JMIR Human Factors最新文献

Background: Access to safe abortion care is a reproductive right for all individuals across Canada. Underserved populations are overrepresented among those with unintended pregnancies and particularly those seeking abortion. Yet, few resources exist to help health care and allied helping professionals provide culturally competent and gender-affirming abortion care to such a population group.

Objective: This project aimed to redesign and adapt an existing subscription-based medication abortion mentorship platform into a culturally appropriate and gender-affirming open-access website of curated health professional resources to promote equitable, accessible, high-quality abortion care, particularly for underserved populations.

Methods: We drew on a user-centered design framework to redesign the web platform in 5 iterative phases. Health care and allied helping professionals were engaged in each stage of the development process including the initial design of the platform, curation of the resources, review of the content, and evaluation of the wireframes and the end product.

Results: This project resulted in an open-access bilingual (English and French) web-based platform containing comprehensive information and resources on abortion care for health care providers (physicians, nurse practitioners, and pharmacists) and allied helping professionals (midwives, medical officers, community workers, and social workers). The website incorporated information on clinical, logistical, and administrative guidance, including culturally competent and gender-affirming toolkits that could equip health care professionals with the requisite knowledge to provide abortion care for underserved populations.

Conclusions: This platform contains resources that can increase the competencies of health care professionals to initiate and sustain culturally and contextually appropriate abortion care for underserved groups while clarifying myths and misconceptions that often militate against initiating abortion. Our resource also has the potential to support equitable access to high-quality abortion care, particularly for those among underserved populations who may have the greatest unmet need for abortion services yet face the greatest barriers to accessing care.

Background: The opaque nature of artificial intelligence (AI) algorithms has led to distrust in medical contexts, particularly in the treatment and monitoring of atrial fibrillation. Although previous studies in explainable AI have demonstrated potential to address this issue, they often focus solely on electrocardiography graphs and lack real-world field insights.

Objective: We addressed this gap by incorporating standardized clinical interpretation of electrocardiography graphs into the system and collaborating with cardiologists to co-design and evaluate this approach using real-world patient cases and data.

Methods: We conducted a 3-stage iterative design process with 23 cardiologists to co-design, evaluate, and pilot an explainable AI application. In the first stage, we identified 4 physician personas and 7 explainability strategies, which were reviewed in the second stage. A total of 4 strategies were deemed highly effective and feasible for pilot deployment. On the basis of these strategies, we developed a progressive web application and tested it with cardiologists in the third stage.

Results: The final progressive web application prototype received above-average user experience evaluations and effectively motivated physicians to adopt it owing to its ease of use, reliable information, and explainable functionality. In addition, we gathered in-depth field insights from cardiologists who used the system in clinical contexts.

Conclusions: Our study identified effective explainability strategies, emphasized the importance of curating actionable features and setting accurate expectations, and suggested that many of these insights could apply to other disease care contexts, paving the way for future real-world clinical evaluations.

Background: The accuracy of the ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) procedure coding system (PCS) is crucial for generating correct Taiwan diagnosis-related groups (DRGs), as coding errors can lead to financial losses for hospitals.

Objective: The study aimed to determine the consistency between an artificial intelligence (AI)-assisted coding module and manual coding, as well as to identify clinical specialties suitable for implementing the developed AI-assisted coding module.

Methods: This study examined the AI-assisted coding module from the perspective of health care professionals. The research period started in February 2023. The study excluded cases outside of Taiwan DRGs, those with incomplete medical records, and cases with Taiwan DRG disposals ICD-10 (International Statistical Classification of Diseases, Tenth Revision) PCS. Data collection was conducted through retrospective medical record review. The AI-assisted module was constructed using a hierarchical attention network. The verification of the Taiwan DRGs results from the AI-assisted coding model focused on the major diagnostic categories (MDCs). Statistical computations were conducted using SPSS version 19. Research variables consisted of categorical variables represented by MDC, and continuous variables were represented by the relative weight of Taiwan DRGs.

Results: A total of 2632 discharge records meeting the research criteria were collected from February to April 2023. In terms of inferential statistics, κ statistics were used for MDC analysis. The infectious and parasitic diseases MDC, as well as the respiratory diseases MDC had κ values exceeding 0.8. Clinical inpatient specialties were statistically analyzed using the Wilcoxon signed rank test. There was not a difference in coding results between the 23 clinical departments, such as the Division of Cardiology, the Division of Nephrology, and the Department of Urology.

Conclusions: For human coders, with the assistance of the ICD-10-CM AI-assisted coding system, work time is reduced. Additionally, strengthening knowledge in clinical documentation enables human coders to maximize their role. This positions them to become clinical documentation experts, preparing them for further career development. Future research will apply the same method to validate the ICD-10 AI-assisted coding module.

Background: With the increasing prevalence of digital technology, adolescent internet addiction (IA) has become a global concern. Excessive internet use, especially among adolescents, has been linked to various negative outcomes such as poor academic performance, social isolation, and mental health issues. Conducted among adolescents of Arab origin, our study addressed the limitations of the literature, which predominantly focuses on Western, educated, industrialized, rich, and democratic populations.

Objective: This study aimed to differentiate between essential and nonessential internet use and how they relate to IA in early and middle adolescents, as well as the relationship between subjective happiness with the amount of time spent on nonessential internet use and IA.

Methods: A cross-sectional survey was conducted among 377 students from 16 schools in Qatar. The survey measured essential and nonessential internet use, subjective happiness with nonessential use, and IA symptoms using the Internet Addiction Diagnostic Questionnaire, as well as participant demographics. To explore age-specific associations, participants were categorized into early (age 11-13 years) and middle (age 14-17 years) adolescents. Factorial analysis, multiple regression, and logistic regression were used for statistical analysis.

Results: Nonessential internet use significantly predicted IA in both early (P<.001) and middle (P<.001) adolescents, with early adolescents showing a stronger association. Subjective happiness with nonessential internet use negatively predicted IA only in middle adolescents (P<.001) as greater dissatisfaction led to a higher IA risk. Essential internet use did not predict IA in either group.

Conclusions: Differentiating between essential and nonessential internet use is crucial in understanding IA. This study highlights the importance of developmental differences in shaping IA symptoms. The findings suggest that interventions aimed at addressing IA should be age specific and focus on addressing nonessential use specifically rather than considering internet use and screen time in general as a single entity. Cultural and regional factors also play a role in shaping internet use patterns and IA in the Middle East, necessitating context-specific, culturally sensitive approaches to IA prevention.

Background: Repeated applications of short-term dietary assessment instruments are recommended for estimating usual dietary intake. For this purpose, NutriDiary, a smartphone app for collecting weighed dietary records (WDRs) in the German population, was developed.

Objective: We aim to describe NutriDiary and evaluate its usability and acceptability.

Methods: NutriDiary was developed as a WDR, allowing users to enter food items via text search, barcode scanning, or free text entry. The sample for the evaluation study included 74 participants (n=51, 69% female, aged 18-64 years), including 27 (37.5%) experts and 47 (63.5%) laypersons (including n=22, 30%, nutrition students). Participants completed a 1-day WDR and entered a predefined sample meal (n=17 foods) the following day by using NutriDiary. An evaluation questionnaire was answered from which the system usability scale (SUS) score (0-100) was calculated. A backward selection procedure (PROC REG in SAS; SAS Institute) was used to identify potential predictors for the SUS score (age, sex, status [expert or laypersons], and operating system [iOS or Android]).

Results: The median SUS score of 75 (IQR 63-88) indicated good usability. Age was the only characteristic identified as a potential predictor for a lower SUS score (P<.001). The median completion time for an individual WDR was 35 (IQR 19-52) minutes. Older participants took longer to enter the data than younger ones (18-30 y: median 1.5, IQR 1.1-2.0 min/item vs 45-64 y: median 1.8, IQR 1.3-2.3 min/item). Most participants expressed a preference for NutriDiary over the traditional paper-based method.

Conclusions: Good usability and acceptability make NutriDiary promising for use in epidemiological studies.

Background: The literature around the safety of digital mental health interventions (DMHIs) is growing. However, the user/patient perspective is still absent from it. Understanding the user/patient perspective can ensure that professionals address issues that are significant to users/patients and help direct future research in the field.

Objective: This qualitative study aims to explore DMHI users' experiences, views, concerns, and suggestions regarding the safety of DMHIs.

Methods: We included individuals aged 18 years old or older, having experience in using a DMHI, and can speak and understand English without the need for a translator. Fifteen individual interviews were conducted. Deductive thematic analysis was used to analyze the data.

Results: The analysis of the interview transcripts yielded 3 main themes: Nonresponse: A Concern, a Risk, and How Users Mitigate It, Symptom Deterioration and Its Management, and Concerns Around Data Privacy and How to Mitigate Them.

Conclusions: The results of this study led to 7 recommendations on how the safety of DMHIs can be improved: provide "easy access" versions of key information, use "approved by..." badges, anticipate and support deterioration, provide real-time feedback, acknowledge the lack of personalization, responsibly manage access, and provide genuine crisis support. These recommendations arose from users' experiences and suggestions. If implemented, these recommendations can improve the safety of DMHIs and enhance users' experience.

Background: Rhinolaryngoscopes are one of the most widely used tools by otolaryngologists and speech-language pathologists in current clinical practice. However, there is limited data on adverse events associated with or caused by the use of rhinolaryngoscopes.

Objective: In this study, we used the Manufacturer and User Facility Device Experience (MAUDE) database with the aim of providing insights that may assist otolaryngologists in better understanding the limitations of these devices and selecting appropriate procedures for their specific clinical setting.

Methods: We characterized complications associated with the postmarket use of rhinolaryngoscope devices from the US Food and Drug Administration MAUDE database from 2016 through 2023.

Results: A total of 2591 reports were identified, including 2534 device malfunctions, 56 injuries, and 1 death, from 2016 through 2023. The most common device problem with rhinolaryngoscopes was breakage (n=1058 reports, 40.8%), followed by fluid leaks (n=632 reports, 24.4%). The third most common problem was poor image quality (n=467 reports, 18%). Other device issues included contamination or device reprocessing problems (n=127 reports, 4.9%), material deformation or wear (n=125 reports, 4.8%), and device detachment (n=73 reports, 2.8%). Of the 63 reported adverse events, the most common patient-related adverse event was hemorrhage or bleeding, accounting for 18 reports, with the root causes including material deformation or wear, breakage, wrinkled rubber, or improper operation.

Conclusions: Our study offers valuable insights for endoscopists and manufacturers to recognize potential issues and adverse events associated with the use of rhinolaryngoscopes. It emphasizes the need for improving device reliability, training, and procedural protocols to enhance patient safety during diagnostic procedures.