Search Articles

View query in Help articles search

Search Results (1 to 10 of 157 Results)

Download search results: CSV END BibTex RIS


Development of a System for Predicting Hospitalization Time for Patients With Traumatic Brain Injury Based on Machine Learning Algorithms: User-Centered Design Case Study

Development of a System for Predicting Hospitalization Time for Patients With Traumatic Brain Injury Based on Machine Learning Algorithms: User-Centered Design Case Study

A total of 88 doctors and nurses from the First Affiliated Hospital of Anhui Medical University and the Second Affiliated Hospital of Anhui Medical University participated in the questionnaire. We set the following questions to assess health care workers’ satisfaction with the system: Have you learned about and used our newly developed system for predicting length of stay for patients with TBI? How well do you think the system supports clinical decision-making?

Huan Zhou, Cheng Fang, Yifeng Pan

JMIR Hum Factors 2024;11:e62866

Use of Web-Based Surveys to Collect Long-Term Pediatric Outcomes in Patients With Twin-Twin Transfusion Syndrome Treated With Fetoscopic Laser Photocoagulation: Observational Study

Use of Web-Based Surveys to Collect Long-Term Pediatric Outcomes in Patients With Twin-Twin Transfusion Syndrome Treated With Fetoscopic Laser Photocoagulation: Observational Study

Does not include the consent questionnaire, which was distributed to all eligible patients via email through REDCap and used the REDCap e-consent framework. b CSQ: child status questionnaire. c Age corrected for prematurity until 24 months of age. d N/A: not applicable. e FCQ: fetal center questionnaire. f ASQ-3: Ages & Stages Questionnaires, Third Edition g M-CHAT-R/F: Modified Checklist for Autism in Toddlers, Revised With Follow-Up. h TYQ: Thank You Questionnaire.

Eric Bergh, Kimberly Rennie, Jimmy Espinoza, Anthony Johnson, Ramesha Papanna

JMIR Pediatr Parent 2024;7:e60039

Measurement of Daily Actions Associated With Mental Health Using the Things You Do Questionnaire–15-Item: Questionnaire Development and Validation Study

Measurement of Daily Actions Associated With Mental Health Using the Things You Do Questionnaire–15-Item: Questionnaire Development and Validation Study

As a result of the aforementioned study, a questionnaire including the 21 daily actions was developed, which comprised the 5 factors. The Things You Do Questionnaire (TYDQ)–21-item (TYDQ21) was found to be psychometrically valid and reliable, and higher scores on the TYDQ21 were associated with lower depression and anxiety symptoms in subsequent studies using treatment-seeking samples [17,18].

Madelyne A Bisby, Michael P Jones, Lauren Staples, Blake Dear, Nickolai Titov

JMIR Form Res 2024;8:e57804

An e-Learning Course to Train General Practitioners in Planetary Health: Pilot Intervention Study

An e-Learning Course to Train General Practitioners in Planetary Health: Pilot Intervention Study

The study design included a preintervention questionnaire, the PCEH course, and the postintervention questionnaire completed immediately after the intervention. An email was sent to the potential participants, inviting them to identify themselves on Moodle, the learning management system of the University of Montpellier. The average duration of the PH module was estimated to be between 30 and 45 minutes. The questionnaire took between 3 and 5 minutes to complete.

Cédric Tourrette, Jean-Baptiste Tostain, Eva Kozub, Maha Badreddine, Julia James, Aurore Noraz, Charlotte De Choudens, Lionel Moulis, Claire Duflos, Francois Carbonnel

JMIR Form Res 2024;8:e56138

The Primary Care and Environmental Health e-Learning Course to Integrate Environmental Health in General Practice: Before-and-After Feasibility Study

The Primary Care and Environmental Health e-Learning Course to Integrate Environmental Health in General Practice: Before-and-After Feasibility Study

These questionnaires were created by the author team given the lack of an existing validated questionnaire for this population in this study context. The posttest questionnaire was available if all 3 first learning modules were completed, as the fourth module (Communication) had been supplied late and was not required to answer the questions.

Jean-Baptiste Tostain, Marina Mathieu, Agnès Oude Engberink, Bernard Clary, Michel Amouyal, Béatrice Lognos, Pascal Demoly, Isabella Annesi-Maesano, Grégory Ninot, Nicolas Molinari, Arnaud Richard, Maha Badreddine, Claire Duflos, Francois Carbonnel

JMIR Form Res 2024;8:e56130

Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

One approach is to develop stress prediction models using data related to stress collected by wearable devices that measure parameters such as heart rate variability [9], physical activity [10], and sleep [11], as well as through questionnaire responses that provide insights into physical activity [12] (eg, outings), absenteeism (failure to report for scheduled work), and the number of times lunch is missed [13].

Hiroki Iwamoto, Saki Nakano, Ryotaro Tajima, Ryo Kiguchi, Yuki Yoshida, Yoshitake Kitanishi, Yasunori Aoki

JMIR AI 2024;3:e55840

Expectations and Preferences for Digital Cessation Treatment: Multimethods Study Among Older Adults Who Smoke Cigarettes

Expectations and Preferences for Digital Cessation Treatment: Multimethods Study Among Older Adults Who Smoke Cigarettes

Those interested were asked to complete a phone-based screening questionnaire to determine eligibility. Second, patients identified as aged 65+ years were referred by providers from the MUSC Tobacco Treatment Program (ie, pharmacotherapy or behavioral counseling). Eligibility criteria included being aged >65 years and having smoked 5+ cigarettes per day on more days than not in the past month.

Margaret C Fahey, Mathew J Carpenter, Riley O'Neal, Kinsey Pebley, Melissa R Schick, Emily Ware, Benjamin A Toll, Jennifer Dahne

J Med Internet Res 2024;26:e52919

Electronic Health Record-Related Safety Concerns: A Cross-Sectional Survey of Electronic Health Record Users

Electronic Health Record-Related Safety Concerns: A Cross-Sectional Survey of Electronic Health Record Users

Consequently, we used a mixed-methods approach in several phases to develop and validate a questionnaire based on Sittig and Singh’s research and findings [15,16]. The final Finnish questionnaire consisted of eight error types, each with three to six related questions. Future research will focus on developing a tool to mitigate EHR-related safety concerns. Our goal was to study health care professionals’ perceptions of common EHR concerns.

Sari Palojoki, Tuuli Pajunen, Kaija Saranto, Lasse Lehtonen

JMIR Med Inform 2016;4(2):e13

Cookie Consent

We use our own cookies and third-party cookies so that we can show you this website and better understand how you use it, with a view to improving the services we offer. If you continue browsing, we consider that you have accepted the cookies.