Background: Tobacco smoking is viewed as a behavioral risk factor for psoriasis initiation and progress, even among those undergoing biologic treatment. However, evidence regarding the association between tobacco smoking and treatment response to biologics among patients with psoriasis is limited.
Objective: This study aimed to explore the impact of tobacco smoking on the efficacy of biologic treatment in patients with psoriasis.
Methods: Patients with psoriasis undergoing biologic treatment were recruited from 2022 to 2024 at the Shanghai Skin Disease Hospital. Demographic characteristics and smoking habits were collected using a structured questionnaire. Clinical features and treatment efficacy were assessed and recorded by dermatologists at baseline and weeks 4, 8, 12, 24, and 48 after treatment, and the Psoriasis Area and Severity Index (PASI) 75 and PASI 90 measures were calculated for treatment efficacy evaluation.
Results: A total of 192 patients with psoriasis were included, of whom 78 (40.6%) were tobacco smokers, with a higher smoking prevalence observed in male patients (74/154, 48.1%). The PASI 75 response rates at weeks 4, 8, 12, 24, and 48 were 29.2% (56/192), 54.2% (104/192), 78.6% (151/192), 84.5% (153/181), and 82.7% (134/162), respectively. The PASI 90 response rates increased from 13.0% (25/192) at week 4 to 62.4% (113/181) at week 24 and 59.9% (97/162) at week 48. Logistic regression analysis indicated that nonsmoking patients with psoriasis had a high PASI 75 response rate. The adjusted odds ratios were 2.57 (95% CI 1.19-5.53), 2.61 (95% CI 1.34-5.08), 2.62 (95% CI 1.13-6.04), 2.27 (95% CI 0.89-5.75), and 2.75 (95% CI 1.01-7.49) at weeks 4, 8, 12, 24, and 48, respectively. Moreover, nonsmoking patients with psoriasis also had a higher PASI 90 response rate than those who smoked. The odds ratios ranged from 1.32 (95% CI 0.49-3.54) to 2.59 (95% CI 1.21-5.55). Correlation analysis showed that both tobacco smoking duration and daily cigarette consumption were negatively correlated with the reduction in PASI score at weeks 4 to 48 after treatment (P<.05).
Conclusions: Tobacco smoking was negatively associated with treatment response among patients with psoriasis undergoing biologic treatment, especially among patients with longer tobacco smoking duration and higher daily cigarette consumption.
背景：吸烟被认为是牛皮癣发生和发展的行为危险因素，即使在接受生物治疗的患者中也是如此。然而，关于银屑病患者吸烟与生物制剂治疗反应之间关系的证据有限。目的：探讨吸烟对银屑病生物治疗疗效的影响。方法：招募2022 - 2024年在上海皮肤病医院接受生物治疗的银屑病患者。采用结构化问卷收集人口统计学特征和吸烟习惯。皮肤科医生在基线及治疗后第4、8、12、24、48周评估并记录临床特征和治疗效果，计算银屑病面积和严重程度指数（PASI） 75和PASI 90指标，评价治疗效果。结果：共纳入192例银屑病患者，其中吸烟78例（40.6%），男性患者吸烟率较高（74/154,48.1%）。第4、8、12、24和48周的PASI 75缓解率分别为29.2%（56/192）、54.2%（104/192）、78.6%（151/192）、84.5%（153/181）和82.7%（134/162）。PASI 90缓解率从第4周的13.0%（25/192）增加到第24周的62.4%（113/181）和第48周的59.9%（97/162）。Logistic回归分析显示，非吸烟银屑病患者的PASI 75有效率较高。校正后的优势比在第4、8、12、24和48周分别为2.57 （95% CI 1.19-5.53）、2.61 （95% CI 1.34-5.08）、2.62 （95% CI 1.13-6.04）、2.27 （95% CI 0.89-5.75）和2.75 （95% CI 1.01-7.49）。此外，不吸烟的银屑病患者的PASI 90反应率也高于吸烟的患者。比值比从1.32 （95% CI 0.49-3.54）到2.59 （95% CI 1.21-5.55）。相关分析显示，吸烟持续时间和每日卷烟消费量与治疗后第4 ~ 48周PASI评分的降低呈负相关(p结论：在接受生物治疗的银屑病患者中，吸烟与治疗反应呈负相关，特别是在吸烟持续时间较长、每日卷烟消费量较高的患者中。
{"title":"The Impact of Tobacco Smoking on Treatment Response Among Patients With Psoriasis Undergoing Biologic Treatment: Prospective Observational Study.","authors":"Fanlingzi Shen, Yuning Ding, Xiuqi Zhang, Quanruo Xu, Zhen Duan, Ruiqi Cai, Rui Zhang, Xiangjin Gao, Ruiping Wang","doi":"10.2196/90963","DOIUrl":"10.2196/90963","url":null,"abstract":"<p><strong>Background: </strong>Tobacco smoking is viewed as a behavioral risk factor for psoriasis initiation and progress, even among those undergoing biologic treatment. However, evidence regarding the association between tobacco smoking and treatment response to biologics among patients with psoriasis is limited.</p><p><strong>Objective: </strong>This study aimed to explore the impact of tobacco smoking on the efficacy of biologic treatment in patients with psoriasis.</p><p><strong>Methods: </strong>Patients with psoriasis undergoing biologic treatment were recruited from 2022 to 2024 at the Shanghai Skin Disease Hospital. Demographic characteristics and smoking habits were collected using a structured questionnaire. Clinical features and treatment efficacy were assessed and recorded by dermatologists at baseline and weeks 4, 8, 12, 24, and 48 after treatment, and the Psoriasis Area and Severity Index (PASI) 75 and PASI 90 measures were calculated for treatment efficacy evaluation.</p><p><strong>Results: </strong>A total of 192 patients with psoriasis were included, of whom 78 (40.6%) were tobacco smokers, with a higher smoking prevalence observed in male patients (74/154, 48.1%). The PASI 75 response rates at weeks 4, 8, 12, 24, and 48 were 29.2% (56/192), 54.2% (104/192), 78.6% (151/192), 84.5% (153/181), and 82.7% (134/162), respectively. The PASI 90 response rates increased from 13.0% (25/192) at week 4 to 62.4% (113/181) at week 24 and 59.9% (97/162) at week 48. Logistic regression analysis indicated that nonsmoking patients with psoriasis had a high PASI 75 response rate. The adjusted odds ratios were 2.57 (95% CI 1.19-5.53), 2.61 (95% CI 1.34-5.08), 2.62 (95% CI 1.13-6.04), 2.27 (95% CI 0.89-5.75), and 2.75 (95% CI 1.01-7.49) at weeks 4, 8, 12, 24, and 48, respectively. Moreover, nonsmoking patients with psoriasis also had a higher PASI 90 response rate than those who smoked. The odds ratios ranged from 1.32 (95% CI 0.49-3.54) to 2.59 (95% CI 1.21-5.55). Correlation analysis showed that both tobacco smoking duration and daily cigarette consumption were negatively correlated with the reduction in PASI score at weeks 4 to 48 after treatment (P<.05).</p><p><strong>Conclusions: </strong>Tobacco smoking was negatively associated with treatment response among patients with psoriasis undergoing biologic treatment, especially among patients with longer tobacco smoking duration and higher daily cigarette consumption.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e90963"},"PeriodicalIF":3.0,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12978889/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147436430","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}
Jennifer Ferrar, Lizzy Winstone, Ian Penton-Voak, Lucy Biddle, Paul Moran, Lydia Grace, Becky Mars
Background: Lived experience stories are often used on formal help sites as a support resource for individuals who self-harm. While self-harm-related internet use provides an alternative for individuals who are not yet ready or are unwilling or unable to access support offline, it has also been shown to unintentionally reinforce self-harm behavior. There are several components that might influence whether a lived experience story is perceived as helpful, unhelpful, or potentially harmful, and the evidence supporting that these encourage help-seeking in the reader is limited.
Objective: This study is part of a mixed methods project that aimed to investigate how variations in help-seeking messages contained within online lived experience stories are interpreted by and psychologically impact those with a history of self-harm.
Methods: Individuals with a recent history of self-harm were recruited via newsletters, social media, and websites run by the university and mental health charities to take part in an online experiment. During the experiment, participants were randomized to read stories that either mentioned (1) self-help strategies, (2) seeking help from informal and formal sources, or (3) did not mention help-seeking. Help-seeking intentions, mood, entrapment, and expectations of future self-harm were measured, and participants provided feedback on the stories.
Results: There was limited evidence for an effect of story type on help-seeking intentions (F2, 230=4.2; P=.02; η2=0.25), and clearer evidence for an effect of story type on negative affect (F2, 230=4.02; P=.02; η2=0.10; adjustment for age, gender, and help-seeking history included). Participants in the "self-help" condition (n=83) reported lower negative affect after reading the stories compared to participants in the "no help" condition (n=80; mean difference=-3.97, 95% CI -7.72 to -0.22; P=.04) and the "informal/formal" help condition (n=75; mean difference=-3.70, 95% CI -7.55 to 0.14; P=.06). A key criticism of the stories was that they were unrelatable, but this sentiment was less prevalent among those in the "no help" condition. Key positives were that the stories included a realistic but hopeful outlook of recovery (less prevalent in the "informal/formal help" condition) and were supportive (less prevalent in the "no help" condition).
Conclusions: While the inclusion of self-help strategies in a lived experience story reduced its impact on negative affect, the inclusion of self-help strategies or seeking help from others did not encourage help-seeking intentions. Making stories relatable, authentic, and providing multiple strategies for support might be key to encouraging help-seeking, but more research is needed.
背景：生活经历故事经常在正式的帮助网站上被用作自我伤害个体的支持资源。虽然与自残相关的互联网使用为那些尚未准备好或不愿或无法获得线下支持的个人提供了另一种选择，但它也被证明无意中强化了自残行为。有几个因素可能会影响一个生活经历的故事是否被认为是有益的，无益的，或者潜在的有害的，支持这些因素鼓励读者寻求帮助的证据是有限的。目的：本研究是一个混合方法项目的一部分，旨在调查在线生活经历故事中包含的求助信息的变化如何被有自残史的人解释和心理影响。方法：通过大学和心理健康慈善机构运营的新闻通讯、社交媒体和网站，招募最近有自残史的人参加一项在线实验。在实验过程中，参与者被随机分成三组，一组是提到了(1)自助策略，(2)从非正式和正式渠道寻求帮助，或者(3)没有提到寻求帮助。他们测量了寻求帮助的意图、情绪、陷阱和对未来自残的预期，并对故事进行了反馈。结果：故事类型对求助意向的影响证据有限（F2, 230=4.2； P= 0.02; η2=0.25），而故事类型对消极情绪的影响证据更明确（F2, 230=4.02； P= 0.02; η2=0.10；包括年龄、性别和求助史校正）。与“无帮助”组（n=80；平均差异=-3.97,95% CI -7.72至-0.22；P= 0.04）和“非正式/正式”帮助组（n=75；平均差异=-3.70,95% CI -7.55至0.14；P= 0.06）相比，“自助”组（n=83）的参与者在阅读故事后的负面影响较低。对这些故事的一个关键批评是，它们没有关联，但这种情绪在“没有帮助”的情况下不那么普遍。关键的积极因素是，这些故事包含了现实但充满希望的康复前景（在“非正式/正式帮助”条件下不那么普遍），并且是支持性的（在“没有帮助”条件下不那么普遍）。结论：虽然在生活经历故事中包含自助策略会降低其对负面情绪的影响，但包含自助策略或向他人寻求帮助并没有鼓励寻求帮助的意图。让故事具有相关性、真实性，并提供多种支持策略可能是鼓励寻求帮助的关键，但还需要更多的研究。
{"title":"Investigating the Impact of Lived Experience Stories on Self-Harm, Mood, and Help-Seeking Intentions: Web-Based Between-Participants Experimental Study in Individuals With Recent Self-Harm.","authors":"Jennifer Ferrar, Lizzy Winstone, Ian Penton-Voak, Lucy Biddle, Paul Moran, Lydia Grace, Becky Mars","doi":"10.2196/71280","DOIUrl":"10.2196/71280","url":null,"abstract":"<p><strong>Background: </strong>Lived experience stories are often used on formal help sites as a support resource for individuals who self-harm. While self-harm-related internet use provides an alternative for individuals who are not yet ready or are unwilling or unable to access support offline, it has also been shown to unintentionally reinforce self-harm behavior. There are several components that might influence whether a lived experience story is perceived as helpful, unhelpful, or potentially harmful, and the evidence supporting that these encourage help-seeking in the reader is limited.</p><p><strong>Objective: </strong>This study is part of a mixed methods project that aimed to investigate how variations in help-seeking messages contained within online lived experience stories are interpreted by and psychologically impact those with a history of self-harm.</p><p><strong>Methods: </strong>Individuals with a recent history of self-harm were recruited via newsletters, social media, and websites run by the university and mental health charities to take part in an online experiment. During the experiment, participants were randomized to read stories that either mentioned (1) self-help strategies, (2) seeking help from informal and formal sources, or (3) did not mention help-seeking. Help-seeking intentions, mood, entrapment, and expectations of future self-harm were measured, and participants provided feedback on the stories.</p><p><strong>Results: </strong>There was limited evidence for an effect of story type on help-seeking intentions (F<sub>2, 230</sub>=4.2; P=.02; η<sup>2</sup>=0.25), and clearer evidence for an effect of story type on negative affect (F<sub>2, 230</sub>=4.02; P=.02; η<sup>2</sup>=0.10; adjustment for age, gender, and help-seeking history included). Participants in the \"self-help\" condition (n=83) reported lower negative affect after reading the stories compared to participants in the \"no help\" condition (n=80; mean difference=-3.97, 95% CI -7.72 to -0.22; P=.04) and the \"informal/formal\" help condition (n=75; mean difference=-3.70, 95% CI -7.55 to 0.14; P=.06). A key criticism of the stories was that they were unrelatable, but this sentiment was less prevalent among those in the \"no help\" condition. Key positives were that the stories included a realistic but hopeful outlook of recovery (less prevalent in the \"informal/formal help\" condition) and were supportive (less prevalent in the \"no help\" condition).</p><p><strong>Conclusions: </strong>While the inclusion of self-help strategies in a lived experience story reduced its impact on negative affect, the inclusion of self-help strategies or seeking help from others did not encourage help-seeking intentions. Making stories relatable, authentic, and providing multiple strategies for support might be key to encouraging help-seeking, but more research is needed.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e71280"},"PeriodicalIF":3.0,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13000381/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147356172","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}
Kristofer Vernmark, Anahita Geranmayeh, Naira Topooco, Gerhard Andersson, Shervin Shahnavaz
<p><strong>Background: </strong>The rising number of refugees and migrants has created growing mental health needs that health care systems struggle to address. Providing assessment and treatment for mental health problems in a digital format could help increase access to care and facilitate the provision of adapted interventions. Psychologists are key stakeholders in the delivery and influence of clinical services within routine care settings, but there are limited data on their perspectives regarding the use of digital solutions to assess and treat common mental health problems in refugees and migrants.</p><p><strong>Objective: </strong>This study aimed to examine psychologists' usage, knowledge, and attitudes toward digital mental health solutions for assessing and treating common mental health problems in refugees and migrants within the Swedish health care system.</p><p><strong>Methods: </strong>A cross-sectional online survey was conducted among psychologists in Sweden between December 2023 and February 2024. Responses included Likert-scale items and categorical variables, which were analyzed using descriptive statistics, independent samples t tests, and Fisher exact test to explore differences between subgroups.</p><p><strong>Results: </strong>A total of 81 psychologists responded to the survey. Among them, 58 (72%) were women, and nearly half (40/81, 49%) worked in a public health care region. Respondents showed the highest acceptance for guided internet-based cognitive behavioral therapy (ICBT), blended treatment, and videoconferencing therapy. Only 20% (16/81) reported using digital solutions for refugees or migrants with mental health problems. Most respondents had low or very low knowledge of digital assessment and screening (61/81, 75%) and digital treatment (58/81, 72%) for these groups. Those using digital formats for refugees and migrants, or working in a setting that did so, had significantly higher ratings on all 5 knowledge items compared to those that did not (P<.001 to P=.01). Respondents emphasized the importance of digital solutions being provided in refugees' and migrants' native languages (70/81, 86%) and being culturally adapted (56/81, 69%). Those using digital formats for refugees and migrants considered cultural adaptation less necessary (P=.05). The preferred implementation approach was through specialized or decentralized units in primary care (66/81, 81%).</p><p><strong>Conclusions: </strong>While psychologists recognize the potential of digital mental health solutions, significant barriers remain, including limited knowledge and experience with using digital formats for refugees and migrants. Psychologists prefer digital solutions in the native language of refugees and migrants that are implemented at the primary care level. The need for cultural adaptation should be further explored. Addressing psychologists' preferences could facilitate the future integration and implementation of digital formats for refugees an
{"title":"Understanding Psychologists' Usage, Knowledge, and Attitudes Toward Digital Mental Health Solutions for Refugees and Migrants: Exploratory Cross-Sectional Survey in Sweden.","authors":"Kristofer Vernmark, Anahita Geranmayeh, Naira Topooco, Gerhard Andersson, Shervin Shahnavaz","doi":"10.2196/75263","DOIUrl":"10.2196/75263","url":null,"abstract":"<p><strong>Background: </strong>The rising number of refugees and migrants has created growing mental health needs that health care systems struggle to address. Providing assessment and treatment for mental health problems in a digital format could help increase access to care and facilitate the provision of adapted interventions. Psychologists are key stakeholders in the delivery and influence of clinical services within routine care settings, but there are limited data on their perspectives regarding the use of digital solutions to assess and treat common mental health problems in refugees and migrants.</p><p><strong>Objective: </strong>This study aimed to examine psychologists' usage, knowledge, and attitudes toward digital mental health solutions for assessing and treating common mental health problems in refugees and migrants within the Swedish health care system.</p><p><strong>Methods: </strong>A cross-sectional online survey was conducted among psychologists in Sweden between December 2023 and February 2024. Responses included Likert-scale items and categorical variables, which were analyzed using descriptive statistics, independent samples t tests, and Fisher exact test to explore differences between subgroups.</p><p><strong>Results: </strong>A total of 81 psychologists responded to the survey. Among them, 58 (72%) were women, and nearly half (40/81, 49%) worked in a public health care region. Respondents showed the highest acceptance for guided internet-based cognitive behavioral therapy (ICBT), blended treatment, and videoconferencing therapy. Only 20% (16/81) reported using digital solutions for refugees or migrants with mental health problems. Most respondents had low or very low knowledge of digital assessment and screening (61/81, 75%) and digital treatment (58/81, 72%) for these groups. Those using digital formats for refugees and migrants, or working in a setting that did so, had significantly higher ratings on all 5 knowledge items compared to those that did not (P<.001 to P=.01). Respondents emphasized the importance of digital solutions being provided in refugees' and migrants' native languages (70/81, 86%) and being culturally adapted (56/81, 69%). Those using digital formats for refugees and migrants considered cultural adaptation less necessary (P=.05). The preferred implementation approach was through specialized or decentralized units in primary care (66/81, 81%).</p><p><strong>Conclusions: </strong>While psychologists recognize the potential of digital mental health solutions, significant barriers remain, including limited knowledge and experience with using digital formats for refugees and migrants. Psychologists prefer digital solutions in the native language of refugees and migrants that are implemented at the primary care level. The need for cultural adaptation should be further explored. Addressing psychologists' preferences could facilitate the future integration and implementation of digital formats for refugees an","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e75263"},"PeriodicalIF":3.0,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12996901/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147348058","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}
Mahima Akula, Kim Erwin, Leah Traeger, Hannah Pick, Fei Gao, Laura Damschroder, Valerie G Press
<p><strong>Background: </strong>Chronic obstructive pulmonary disease (COPD) affects more than 16 million US adults, many of whom experience high rates of acute care revisits (emergency department and hospital) after initial hospitalization. These frequent exacerbations, often due to failures in transitions of care (TOC), lead to lung function decline and premature mortality. While effective interventions exist to reduce readmissions, wide-scale implementation of COPD TOC programs remains limited. The National Institutes of Health-funded Reducing Respiratory Emergency Visits Using Implementation Science Interventions Tailored to Settings (REVISITS) study was designed to address this implementation gap by developing and implementing bundled COPD TOC programs across diverse US hospitals.</p><p><strong>Objective: </strong>This study aimed to conduct pre-implementation contextual assessments at US hospitals to guide the development of site-specific, evidence-based COPD TOC programs.</p><p><strong>Methods: </strong>We conducted pre-implementation contextual assessments using a novel semi-structured interview format that integrated the Consolidated Framework for Implementation Research (CFIR) with human-centered design approaches (ethnographic interviewing) to capture real-world experiences of COPD care across inpatient, outpatient, and home settings. We used a sequential explanatory mixed methods design in which pre-interview survey data completed by site leads informed and shaped the subsequent semi-structured interviews. Site leads, clinicians, organizational leaders, patients, and caregivers were interviewed. Interviews explored baseline COPD TOC practices, local resources, opportunities for improvement, as well as participant priorities from a menu of 12 evidence-based interventions (eg, pulmonary rehabilitation, patient navigation, and inhaler teaching). Rapid analysis methods identified intervention priorities across participant groups, along with perceived barriers and facilitators to implementation. Findings were shared with site leads to help guide their development of tailored COPD TOC programs.</p><p><strong>Results: </strong>Among 194 participants from 21 sites (42 site leads, 29 organizational leaders, 105 clinicians, and 18 patients or caregivers), the highest priority interventions identified during interviews were post-emergency department follow-up visits, education (inhaler technique, disease management, and action plan), and pulmonary rehabilitation. Reported barriers included clinician-level challenges (limited training, staffing, and time), patient-level challenges (social needs and physical burden of COPD), and system-level challenges (lack of standardization, limited resources, and cost). Key facilitators included the presence of dedicated staff and the availability of pre-existing programs or infrastructure. The 3 most commonly chosen interventions for implementation were patient education (eg, inhaler education and COPD action
{"title":"Contextual Assessments for Chronic Obstructive Pulmonary Disease Transition of Care Bundle Implementation Planning for the Reduce REVISITS Study: Rapid Sequential Explanatory Mixed Methods Approach.","authors":"Mahima Akula, Kim Erwin, Leah Traeger, Hannah Pick, Fei Gao, Laura Damschroder, Valerie G Press","doi":"10.2196/82078","DOIUrl":"10.2196/82078","url":null,"abstract":"<p><strong>Background: </strong>Chronic obstructive pulmonary disease (COPD) affects more than 16 million US adults, many of whom experience high rates of acute care revisits (emergency department and hospital) after initial hospitalization. These frequent exacerbations, often due to failures in transitions of care (TOC), lead to lung function decline and premature mortality. While effective interventions exist to reduce readmissions, wide-scale implementation of COPD TOC programs remains limited. The National Institutes of Health-funded Reducing Respiratory Emergency Visits Using Implementation Science Interventions Tailored to Settings (REVISITS) study was designed to address this implementation gap by developing and implementing bundled COPD TOC programs across diverse US hospitals.</p><p><strong>Objective: </strong>This study aimed to conduct pre-implementation contextual assessments at US hospitals to guide the development of site-specific, evidence-based COPD TOC programs.</p><p><strong>Methods: </strong>We conducted pre-implementation contextual assessments using a novel semi-structured interview format that integrated the Consolidated Framework for Implementation Research (CFIR) with human-centered design approaches (ethnographic interviewing) to capture real-world experiences of COPD care across inpatient, outpatient, and home settings. We used a sequential explanatory mixed methods design in which pre-interview survey data completed by site leads informed and shaped the subsequent semi-structured interviews. Site leads, clinicians, organizational leaders, patients, and caregivers were interviewed. Interviews explored baseline COPD TOC practices, local resources, opportunities for improvement, as well as participant priorities from a menu of 12 evidence-based interventions (eg, pulmonary rehabilitation, patient navigation, and inhaler teaching). Rapid analysis methods identified intervention priorities across participant groups, along with perceived barriers and facilitators to implementation. Findings were shared with site leads to help guide their development of tailored COPD TOC programs.</p><p><strong>Results: </strong>Among 194 participants from 21 sites (42 site leads, 29 organizational leaders, 105 clinicians, and 18 patients or caregivers), the highest priority interventions identified during interviews were post-emergency department follow-up visits, education (inhaler technique, disease management, and action plan), and pulmonary rehabilitation. Reported barriers included clinician-level challenges (limited training, staffing, and time), patient-level challenges (social needs and physical burden of COPD), and system-level challenges (lack of standardization, limited resources, and cost). Key facilitators included the presence of dedicated staff and the availability of pre-existing programs or infrastructure. The 3 most commonly chosen interventions for implementation were patient education (eg, inhaler education and COPD action","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e82078"},"PeriodicalIF":3.0,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12954717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147345437","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}
Laura Asché, Julian Pakos, Hannah Schrage, Johanna Schuder, Luisa Jung, Dario Sanchez, Benjamin Selaskowski, Annika Wiebe, Alexandra Philipsen, Niclas Braun
<p><strong>Background: </strong>Over the past 2 decades, virtual reality-based neuropsychological tasks have gained traction as tools for objectively assessing symptoms of attention-deficit/hyperactivity disorder (ADHD), offering enhanced ecological validity by simulating naturalistic environments. To complement realistic settings with an ecologically valid task, we recently developed the virtual email sorting task (VEST), which immerses participants into an office environment where they sort emails while being exposed to distractors.</p><p><strong>Objective: </strong>This study examined for the first time the VEST's sensitivity to medication effects and its specificity in differentiating ADHD from other psychiatric disorders that share overlapping cognitive symptoms, such as major depressive disorder (MDD).</p><p><strong>Methods: </strong>A total of 23 unmedicated individuals with ADHD, 23 medicated individuals with ADHD, and 16 unmedicated individuals with MDD completed the VEST. During alternating distractor phases (DP) and nondistractor phases (NDP), we recorded the participants' task performance; head, torso, and leg actigraphy; eye movements; and brain activity using functional near-infrared spectroscopy (fNIRS), and subjective symptom ratings. Correlational analyses of main objective and subjective task-related parameters were computed. Data were analyzed using mixed-design ANOVAs.</p><p><strong>Results: </strong>Processing time variability increased over time in participants with MDD and unmedicated ADHD as indicated by a group × block interaction (P=.04; η<sup>2</sup><sub>p</sub>=0.10), while a group × phase interaction (P=.009; η<sup>2</sup><sub>p</sub>=0.15) revealed that medicated participants with ADHD showed an increase during DP compared to NDP. Moreover, both ADHD groups exhibited increased head movements during DP compared to NDP (trend group × phase interaction: P=.09; η<sup>2</sup><sub>p</sub>=0.08), an effect not observed in the MDD group, and higher rotation during DP in unmedicated individuals with ADHD (P<.001; η<sup>2</sup><sub>p</sub>=0.23). Also, scores in 3 out of 4 subjective symptom intensity ratings of inattention, impulsivity, and emotional dysregulation were higher in at least 1 of the ADHD groups compared to the MDD group. No significant group differences were found in actigraphy measures of the arm and torso, fNIRS brain activity, or eye-tracking data. Regarding correlational analyses, inattention was correlated to off-task gaze (r=0.28; P=.03), hyperactivity with mean processing time (r=0.33; P=.01) and head movement (r=0.35; P=.006), and impulsivity with error rate (r=0.35; P=.006), and various significant correlations between objective parameters were found.</p><p><strong>Conclusions: </strong>Our findings highlight the potential of the VEST to differentiate between ADHD and MDD, as well as to detect medication-related effects within ADHD. The results underscore the value of multimodal and ecological assessmen
{"title":"Multimodal Virtual Reality Assessment of Medication Effects in Attention-Deficit/Hyperactivity Disorder and Its Distinction From Depression: Cross-Sectional Study.","authors":"Laura Asché, Julian Pakos, Hannah Schrage, Johanna Schuder, Luisa Jung, Dario Sanchez, Benjamin Selaskowski, Annika Wiebe, Alexandra Philipsen, Niclas Braun","doi":"10.2196/85351","DOIUrl":"10.2196/85351","url":null,"abstract":"<p><strong>Background: </strong>Over the past 2 decades, virtual reality-based neuropsychological tasks have gained traction as tools for objectively assessing symptoms of attention-deficit/hyperactivity disorder (ADHD), offering enhanced ecological validity by simulating naturalistic environments. To complement realistic settings with an ecologically valid task, we recently developed the virtual email sorting task (VEST), which immerses participants into an office environment where they sort emails while being exposed to distractors.</p><p><strong>Objective: </strong>This study examined for the first time the VEST's sensitivity to medication effects and its specificity in differentiating ADHD from other psychiatric disorders that share overlapping cognitive symptoms, such as major depressive disorder (MDD).</p><p><strong>Methods: </strong>A total of 23 unmedicated individuals with ADHD, 23 medicated individuals with ADHD, and 16 unmedicated individuals with MDD completed the VEST. During alternating distractor phases (DP) and nondistractor phases (NDP), we recorded the participants' task performance; head, torso, and leg actigraphy; eye movements; and brain activity using functional near-infrared spectroscopy (fNIRS), and subjective symptom ratings. Correlational analyses of main objective and subjective task-related parameters were computed. Data were analyzed using mixed-design ANOVAs.</p><p><strong>Results: </strong>Processing time variability increased over time in participants with MDD and unmedicated ADHD as indicated by a group × block interaction (P=.04; η<sup>2</sup><sub>p</sub>=0.10), while a group × phase interaction (P=.009; η<sup>2</sup><sub>p</sub>=0.15) revealed that medicated participants with ADHD showed an increase during DP compared to NDP. Moreover, both ADHD groups exhibited increased head movements during DP compared to NDP (trend group × phase interaction: P=.09; η<sup>2</sup><sub>p</sub>=0.08), an effect not observed in the MDD group, and higher rotation during DP in unmedicated individuals with ADHD (P<.001; η<sup>2</sup><sub>p</sub>=0.23). Also, scores in 3 out of 4 subjective symptom intensity ratings of inattention, impulsivity, and emotional dysregulation were higher in at least 1 of the ADHD groups compared to the MDD group. No significant group differences were found in actigraphy measures of the arm and torso, fNIRS brain activity, or eye-tracking data. Regarding correlational analyses, inattention was correlated to off-task gaze (r=0.28; P=.03), hyperactivity with mean processing time (r=0.33; P=.01) and head movement (r=0.35; P=.006), and impulsivity with error rate (r=0.35; P=.006), and various significant correlations between objective parameters were found.</p><p><strong>Conclusions: </strong>Our findings highlight the potential of the VEST to differentiate between ADHD and MDD, as well as to detect medication-related effects within ADHD. The results underscore the value of multimodal and ecological assessmen","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e85351"},"PeriodicalIF":3.0,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12993270/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147327448","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}
Jordan R Hill, Aaron Ganci, Noll L Campbell, Andrew C Pickett, Michelle A Chui, Ephrem Abebe, Richard J Holden
Background: Participatory co-design is a design approach that involves end users in intervention design and its use in health care applications has become widespread. Traditionally, co-design has been conducted in person in a laboratory-based setting; however, it has recently shifted to being performed remotely. Remote co-design has the potential to overcome some of the limitations of traditional in-person approaches, including expanding a study's geographic reach, recruiting participants from underrepresented groups, reducing power imbalances between researchers and participants, and enhancing engagement through online tools. Given these benefits, further reporting and refinement of remote co-design methods are needed.
Objective: This paper's objective is to present our Remote and Accessible Participatory Intervention Design (RAPID) method and discuss the choices and challenges we encountered adapting participatory co-design for remote use.
Methods: We adapted our previously developed 5-step in-person participatory co-design method for health intervention design. To apply the adapted co-design method, we recruited 2 groups of 5 participants (one of older adult pharmacy patients and the other of pharmacy staff) to design a digital kiosk for use by older adults to promote safe over-the-counter medication purchases in retail pharmacies.
Results: Adaptations made to the co-design process were classified under the following categories: facilitation; collaboration, communication, and sensemaking; accessibility and universality; tangible tools and games; and research compliance. Anecdotally, the remote co-design process took longer when compared to in person due to shorter sessions and between-session refinement, but it allowed for flexible scheduling and makeup sessions when required.
Conclusions: Our RAPID method offers an approach to remote co-design that other teams can implement or adapt to their needs. Our experiences with RAPID identify certain drawbacks to remote co-design; however, these are balanced by advantages in convenience and flexibility.
{"title":"Developing mHealth IT for Older Adult Medication Safety: Remote Participatory Co-Design Using the RAPID Method.","authors":"Jordan R Hill, Aaron Ganci, Noll L Campbell, Andrew C Pickett, Michelle A Chui, Ephrem Abebe, Richard J Holden","doi":"10.2196/82366","DOIUrl":"10.2196/82366","url":null,"abstract":"<p><strong>Background: </strong>Participatory co-design is a design approach that involves end users in intervention design and its use in health care applications has become widespread. Traditionally, co-design has been conducted in person in a laboratory-based setting; however, it has recently shifted to being performed remotely. Remote co-design has the potential to overcome some of the limitations of traditional in-person approaches, including expanding a study's geographic reach, recruiting participants from underrepresented groups, reducing power imbalances between researchers and participants, and enhancing engagement through online tools. Given these benefits, further reporting and refinement of remote co-design methods are needed.</p><p><strong>Objective: </strong>This paper's objective is to present our Remote and Accessible Participatory Intervention Design (RAPID) method and discuss the choices and challenges we encountered adapting participatory co-design for remote use.</p><p><strong>Methods: </strong>We adapted our previously developed 5-step in-person participatory co-design method for health intervention design. To apply the adapted co-design method, we recruited 2 groups of 5 participants (one of older adult pharmacy patients and the other of pharmacy staff) to design a digital kiosk for use by older adults to promote safe over-the-counter medication purchases in retail pharmacies.</p><p><strong>Results: </strong>Adaptations made to the co-design process were classified under the following categories: facilitation; collaboration, communication, and sensemaking; accessibility and universality; tangible tools and games; and research compliance. Anecdotally, the remote co-design process took longer when compared to in person due to shorter sessions and between-session refinement, but it allowed for flexible scheduling and makeup sessions when required.</p><p><strong>Conclusions: </strong>Our RAPID method offers an approach to remote co-design that other teams can implement or adapt to their needs. Our experiences with RAPID identify certain drawbacks to remote co-design; however, these are balanced by advantages in convenience and flexibility.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e82366"},"PeriodicalIF":3.0,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12980070/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147345424","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}
Tony Estrella, Lluis Capdevila, Carla Alfonso, Josep-Maria Losilla
<p><strong>Background: </strong>Advances in data science and technology have transformed lifestyle research by enabling the integration of multimodal information and the generation of large-scale datasets. Despite the growing interest in machine learning (ML) within health behavior research, significant methodological gaps remain.</p><p><strong>Objective: </strong>The study aims to systematically review the applications of supervised ML algorithms in the analysis of healthy lifestyle data, with a particular focus on the methodological approaches used. The specific objectives are to explore the types and sources of data used for health outcomes, examine the ML processes used, including explainable artificial intelligence (XAI) methods, and review the software tools used. Additionally, this review aims to provide practical guidelines to enhance the quality and transparency of future ML research in health.</p><p><strong>Methods: </strong>Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) recommendations, the search was conducted across PubMed, PsycINFO, and Web of Science, yielding 65 studies that met the inclusion criteria.</p><p><strong>Results: </strong>Most studies (48/65, 74%) integrated multidomain data from physical activity, diet, sleep, and stress. Data sources were split between self-acquired data (33/65, 51%) and health repositories (32/65, 49%). Single-item measurements were common, particularly for physical activity, diet, and sleep. Although 40 of 65 studies used a multimodel approach, random forest was the most frequently applied algorithm. To improve explainability, 22 of 65 (33.84%) studies incorporated specific XAI methods, with 21 using Shapley Additive Explanation values and 1 using local interpretable model-agnostic explanations. R (R Core Team) and Python (Python Software Foundation) were the most widely used software tools, with variation in the libraries used.</p><p><strong>Conclusions: </strong>This review highlights methodological gaps in the application of supervised ML to healthy lifestyle data. The ML workflow should span from data acquisition to explainability, using iterative steps to improve methodological rigor. Although multidomain data collection enhances the understanding of health issues related to lifestyle, representativeness remains limited due to methodological shortcomings in data acquisition. While random forest was the most commonly used algorithm, a multimodel approach is recommended for a comprehensive comparison. Lifestyle components consistently ranked among the top features in studies integrating XAI. Incorporating XAI methods into the ML pipeline can support personalized interventions, provided data collection is accurate. The R metapackage (tidymodels; Max Kuhn and Hadley Wickham) facilitates process evaluation through unified syntax, improving replicability. Methodological and reporting guidelines and a checklist are provided
背景：数据科学和技术的进步使多模式信息的集成和大规模数据集的生成成为可能，从而改变了生活方式研究。尽管人们对健康行为研究中的机器学习（ML）越来越感兴趣，但在方法上仍然存在重大差距。目的：本研究旨在系统地回顾监督机器学习算法在健康生活方式数据分析中的应用，特别关注所使用的方法方法。具体目标是探索用于健康结果的数据类型和来源，检查所使用的机器学习过程，包括可解释的人工智能（XAI）方法，并审查所使用的软件工具。此外，本综述旨在提供实用指南，以提高卫生领域未来ML研究的质量和透明度。方法：根据PRISMA-ScR（系统评价和荟萃分析扩展范围评价的首选报告项目）建议，在PubMed， PsycINFO和Web of Science上进行搜索，产生65项符合纳入标准的研究。结果：大多数研究（48/ 65,74 %）整合了来自身体活动、饮食、睡眠和压力的多领域数据。数据源分为自获取数据（33/65,51%）和健康存储库（32/65,49%）。单项测量很常见，尤其是在体力活动、饮食和睡眠方面。虽然65项研究中有40项使用了多模型方法，但随机森林是最常用的算法。为了提高可解释性，65项研究中有22项（33.84%）采用了特定的XAI方法，其中21项使用了Shapley加性解释值，1项使用了局部可解释的模型不可知论解释。R （R Core Team）和Python （Python Software Foundation）是使用最广泛的软件工具，使用的库有所不同。结论：这篇综述强调了监督式机器学习在健康生活方式数据应用中的方法学空白。机器学习工作流应该从数据获取到可解释性，使用迭代步骤来提高方法的严谨性。尽管多领域数据收集增强了对与生活方式相关的健康问题的理解，但由于数据获取方法上的缺陷，代表性仍然有限。虽然随机森林是最常用的算法，但建议采用多模型方法进行全面比较。在集成XAI的研究中，生活方式组件始终名列前茅。将XAI方法整合到ML管道中可以支持个性化干预，前提是数据收集准确。R元包（tidymodels； Max Kuhn和Hadley Wickham）通过统一的语法简化了过程评估，提高了可复制性。提供了方法和报告指南以及清单，以提高多学科ML研究的透明度和可重复性。
{"title":"Machine Learning for the Analysis of Healthy Lifestyle Data: Scoping Review and Guidelines.","authors":"Tony Estrella, Lluis Capdevila, Carla Alfonso, Josep-Maria Losilla","doi":"10.2196/78648","DOIUrl":"10.2196/78648","url":null,"abstract":"<p><strong>Background: </strong>Advances in data science and technology have transformed lifestyle research by enabling the integration of multimodal information and the generation of large-scale datasets. Despite the growing interest in machine learning (ML) within health behavior research, significant methodological gaps remain.</p><p><strong>Objective: </strong>The study aims to systematically review the applications of supervised ML algorithms in the analysis of healthy lifestyle data, with a particular focus on the methodological approaches used. The specific objectives are to explore the types and sources of data used for health outcomes, examine the ML processes used, including explainable artificial intelligence (XAI) methods, and review the software tools used. Additionally, this review aims to provide practical guidelines to enhance the quality and transparency of future ML research in health.</p><p><strong>Methods: </strong>Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) recommendations, the search was conducted across PubMed, PsycINFO, and Web of Science, yielding 65 studies that met the inclusion criteria.</p><p><strong>Results: </strong>Most studies (48/65, 74%) integrated multidomain data from physical activity, diet, sleep, and stress. Data sources were split between self-acquired data (33/65, 51%) and health repositories (32/65, 49%). Single-item measurements were common, particularly for physical activity, diet, and sleep. Although 40 of 65 studies used a multimodel approach, random forest was the most frequently applied algorithm. To improve explainability, 22 of 65 (33.84%) studies incorporated specific XAI methods, with 21 using Shapley Additive Explanation values and 1 using local interpretable model-agnostic explanations. R (R Core Team) and Python (Python Software Foundation) were the most widely used software tools, with variation in the libraries used.</p><p><strong>Conclusions: </strong>This review highlights methodological gaps in the application of supervised ML to healthy lifestyle data. The ML workflow should span from data acquisition to explainability, using iterative steps to improve methodological rigor. Although multidomain data collection enhances the understanding of health issues related to lifestyle, representativeness remains limited due to methodological shortcomings in data acquisition. While random forest was the most commonly used algorithm, a multimodel approach is recommended for a comprehensive comparison. Lifestyle components consistently ranked among the top features in studies integrating XAI. Incorporating XAI methods into the ML pipeline can support personalized interventions, provided data collection is accurate. The R metapackage (tidymodels; Max Kuhn and Hadley Wickham) facilitates process evaluation through unified syntax, improving replicability. Methodological and reporting guidelines and a checklist are provided ","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e78648"},"PeriodicalIF":3.0,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12954701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147345445","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}
Henrik Pedersen, Tatiana Skliarova, Liv S Engvik, Arthur Mandahl, Carlos De Las Cuevas, Audun Havnen, Mariela Loreto Lara-Cabrera
<p><strong>Background: </strong>Specialized mental health services are facing high demand, potentially leading to lower-quality care. One solution may be to prepare patients for attending treatment. Digital pretherapy psychoeducation may be particularly relevant. However, the effectiveness of such an intervention depends on user engagement and satisfaction, and usability is therefore one of the most important factors.</p><p><strong>Objective: </strong>This article has 2 objectives. Study 1 describes the development of StartHelp, a co-created digital pretherapy psychoeducation program for patients on waiting lists before their first consultation in outpatient specialized mental health services. Study 2 explores the usability of StartHelp, aiming to identify potential issues and assess whether the intervention is suitable for further evaluation in a randomized controlled trial.</p><p><strong>Methods: </strong>Guided by co-creation principles, we developed StartHelp in accordance with the Guidance for Reporting Involvement of Patients and the Public (GRIPP2) checklist. To assess the app's usability, we recruited 10 patients from specialized mental health care to complete tasks during individual think-aloud interviews. Afterward, they completed questionnaires, including open-ended questions, an item assessing perceived video quality, 2 versions of the System Usability Scale (SUS), the 4-item Client Satisfaction Questionnaire (CSQ-4), and a modified version of the CSQ-4 (CSQ-Video). The StartHelp project group discussed the results, and solutions to the identified issues were proposed and implemented.</p><p><strong>Results: </strong>Study 1 involved the development of StartHelp over 24 months. The app comprises 27 tasks, including 24 videos and links to 14 websites containing in-depth information. Study 2 involved usability testing with 5 men and 5 women. SUS scores for StartHelp's videos indicated good usability, with a mean of 83.7. By contrast, SUS scores related to navigating StartHelp's overarching architecture were barely acceptable, with a mean of 63.6. For the CSQ-4, the sample mean was 12.3, indicating moderate satisfaction. Mean scores on the CSQ-Video (10.9) indicated satisfaction in the lower moderate range. However, patients perceived the videos as high quality and rated them as nonoffensive. The qualitative findings supported the quantitative results. The usability tests revealed 1 major issue and several minor issues. The primary issue concerned navigation of the overarching technological infrastructure on which StartHelp was developed, rather than StartHelp itself. To address these issues and impracticalities related to interacting with the overarching technological infrastructure, we made minor changes to the StartHelp app.</p><p><strong>Conclusions: </strong>Through a collaborative co-creation process, we developed StartHelp, a digital pretherapy psychoeducation program. Usability testing indicated that the content itself was highly
{"title":"Co-Created Digital Pretherapy Psychoeducation for Outpatients in Specialized Mental Health Care: Usability Evaluation and Patient Satisfaction Study.","authors":"Henrik Pedersen, Tatiana Skliarova, Liv S Engvik, Arthur Mandahl, Carlos De Las Cuevas, Audun Havnen, Mariela Loreto Lara-Cabrera","doi":"10.2196/80130","DOIUrl":"10.2196/80130","url":null,"abstract":"<p><strong>Background: </strong>Specialized mental health services are facing high demand, potentially leading to lower-quality care. One solution may be to prepare patients for attending treatment. Digital pretherapy psychoeducation may be particularly relevant. However, the effectiveness of such an intervention depends on user engagement and satisfaction, and usability is therefore one of the most important factors.</p><p><strong>Objective: </strong>This article has 2 objectives. Study 1 describes the development of StartHelp, a co-created digital pretherapy psychoeducation program for patients on waiting lists before their first consultation in outpatient specialized mental health services. Study 2 explores the usability of StartHelp, aiming to identify potential issues and assess whether the intervention is suitable for further evaluation in a randomized controlled trial.</p><p><strong>Methods: </strong>Guided by co-creation principles, we developed StartHelp in accordance with the Guidance for Reporting Involvement of Patients and the Public (GRIPP2) checklist. To assess the app's usability, we recruited 10 patients from specialized mental health care to complete tasks during individual think-aloud interviews. Afterward, they completed questionnaires, including open-ended questions, an item assessing perceived video quality, 2 versions of the System Usability Scale (SUS), the 4-item Client Satisfaction Questionnaire (CSQ-4), and a modified version of the CSQ-4 (CSQ-Video). The StartHelp project group discussed the results, and solutions to the identified issues were proposed and implemented.</p><p><strong>Results: </strong>Study 1 involved the development of StartHelp over 24 months. The app comprises 27 tasks, including 24 videos and links to 14 websites containing in-depth information. Study 2 involved usability testing with 5 men and 5 women. SUS scores for StartHelp's videos indicated good usability, with a mean of 83.7. By contrast, SUS scores related to navigating StartHelp's overarching architecture were barely acceptable, with a mean of 63.6. For the CSQ-4, the sample mean was 12.3, indicating moderate satisfaction. Mean scores on the CSQ-Video (10.9) indicated satisfaction in the lower moderate range. However, patients perceived the videos as high quality and rated them as nonoffensive. The qualitative findings supported the quantitative results. The usability tests revealed 1 major issue and several minor issues. The primary issue concerned navigation of the overarching technological infrastructure on which StartHelp was developed, rather than StartHelp itself. To address these issues and impracticalities related to interacting with the overarching technological infrastructure, we made minor changes to the StartHelp app.</p><p><strong>Conclusions: </strong>Through a collaborative co-creation process, we developed StartHelp, a digital pretherapy psychoeducation program. Usability testing indicated that the content itself was highly ","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e80130"},"PeriodicalIF":3.0,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12982959/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147310280","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}
Ken Kurisu, Yoshiharu Yamamoto, Tomohisa Aoyama, Toshimasa Yamauchi, Kazuhiro Yoshiuchi
Background: While behavioral interventions remain an evidence-based treatment for obesity, they often require long durations and frequent sessions. To address this, we hypothesized that interventions delivered in daily life via a smartphone app combined with personalized optimization using reinforcement learning may effectively support behavior changes.
Objective: This study aimed to develop and evaluate the feasibility of such an app for individuals with obesity.
Methods: We developed a smartphone app to assist in setting and reviewing daily behaviors related to weight loss. On the screen on which daily behaviors were shown, the order of presentation was optimized using Thompson sampling, a multiarmed bandit algorithm. Twenty individuals with obesity used the app for 4 weeks, and the daily app use rates were quantified. Body weight and mood status were measured daily during the study, and a brief-type self-administered diet history questionnaire and the International Physical Activity Questionnaire were administered at the beginning and end of the study. Changes in these measures were evaluated using the Wilcoxon signed rank test. Furthermore, the longitudinal data collected during this study were analyzed using a linear mixed-effects model to examine factors related to the number of behaviors performed daily.
Results: All 20 recruited individuals with obesity completed the 4-week study schedule. The median app use rate was 98.3% (range 76.9%-100%). Significant improvements were observed in BMI (median at start 34.9 kg/m2, range 27.4-52.9; median at end 34.1 kg/m2, range 26.7-51.0; P=.01), as well as daily energy intake and weekend sitting time. The linear mixed-effects model showed a significant association between higher preceding depressive mood levels and fewer behaviors (P<.001).
Conclusions: The feasibility of the smartphone app using reinforcement learning for obesity was sufficient, and the potential effectiveness of the treatment was suggested. Preceding depressive mood may influence daily behaviors related to weight loss.
{"title":"Smartphone App Using Reinforcement Learning for Obesity: Single-Arm Feasibility Study.","authors":"Ken Kurisu, Yoshiharu Yamamoto, Tomohisa Aoyama, Toshimasa Yamauchi, Kazuhiro Yoshiuchi","doi":"10.2196/77323","DOIUrl":"10.2196/77323","url":null,"abstract":"<p><strong>Background: </strong>While behavioral interventions remain an evidence-based treatment for obesity, they often require long durations and frequent sessions. To address this, we hypothesized that interventions delivered in daily life via a smartphone app combined with personalized optimization using reinforcement learning may effectively support behavior changes.</p><p><strong>Objective: </strong>This study aimed to develop and evaluate the feasibility of such an app for individuals with obesity.</p><p><strong>Methods: </strong>We developed a smartphone app to assist in setting and reviewing daily behaviors related to weight loss. On the screen on which daily behaviors were shown, the order of presentation was optimized using Thompson sampling, a multiarmed bandit algorithm. Twenty individuals with obesity used the app for 4 weeks, and the daily app use rates were quantified. Body weight and mood status were measured daily during the study, and a brief-type self-administered diet history questionnaire and the International Physical Activity Questionnaire were administered at the beginning and end of the study. Changes in these measures were evaluated using the Wilcoxon signed rank test. Furthermore, the longitudinal data collected during this study were analyzed using a linear mixed-effects model to examine factors related to the number of behaviors performed daily.</p><p><strong>Results: </strong>All 20 recruited individuals with obesity completed the 4-week study schedule. The median app use rate was 98.3% (range 76.9%-100%). Significant improvements were observed in BMI (median at start 34.9 kg/m2, range 27.4-52.9; median at end 34.1 kg/m2, range 26.7-51.0; P=.01), as well as daily energy intake and weekend sitting time. The linear mixed-effects model showed a significant association between higher preceding depressive mood levels and fewer behaviors (P<.001).</p><p><strong>Conclusions: </strong>The feasibility of the smartphone app using reinforcement learning for obesity was sufficient, and the potential effectiveness of the treatment was suggested. Preceding depressive mood may influence daily behaviors related to weight loss.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e77323"},"PeriodicalIF":3.0,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12945086/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147310703","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}
Marco A García-Luna, Miguel García-Jaén, Daniel Ruiz-Fernández, Carmen Manchado, Juan M Cortell-Tormo
<p><strong>Background: </strong>Postural education is crucial during childhood and adolescence, yet traditional approaches often lack engaging tools that promote awareness and behavioral change. Wearable technologies and real-time biofeedback systems offer new opportunities to support postural learning through immediate, embodied feedback. However, most existing systems focus on clinical rehabilitation, with few designed specifically for educational use.</p><p><strong>Objective: </strong>This study aimed to design, develop, and evaluate the usability and technical performance of EduBack, a mobile app that delivers real-time lumbar posture biofeedback through inertial sensors, with a specific focus on educational settings such as schools and physical education environments.</p><p><strong>Methods: </strong>EduBack was developed using Kotlin (JetBrains) for Android OS (Google; version 8.0 and above) and integrates with 2 inertial measurement units via Bluetooth (2.4 GHz). The app provides visual biofeedback through a dynamic interface showing a virtual spine, corrective messages, and a color-coded alignment bar. The usability evaluation involved 24 undergraduate students (mean age 21.4, SD 1.8 y) who used the app in a controlled session. Participants completed the system usability scale and open-ended qualitative feedback questions. Technical performance data were collected from system logs, latency measurements, and received signal strength indicator values to assess connection stability and sensor-to-app communication.</p><p><strong>Results: </strong>The average system usability scale score was 83.5 (SD 8.7), indicating excellent usability. Participants reported the interface to be intuitive, the biofeedback visualization clear, and the posture information easy to interpret. Qualitative responses highlighted the app's potential to support postural awareness and motor learning, especially in school-aged populations. From a technical perspective, the system demonstrated robust performance: mean data transfer latency was approximately 120 milliseconds, with less than 1% packet loss across sessions. Received signal strength indicator values consistently remained within the optimal signal range, confirming stable Bluetooth connectivity. All session data were successfully stored and exported without errors. The real-time posture tracking displayed on the app closely matched raw sensor data, ensuring fidelity in feedback.</p><p><strong>Conclusions: </strong>EduBack is a usable and technically stable mobile app designed to support postural education through wearable sensors and real-time biofeedback. Its user-friendly interface and reliable data transmission make it well-suited for use in schools and educational programs targeting postural health. The app fills a gap in the mobile health field by offering a preventive, educational tool rather than a clinical one. Future research should explore its application in younger populations, integration into physi
{"title":"Postural Education in School-Aged Populations: Development and Usability Evaluation of a Mobile Biofeedback App (EduBack).","authors":"Marco A García-Luna, Miguel García-Jaén, Daniel Ruiz-Fernández, Carmen Manchado, Juan M Cortell-Tormo","doi":"10.2196/79282","DOIUrl":"10.2196/79282","url":null,"abstract":"<p><strong>Background: </strong>Postural education is crucial during childhood and adolescence, yet traditional approaches often lack engaging tools that promote awareness and behavioral change. Wearable technologies and real-time biofeedback systems offer new opportunities to support postural learning through immediate, embodied feedback. However, most existing systems focus on clinical rehabilitation, with few designed specifically for educational use.</p><p><strong>Objective: </strong>This study aimed to design, develop, and evaluate the usability and technical performance of EduBack, a mobile app that delivers real-time lumbar posture biofeedback through inertial sensors, with a specific focus on educational settings such as schools and physical education environments.</p><p><strong>Methods: </strong>EduBack was developed using Kotlin (JetBrains) for Android OS (Google; version 8.0 and above) and integrates with 2 inertial measurement units via Bluetooth (2.4 GHz). The app provides visual biofeedback through a dynamic interface showing a virtual spine, corrective messages, and a color-coded alignment bar. The usability evaluation involved 24 undergraduate students (mean age 21.4, SD 1.8 y) who used the app in a controlled session. Participants completed the system usability scale and open-ended qualitative feedback questions. Technical performance data were collected from system logs, latency measurements, and received signal strength indicator values to assess connection stability and sensor-to-app communication.</p><p><strong>Results: </strong>The average system usability scale score was 83.5 (SD 8.7), indicating excellent usability. Participants reported the interface to be intuitive, the biofeedback visualization clear, and the posture information easy to interpret. Qualitative responses highlighted the app's potential to support postural awareness and motor learning, especially in school-aged populations. From a technical perspective, the system demonstrated robust performance: mean data transfer latency was approximately 120 milliseconds, with less than 1% packet loss across sessions. Received signal strength indicator values consistently remained within the optimal signal range, confirming stable Bluetooth connectivity. All session data were successfully stored and exported without errors. The real-time posture tracking displayed on the app closely matched raw sensor data, ensuring fidelity in feedback.</p><p><strong>Conclusions: </strong>EduBack is a usable and technically stable mobile app designed to support postural education through wearable sensors and real-time biofeedback. Its user-friendly interface and reliable data transmission make it well-suited for use in schools and educational programs targeting postural health. The app fills a gap in the mobile health field by offering a preventive, educational tool rather than a clinical one. Future research should explore its application in younger populations, integration into physi","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e79282"},"PeriodicalIF":3.0,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12945092/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147310188","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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