JMIR Formative Research最新文献

{"title":"Online Health Information-Seeking Behaviors Among the Chongqing Population: Cross-Sectional Questionnaire Study.","authors":"Honghui Rong, Lu Lu, Miao He, Tian Guo, Xian Li, Qingliu Tao, Yixin Li, Chuanfen Zheng, Ling Zhang, Fengju Li, Dali Yi, Enyu Lei, Ting Luo, Qinghua Yang, Ji-An Chen","doi":"10.2196/56028","DOIUrl":"10.2196/56028","url":null,"abstract":"<p><strong>Background: </strong>With the rapid development of the internet and its widespread use, online health information-seeking (OHIS) has become a popular and important research topic. Various benefits of OHIS are well recognized. However, OHIS seems to be a mixed blessing. Research on OHIS has been reported in Western countries and in high-income regions in eastern China. Studies on the population in the western region of China, such as Chongqing, are still limited.</p><p><strong>Objective: </strong>The aim of the study was to identify the prevalence, common topics, and common methods of health information-seeking and the factors influencing these behaviors among the Chongqing population.</p><p><strong>Methods: </strong>This cross-sectional questionnaire study was conducted from September to October 2021. A web-based questionnaire was sent to users aged 15 years and older in Chongqing using a Chinese web-based survey hosting site (N=14,466). Data on demographics, web-based health information resources, and health topics were collected. Factors that may influence health literacy were assessed using the chi-square test and multivariate logistic regression models.</p><p><strong>Results: </strong>A total of 67.1% (9704/14,466) of the participants displayed OHIS behaviors. Participants who were younger, had a higher educational level, and worked as medical staff or teachers were more likely to engage in OHIS, while those living in rural areas, ethnic minorities, and farmers were less likely to seek health information on the web (P<.01). Among the Chongqing population, the most common topic searched on the internet was health behavior and literacy (87.4%, 8483/9704), and the most popular method of seeking health information on the web was through WeChat (77.0%, 7468/9704).</p><p><strong>Conclusions: </strong>OHIS is prevalent in Chongqing. Further research could be performed based on the influencing factors identified herein and high-priority, effective ways of improving the OHIS behaviors of the Chongqing population.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e56028"},"PeriodicalIF":2.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12068888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144016261","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}

{"title":"Characterizing Patient-Reported Fatigue Using Electronic Diaries in Neurodegenerative and Immune-Mediated Inflammatory Diseases: Observational Study.","authors":"Adrien Bennetot, Rana Zia Ur Rehman, Robbin Romijnders, Zhi Li, Victoria Macrae, Kristen Davies, Wan-Fai Ng, Walter Maetzler, Jennifer Kudelka, Hanna Hildesheim, Kirsten Emmert, Emma Paulides, C Janneke van der Woude, Ralf Reilmann, Svenja Aufenberg, Meenakshi Chatterjee, Nikolay V Manyakov, Clémence Pinaud, Stefan Avey","doi":"10.2196/65879","DOIUrl":"https://doi.org/10.2196/65879","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Fatigue is a prevalent and debilitating symptom in many chronic conditions, including immune-mediated inflammatory diseases (IMIDs) and neurodegenerative diseases (NDDs). Fatigue often fluctuates significantly within and between days, yet traditional patient-reported outcomes (PROs) typically rely on recall periods of a week or more, potentially missing these short-term variations. The development of digital tools, such as electronic diaries (eDiaries), offers a unique opportunity to collect granular, real-time data. However, the feasibility, adherence, and comparability of eDiary-based assessments to established PROs require further investigation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to evaluate the feasibility and acceptability of using a high-frequency eDiary to capture intraday variability in fatigue and to compare eDiary data with scores obtained from the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F), a validated weekly recall PRO.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Data were collected from 159 participants enrolled in the IDEA-FAST (Identifying Digital Endpoints to Assess Fatigue, Sleep and Activities in Daily Living in Neurodegenerative Disorders and Immune-Mediated Inflammatory Diseases) feasibility study; a 4-week prospective observational study conducted at 4 European centers. Participants included individuals with NDDs (n=39), IMIDs (n=78), and healthy volunteers (n=42). Participants used an eDiary to report their physical and mental fatigue levels up to 4 times daily on a 7-point Likert scale (0=low and 6=high). Adherence was calculated as the proportion of completed eDiary entries relative to the total expected entries. Correlations between averaged eDiary scores and weekly FACIT-F scores were analyzed.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Adherence to the eDiary protocol was 5505/8880 (61.99%) overall, varying by cohort, with the highest adherence (1117/1200, 93.07%) observed in the primary Sjögren syndrome cohort and the lowest adherence in the Parkinson disease (410/960, 42.7%) and Huntington disease (320/720, 44.4%) cohorts. The average adherence was 430/1680 (43.45%) in the NDD cohorts and 3367/4560 (73.84%) in the IMID cohorts. Fatigue levels showed clear diurnal variation, with significantly higher fatigue reported in the evening compared to the morning (P&lt;.001). A moderate correlation (Spearman=0.46, P&lt;.001) was observed between eDiary fatigue scores and FACIT-F scores, with stronger cohort-specific associations for certain FACIT-F items. These results indicate that eDiaries provide complementary insights to weekly PROs by capturing intraday fluctuations in fatigue.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study demonstrates the feasibility, acceptability, and validity of using high-frequency eDiaries to assess fatigue in chronic conditions. By effectively detecting intra- and interday fatigue variations, eDiaries complement traditional PROs such as FACIT-F, offering ","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65879"},"PeriodicalIF":2.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12068833/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143965404","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}

{"title":"Acceptability and Usability of a Digital Behavioral Health Platform for Youth at Risk of Suicide: User-Centered Design Study With Patients, Practitioners, and Business Gatekeepers.","authors":"Trinity Chloe Tse, Lauren S Weiner, Carter J Funkhouser, Danielle DeLuise, Colleen Cullen, Zachary Blumkin, Casey O'Brien, Randy P Auerbach, Nicholas B Allen","doi":"10.2196/65418","DOIUrl":"10.2196/65418","url":null,"abstract":"<p><strong>Background: </strong>Youth suicide rates are climbing, underscoring the need to improve clinical care. Personal smartphones can provide an understanding of proximal risk factors associated with suicide and facilitate consistent contact between patients and practitioners to improve treatment engagement and effectiveness. The Vira digital behavior change platform (Vira) consists of a patient smartphone app and a web-based practitioner portal (Vira Pro) that integrates objective mobile sensing data with Health Insurance Portability and Accountability Act (HIPAA)-compliant communication tools. Through Vira, practitioners can continuously assess patients' real-world behavior and provide clinical tools to enhance treatment via just-in-time behavior change support.</p><p><strong>Objective: </strong>This study aimed to explore the acceptability and usability of the minimal viable product version of Vira through a user-centered design (UCD) approach and to identify barriers to implementing Vira in the context of an adolescent intensive outpatient program.</p><p><strong>Methods: </strong>Over 2 iterative phases, feedback was gathered from adolescent patients (n=16), mental health practitioners (n=11), and business gatekeepers (n=5). The mixed methods UCD approach included individual semistructured interviews (eg, perspectives on treatment and attitudes toward digital tools), surveys (eg, usability), and unmoderated user testing sessions (eg, user experience).</p><p><strong>Results: </strong>Overall, participants expressed optimism regarding Vira, particularly among adolescents, who showed high satisfaction with the app's interface and design. However, clinicians reported more mixed views, agreeing that it would be useful in treatment but also expressing concerns about the volume and displays of patient data in Vira Pro, workload management, and boundaries. Gatekeepers identified usability issues and implementation barriers related to electronic health records but also recognized Vira's potential to enhance treatment outcomes. Feedback from stakeholders informed several crucial changes to the platform, including adjustments to data-sharing protocols, user interface enhancements, and modifications to training methods.</p><p><strong>Conclusions: </strong>Vira has a high potential to improve patient engagement and improve clinical outcomes among high-risk youth. Iterative UCD and ongoing stakeholder engagement are essential for developing technology-based interventions that effectively meet the needs of diverse end users and align with clinical workflows.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65418"},"PeriodicalIF":2.0,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12084771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143965399","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}

{"title":"Evaluating Feasibility and Acceptability of the \"My HeartHELP\" Mobile App for Promoting Heart-Healthy Lifestyle Behaviors: Mixed Methods Study.","authors":"Jina Choo, Songwhi Noh, Yura Shin","doi":"10.2196/66108","DOIUrl":"https://doi.org/10.2196/66108","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Few mobile apps have strategies for self-monitoring multiple heart-healthy behaviors simultaneously, as well as automated and tailored feedback on individual behavioral outcomes for cardiovascular health. An app named \"My HeartHELP\" was developed for the general adult population to promote 6 heart-healthy lifestyle behaviors-physical activity, nonsedentary behaviors, healthy eating behaviors, nonsmoking, no alcohol binge drinking, and self-assessment of body weight. Three behavioral strategies were used: (1) text messaging the users for information on cardiovascular health, (2) self-monitoring of 6 heart-healthy behaviors to fill out the blanks of behavioral items, and (3) automated and tailored feedback messaging to users for behavioral outcomes obtained from self-monitoring.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;This study aimed to evaluate the feasibility and acceptability of the \"My HeartHELP\" app.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The participants were 29 community residents in Seoul, South Korea, who met at least 1 criterion of metabolic syndrome. To evaluate the feasibility, we assessed 3 records, which are as follows: First, the \"record for self-monitoring\" was determined as feasible if an average percentage for each of the 6 behaviors over 4 weeks was 75% or higher based on percentages of participants who completed to record each of 6 heart-healthy behaviors. Second, the \"record for access to the app\" was determined as feasible if users accessed at least once a day on average per week. Third, \"records for behavioral changes\" over 4 weeks were collected via a self-reported questionnaire. To evaluate acceptability, we used an assessment tool comprising 12 items that included subscales for comprehensibility, ease, health benefits, technical completeness, overall satisfaction, and recommendation to others on a 5-point Likert scale. Acceptability was determined as acceptable if the average scores for the total scale and each subscale were 3.5 points or greater. Second, qualitative data were collected through 2 focus groups, each consisting of 14 or 15 participants. All data were collected in June and July 2022.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;During the 4 weeks, 95.6% (range: 85.8%-97.4%) of the participants adhered to more than 75% of \"completion of daily self-monitoring of each heart-healthy behavior,\" having met the criterion. The participants accessed the app on average 1.8 (SD 1.70) times per day, meeting the criteria. Participants had positive behavioral changes in all 6 behaviors, of which nonsedentary behavior (10%-28%; χ21=1.76; P&lt;.001) and non-fast-food intake were especially statistically significant (72%-93%; χ21=5.64; P=.03) over 4 weeks. Participants reported 3.8 points for a total score of acceptability and more than 3.5 points for all subscales, which met the criterion. Qualitative data obtained from focus groups indicated that automated and tailored feedback messages motivated participants to promot","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e66108"},"PeriodicalIF":2.0,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12064136/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144019532","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}

{"title":"Predicting Transvaginal Surgical Mesh Exposure Outcomes Using an Integrated Dataset of Blood Cytokine Levels and Medical Record Data: Machine Learning Approach.","authors":"Mihyun Lim Waugh, Tyler Mills, Nicholas Boltin, Lauren Wolf, Patti Parker, Ronnie Horner, Thomas L Wheeler Ii, Richard L Goodwin, Melissa A Moss","doi":"10.2196/59631","DOIUrl":"https://doi.org/10.2196/59631","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Transvaginal insertion of polypropylene mesh was extensively used in surgical procedures to treat pelvic organ prolapse (POP) due to its cost-efficiency and durability. However, studies have reported a high rate of complications, including mesh exposure through the vaginal wall. Developing predictive models via supervised machine learning holds promise in identifying risk factors associated with such complications, thereby facilitating better informed surgical decisions. Previous studies have demonstrated the efficacy of anticipating medical outcomes by employing supervised machine learning approaches that integrate patient health care data with laboratory findings. However, such an approach has not been adopted within the realm of POP mesh surgery.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We examined the efficacy of supervised machine learning to predict mesh exposure following transvaginal POP surgery using 3 different datasets: (1) patient medical record data, (2) biomaterial-induced blood cytokine levels, and (3) the integration of both.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Blood samples and medical record data were collected from 20 female patients who had prior surgical intervention for POP using transvaginal polypropylene mesh. Of these subjects, 10 had experienced mesh exposure through the vaginal wall following surgery, and 10 had not. Standardized medical record data, including vital signs, previous diagnoses, and social history, were acquired from patient records. In addition, cytokine levels in patient blood samples incubated with sterile polypropylene mesh were measured via multiplex assay. Datasets were created with patient medical record data alone, blood cytokine levels alone, and the integration of both data. The data were split into 70% and 30% for training and testing sets, respectively, for machine learning models that predicted the presence or absence of postsurgical mesh exposure.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Upon training the models with patient medical record data, systolic blood pressure, pulse pressure, and a history of alcohol usage emerged as the most significant factors for predicting mesh exposure. Conversely, when the models were trained solely on blood cytokine levels, interleukin (IL)-1β and IL-12 p40 stood out as the most influential cytokines in predicting mesh exposure. Using the combined dataset, new factors emerged as the primary predictors of mesh exposure: IL-8, tumor necrosis factor-α, and the presence of hemorrhoids. Remarkably, models trained on the integrated dataset demonstrated superior predictive capabilities with a prediction accuracy as high as 94%, surpassing the predictive performance of individual datasets.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Supervised machine learning models demonstrated improved prediction accuracy when trained using a composite dataset that combined patient medical record data and biomaterial-induced blood cytokine levels, surpassing the performance of","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e59631"},"PeriodicalIF":2.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12061202/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143999548","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}

{"title":"Identification of Major Bleeding Events in Postoperative Patients With Malignant Tumors in Chinese Electronic Medical Records: Algorithm Development and Validation.","authors":"Hui Li, Haiyang Yao, Yuxiang Gao, Hang Luo, Changbin Cai, Zhou Zhou, Muhan Yuan, Wei Jiang","doi":"10.2196/66189","DOIUrl":"https://doi.org/10.2196/66189","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Postoperative bleeding is a serious complication following abdominal tumor surgery, but it is often not clearly diagnosed and documented in clinical practice in China. Previous studies have relied on manual interpretation of medical records to determine the presence of postoperative bleeding in patients, which is time-consuming and laborious. More critically, this manual approach severely hinders the efficient analysis of large volumes of medical data, impeding in-depth research into the incidence patterns and risk factors of postoperative bleeding. It remains unclear whether machine learning can play a role in processing large volumes of medical text to identify postoperative bleeding effectively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to develop a machine learning model tool for identifying postoperative patients with major bleeding based on the electronic medical record system.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study used data from the available information in the National Health and Medical Big Data (Eastern) Center in Jiangsu Province of China. We randomly selected the medical records of 2,000 patients who underwent in-hospital tumor resection surgery between January 2018 and December 2021 from the database. Physicians manually classified each note as present or absent for a major bleeding event during the postoperative hospital stay. Feature engineering involved bleeding expressions, high-frequency related expressions, and quantitative logical judgment, resulting in 270 features. Logistic regression (LR), K-nearest neighbor (KNN), and convolutional neural network (CNN) models were developed and trained using the 1600-note training set. The main outcomes were accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Major bleeding was present in 4.31% (69/1600) of the training set and 4.75% (19/400) of the test set. In the test set, the LR method achieved an accuracy of 0.8275, a sensitivity of 0.8947, a specificity of 0.8241, a PPV of 0.2024, an NPV of 0.9937, and an F1-score of 0.3301. The CNN method demonstrated an accuracy of 0.8900, sensitivity of 0.8421, specificity of 0.8924, PPV of 0.2807, NPV of 0.9913, and an F1-score of 0.4211. While the KNN method showed a high specificity of 0.9948 and an accuracy of 0.9575 in the test set, its sensitivity was notably low at 0.2105. The C-statistic for the LR method was 0.9018 and for the CNN method was 0.8830.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Both the LR and CNN methods demonstrate good performance in identifying major bleeding in patients with postoperative malignant tumors from electronic medical records, exhibiting high sensitivity and specificity. Given the higher sensitivity of the LR method (89.47%) and the higher specificity of the CNN method (89.24%) in the test set, both models hold promise for practical application, depending on specific clin","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e66189"},"PeriodicalIF":2.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12061345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144015797","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}

{"title":"Integration of a Mental Health App (e-MICHI) Into a Blended Treatment of Depression in Adolescents: Single-Group, Naturalistic Feasibility Trial.","authors":"Lena Lincke, Tim Martin-Döring, Andrea Daunke, Antonia Sadkowiak, Daria Alexandra Nolkemper, Nina Sproeber-Kolb, Stefanie Bienioschek, Olaf Reis, Michael Kölch","doi":"10.2196/58427","DOIUrl":"https://doi.org/10.2196/58427","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Major depressive disorder is a common diagnosis among adolescents. Cognitive behavioral therapy is recommended as the first line of treatment. Digital health interventions, such as apps, could contribute to treatment. Advantages could be easy accessibility and availability, reduced time for face-to-face therapy, and the ability to intensify therapy by incorporating it into the patients' everyday lives. Challenges such as low adherence rates are common in digital health interventions. Therefore, they need to undergo rigorous testing for feasibility and effectiveness.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;An evaluated, cognitive behavioral therapy-based face-to-face therapy program for depression in adolescents was transformed into an app called e-MICHI. This study examined its feasibility and efficacy for use in blended therapy in outpatient settings.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Adolescents aged 12 to 18 years with major depressive disorder receiving outpatient care were recruited from 2 university hospitals (n=36 included in analysis). The e-MICHI intervention combined daily app engagement over 6 weeks with 3 face-to-face sessions with a therapist. Feasibility was measured using various variables, including an adherence score (0=no or little patient engagement to 3=excellent engagement) and engagement rates (number of modules completed, number of messages sent by participants via the in-app messenger), satisfaction ratings from both participants and therapists, as well as participants' ratings of the usefulness of the antidepressant strategies covered in the app and the transfer of these strategies to everyday practice. Trends of efficacy were evaluated from multiple perspectives (participant self-rating, independent rater, or therapist), using the Beck Depression Inventory-II, the Children's Depression Rating Scale-Revised, and the Clinical Global Impressions-Severity Scale. Feasibility metrics were assessed by analyzing their central tendency and dispersion, efficacy data were analyzed using a repeated measures ANOVA.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;e-MICHI was positively evaluated by both participants and therapists (participants: mean 7.3, SD 1.2 and therapists: mean 7.3, SD 1.1, on a scale from 0=bad to 10=excellent). Participants demonstrated high adherence rates (nearly 80%, n=25, received a \"good\" or \"excellent\" adherence score) and showed overall good engagement (app modules completed [maximum 6]: mean 5.03, SD 1.27 and messages sent via messenger: mean 23, SD 22.1). Participants rated the psychoeducational content of the app as particularly useful and reported consistent practice of the e-MICHI strategies in everyday life. Use of the app was associated with a significant reduction of depressive symptoms (before app use vs 3-month follow-up, Beck Depression Inventory-II: mean -6.76, SD 11.49, P=.01; Children's Depression Rating Scale-Revised: mean -16.45, SD 16.76, P&lt;.001; Clinical Global Impressions-Sever","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e58427"},"PeriodicalIF":2.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12061348/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143966170","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}

{"title":"Incorporating Patient-Reported Outcome Measures and Patient-Reported Experience Measures in Addiction Treatment Services in Belgium: Naturalistic, Longitudinal, Multicenter Cohort Study.","authors":"Amine Zerrouk, Charlotte Migchels, Clara De Ruysscher, Kim Fernandez, Jerome Antoine, Florian De Meyer, Frieda Matthys, Wim van den Brink, Cleo Lina Crunelle, Wouter Vanderplasschen","doi":"10.2196/65686","DOIUrl":"10.2196/65686","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Traditionally, treatment outcomes of service users with a substance use disorder (SUD) are measured using objective and provider-reported indicators. In recent years, there has been a shift toward incorporating patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) to capture service users' perspectives on treatment outcomes and experiences.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The OMER-BE (Outcome Measurement and Evaluation as a Routine Practice in Alcohol and Other Drug Services in Belgium) study evaluates the acceptability and feasibility of PROMs and PREMs in different SUD treatment services, using the recently developed International Consortium for Health Outcomes Measurement Standard Set for Addictions. This paper presents the design and baseline characteristics of the study, indicators of attrition at 45-day follow-up, and the feasibility of the implementation of PROMs and PREMs in residential and outpatient services.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A convenience sample of 189 treatment-seeking individuals with SUD from different inpatient (therapeutic communities and psychiatric centers) and outpatient treatment services was followed for six months. Sociodemographic characteristics; clinical factors; and PROMs including recovery strengths, quality of life, and global health were assessed at baseline and within 3 weeks after starting treatment. Additionally, PROMs and PREMs were measured 45, 90, and 180 days later. Comparisons were made between treatment modalities, and indicators of attrition at the 45-day follow-up were assessed using ANOVA and chi-square tests.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Baseline differences were observed between the three treatment modalities regarding education, SUD treatment history, primary substance, and Attention-Deficit/Hyperactivity Disorder Self-Report scores. Overall, patients in psychiatric treatment centers had a higher education level and less polysubstance use, while outpatients had fewer previous SUD treatments but received relatively more often opioid agonist treatment. Inpatients reported more attention-deficit/hyperactivity disorder symptoms and higher SUD severity than outpatients. Additionally, recovery strength scores were significantly lower in the outpatient group compared to the other groups, particularly in the subdomains of \"Substance Use,\" \"Self-care,\" and \"Outlook on Life.\" At the 45-day follow-up assessment, the attrition rate was 36.6%. Comparisons between participants who completed the 45-day follow-up and those who dropped out revealed that completers were significantly older, had a higher level of education, were more likely to live alone, and were more likely to have a mother born in Belgium. They also had higher average scores on the \"Material Resources\" domain of the Substance Use Recovery Evaluator, which includes questions about stable housing, a steady income, and effective financial management.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Con","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65686"},"PeriodicalIF":2.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12079064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143984721","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}

{"title":"Assessing the Utilization of Electronic Consultations in Genetics: Seven-Year Retrospective Study.","authors":"Sawona Biswas, Joyce So, Robert Wallerstein, Ralph Gonzales, Delphine Tout, Lisa DeAngelis, Aleksandar Rajkovic","doi":"10.2196/63028","DOIUrl":"https://doi.org/10.2196/63028","url":null,"abstract":"<p><strong>Background: </strong>Patient and health care provider access to genetic subspecialists is challenging owing to limited number of genetics experts across the United States. The University of California San Francisco (UCSF) Genetics electronic consultation (e-Consult) service was implemented along with the usual referral pathway to improve access to timely genetic expertise through robust asynchronous provider-to-provider communication.</p><p><strong>Objectives: </strong>This study examined the impact of the UCSF Genetics e-Consult service on patient access to genetics expertise.</p><p><strong>Methods: </strong>A retrospective chart review of 622 e-Consult requests was conducted. Data pertinent to e-Consult completion rates, provider response times, consultation content, and adherence to geneticist recommendations were abstracted.</p><p><strong>Results: </strong>From October 2016 to March 2024, the UCSF Genetics e-Consult service received a total of 622 consultation orders, with yearly volumes increasing from 34 in 2017 to 144 in 2023. A total of 360/622 (57.8%) consultations were completed, of which 197/360 (54.6%) were resolved without requiring a specialty care visit. Of the 262/622 (42.1%) e-Consult orders declined by the geneticist reviewer, 184/262 (70.2%) were scheduled for a synchronous genetics visit due to case complexity precluding an appropriate e-Consult response and 29.8% (78/262) were recommended to be referred to a different and more appropriate specialty. Geneticists responded to 83.9% (522/622) of e-Consults within 3 days, with most spending between 5 and 20 minutes on their e-Consult response. Nearly half of the genetics e-Consult requests (69/144; 47.9%) came from primary care providers and pediatricians. Among the 144 e-Consult requests in 2023, 50.6% (73/144) were about diagnostic queries, 17% (25/144) were on symptom management, and 11% (16/144) were about test interpretation. Provider adherence to geneticists' recommendations was observed in 84% (116/144) of cases.</p><p><strong>Conclusions: </strong>The UCSF Genetics e-Consult service has demonstrated efficiency in providing timely genetic consultations, with a high rate of provider adherence to recommendations. These findings support the potential of e-Consult frameworks as a viable strategy for enhancing access to genetic health care services.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e63028"},"PeriodicalIF":2.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12058035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143999537","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}

{"title":"Correction: Assessing and Improving Data Integrity in Web-Based Surveys: Comparison of Fraud Detection Systems in a COVID-19 Study.","authors":"Stephen Bonett, Willey Lin, Patrina Sexton Topper, James Wolfe, Jesse Golinkoff, Aayushi Deshpande, Antonia Villarruel, José Bauermeister","doi":"10.2196/76462","DOIUrl":"10.2196/76462","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.2196/47091.].</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e76462"},"PeriodicalIF":2.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12079077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143967811","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}