy settings. Method This study applied an adapted Macroergonomic Analysis and Design (MEAD) 10-step model to guide iterative qualitative observations across six community pharmacies in Wisconsin. Two trained researchers conducted three six-hour observation sessions at each site. Observations progressed through three cycles, moving from a broad assessment of the pharmacy work system to focused examination of two micro-level workflows: prescription dispensing and non-dispensing activities. Analytic pauses between observations aligned with MEAD principles to identify workflow unit operations, variances, and control mechanisms. Results Observations revealed prescription dispensing as the foundational workflow within community pharmacies, with other activities layered onto it. Frequent interruptions, multitasking, and task-switching were observed across sites. Non-dispensing services, including vaccination and medication management activities, were integrated informally into existing workflows, contributing to workflow bottlenecks and role ambiguity. Conclusion Using macroergonomic theory to structure qualitative observation provided a systematic approach for capturing the complexity and variability of pharmacy work systems in situ. Application This approach offers human factors researchers a theory-driven method for conducting qualitative observations that capture real-world work system dynamics and support context-sensitive healthcare workflow research. Funding This work was supported by the Agency for Healthcare Research and Quality (grant number R18HS029608)
Background: Obstructive sleep apnea (OSA) is characterized by repeated airway obstruction and associated oxygen desaturation during sleep. Positive airway pressure remains the most common treatment, but some patients use non–positive airway pressure (non-PAP) therapies such as positional devices and oral appliances. Unlike PAP devices, these therapies do not typically provide ongoing physiologic feedback. This lack of feedback can make it difficult for patients to understand their nightly physiology between sleep studies. While consumer-grade wearables are not intended to diagnose OSA, they offer an opportunity to design patient-facing tools that support access to and interpretation of peripheral oxygen saturation (SpO₂) data for self-management and treatment decision-making. Methods: This clinical demonstration project developed and iteratively refined a workflow for generating a weekly report that combined smartwatch-derived SpO₂ data with self-reported sleep-related outcomes for patients using non-PAP OSA therapies. Patients viewed a weekly electronic report on their own and again with a clinician at program completion. Report content and implementation procedures were adjusted through a series of Plan–Do–Study–Act cycles, with emphasis on reducing information complexity and supporting patient sensemaking. Think-aloud interviews with a subset of patients explored how they interpreted and used the report. Post-program survey data were summarized descriptively, and interview notes were reviewed to identify report-related interpretive challenges and guide iterative refinement. Results: Of the 17 patients who enrolled, 16 completed the program and 15 completed the post-program survey. At least 70% of respondents agreed that the program was feasible, acceptable, and appropriate. The System Usability Scale score was 75.8, indicating above-average usability. The Net Promoter Score was 64, suggesting willingness to recommend the program. Most respondents (≥85%) reported that “at least some effort” was made to engage them in shared decision-making during the clinician review session. Think-aloud interviews indicated that patients who were interviewed found the report helpful for making sense of their data and preferred side-by-side visualizations of higher (≥93%) and lower (<93%) SpO₂ levels, which informed revisions to simplify and clarify the report. Conclusion: Incorporating consumer-grade smartwatch SpO₂ data into a structured, patient-facing weekly report appears to be a feasible and acceptable way to complement OSA care for patients using non-PAP therapies.
Background: Robust anthropometric data, particularly hand size measurements, are imperative to ensuring biomedical devices are ergonomically appropriate. Anthropometric data applied to device design should be representative of the end-user group. Methods: A systematic review was conducted in October 2025 following the PRISMA guidelines to investigate hand anthropometry and stature data relevant to the design of interventional device interfaces used by interventional proceduralists. Literature searches were performed across Scopus, Web of Science, PubMed, and Google Scholar. Two independent reviewers conducted title and abstract screening. Full-text review and data extraction were carried out by one reviewer and cross-verified. Data extracted during the review were compared to ANSUR I, an anthropometric survey of military personnel often referenced in medical device design when population specific data are unavailable. Results: The review protocol was registered with PROSPERO (CRD420251177788) and risk of bias assessed using the CASP checklist. An initial search identified 205 citations, with 67 studies eligible for full-text review and 14 included in the final analysis. Hand length was the most common hand measurement gathered, ranging from 169.5 mm to 190.7 mm. Statistically significant differences in stature, and hand length measurements were identified between interventional proceduralists and military data from ANSUR I (p < 0.001). Conclusions: This review sought hand anthropometric data of interventional proceduralists and uncovered heterogeneity in terms of specific data measurements and metrics reported in included studies. Anthropometric differences in hand dimensions and stature between interventional proceduralists and the ANSUR I military dataset were identified. The review highlights a lack of comprehensive data on hand anthropometry of interventional proceduralists.
Silicone breast prostheses are the most common type used for mastectomy in patients who do not undergo breast reconstruction surgery. This study examined mastectomy patients' experiences with silicone breast prostheses and identified limitations that could be addressed with alternative solutions, such as bespoke 3D printed solutions. A questionnaire was completed by 36 mastectomy patients using silicone prostheses. The survey assessed the impact of current prostheses on body image, satisfaction with current prostheses, and design preferences for custom prostheses.While prostheses helped restore body image for many, 53% (n=18) of participants reported problems with the weight and movement of the prosthesis in the bra being a common issue. 29% (n=10) felt that their prosthesis restricted their clothing choices, and 25% (n=9) discontinued certain activities due to their prosthesis. For the bespoke breast prostheses design, 62% (n=21) desired lighter prostheses, 97% (n=33) wanted skin tone matching, and 54% (n=19) prioritized symmetry over comfort. Standard silicone prostheses do not fully meet all patient needs regarding weight, stability, and customization. There is an opportunity to improve prostheses design through 3D printing to create lighter, personalized options that enhance the comfort, appearance, and quality of life of patients.
Background As with many other parts of Canada, New Brunswick (NB) has experienced rapid demographic growth driven by immigration, with many newcomers arriving from regions with healthcare systems that differ significantly from Canada's. Understanding healthcare utilization patterns among immigrant populations is important not only for service planning but also for assessing how healthcare system design supports access, navigation, and use within an increasingly diverse population. Purpose This study examines and compares healthcare utilization patterns among newcomers (defined to be non-Canadian-born, residing in NB <5 years), longer-term immigrants (non-Canadian-born, >= 5 years), and non-immigrants (Canadian-born or interprovincial migrants), interpreting observed differences as indicators of how different user groups access and navigate a complex healthcare socio-technical system. Methods A retrospective cohort study (2017-2021) was conducted using linked Provincial administrative and Federal immigration data accessed through the New Brunswick Institute for Research, Data, and Training. Age-standardized utilization rates per 100 individuals were calculated for four domains: walk-in clinic visits, general practitioner (GP) visits, emergency department (ED) visits, and hospital admissions. Adjusted logistic regression models controlled for age, sex, health zone, socioeconomic status, and length of residence. Results Newcomers demonstrated higher use of walk-in clinics and lower use of GP and ED than non-immigrants, particularly in their early years of residence. Over time, utilization patterns shifted toward greater engagement with GP services and reduced reliance on episodic care services, suggesting gradual integration into primary care pathways. Refugees consistently demonstrated the highest ED visit rates, while international students and temporary foreign workers (TFWs) exhibited the lowest overall engagement, indicating potential underutilization and/or unmet needs. Conclusions Healthcare utilization patterns in NB varied by immigration status and duration of residence, reflecting differences in how population groups interact with available care pathways. The observed reliance of episodic care among some newcomer groups suggests misalignment between healthcare system design and user needs during early settlement. Addressing these patterns requires culturally responsive, equity-oriented care models, and system-level design interventions that better align healthcare structures, access pathways, and organizational workflows with the needs of diverse user groups.
Embedded clinical human factors (HF) practitioners have started to bring systems engineering and human centered organizational principles into healthcare, and patient care environments present a variety of unique challenges for practitioners transitioning into hospitals. Here we provide a collection of insights and suggestions for success for clinically embedded HF practitioners. We discuss the demanding aspects of healthcare work, the importance of establishing collaborative relationships with clinicians and care teams, and how to demonstrate value through systems thinking to ease the transition of the next generation of HF practitioners into healthcare.
Disruptive behavior in the operating room (OR) poses risks to team performance and patient safety. Paradoxically, traits that are often associated with surgical excellence, like confidence, decisiveness, and strong professional identity, may, within high pressure and hierarchical environments, also manifest destructive behaviors that undermine performance and teamwork. In this viewpoint, we examine the paradox of surgical excellence through a human factors lens, proposing that interactions between leadership culture, authority dynamics, and systems pressures may influence disruptive behaviors. We explore the impact of disruptive behaviors on OR dynamics and highlight opportunities for systems-level strategies to mitigate these risks, including fostering psychological safety, enhancing team resilience, and designing organizational structures that support leadership behaviors. This viewpoint aims to stimulate dialog and future empirical investigation while encouraging healthcare system designs that support surgical mastery and high-performing teams.
Background: Participation in digital health programs often depends on successful setup and early use of digital tools, yet individuals with lower digital familiarity may encounter barriers during virtual onboarding. To support engagement in Closing The Loop (CTL), a virtual self-management program for type 2 diabetes (T2D), we developed and refined a structured approach to remote setup of devices and mobile applications. This paper describes the onboarding process, the barriers encountered during virtual setup, and how these observations informed a more systematic workflow for guided setup, troubleshooting, and verification of data-sharing during early program use. Methods: Individuals with T2D receiving care at the VA Connecticut Healthcare System were mailed a smart-watch and user guide before a scheduled virtual onboarding session. During onboarding, participants configured devices and mobile applications required for program participation. Participants completed a survey assessing demographic characteristics and self-reported digital health literacy using the eHealth Literacy Scale (eHEALS). Field notes from onboarding sessions were synthesized into case summaries to characterize onboarding experiences, identify common barriers, and inform iterative refinement of a more structured onboarding workflow. Results: All 12 participants completed onboarding. Participants were 25% women, and 59% were aged 60 years or older. Common onboarding barriers included device syncing, application permissions, difficulty locating downloaded applications, and inaccessible accounts. Session duration ranged from under 20 minutes to over 60 minutes, with two-thirds of participants completing onboarding in 20 to 60 minutes. Case summaries suggested that participants with lower self-reported digital health literacy generally required more stepwise guidance and longer onboarding sessions. Observations from these sessions informed refinement of the onboarding process into the Structured Onboarding Session (SOS) and TechList, a more systematic workflow for guided setup, troubleshooting, and verification of data-sharing during early program use. Discussion: This quality improvement project identified recurring barriers encountered during remote onboarding and informed development of a more systematic workflow for early setup of digital health tools. Findings underscore the importance of anticipatory troubleshooting, structured branching, and verification of actual data flow or task completion rather than installation alone. Conclusion: The SOS and TechList formalize onboarding as a structured implementation component within a virtual T2D self-management program. The resulting workflow may offer transferable design principles for digital health interventions that require device setup, account creation, data-sharing, or coordination across multiple apps and platforms.
As artificial intelligence (AI) becomes increasingly embedded in critical care settings, there is a pressing need to understand how these technologies interact with human teams responsible for high-stakes decision-making. This paper introduces a tailored Input-Mediator-Output-Input (IMOI) model to conceptualize the complex, cyclical dynamics of human-AI teaming in environments such as intensive care units and emergency departments. Building on principles from team science and information processing theory, the model identifies key inputs (e.g., AI capabilities, team composition, interface design), mediators (e.g., trust, communication, coordination), and outputs (e.g., team performance, patient outcomes), while accounting for moderating factors like clinician experience, stress, and AI transparency. A critical feature of the model is its feedback loop, through which outcomes inform future team behaviors, training, and system redesign. The paper outlines practical applications for healthcare training, AI system design, and simulation-based evaluation, offering a comprehensive roadmap for integrating AI as an adaptive, trustworthy member of clinical teams. Importantly, this model is conceptual and has not yet been empirically validated; it is intended to serve as a foundation for future empirical research. This model supports ongoing quality improvement initiatives and promotes safer, more effective human-AI collaboration in time-sensitive, high-pressure care environments.
Background Parkinson’s disease is becoming one of the fastest-growing neurological diseases worldwide, placing significant financial, physical, and emotional burden on patients and caregivers. Wearable monitoring technologies have the potential to improve care, but existing devices are often at a high price point or assume high health literacy, limiting adoption. Objective Evaluate how a human-centered design framework can inform the development of wearable health technologies for Parkinson’s disease management in Kazakhstan. Method We held a stakeholder workshop in Almaty, Kazakhstan, with patients, caregivers, clinicians, and university students (n=21). Participants completed pre- and post- surveys measuring confidence and knowledge of Parkinson’s disease and dysphagia. The workshop included educational sessions and facilitated group discussions. Quantitative data was analyzed descriptively, and qualitative feedback was analyzed using descriptive qualitative pattern and frequency analysis supported by Python. Results Post-workshop surveys illustrated increased confidence in recognizing symptoms, understanding impacts on quality of life, and discussing Parkinson’s disease. Qualitative findings highlighted affordability, usability, and cultural sensitivity as key priorities. Conclusion A human-centered approach can reduce stigma, improve adoption, and warrant equitable access to wearable health technologies for Parkinson's disease management across diverse healthcare systems. Application This study demonstrated how participatory methods can guide equitable design of health monitoring wearable devices. The findings offer transferable insights to researchers, clinicians, and designers seeking to improve adoption and impact of health technologies in under-resourced settings.
Filipino nurses are highly regarded for their strong clinical skills and commitment to patient care, but they face challenges in traditional hospital settings including dissatisfaction with benefits, salary, and working conditions. As a reflection, many Filipino nurses transitioned to telemedicine in the healthcare business process outsourcing (BPO) industry. This study investigated nurses’ career satisfaction and growth in BPO telemedicine by analyzing the motivating factors such as achievement, compensation, responsibility, and advancement in the Philippines. To achieve this, 309 responses were gathered from nurses working in various healthcare BPO companies using a 5-point Likert Scale with agreeable statements, and the survey was disseminated through online platforms. The study employed a neutral network approach, integrating the artificial neural network (ANN) and long short-term memory (LSTM) ensemble as a decision support system to forecast factors affecting career growth. Career advancement was the highest predictor of career growth, followed by job responsibility, achievement, satisfaction, and least important is compensation. A forecasted average score ranging from 4 to 4.5 (strongly agree) was generated, implicating a high level of perceived career growth. This suggests that the BPO industry provides sufficient opportunities for professional development among nurses. Moreover, this positive outlook indicates the potential of the BPO sector as a helpful environment for nurturing and advancing nursing careers, fostering growth and fulfillment within the profession. The results of the study can also serve as a guide for BPO companies to address areas for improvement in career advancement opportunities and create a supportive work environment. Further theoretical and practical implications have been made for application and study extension.
