JMIR Human Factors最新文献

Background: Remote patient monitoring (RPM) has the potential to reduce in-clinic visits and promote proactive and preventive care for patients with chronic diseases in primary care. However, a decentralized approach to RPM in a primary health care (PHC) setting has not met stakeholders' expectations regarding scalability. This study introduces a centralized virtual ward (CVW)-led RPM, utilizing a multidisciplinary team approach to monitor patients with chronic diseases by clinicians who do not belong to the patients' PHC center.

Objective: This study aimed to gain a better understanding of patients' perceptions of CVW-led RPM for managing chronic diseases in a PHC setting.

Methods: In-depth interviews were conducted with 22 patients with chronic diseases enrolled at a PHC center in Stockholm, Sweden. The RPM project ran between October 2018 and April 2019 and included a total of 395 patients. Interviews followed a semistructured interview guide and were analyzed using qualitative content analysis.

Results: Primary care patients with chronic diseases expressed that their contact with the CVW felt impersonal but at the same time secure and accessible. They noted a lack of coordination and communication between the clinicians of the CVW and their PHC providers. Captured data resulted in 1 overarching theme "Sense of security and accessibility, but impersonal and uncoordinated" based on 5 categories: sense of security, care and self-care, accessibility, quality of care, and communication.

Conclusions: Our findings suggest that by addressing patients' needs for new organizational routines for patient-caregiver communication, RPM via centralized virtual wards can better realize the potential of this technology.

Background: Digital health applications (DiGA) have been integrated into Germany's health care system since 2019, offering certified medical devices for various health conditions. This study focuses on deprexis and Selfapy, the first 2 permanently approved DiGA for depressive disorders in Germany, to evaluate their usability for people ≥60 years. The study's significance is underscored by the underrepresentation of older people in previous DiGA studies, accompanied by an emergent risk of inequalities in distribution for this vulnerable population.

Objective: This study assessed the usability of DiGA deprexis and Selfapy for adults aged ≥60 years with mild to moderate depression. The more user-friendly option will be chosen for the DiGA4Aged project's upcoming randomized controlled trial.

Methods: The prospective observational study uses the People at the Centre of Mobile Application Development (PACMAD) usability model in a mixed methods design. The study's multistage data collection encompasses sociodemographic data and quantitative questionnaires about health literacy (European Health Literacy Survey Questionnaire [HLS-EU-Q16]), electronic health literacy (revised German eHealth Literacy Scale [GR-eHEALS]), media affinity, depressive symptoms (9-item Patient Health Questionnaire [PHQ-9]), and perceived usability (System Usability Scale [SUS]), as well as a qualitative think-aloud and semistructured interview. Participants were equally allocated to use either deprexis or Selfapy. Recruitment of 18 participants was conducted at 3 hospital departments (ie, psychiatry, psychosomatics, and geriatrics) in spring 2024. Participants were eligible if they were aged ≥60 years, were diagnosed with mild or moderate depressive disorder, owned a digital device, and gave written consent to participate.

Results: Quantitative analysis revealed age, gender, depressive severity, and health literacy parity between both groups. Selfapy users displayed marginally lower technical proficiency and lower usability scores. Qualitative data showed lower usability among participants in the Selfapy group due to design-related errors and higher cognitive load. Despite visual, psychomotor, and cognitive challenges, participants endorsed both DiGA for older users, stressing the importance of assistance and practicing the usage.

Conclusions: Reported difficulties in usability may help to improve future DiGA development for older people, especially as the willingness to use DiGA exists.

Background: Subjective report of pain remains the gold standard for assessing symptoms in patients with chronic pain and their response to analgesics. This subjectivity underscores the importance of understanding patients' personal narratives, as they offer an accurate representation of the illness experience.

Objective: In this pilot study involving 20 patients with chronic low back pain (CLBP), we applied emerging tools from natural language processing (NLP) to derive quantitative measures that captured patients' pain narratives.

Methods: Patients' narratives were collected during recorded semistructured interviews in which they spoke about their lives in general and their experiences with CLBP. Given that NLP is a novel approach in this field, our goal was to demonstrate its ability to extract measures that relate to commonly used tools, such as validated pain questionnaires and rating scales, including the numerical rating scale and visual analog scale.

Results: First, we showed that patients' utterances were significantly closer in semantic space to anchor sentences derived from validated pain questionnaires than to their antithetical counterparts. Furthermore, we found that the semantic distances between patients' utterances and anchor sentences related to quality of life were strongly correlated with reported CLBP intensity on the numerical rating and visual analog scales. Consistently, we observed significant differences between individuals with low and high pain levels.

Conclusions: Although our small sample size limits the generalizability of these findings, the results provide preliminary evidence that NLP can be used to quantify the subjective experience of chronic pain and may hold promise for clinical applications.

Background: Within the surgical field, there has been an evolution in the application of robotic technology. Fully automatic robotic systems and augmented visualization tools are being introduced and may eventually replace existing surgical extenders such as the da Vinci surgical system. The literature on public perception of robotic surgery is growing, though specific drivers of these attitudes remain under investigation.

Objective: The aim of this study is to investigate the underlying motivators of public perceptions toward robotic surgeries with varying levels of autonomy through a formal technology acceptance model.

Methods: An online survey was distributed via the Amazon Mechanical Turk platform. Survey participants were provided definitions of a continuum of robotic technologies: robotic surgical extenders (technology without independent actions), semiautonomous robotic surgery (technology that provides guidance to the surgeon and requires surgeon input), and fully autonomous robotic surgery (technology that performs tasks autonomously without direct human interaction). The survey assessed overall attitudes toward each application of robotic technology in surgery and included questions delineating specific receptivity based on (1) perceived usefulness, (2) social risk, (3) time risk, (4) personal risk, and (5) reliability. A technology acceptance model was built to identify associations between these factors and overall attitudes toward robotic and semiautonomous surgeries.

Results: A total of 1221 survey responses were recorded (mean age 38, SD 12 y; females: n=635, 52%). Individuals were more willing to accept robotic surgical extenders and semiautonomous robotic surgery compared to autonomous robotic surgery. Higher levels of education and better self-reported health were correlated with more positive attitudes toward autonomous robotic surgery. Perceptions of these technologies were not associated with age, gender, or income. Overall, attitudes toward robotic technologies in surgery were driven by views on the reliability, safety, and efficiency of the procedures. There was less concern regarding time risk and social risk associated with robotic and semirobotic surgeries.

Conclusions: The public is more accepting of semiautonomous surgery and surgical extenders than fully autonomous surgery. General perceptions of the reliability, safety, and efficiency of these technologies drive variations in attitude. Time and social risk do not appear to have a significant impact on receptivity. Understanding these perspectives can help guide education within an advancing surgical field.

Background: The aging population presents challenges for health care systems. Assistive technologies (ATs), such as telemonitoring, fall detection, and self-monitoring devices, offer potential solutions to support older adults and their care. However, successful implementation relies on their acceptance, which remains poorly understood, particularly among nonusers.

Objective: This study aimed to explore older adults' perceptions of ATs, including perceived benefits, adoption barriers, and factors influencing willingness to use these technologies.

Methods: A qualitative study was conducted with 31 participants (aged ≥65 years) with varying levels of health and care needs. Data were collected through 6 focus groups and 6 in-depth interviews and then analyzed thematically using NVivo software.

Results: A total of 7 themes emerged: (1) limited familiarity, with greater recognition of fall detection and self-monitoring devices compared to telemonitoring; (2) perceived benefits, including safety, independence, and chronic disease management; (3) key concerns, including usability, cost, reliability, privacy, and psychological impacts; (4) suggested improvements, including user-friendly designs and training programs; (5) contextual influences identified with independent older adults perceiving greater utility; (6) strategies for ATs' promotion proposed, such as media campaigns, government subsidies, and health care endorsements; and (7) overall willingness to adopt ATs, driven by perceived need, social and health care influence, and ease of use.

Conclusions: Although ATs offer clear benefits, adoption remains limited due to usability, cost, and psychological concerns. Improving accessibility, training, and integration into traditional health care service delivery may facilitate acceptance and use. Future research should focus on inclusive designs and policy interventions to maximize ATs' potential in aging populations.

Background: Digital health tools such as smartphone apps have the potential to improve supportive cancer care. Although numerous smartphone apps for supportive care are available, few are designed using a user-centered approach. Such an approach is crucial for successful implementation, as it may improve user engagement, usability, and adoption in clinical settings.

Objective: This study aimed to co-design and develop a digital health app for supportive cancer care in collaboration with patients with cancer and health care professionals and to explore factors influencing its future acceptance.

Methods: We conducted a participatory study with the major stakeholders at the University Hospital Zurich. Workshops, individual qualitative interviews, and focus groups were held with health care professionals, survivors of cancer, and patients with cancer. The co-design process was divided into 3 phases: predesign, generative phase, and prototyping. User-centered design methods included scoring cards and think-aloud protocols to co-create design ideas, identify important functionalities, and test usability. Qualitative data were analyzed using thematic analysis.

Results: Patients and health care professionals emphasized the need for a digital health app to improve patient-healthcare professional communication, digitalize supportive care screening and processes, and enhance self-efficacy. The resulting app, OncoSupport+, was co-designed and integrated into the clinical workflow for supportive cancer care. It consists of (1) a patient dashboard to record patient-reported outcome measures and to provide access to personalized supportive care information and contact details, and (2) a nurse dashboard to visualize patient data, which can be used during nursing consultations. Potential facilitators for adoption included ease of use, workflow integration, introduction by health care professionals, and technical support, whereas internet anxiety may be a potential barrier.

Conclusions: Collaborative development with patients and health care professionals is crucial for creating digital health tools that can be implemented successfully. Future research should evaluate the feasibility of long-term implementation and the real-world usability and effectiveness of OncoSupport+ for improving communication, self-efficacy, and quality of life.

[This corrects the article DOI: 10.2196/59558.].