Background: Bystander intervention is a common method to address the ubiquitous issue that is sexual violence across college campuses. Short messages that incentivize bystander intervention behavior can be another tool to fight sexual violence.
Objective: This study aimed to conduct formative research surrounding social norms and bystander barriers to pilot and develop Instagram (Meta) reel-based messages addressing bystander intervention among college students.
Methods: The first step was to conduct a formative survey to identify peer norms and actual behavior of the intended population. Once that data were collected, a mixed methods message pilot was conducted by a survey where participants randomly saw 5 of the 12 messages developed, assessing them for credibility, perceived message effect, and intended audience.
Results: The formative survey was conducted among 195 college students from the same institution, and the pilot test was conducted among 107 college students. The formative survey indicated a discrepancy between perceived peer behavior and actual behavior of the participants in all 3 measures, allowing for the development of normative messaging. The pilot testing indicated the credibility was acceptable (eg, mean 3.94, SD 1.15 on a 5-point scale) as well as the perceived message effect (eg, mean 4.26, SD 0.94 on a 5-point scale). Intended audiences were also identified and reached. Qualitative results indicated that the messages may have lacked credibility, although the quantitative results suggest otherwise.
Conclusions: Participants understood the messages concerned bystander intervention, and perceived message effects results indicated the messages to be effective in assisting bystander intervention engagement by normative messaging. Messages were considered credible and reached the intended audience. The qualitative results provided further insights on how the messages can be adapted before being tested for effects. Future research should focus on further adapting the messages and testing their effects among the studied population.
{"title":"The Development of an Instagram Reel-Based Bystander Intervention Message Among College Students: Formative Survey and Mixed Methods Pilot Study.","authors":"Leticia Couto","doi":"10.2196/66769","DOIUrl":"10.2196/66769","url":null,"abstract":"<p><strong>Background: </strong>Bystander intervention is a common method to address the ubiquitous issue that is sexual violence across college campuses. Short messages that incentivize bystander intervention behavior can be another tool to fight sexual violence.</p><p><strong>Objective: </strong>This study aimed to conduct formative research surrounding social norms and bystander barriers to pilot and develop Instagram (Meta) reel-based messages addressing bystander intervention among college students.</p><p><strong>Methods: </strong>The first step was to conduct a formative survey to identify peer norms and actual behavior of the intended population. Once that data were collected, a mixed methods message pilot was conducted by a survey where participants randomly saw 5 of the 12 messages developed, assessing them for credibility, perceived message effect, and intended audience.</p><p><strong>Results: </strong>The formative survey was conducted among 195 college students from the same institution, and the pilot test was conducted among 107 college students. The formative survey indicated a discrepancy between perceived peer behavior and actual behavior of the participants in all 3 measures, allowing for the development of normative messaging. The pilot testing indicated the credibility was acceptable (eg, mean 3.94, SD 1.15 on a 5-point scale) as well as the perceived message effect (eg, mean 4.26, SD 0.94 on a 5-point scale). Intended audiences were also identified and reached. Qualitative results indicated that the messages may have lacked credibility, although the quantitative results suggest otherwise.</p><p><strong>Conclusions: </strong>Participants understood the messages concerned bystander intervention, and perceived message effects results indicated the messages to be effective in assisting bystander intervention engagement by normative messaging. Messages were considered credible and reached the intended audience. The qualitative results provided further insights on how the messages can be adapted before being tested for effects. Future research should focus on further adapting the messages and testing their effects among the studied population.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e66769"},"PeriodicalIF":2.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11789691/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani
<p><strong>Background: </strong>Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems. However, most previous work has focused on healthy subjects in controlled environments, with limited attention to real-world postoperative pain scenarios. This gap necessitates the development of robust, multimodal approaches capable of addressing the unique challenges associated with assessing pain in clinical settings, where factors like motion artifacts, imbalanced label distribution, and sparse data further complicate pain monitoring.</p><p><strong>Objective: </strong>This study aimed to develop and evaluate a multimodal machine learning-based framework for the objective assessment of pain in postoperative patients in real clinical settings using biosignals such as electrocardiogram, electromyogram, electrodermal activity, and respiration rate (RR) signals.</p><p><strong>Methods: </strong>The iHurt study was conducted on 25 postoperative patients at the University of California, Irvine Medical Center. The study captured multimodal biosignals during light physical activities, with concurrent self-reported pain levels using the Numerical Rating Scale. Data preprocessing involved noise filtering, feature extraction, and combining handcrafted and automatic features through convolutional and long-short-term memory autoencoders. Machine learning classifiers, including support vector machine, random forest, adaptive boosting, and k-nearest neighbors, were trained using weak supervision and minority oversampling to handle sparse and imbalanced pain labels. Pain levels were categorized into baseline and 3 levels of pain intensity (1-3).</p><p><strong>Results: </strong>The multimodal pain recognition models achieved an average balanced accuracy of over 80% across the different pain levels. RR models consistently outperformed other single modalities, particularly for lower pain intensities, while facial muscle activity (electromyogram) was most effective for distinguishing higher pain intensities. Although single-modality models, especially RR, generally provided higher performance compared to multimodal approaches, our multimodal framework still delivered results that surpassed most previous works in terms of overall accuracy.</p><p><strong>Conclusions: </strong>This study presents a novel, multimodal machine learning framework for objective pain recognition in postoperative patients. The results highlight the potential of integrating multiple biosignal modalities for more accurate pain assessment, with particular value in real-world clin
{"title":"Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach.","authors":"Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani","doi":"10.2196/67969","DOIUrl":"10.2196/67969","url":null,"abstract":"<p><strong>Background: </strong>Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems. However, most previous work has focused on healthy subjects in controlled environments, with limited attention to real-world postoperative pain scenarios. This gap necessitates the development of robust, multimodal approaches capable of addressing the unique challenges associated with assessing pain in clinical settings, where factors like motion artifacts, imbalanced label distribution, and sparse data further complicate pain monitoring.</p><p><strong>Objective: </strong>This study aimed to develop and evaluate a multimodal machine learning-based framework for the objective assessment of pain in postoperative patients in real clinical settings using biosignals such as electrocardiogram, electromyogram, electrodermal activity, and respiration rate (RR) signals.</p><p><strong>Methods: </strong>The iHurt study was conducted on 25 postoperative patients at the University of California, Irvine Medical Center. The study captured multimodal biosignals during light physical activities, with concurrent self-reported pain levels using the Numerical Rating Scale. Data preprocessing involved noise filtering, feature extraction, and combining handcrafted and automatic features through convolutional and long-short-term memory autoencoders. Machine learning classifiers, including support vector machine, random forest, adaptive boosting, and k-nearest neighbors, were trained using weak supervision and minority oversampling to handle sparse and imbalanced pain labels. Pain levels were categorized into baseline and 3 levels of pain intensity (1-3).</p><p><strong>Results: </strong>The multimodal pain recognition models achieved an average balanced accuracy of over 80% across the different pain levels. RR models consistently outperformed other single modalities, particularly for lower pain intensities, while facial muscle activity (electromyogram) was most effective for distinguishing higher pain intensities. Although single-modality models, especially RR, generally provided higher performance compared to multimodal approaches, our multimodal framework still delivered results that surpassed most previous works in terms of overall accuracy.</p><p><strong>Conclusions: </strong>This study presents a novel, multimodal machine learning framework for objective pain recognition in postoperative patients. The results highlight the potential of integrating multiple biosignal modalities for more accurate pain assessment, with particular value in real-world clin","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e67969"},"PeriodicalIF":2.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143052434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elizabeth Ak Rowley, Patrick K Mitchell, Duck-Hye Yang, Ned Lewis, Brian E Dixon, Gabriela Vazquez-Benitez, William F Fadel, Inih J Essien, Allison L Naleway, Edward Stenehjem, Toan C Ong, Manjusha Gaglani, Karthik Natarajan, Peter Embi, Ryan E Wiegand, Ruth Link-Gelles, Mark W Tenforde, Bruce Fireman
Background: Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial.
Objective: This simulation study aimed to investigate alternative methods to adjust for confounding in VE studies that have a test-negative design.
Methods: Adjustment for a disease risk score (DRS) is compared with multivariable logistic regression. Both stratification on the DRS and direct covariate adjustment of the DRS are examined. Multivariable logistic regression with all the covariates and with a limited subset of key covariates is considered. The performance of VE estimators is evaluated across a multinomial vaccination exposure in simulated datasets.
Results: Bias in VE estimates from multivariable models ranged from -5.3% to 6.1% across 4 levels of vaccination. Standard errors of VE estimates were unbiased, and 95% coverage probabilities were attained in most scenarios. The lowest coverage in the multivariable scenarios was 93.7% (95% CI 92.2%-95.2%) and occurred in the multivariable model with key covariates, while the highest coverage in the multivariable scenarios was 95.3% (95% CI 94.0%-96.6%) and occurred in the multivariable model with all covariates. Bias in VE estimates from DRS-adjusted models was low, ranging from -2.2% to 4.2%. However, the DRS-adjusted models underestimated the standard errors of VE estimates, with coverage sometimes below the 95% level. The lowest coverage in the DRS scenarios was 87.8% (95% CI 85.8%-89.8%) and occurred in the direct adjustment for the DRS model. The highest coverage in the DRS scenarios was 94.8% (95% CI 93.4%-96.2%) and occurred in the model that stratified on DRS. Although variation in the performance of VE estimates occurred across modeling strategies, variation in performance was also present across exposure groups.
Conclusions: Overall, models using a DRS to adjust for confounding performed adequately but not as well as the multivariable models that adjusted for covariates individually.
{"title":"Methods to Adjust for Confounding in Test-Negative Design COVID-19 Effectiveness Studies: Simulation Study.","authors":"Elizabeth Ak Rowley, Patrick K Mitchell, Duck-Hye Yang, Ned Lewis, Brian E Dixon, Gabriela Vazquez-Benitez, William F Fadel, Inih J Essien, Allison L Naleway, Edward Stenehjem, Toan C Ong, Manjusha Gaglani, Karthik Natarajan, Peter Embi, Ryan E Wiegand, Ruth Link-Gelles, Mark W Tenforde, Bruce Fireman","doi":"10.2196/58981","DOIUrl":"10.2196/58981","url":null,"abstract":"<p><strong>Background: </strong>Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial.</p><p><strong>Objective: </strong>This simulation study aimed to investigate alternative methods to adjust for confounding in VE studies that have a test-negative design.</p><p><strong>Methods: </strong>Adjustment for a disease risk score (DRS) is compared with multivariable logistic regression. Both stratification on the DRS and direct covariate adjustment of the DRS are examined. Multivariable logistic regression with all the covariates and with a limited subset of key covariates is considered. The performance of VE estimators is evaluated across a multinomial vaccination exposure in simulated datasets.</p><p><strong>Results: </strong>Bias in VE estimates from multivariable models ranged from -5.3% to 6.1% across 4 levels of vaccination. Standard errors of VE estimates were unbiased, and 95% coverage probabilities were attained in most scenarios. The lowest coverage in the multivariable scenarios was 93.7% (95% CI 92.2%-95.2%) and occurred in the multivariable model with key covariates, while the highest coverage in the multivariable scenarios was 95.3% (95% CI 94.0%-96.6%) and occurred in the multivariable model with all covariates. Bias in VE estimates from DRS-adjusted models was low, ranging from -2.2% to 4.2%. However, the DRS-adjusted models underestimated the standard errors of VE estimates, with coverage sometimes below the 95% level. The lowest coverage in the DRS scenarios was 87.8% (95% CI 85.8%-89.8%) and occurred in the direct adjustment for the DRS model. The highest coverage in the DRS scenarios was 94.8% (95% CI 93.4%-96.2%) and occurred in the model that stratified on DRS. Although variation in the performance of VE estimates occurred across modeling strategies, variation in performance was also present across exposure groups.</p><p><strong>Conclusions: </strong>Overall, models using a DRS to adjust for confounding performed adequately but not as well as the multivariable models that adjusted for covariates individually.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e58981"},"PeriodicalIF":2.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143052431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Neda Barbazi, Ji Youn Shin, Gurumurthy Hiremath, Carlye Anne Lauff
Background: Congenital heart disease (CHD) is a birth defect of the heart that requires long-term care and often leads to additional health complications. Effective educational strategies are essential for improving health literacy and care outcomes. Despite affecting around 40,000 children annually in the United States, there is a gap in understanding children's health literacy, parental educational burdens, and the efficiency of health care providers in delivering education.
Objective: This qualitative pilot study aims to develop tailored assessment tools to evaluate educational needs and burdens among children with CHD, their parents, and health care providers. These assessments will inform the design of medical education toys to enhance health management and outcomes for pediatric patients with CHD and key stakeholders.
Methods: Through stakeholder feedback from pediatric patients with CHD, parents, and health care providers, we developed three tailored assessments in two phases: (1) iterative development of the assessment tools and (2) pilot testing. In the first phase, we defined key concepts, conducted a literature review, and created initial drafts of the assessments. During the pilot-testing phase, 12 participants were recruited at the M Health Fairview Pediatric Specialty Clinic for Cardiology-Explorer in Minneapolis, Minnesota, United States. We gathered feedback using qualitative methods, including cognitive interviews such as think-aloud techniques, verbal probing, and observations of nonverbal cues. The data were analyzed to identify the strengths and weaknesses of each assessment item and areas for improvement.
Results: The 12 participants included children with CHD (n=5), parents (n=4), and health care providers (n=3). The results showed the feasibility and effectiveness of the tailored assessments. Participants showed high levels of engagement and found the assessment items relevant to their education needs. Iterative revisions based on participant feedback improved the assessments' clarity, relevance, and engagement for all stakeholders, including children with CHD.
Conclusions: This pilot study emphasizes the importance of iterative assessment development, focusing on multistakeholder engagement. The insights gained from the development process will guide the creation of tailored assessments and inform the development of child-led educational interventions for pediatric populations with CHD.
背景：先天性心脏病（CHD）是一种需要长期护理的先天性心脏缺陷，通常会导致其他健康并发症。有效的教育策略对于提高健康素养和护理效果至关重要。尽管美国每年约有 40,000 名儿童受到先天性心脏病的影响，但在了解儿童的健康素养、父母的教育负担以及医疗服务提供者提供教育的效率方面仍存在差距：本定性试点研究旨在开发量身定制的评估工具，以评估患有先天性心脏病的儿童、其父母和医疗服务提供者的教育需求和负担。这些评估将为医学教育玩具的设计提供参考，以提高患有先天性心脏病的儿科患者和主要利益相关者的健康管理水平和治疗效果：通过来自患有先天性心脏病的儿科患者、家长和医疗服务提供者的利益相关者的反馈，我们分两个阶段开发了三种量身定制的评估工具：(1) 评估工具的迭代开发；(2) 试点测试。在第一阶段，我们定义了关键概念，进行了文献综述，并创建了评估初稿。在试点测试阶段，我们在美国明尼苏达州明尼阿波利斯市的 M Health Fairview 儿科专科诊所招募了 12 名心脏病学探索者参与者。我们采用定性方法收集反馈意见，包括认知访谈（如思考-朗读技术）、口头询问和非语言线索观察。我们对数据进行了分析，以确定每个评估项目的优缺点以及需要改进的地方：12 名参与者包括患有先天性心脏病的儿童（5 人）、家长（4 人）和医护人员（3 人）。结果显示，量身定制的评估具有可行性和有效性。参与者的参与度很高，并认为评估项目与他们的教育需求相关。根据参与者的反馈进行的迭代修订提高了评估的清晰度、相关性和所有利益相关者（包括患有慢性阻塞性肺病的儿童）的参与度：这项试点研究强调了迭代式评估开发的重要性，重点是多方利益相关者的参与。从开发过程中获得的启示将指导量身定制的评估，并为针对患有先天性心脏病的儿科人群开发以儿童为主导的教育干预措施提供参考。
{"title":"Developing Assessments for Key Stakeholders in Pediatric Congenital Heart Disease: Qualitative Pilot Study to Inform Designing of a Medical Education Toy.","authors":"Neda Barbazi, Ji Youn Shin, Gurumurthy Hiremath, Carlye Anne Lauff","doi":"10.2196/63818","DOIUrl":"10.2196/63818","url":null,"abstract":"<p><strong>Background: </strong>Congenital heart disease (CHD) is a birth defect of the heart that requires long-term care and often leads to additional health complications. Effective educational strategies are essential for improving health literacy and care outcomes. Despite affecting around 40,000 children annually in the United States, there is a gap in understanding children's health literacy, parental educational burdens, and the efficiency of health care providers in delivering education.</p><p><strong>Objective: </strong>This qualitative pilot study aims to develop tailored assessment tools to evaluate educational needs and burdens among children with CHD, their parents, and health care providers. These assessments will inform the design of medical education toys to enhance health management and outcomes for pediatric patients with CHD and key stakeholders.</p><p><strong>Methods: </strong>Through stakeholder feedback from pediatric patients with CHD, parents, and health care providers, we developed three tailored assessments in two phases: (1) iterative development of the assessment tools and (2) pilot testing. In the first phase, we defined key concepts, conducted a literature review, and created initial drafts of the assessments. During the pilot-testing phase, 12 participants were recruited at the M Health Fairview Pediatric Specialty Clinic for Cardiology-Explorer in Minneapolis, Minnesota, United States. We gathered feedback using qualitative methods, including cognitive interviews such as think-aloud techniques, verbal probing, and observations of nonverbal cues. The data were analyzed to identify the strengths and weaknesses of each assessment item and areas for improvement.</p><p><strong>Results: </strong>The 12 participants included children with CHD (n=5), parents (n=4), and health care providers (n=3). The results showed the feasibility and effectiveness of the tailored assessments. Participants showed high levels of engagement and found the assessment items relevant to their education needs. Iterative revisions based on participant feedback improved the assessments' clarity, relevance, and engagement for all stakeholders, including children with CHD.</p><p><strong>Conclusions: </strong>This pilot study emphasizes the importance of iterative assessment development, focusing on multistakeholder engagement. The insights gained from the development process will guide the creation of tailored assessments and inform the development of child-led educational interventions for pediatric populations with CHD.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e63818"},"PeriodicalIF":2.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143052685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fiona Schürmann, Daniel Westmattelmann, Gerhard Schewe
<p><strong>Background: </strong>Telemedicine is transforming health care by enabling remote diagnosis, consultation, and treatment. Despite rapid adoption during the COVID-19 pandemic, telemedicine uptake among health care professionals (HCPs) remains inconsistent due to perceived risks and lack of tailored policies. Existing studies focus on patient perspectives or general adoption factors, neglecting the complex interplay of contextual variables and trust constructs influencing HCPs' telemedicine adoption. This gap highlights the need for a framework integrating risks, benefits, and trust in telemedicine adoption, while addressing health care's unique dynamics.</p><p><strong>Objective: </strong>This study aimed to adapt and extend the extended valence framework (EVF) to telemedicine, deconstructing factors driving adoption from an HCP perspective. Specifically, it investigated the nuanced roles of perceived risks, benefits, and trust referents (eg, technology, treatment, technology provider, and patient) in shaping behavioral intentions, while integrating contextual factors.</p><p><strong>Methods: </strong>We used a qualitative research design involving semistructured interviews with 14 HCPs experienced in offering video consultations. The interview data were analyzed with deductive and inductive coding based on the EVF. Two coders conducted the coding process independently, achieving an intercoder reliability of 86.14%. The qualitative content analysis aimed to uncover the nuanced perspectives of HCPs, identifying key risk and benefit dimensions and trust referents relevant to telemedicine adoption.</p><p><strong>Results: </strong>The study reveals the complex considerations HCPs have when adopting telemedicine. Perceived risks were multidimensional, including performance risks such as treatment limitations (mentioned by 7/14, 50% of the participants) and reliance on technical proficiency of patients (5/14, 36%), privacy risks related to data security (10/14, 71%), and time and financial risks associated with training (7/14, 50%) and equipment costs (4/14, 29%). Perceived benefits encompassed convenience through reduced travel time (5/14, 36%), improved care quality due to higher accessibility (8/14, 57%), and operational efficiency (7/14, 50%). Trust referents played a pivotal role; trust in technology was linked to functionality (6/14, 43%) and reliability (5/14, 36%), while trust in treatment depended on effective collaboration (9/14, 64%). Transparency emerged as a critical antecedent of trust across different referents, comprising disclosure, clarity, and accuracy. In addition, the study highlighted the importance of context-specific variables such as symptom characteristics (10/14, 71%) and prior professional experience with telemedicine (11/14, 79%).</p><p><strong>Conclusions: </strong>This study expands the EVF for telemedicine, providing a framework integrating multidimensional risks, benefits, trust, and contextual factors. It advanc
{"title":"Factors Influencing Telemedicine Adoption Among Health Care Professionals: Qualitative Interview Study.","authors":"Fiona Schürmann, Daniel Westmattelmann, Gerhard Schewe","doi":"10.2196/54777","DOIUrl":"10.2196/54777","url":null,"abstract":"<p><strong>Background: </strong>Telemedicine is transforming health care by enabling remote diagnosis, consultation, and treatment. Despite rapid adoption during the COVID-19 pandemic, telemedicine uptake among health care professionals (HCPs) remains inconsistent due to perceived risks and lack of tailored policies. Existing studies focus on patient perspectives or general adoption factors, neglecting the complex interplay of contextual variables and trust constructs influencing HCPs' telemedicine adoption. This gap highlights the need for a framework integrating risks, benefits, and trust in telemedicine adoption, while addressing health care's unique dynamics.</p><p><strong>Objective: </strong>This study aimed to adapt and extend the extended valence framework (EVF) to telemedicine, deconstructing factors driving adoption from an HCP perspective. Specifically, it investigated the nuanced roles of perceived risks, benefits, and trust referents (eg, technology, treatment, technology provider, and patient) in shaping behavioral intentions, while integrating contextual factors.</p><p><strong>Methods: </strong>We used a qualitative research design involving semistructured interviews with 14 HCPs experienced in offering video consultations. The interview data were analyzed with deductive and inductive coding based on the EVF. Two coders conducted the coding process independently, achieving an intercoder reliability of 86.14%. The qualitative content analysis aimed to uncover the nuanced perspectives of HCPs, identifying key risk and benefit dimensions and trust referents relevant to telemedicine adoption.</p><p><strong>Results: </strong>The study reveals the complex considerations HCPs have when adopting telemedicine. Perceived risks were multidimensional, including performance risks such as treatment limitations (mentioned by 7/14, 50% of the participants) and reliance on technical proficiency of patients (5/14, 36%), privacy risks related to data security (10/14, 71%), and time and financial risks associated with training (7/14, 50%) and equipment costs (4/14, 29%). Perceived benefits encompassed convenience through reduced travel time (5/14, 36%), improved care quality due to higher accessibility (8/14, 57%), and operational efficiency (7/14, 50%). Trust referents played a pivotal role; trust in technology was linked to functionality (6/14, 43%) and reliability (5/14, 36%), while trust in treatment depended on effective collaboration (9/14, 64%). Transparency emerged as a critical antecedent of trust across different referents, comprising disclosure, clarity, and accuracy. In addition, the study highlighted the importance of context-specific variables such as symptom characteristics (10/14, 71%) and prior professional experience with telemedicine (11/14, 79%).</p><p><strong>Conclusions: </strong>This study expands the EVF for telemedicine, providing a framework integrating multidimensional risks, benefits, trust, and contextual factors. It advanc","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e54777"},"PeriodicalIF":2.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811669/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143051859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Background: </strong>Physician burnout is widespread in health care systems, with harmful consequences on physicians, patients, and health care organizations. Mindfulness training (MT) has proven effective in reducing burnout; however, its time-consuming requirements often pose challenges for physicians who are already struggling with their busy schedules.</p><p><strong>Objective: </strong>This study aimed to design a short and pragmatic digital MT program with input from clinicians specifically to address burnout and to test its efficacy in physicians.</p><p><strong>Methods: </strong>Two separate nonrandomized pilot studies were conducted. In the first study, 27 physicians received the digital MT in a podcast format, while in the second study, 29 physicians and nurse practitioners accessed the same training through a free app-based platform. The main outcome measure was cynicism, one dimension of burnout. The secondary outcome measures were emotional exhaustion (the second dimension of burnout), anxiety, depression, intolerance of uncertainty, empathy (personal distress, perspective taking, and empathic concern subscales), self-compassion, and mindfulness (nonreactivity and nonjudgment subscales). In the second study, worry, sleep disturbances, and difficulties in emotion regulation were also measured. Changes in outcomes were assessed using self-report questionnaires administered before and after the treatment and 1 month later as follow-up.</p><p><strong>Results: </strong>Both studies showed that MT decreased cynicism (posttreatment: 33% reduction; P≤.04; r≥0.41 and follow-up: 33% reduction; P≤.04; r≥0.45), while improvements in emotional exhaustion were observed solely in the first study (25% reduction, P=.02, r=.50 at posttreatment; 25% reduction, P=.008, r=.62 at follow-up). There were also significant reductions in anxiety (P≤.01, r≥0.49 at posttreatment; P≤.01, r≥0.54 at follow-up), intolerance of uncertainty (P≤.03, r≥.57 at posttreatment; P<.001, r≥0.66 at follow-up), and personal distress (P=.03, r=0.43 at posttreatment; P=.03, r=0.46 at follow-up), while increases in self-compassion (P≤.02, r≥0.50 at posttreatment; P≤.006, r≥0.59 at follow-up) and mindfulness (nonreactivity: P≤.001, r≥0.69 at posttreatment; P≤.004, r≥0.58 at follow-up; nonjudgment: P≤.009, r≥0.50 at posttreatment; P≤.03, r≥0.60 at follow-up). In addition, the second study reported significant decreases in worry (P=.04, r=0.40 at posttreatment; P=.006, r=0.58 at follow-up), sleep disturbances (P=.04, r=0.42 at posttreatment; P=.01, r=0.53 at follow-up), and difficulties in emotion regulation (P=.005, r=0.54 at posttreatment; P<.001, r=0.70 at follow-up). However, no changes were observed over time for depression or perspective taking and empathic concern. Finally, both studies revealed significant positive correlations between burnout and anxiety (cynicism: r≥0.38; P≤.04; emotional exhaustion: r≥0.58; P≤.001).</p><p><strong>Conclusions: </strong>To our knowl
{"title":"Digital Mindfulness Training for Burnout Reduction in Physicians: Clinician-Driven Approach.","authors":"Lia Antico, Judson Brewer","doi":"10.2196/63197","DOIUrl":"10.2196/63197","url":null,"abstract":"<p><strong>Background: </strong>Physician burnout is widespread in health care systems, with harmful consequences on physicians, patients, and health care organizations. Mindfulness training (MT) has proven effective in reducing burnout; however, its time-consuming requirements often pose challenges for physicians who are already struggling with their busy schedules.</p><p><strong>Objective: </strong>This study aimed to design a short and pragmatic digital MT program with input from clinicians specifically to address burnout and to test its efficacy in physicians.</p><p><strong>Methods: </strong>Two separate nonrandomized pilot studies were conducted. In the first study, 27 physicians received the digital MT in a podcast format, while in the second study, 29 physicians and nurse practitioners accessed the same training through a free app-based platform. The main outcome measure was cynicism, one dimension of burnout. The secondary outcome measures were emotional exhaustion (the second dimension of burnout), anxiety, depression, intolerance of uncertainty, empathy (personal distress, perspective taking, and empathic concern subscales), self-compassion, and mindfulness (nonreactivity and nonjudgment subscales). In the second study, worry, sleep disturbances, and difficulties in emotion regulation were also measured. Changes in outcomes were assessed using self-report questionnaires administered before and after the treatment and 1 month later as follow-up.</p><p><strong>Results: </strong>Both studies showed that MT decreased cynicism (posttreatment: 33% reduction; P≤.04; r≥0.41 and follow-up: 33% reduction; P≤.04; r≥0.45), while improvements in emotional exhaustion were observed solely in the first study (25% reduction, P=.02, r=.50 at posttreatment; 25% reduction, P=.008, r=.62 at follow-up). There were also significant reductions in anxiety (P≤.01, r≥0.49 at posttreatment; P≤.01, r≥0.54 at follow-up), intolerance of uncertainty (P≤.03, r≥.57 at posttreatment; P<.001, r≥0.66 at follow-up), and personal distress (P=.03, r=0.43 at posttreatment; P=.03, r=0.46 at follow-up), while increases in self-compassion (P≤.02, r≥0.50 at posttreatment; P≤.006, r≥0.59 at follow-up) and mindfulness (nonreactivity: P≤.001, r≥0.69 at posttreatment; P≤.004, r≥0.58 at follow-up; nonjudgment: P≤.009, r≥0.50 at posttreatment; P≤.03, r≥0.60 at follow-up). In addition, the second study reported significant decreases in worry (P=.04, r=0.40 at posttreatment; P=.006, r=0.58 at follow-up), sleep disturbances (P=.04, r=0.42 at posttreatment; P=.01, r=0.53 at follow-up), and difficulties in emotion regulation (P=.005, r=0.54 at posttreatment; P<.001, r=0.70 at follow-up). However, no changes were observed over time for depression or perspective taking and empathic concern. Finally, both studies revealed significant positive correlations between burnout and anxiety (cynicism: r≥0.38; P≤.04; emotional exhaustion: r≥0.58; P≤.001).</p><p><strong>Conclusions: </strong>To our knowl","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e63197"},"PeriodicalIF":2.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11806274/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143033207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Heather McClelland, Rory C O'Connor, Laura Gibson, Donald J MacIntyre
<p><strong>Background: </strong>Suicide is a global health concern. In the United Kingdom, Scotland has the highest suicide rate. Lived experience and suicide prevention stakeholders in Scotland have identified a key gap in suicide prevention activities: the lack of 24-hour peer-driven web-based support for people who are suicidal.</p><p><strong>Objective: </strong>This usability study aimed to evaluate the feasibility, acceptability, utility, and reach of a suicide prevention website (Surviving Suicidal Thoughts) specifically designed to support residents in Scotland who are experiencing suicidal thoughts themselves or suspect or know someone who is experiencing suicidal thoughts. Intended support was delivered through the provision of personal testimony videos of individuals with lived experience.</p><p><strong>Methods: </strong>A peer-driven website was developed specifically to support residents of Scotland experiencing suicidal thoughts. The website included resources (eg, videos from lived experience and written guidance about how to respond to someone who may be experiencing suicidal thoughts) to help reduce distress, normalize experiences, and challenge distressing thoughts. The website was promoted via leading web-based social media channels and Google Ads. Evaluation of the website was based on website engagement, marketing strategy, and direct web user feedback via a cross-sectional survey.</p><p><strong>Results: </strong>Data were collected for 41 weeks (June 2022 to February 2023) spanning the launch of the website and the conclusion of the second marketing campaign. On average, the website received 99.9 visitors per day. A total of 56% (n=14,439) of visitors were female, ages ranged from younger than 18 years to older than 70 years (commonly between 25 and 34 years) and originated from all regions of Scotland. According to Google Search terms of Scottish residents, of the individuals indicated to be experiencing suicidal thoughts but not looking for help, 5.3% (n=920) engaged with the website compared to 10.5% (n=2898) who were indicated to be looking for help for themselves. Based on participant responses to the evaluation survey (n=101), the website was associated with a significant reduction in suicidal thoughts (P=.03). Reasons for visiting the website varied. Marketing data implied that people were more likely to engage with advertisements, which they felt were more personal, and visitors to the website were more likely to engage with videos, which corresponded to their age.</p><p><strong>Conclusions: </strong>A peer-led website may help residents of Scotland who are experiencing suicidal thoughts. Web-based interventions may have considerable reach in Scotland both in terms of age and geographic area. Engagement with the website was similar to other self-help websites for suicidal ideation; however, more nuanced methods of analyzing website engagement for help-seeking behavior are recommended. Future work would benefit from ex
{"title":"Exploring Web-Based Support for Suicidal Ideation in the Scottish Population: Usability Study.","authors":"Heather McClelland, Rory C O'Connor, Laura Gibson, Donald J MacIntyre","doi":"10.2196/55932","DOIUrl":"10.2196/55932","url":null,"abstract":"<p><strong>Background: </strong>Suicide is a global health concern. In the United Kingdom, Scotland has the highest suicide rate. Lived experience and suicide prevention stakeholders in Scotland have identified a key gap in suicide prevention activities: the lack of 24-hour peer-driven web-based support for people who are suicidal.</p><p><strong>Objective: </strong>This usability study aimed to evaluate the feasibility, acceptability, utility, and reach of a suicide prevention website (Surviving Suicidal Thoughts) specifically designed to support residents in Scotland who are experiencing suicidal thoughts themselves or suspect or know someone who is experiencing suicidal thoughts. Intended support was delivered through the provision of personal testimony videos of individuals with lived experience.</p><p><strong>Methods: </strong>A peer-driven website was developed specifically to support residents of Scotland experiencing suicidal thoughts. The website included resources (eg, videos from lived experience and written guidance about how to respond to someone who may be experiencing suicidal thoughts) to help reduce distress, normalize experiences, and challenge distressing thoughts. The website was promoted via leading web-based social media channels and Google Ads. Evaluation of the website was based on website engagement, marketing strategy, and direct web user feedback via a cross-sectional survey.</p><p><strong>Results: </strong>Data were collected for 41 weeks (June 2022 to February 2023) spanning the launch of the website and the conclusion of the second marketing campaign. On average, the website received 99.9 visitors per day. A total of 56% (n=14,439) of visitors were female, ages ranged from younger than 18 years to older than 70 years (commonly between 25 and 34 years) and originated from all regions of Scotland. According to Google Search terms of Scottish residents, of the individuals indicated to be experiencing suicidal thoughts but not looking for help, 5.3% (n=920) engaged with the website compared to 10.5% (n=2898) who were indicated to be looking for help for themselves. Based on participant responses to the evaluation survey (n=101), the website was associated with a significant reduction in suicidal thoughts (P=.03). Reasons for visiting the website varied. Marketing data implied that people were more likely to engage with advertisements, which they felt were more personal, and visitors to the website were more likely to engage with videos, which corresponded to their age.</p><p><strong>Conclusions: </strong>A peer-led website may help residents of Scotland who are experiencing suicidal thoughts. Web-based interventions may have considerable reach in Scotland both in terms of age and geographic area. Engagement with the website was similar to other self-help websites for suicidal ideation; however, more nuanced methods of analyzing website engagement for help-seeking behavior are recommended. Future work would benefit from ex","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e55932"},"PeriodicalIF":2.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11806263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marcia Shade, Changmin Yan, Valerie K Jones, Julie Boron
Background: Technologies that serve as assistants are growing more popular for entertainment and aiding in daily tasks. Artificial intelligence (AI) in these technologies could also be helpful to deliver interventions that assist older adults with symptoms or self-management. Personality traits may play a role in how older adults engage with AI technologies. To ensure the best intervention delivery, we must understand older adults' engagement with and usability of AI-driven technologies.
Objective: This study aimed to describe how older adults engaged with routines facilitated by a conversational AI assistant.
Methods: A randomized pilot trial was conducted for 12-weeks in adults aged 60 years or older, self-reported living alone, and having chronic musculoskeletal pain. Participants (N=50) were randomly assigned to 1 of 2 intervention groups (standard vs enhanced) to engage with routines delivered by the AI assistant Alexa (Amazon). Participants were encouraged to interact with prescribed routines twice daily (morning and evening) and as needed. Data were collected and analyzed on routine engagement characteristics and perceived usability of the AI assistant. An analysis of the participants' personality traits was conducted to describe how personality may impact engagement and usability of AI technologies as interventions.
Results: The participants had a mean age of 79 years, with moderate to high levels of comfort and trust in technology, and were predominately White (48/50, 96%) and women (44/50, 88%). In both intervention groups, morning routines (n=62, 74%) were initiated more frequently than evening routines (n=52, 62%; z=-2.81, P=.005). Older adult participants in the enhanced group self-reported routine usability as good (mean 74.50, SD 11.90), and those in the standard group reported lower but acceptable usability scores (mean 66.29, SD 6.94). Higher extraversion personality trait scores predicted higher rates of routine initiation throughout the whole day and morning in both groups (standard day: B=0.47, P=.004; enhanced day: B=0.44, P=.045; standard morning: B=0.50, P=.03; enhanced morning: B=0.53, P=.02). Higher agreeableness (standard: B=0.50, P=.02; enhanced B=0.46, P=.002) and higher conscientiousness (standard: B=0.33, P=.04; enhanced: B=0.38, P=.006) personality trait scores predicted better usability scores in both groups.
Conclusions: he prescribed interactive routines delivered by an AI assistant were feasible to use as interventions with older adults. Engagement and usability by older adults may be influenced by personality traits such as extraversion, agreeableness, and conscientiousness. While integrating AI-driven interventions into health care, it is important to consider these factors to promote positive outcomes.
{"title":"Evaluating Older Adults' Engagement and Usability With AI-Driven Interventions: Randomized Pilot Study.","authors":"Marcia Shade, Changmin Yan, Valerie K Jones, Julie Boron","doi":"10.2196/64763","DOIUrl":"10.2196/64763","url":null,"abstract":"<p><strong>Background: </strong>Technologies that serve as assistants are growing more popular for entertainment and aiding in daily tasks. Artificial intelligence (AI) in these technologies could also be helpful to deliver interventions that assist older adults with symptoms or self-management. Personality traits may play a role in how older adults engage with AI technologies. To ensure the best intervention delivery, we must understand older adults' engagement with and usability of AI-driven technologies.</p><p><strong>Objective: </strong>This study aimed to describe how older adults engaged with routines facilitated by a conversational AI assistant.</p><p><strong>Methods: </strong>A randomized pilot trial was conducted for 12-weeks in adults aged 60 years or older, self-reported living alone, and having chronic musculoskeletal pain. Participants (N=50) were randomly assigned to 1 of 2 intervention groups (standard vs enhanced) to engage with routines delivered by the AI assistant Alexa (Amazon). Participants were encouraged to interact with prescribed routines twice daily (morning and evening) and as needed. Data were collected and analyzed on routine engagement characteristics and perceived usability of the AI assistant. An analysis of the participants' personality traits was conducted to describe how personality may impact engagement and usability of AI technologies as interventions.</p><p><strong>Results: </strong>The participants had a mean age of 79 years, with moderate to high levels of comfort and trust in technology, and were predominately White (48/50, 96%) and women (44/50, 88%). In both intervention groups, morning routines (n=62, 74%) were initiated more frequently than evening routines (n=52, 62%; z=-2.81, P=.005). Older adult participants in the enhanced group self-reported routine usability as good (mean 74.50, SD 11.90), and those in the standard group reported lower but acceptable usability scores (mean 66.29, SD 6.94). Higher extraversion personality trait scores predicted higher rates of routine initiation throughout the whole day and morning in both groups (standard day: B=0.47, P=.004; enhanced day: B=0.44, P=.045; standard morning: B=0.50, P=.03; enhanced morning: B=0.53, P=.02). Higher agreeableness (standard: B=0.50, P=.02; enhanced B=0.46, P=.002) and higher conscientiousness (standard: B=0.33, P=.04; enhanced: B=0.38, P=.006) personality trait scores predicted better usability scores in both groups.</p><p><strong>Conclusions: </strong>he prescribed interactive routines delivered by an AI assistant were feasible to use as interventions with older adults. Engagement and usability by older adults may be influenced by personality traits such as extraversion, agreeableness, and conscientiousness. While integrating AI-driven interventions into health care, it is important to consider these factors to promote positive outcomes.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e64763"},"PeriodicalIF":2.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11784632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christel McMullan, Grace Turner, Ameeta Retzer, Antonio Belli, Elin Haf Davies, Laura Nice, Luke Flavell, Jackie Flavell, Melanie Calvert
<p><strong>Background: </strong>Traumatic brain injury (TBI) is a significant public health issue and a leading cause of death and disability globally. Advances in clinical care have improved survival rates, leading to a growing population living with long-term effects of TBI, which can impact physical, cognitive, and emotional health. These effects often require continuous management and individualized care. Traditional paper-based assessments can be cumbersome, potentially impeding regular monitoring of patient-reported outcomes (PROs). Electronic PROs (ePROs) offer a promising alternative by enabling real-time symptom tracking, which can facilitate early identification of issues, support shared decision-making, and improve outcomes for patients with TBI.</p><p><strong>Objective: </strong>This study evaluates the usability of an ePRO platform-Atom5-for individuals with TBI. By analyzing how patients use the system to report their symptoms, the study aims to identify usability issues, assess user satisfaction, and determine the potential of Atom5 to support ongoing patient-centered care.</p><p><strong>Methods: </strong>Atom5 was customized to enable individuals with TBI to report their symptoms. Usability testing was conducted through one-on-one sessions with participants recruited from Headway UK-an organization supporting brain injury survivors. Each participant took part in cognitive interviews using with the "Think Aloud" method, encouraging them to verbalize their thoughts and experiences while using the platform. This approach provided qualitative insights into areas of difficulty, usability strengths, and accessibility barriers. User satisfaction was quantitatively assessed with a brief 4-item questionnaire based on the System Usability Scale. Usability outcomes were analyzed for critical and noncritical errors, focusing on user experience and overall satisfaction.</p><p><strong>Results: </strong>In total, 9 participants completed a single usability testing session using Atom5, including 4 men, 4 women, and 1 nonbinary individual; 4 participants were under 55 years old, and 6 had their TBI <10 years ago. Finally, 8 participants used an Android device. The platform included measures for anxiety (Generalized Anxiety Disorder-2 item), depression (Patient Health Questionnaire-2), posttraumatic stress disorder (Posttraumatic Stress Disorder checklist 2), and TBI-specific quality of life (Traumatic Brain Injury - Quality of Life Short form) and a total of 26 questions. Overall, all participants were satisfied with the system, noting that it was easy to navigate and accessible despite difficulties in understanding some questions. Further, 6 participants encountered no errors, while 1 participant reported one critical error and 2 others reported one noncritical error each. The participants rated their overall satisfaction with the platform at an average score of 3.9 (SD 0.49) out of 5.</p><p><strong>Conclusions: </strong>This usability study sugg
{"title":"Testing an Electronic Patient-Reported Outcome Platform in the Context of Traumatic Brain Injury: PRiORiTy Usability Study.","authors":"Christel McMullan, Grace Turner, Ameeta Retzer, Antonio Belli, Elin Haf Davies, Laura Nice, Luke Flavell, Jackie Flavell, Melanie Calvert","doi":"10.2196/58128","DOIUrl":"10.2196/58128","url":null,"abstract":"<p><strong>Background: </strong>Traumatic brain injury (TBI) is a significant public health issue and a leading cause of death and disability globally. Advances in clinical care have improved survival rates, leading to a growing population living with long-term effects of TBI, which can impact physical, cognitive, and emotional health. These effects often require continuous management and individualized care. Traditional paper-based assessments can be cumbersome, potentially impeding regular monitoring of patient-reported outcomes (PROs). Electronic PROs (ePROs) offer a promising alternative by enabling real-time symptom tracking, which can facilitate early identification of issues, support shared decision-making, and improve outcomes for patients with TBI.</p><p><strong>Objective: </strong>This study evaluates the usability of an ePRO platform-Atom5-for individuals with TBI. By analyzing how patients use the system to report their symptoms, the study aims to identify usability issues, assess user satisfaction, and determine the potential of Atom5 to support ongoing patient-centered care.</p><p><strong>Methods: </strong>Atom5 was customized to enable individuals with TBI to report their symptoms. Usability testing was conducted through one-on-one sessions with participants recruited from Headway UK-an organization supporting brain injury survivors. Each participant took part in cognitive interviews using with the \"Think Aloud\" method, encouraging them to verbalize their thoughts and experiences while using the platform. This approach provided qualitative insights into areas of difficulty, usability strengths, and accessibility barriers. User satisfaction was quantitatively assessed with a brief 4-item questionnaire based on the System Usability Scale. Usability outcomes were analyzed for critical and noncritical errors, focusing on user experience and overall satisfaction.</p><p><strong>Results: </strong>In total, 9 participants completed a single usability testing session using Atom5, including 4 men, 4 women, and 1 nonbinary individual; 4 participants were under 55 years old, and 6 had their TBI <10 years ago. Finally, 8 participants used an Android device. The platform included measures for anxiety (Generalized Anxiety Disorder-2 item), depression (Patient Health Questionnaire-2), posttraumatic stress disorder (Posttraumatic Stress Disorder checklist 2), and TBI-specific quality of life (Traumatic Brain Injury - Quality of Life Short form) and a total of 26 questions. Overall, all participants were satisfied with the system, noting that it was easy to navigate and accessible despite difficulties in understanding some questions. Further, 6 participants encountered no errors, while 1 participant reported one critical error and 2 others reported one noncritical error each. The participants rated their overall satisfaction with the platform at an average score of 3.9 (SD 0.49) out of 5.</p><p><strong>Conclusions: </strong>This usability study sugg","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e58128"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11781241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Savannah Lucia Caterina Glaser, Itske Fraterman, Noah van Brummelen, Valentina Tibollo, Laura Maria Del Campo, Henk Mallo, Sofie Wilgenhof, Szymon Wilk, Vitali Gisko, Vadzim Khadakou, Ronald Cornet, Manuel Ottaviano, Stephanie Medlock
<p><strong>Background: </strong>The prognosis for patients with several types of cancer has substantially improved following the introduction of immune checkpoint inhibitors, a novel type of immunotherapy. However, patients may experience symptoms both from the cancer itself and from the medication. A prototype of the eHealth tool Cancer Patients Better Life Experience (CAPABLE) was developed to facilitate symptom management, aimed at patients with melanoma and renal cell carcinoma treated with immunotherapy. Better usability of such eHealth tools can lead to improved user well-being and reduced risk of harm. It is unknown for usability evaluations whether certain usability problems would only be evident to patients whose condition closely resembles the target population, or if a broader group of patients would lead to the identification of a broader range of potential usability issues.</p><p><strong>Objective: </strong>This study aims to evaluate the CAPABLE prototype by conducting tests to assess usability, user experience, and perceived acceptability among end users, and to assess any agreements or differences in the results of our wide range of participants.</p><p><strong>Methods: </strong>This usability study was executed by interviewing participants with a melanoma or renal cell carcinoma diagnosis who have received immunotherapy and participants without direct experience with the targeted cancer types who have not received immunotherapy. Participants were asked to review the concept of the tool, perform think-aloud tasks, and complete the System Usability Scale and a Perceived Usefulness questionnaire. Usability problems were extracted from the interview data by independent coding and mapped to an eHealth Usability Problem Framework.</p><p><strong>Results: </strong>We included 21 participants in the study, aged 29 to 73 years; 13 participants who had received immunotherapy and 8 participants who had not received immunotherapy. In total, 76 usability problems were identified. A total of 22 usability problems were in the task-technology fit category of the usability framework, mostly regarding the coaching and symptom functionality of the prototype. Critical problems regarding the symptom monitoring functionality were mainly found by participants who had received immunotherapy. For 8 out of 10 statements in the Perceived Usefulness questionnaire, more than 75% of participants agreed or strongly agreed. The overall mean System Usability Scale score was 80 out of 100 (SD 11.3).</p><p><strong>Conclusions: </strong>Despite identified usability issues, participants responded positively to the Perceived Usefulness questionnaire regarding the evaluated tool. Further analysis of the usability problems indicates that it was essential to include participants who matched the target end users. Participants treated with immunotherapy, specifically with previous experience in immune-related adverse events, encountered critical problems with symptom report
{"title":"Usability and Usefulness of a Symptom Management Coaching System for Patients With Cancer Treated With Immune Checkpoint Inhibitors: Comparative Mixed Methods Study.","authors":"Savannah Lucia Caterina Glaser, Itske Fraterman, Noah van Brummelen, Valentina Tibollo, Laura Maria Del Campo, Henk Mallo, Sofie Wilgenhof, Szymon Wilk, Vitali Gisko, Vadzim Khadakou, Ronald Cornet, Manuel Ottaviano, Stephanie Medlock","doi":"10.2196/57659","DOIUrl":"10.2196/57659","url":null,"abstract":"<p><strong>Background: </strong>The prognosis for patients with several types of cancer has substantially improved following the introduction of immune checkpoint inhibitors, a novel type of immunotherapy. However, patients may experience symptoms both from the cancer itself and from the medication. A prototype of the eHealth tool Cancer Patients Better Life Experience (CAPABLE) was developed to facilitate symptom management, aimed at patients with melanoma and renal cell carcinoma treated with immunotherapy. Better usability of such eHealth tools can lead to improved user well-being and reduced risk of harm. It is unknown for usability evaluations whether certain usability problems would only be evident to patients whose condition closely resembles the target population, or if a broader group of patients would lead to the identification of a broader range of potential usability issues.</p><p><strong>Objective: </strong>This study aims to evaluate the CAPABLE prototype by conducting tests to assess usability, user experience, and perceived acceptability among end users, and to assess any agreements or differences in the results of our wide range of participants.</p><p><strong>Methods: </strong>This usability study was executed by interviewing participants with a melanoma or renal cell carcinoma diagnosis who have received immunotherapy and participants without direct experience with the targeted cancer types who have not received immunotherapy. Participants were asked to review the concept of the tool, perform think-aloud tasks, and complete the System Usability Scale and a Perceived Usefulness questionnaire. Usability problems were extracted from the interview data by independent coding and mapped to an eHealth Usability Problem Framework.</p><p><strong>Results: </strong>We included 21 participants in the study, aged 29 to 73 years; 13 participants who had received immunotherapy and 8 participants who had not received immunotherapy. In total, 76 usability problems were identified. A total of 22 usability problems were in the task-technology fit category of the usability framework, mostly regarding the coaching and symptom functionality of the prototype. Critical problems regarding the symptom monitoring functionality were mainly found by participants who had received immunotherapy. For 8 out of 10 statements in the Perceived Usefulness questionnaire, more than 75% of participants agreed or strongly agreed. The overall mean System Usability Scale score was 80 out of 100 (SD 11.3).</p><p><strong>Conclusions: </strong>Despite identified usability issues, participants responded positively to the Perceived Usefulness questionnaire regarding the evaluated tool. Further analysis of the usability problems indicates that it was essential to include participants who matched the target end users. Participants treated with immunotherapy, specifically with previous experience in immune-related adverse events, encountered critical problems with symptom report","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e57659"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11803325/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143028720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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