Interactive Journal of Medical Research最新文献

{"title":"Benefits and Risks of AI in Health Care: Narrative Review.","authors":"Margaret Chustecki","doi":"10.2196/53616","DOIUrl":"10.2196/53616","url":null,"abstract":"<p><strong>Background: </strong>The integration of artificial intelligence (AI) into health care has the potential to transform the industry, but it also raises ethical, regulatory, and safety concerns. This review paper provides an in-depth examination of the benefits and risks associated with AI in health care, with a focus on issues like biases, transparency, data privacy, and safety.</p><p><strong>Objective: </strong>This study aims to evaluate the advantages and drawbacks of incorporating AI in health care. This assessment centers on the potential biases in AI algorithms, transparency challenges, data privacy issues, and safety risks in health care settings.</p><p><strong>Methods: </strong>Studies included in this review were selected based on their relevance to AI applications in health care, focusing on ethical, regulatory, and safety considerations. Inclusion criteria encompassed peer-reviewed articles, reviews, and relevant research papers published in English. Exclusion criteria included non-peer-reviewed articles, editorials, and studies not directly related to AI in health care. A comprehensive literature search was conducted across 8 databases: OVID MEDLINE, OVID Embase, OVID PsycINFO, EBSCO CINAHL Plus with Full Text, ProQuest Sociological Abstracts, ProQuest Philosopher's Index, ProQuest Advanced Technologies & Aerospace, and Wiley Cochrane Library. The search was last updated on June 23, 2023. Results were synthesized using qualitative methods to identify key themes and findings related to the benefits and risks of AI in health care.</p><p><strong>Results: </strong>The literature search yielded 8796 articles. After removing duplicates and applying the inclusion and exclusion criteria, 44 studies were included in the qualitative synthesis. This review highlights the significant promise that AI holds in health care, such as enhancing health care delivery by providing more accurate diagnoses, personalized treatment plans, and efficient resource allocation. However, persistent concerns remain, including biases ingrained in AI algorithms, a lack of transparency in decision-making, potential compromises of patient data privacy, and safety risks associated with AI implementation in clinical settings.</p><p><strong>Conclusions: </strong>In conclusion, while AI presents the opportunity for a health care revolution, it is imperative to address the ethical, regulatory, and safety challenges linked to its integration. Proactive measures are required to ensure that AI technologies are developed and deployed responsibly, striking a balance between innovation and the safeguarding of patient well-being.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e53616"},"PeriodicalIF":1.9,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11612599/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142669575","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":"Knowledge, Attitudes, and Behaviors Toward Salt Consumption and Its Association With 24-Hour Urinary Sodium and Potassium Excretion in Adults Living in Mexico City: Cross-Sectional Study.","authors":"Gabriela Gutiérrez-Salmeán, Paola Vanessa Miranda-Alatriste, Patricio Benítez-Alday, Luis Enrique Orozco-Rivera, Nurit Islas-Vargas, Ángeles Espinosa-Cuevas, Ricardo Correa-Rotter, Eloisa Colin-Ramirez","doi":"10.2196/57265","DOIUrl":"10.2196/57265","url":null,"abstract":"<p><strong>Background: </strong>The World Health Organization recommends a daily sodium intake of less than 2000 mg for adults; however, the Mexican population, like many others globally, consumes more sodium than this recommended amount. Excessive sodium intake is often accompanied by inadequate potassium intake. The association between knowledge, attitudes, and behaviors (KAB) and actual sodium intake has yielded mixed results across various populations. In Mexico, however, salt/sodium-related KAB and its relationship with sodium and potassium intake have not been evaluated.</p><p><strong>Objective: </strong>This study primarily aims to describe salt/sodium-related KAB in a Mexican population and, secondarily, to explore the association between KAB and 24-hour urinary sodium and potassium excretion.</p><p><strong>Methods: </strong>We conducted a cross-sectional study in an adult population from Mexico City and the surrounding metropolitan area. Self-reported KAB related to salt/sodium intake was assessed using a survey developed by the Pan American Health Organization. Anthropometric measurements were taken, and 24-hour urinary sodium and potassium excretion levels were determined. Descriptive statistics were stratified by sex and presented as means (SD) or median (25th-75th percentiles) for continuous variables, and as absolute and relative frequencies for categorical variables. The associations between KAB and sodium and potassium excretion were assessed using analysis of covariance, adjusting for age, sex, BMI, and daily energy intake as covariates, with the Šidák correction applied for multiple comparisons.</p><p><strong>Results: </strong>Overall, 232 participants were recruited (women, n=184, 79.3%). The mean urinary sodium and potassium excretion were estimated to be 2582.5 and 1493.5 mg/day, respectively. A higher proportion of men did not know the amount of sodium they consumed compared with women (12/48, 25%, vs 15/184, 8.2%, P=.01). More women reported knowing that there is a recommended amount for daily sodium intake than men (46/184, 25%, vs 10/48, 20.8%, P=.02). Additionally, more than half of men (30/48, 62.5%) reported never or rarely reading food labels, compared with women (96/184, 52.1%, P=.04). Better salt/sodium-related KAB was associated with higher adjusted mean sodium and potassium excretion. For example, mean sodium excretion was 3011.5 (95% CI 2640.1-3382.9) mg/day among participants who reported knowing the difference between salt and sodium, compared with 2592.8 (95% CI 2417.2-2768.3) mg/day in those who reported not knowing this difference (P=.049). Similarly, potassium excretion was 1864.9 (95% CI 1669.6-2060.3) mg/day for those who knew the difference, compared with 1512.5 (95% CI 1420.1-1604.8) mg/day for those who did not (P=.002). Additionally, higher urinary sodium excretion was observed among participants who reported consuming too much sodium (3216.0 mg/day, 95% CI 2867.1-3565.0 mg/day) compared with those wh","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e57265"},"PeriodicalIF":1.9,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11612592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142669579","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":"Visual Modeling Languages in Patient Pathways: Scoping Review.","authors":"Binyam Bogale, Märt Vesinurm, Paul Lillrank, Elisabeth Gulowsen Celius, Ragnhild Halvorsrud","doi":"10.2196/55865","DOIUrl":"10.2196/55865","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Patient pathways (PPs) are presented as a panacea solution to enhance health system functions. It is a complex concept that needs to be described and communicated well. Modeling plays a crucial role in promoting communication, fostering a shared understanding, and streamlining processes. Only a few existing systematic reviews have focused on modeling methods and standardized modeling languages. There remains a gap in consolidated knowledge regarding the use of diverse visual modeling languages.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This scoping review aimed to compile visual modeling languages used to represent PPs, including the justifications and the context in which a modeling language was adopted, adapted, combined, or developed.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;After initial experimentation with the keywords used to describe the concepts of PPs and visual modeling languages, we developed a search strategy that was further refined and customized to the major databases identified as topically relevant. In addition, we consulted gray literature and conducted hand searches of the referenced articles. Two reviewers independently screened the articles in 2 stages using preset inclusion criteria, and a third reviewer voted on the discordance. Data charting was done using an iteratively developed form in the Covidence software. Descriptive and thematic summaries were presented following rounds of discussion to produce the final report.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of 1838 articles retrieved after deduplication, 22 satisfied our inclusion criteria. Clinical pathway is the most used phrase to represent the PP concept, and most papers discussed the concept without providing their operational definition. We categorized the visual modeling languages into five categories: (1) general purpose-modeling language (GPML) adopted without major extension or modification, (2) GPML used with formal extension recommendations, (3) combination of 2 or more modeling languages, (4) a developed domain-specific modeling language (DSML), and (5) ontological modeling languages. The justifications for adopting, adapting, combining, and developing visual modeling languages varied accordingly and ranged from versatility, expressiveness, tool support, and extensibility of a language to domain needs, integration, and simplification.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Various visual modeling languages were used in PP modeling, each with varying levels of abstraction and granularity. The categorization we made could aid in a better understanding of the complex combination of PP and modeling languages. Standardized GPMLs were used with or without any modifications. The rationale to propose any modification to GPMLs evolved as more evidence was presented following requirement analyses to support domain constructs. DSMLs are infrequently used due to their resource-intensive development, often initiated at a project level. The justifications provided an","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e55865"},"PeriodicalIF":1.9,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11607556/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142640354","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":"Dropout in a Longitudinal Survey of Amazon Mechanical Turk Workers With Low Back Pain: Observational Study.","authors":"Nabeel Qureshi, Ron D Hays, Patricia M Herman","doi":"10.2196/58771","DOIUrl":"10.2196/58771","url":null,"abstract":"<p><strong>Background: </strong>Surveys of internet panels such as Amazon's Mechanical Turk (MTurk) are common in health research. Nonresponse in longitudinal studies can limit inferences about change over time.</p><p><strong>Objective: </strong>This study aimed to (1) describe the patterns of survey responses and nonresponse among MTurk members with back pain, (2) identify factors associated with survey response over time, (3) assess the impact of nonresponse on sample characteristics, and (4) assess how well inverse probability weighting can account for differences in sample composition.</p><p><strong>Methods: </strong>We surveyed adult MTurk workers who identified as having back pain. We report participation trends over 3 survey waves and use stepwise logistic regression to identify factors related to survey participation in successive waves.</p><p><strong>Results: </strong>A total of 1678 adults participated in wave 1. Of those, 983 (59%) participated in wave 2 and 703 (42%) in wave 3. Participants who did not drop out took less time to complete previous surveys (30 min vs 35 min in wave 1, P<.001; 24 min vs 26 min in wave 2, P=.02) and reported having fewer health conditions (5.88 vs 6.6, P<.001). In multivariate models predicting responding at wave 2, lower odds of participation were associated with more time to complete the baseline survey (odds ratio [OR] 0.98, 95% CI 0.97-0.99), being Hispanic (compared with non-Hispanic, OR 0.69, 95% CI 0.49-0.96), having a bachelor's degree as their terminal degree (compared with all other levels of education, OR 0.58, 95% CI 0.46-0.73), having more pain interference and intensity (OR 0.75, 95% CI 0.64-0.89), and having more health conditions. In contrast, older respondents (older than 45 years age compared with 18-24 years age) were more likely to respond to the wave 2 survey (OR 2.63 and 3.79, respectively) and those whose marital status was divorced (OR 1.81) and separated (OR 1.77) were also more likely to respond to the wave 2 survey. Weighted analysis showed slight differences in sample demographics and conditions and larger differences in pain assessments, particularly for those who responded to wave 2.</p><p><strong>Conclusions: </strong>Longitudinal studies on MTurk have large, differential dropouts between waves. This study provided information about the individuals more likely to drop out over time, which can help researchers prepare for future surveys.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e58771"},"PeriodicalIF":1.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11589496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632302","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":"Methods Used in Co-Creation Within the Health CASCADE Co-Creation Database and Gray Literature: Systematic Methods Overview.","authors":"Danielle Marie Agnello, George Balaskas, Artur Steiner, Sebastien Chastin","doi":"10.2196/59772","DOIUrl":"10.2196/59772","url":null,"abstract":"<p><strong>Background: </strong>Co-creation is increasingly recognized for its potential to generate innovative solutions, particularly in addressing complex and wicked problems in public health. Despite this growing recognition, there are no standards or recommendations for method use in co-creation, leading to confusion and inconsistency. While some studies have examined specific methods, a comprehensive overview is lacking, limiting the collective understanding and ability to make informed decisions about the most appropriate methods for different contexts and research objectives.</p><p><strong>Objective: </strong>This study aimed to systematically compile and analyze methods used in co-creation to enhance transparency and deepen understanding of how co-creation is practiced.</p><p><strong>Methods: </strong>To enhance transparency and deepen understanding of how co-creation is practiced, this study systematically inventoried and analyzed methods used in co-creation. We conducted a systematic methods overview, applying 2 parallel processes: one within the peer-reviewed Health CASCADE Co-Creation Database and another within gray literature. An artificial intelligence-assisted recursive search strategy, coupled with a 2-step screening process, ensured that we captured relevant methods. We then extracted method names and conducted textual, comparative, and bibliometric analyses to assess the content, relationship between methods, fields of research, and the methodological underpinnings of the included sources.</p><p><strong>Results: </strong>We examined a total of 2627 academic papers and gray literature sources, with the literature primarily drawn from health sciences, medical research, and health services research. The dominant methodologies identified were co-creation, co-design, coproduction, participatory research methodologies, and public and patient involvement. From these sources, we extracted and analyzed 956 co-creation methods, noting that only 10% (n=97) of the methods overlap between academic and gray literature. Notably, 91.3% (230/252) of the methods in academic literature co-occurred, often involving combinations of multiple qualitative methods. The most frequently used methods in academic literature included surveys, focus groups, photo voice, and group discussion, whereas gray literature highlighted methods such as world café, focus groups, role-playing, and persona.</p><p><strong>Conclusions: </strong>This study presents the first systematic overview of co-creation methods, providing a clear understanding of the diverse methods currently in use. Our findings reveal a significant methodological gap between researchers and practitioners, offering insights into the relative prevalence and combinations of methods. By shedding light on these methods, this study helps bridge the gap and supports researchers in making informed decisions about which methods to apply in their work. Additionally, it offers a foundation for further investi","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e59772"},"PeriodicalIF":1.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11589503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632306","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":"Screening for Depression Using Natural Language Processing: Literature Review.","authors":"Bazen Gashaw Teferra, Alice Rueda, Hilary Pang, Richard Valenzano, Reza Samavi, Sridhar Krishnan, Venkat Bhat","doi":"10.2196/55067","DOIUrl":"10.2196/55067","url":null,"abstract":"<p><strong>Background: </strong>Depression is a prevalent global mental health disorder with substantial individual and societal impact. Natural language processing (NLP), a branch of artificial intelligence, offers the potential for improving depression screening by extracting meaningful information from textual data, but there are challenges and ethical considerations.</p><p><strong>Objective: </strong>This literature review aims to explore existing NLP methods for detecting depression, discuss successes and limitations, address ethical concerns, and highlight potential biases.</p><p><strong>Methods: </strong>A literature search was conducted using Semantic Scholar, PubMed, and Google Scholar to identify studies on depression screening using NLP. Keywords included \"depression screening,\" \"depression detection,\" and \"natural language processing.\" Studies were included if they discussed the application of NLP techniques for depression screening or detection. Studies were screened and selected for relevance, with data extracted and synthesized to identify common themes and gaps in the literature.</p><p><strong>Results: </strong>NLP techniques, including sentiment analysis, linguistic markers, and deep learning models, offer practical tools for depression screening. Supervised and unsupervised machine learning models and large language models like transformers have demonstrated high accuracy in a variety of application domains. However, ethical concerns related to privacy, bias, interpretability, and lack of regulations to protect individuals arise. Furthermore, cultural and multilingual perspectives highlight the need for culturally sensitive models.</p><p><strong>Conclusions: </strong>NLP presents opportunities to enhance depression detection, but considerable challenges persist. Ethical concerns must be addressed, governance guidance is needed to mitigate risks, and cross-cultural perspectives must be integrated. Future directions include improving interpretability, personalization, and increased collaboration with domain experts, such as data scientists and machine learning engineers. NLP's potential to enhance mental health care remains promising, depending on overcoming obstacles and continuing innovation.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e55067"},"PeriodicalIF":1.9,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11574504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577343","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":"Telemedicine for Patients With Systemic Lupus Erythematosus in a Publicly Funded Hospital System: Retrospective Study.","authors":"Sebastian Bruera, Kristen Andrews Staggers, Maria Eugenia Suarez-Almazor, Sandeep Krishna Agarwal","doi":"10.2196/49065","DOIUrl":"10.2196/49065","url":null,"abstract":"<p><strong>Background: </strong>Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that requires frequent clinic and laboratory visits. However, patients with SLE, particularly those who are underresourced, have unacceptably high rates of no-shows.</p><p><strong>Objective: </strong>This study aims to determine no-show rates associated with telemedicine visits during the COVID-19 pandemic in comparison to no-show rates associated with contemporaneous and historic in-person visits.</p><p><strong>Methods: </strong>We performed a retrospective cohort study in a publicly funded county hospital system in Houston, Texas. We identified a cohort of established patients with SLE by the International Classification of Diseases codes that were independently confirmed as SLE by a review of medical records. We identified patients who were seen from March to December in 2018, 2019, and 2020 (to reflect the height of the COVID-19 pandemic and account for seasonal changes in disease activity). Our primary outcome was the percentage of no-shows for rheumatology clinic appointments. Our secondary outcome was laboratory use adherence, which was defined as lupus-specific blood and urine studies conducted within 30 days of the scheduled appointment. Covariates included age, sex, race, ethnicity, and SLE-related prescription drugs.</p><p><strong>Results: </strong>We included 156 patients with SLE in our analysis. Most were female (n=141, 90.4%), were Hispanic (n=75, 49.3%), and had a median age of 43 (range 19-80) years. In 2020, the no-show rate for telemedicine was 5.5% (10/182) compared to a no-show rate of 16.2% (31/191) for in-person visits (P=.002). After multivariable adjustment for covariates, the odds of no-show were lower for telemedicine visits (odds ratio 0.39, 95% CI 0.20-0.77). There were no differences in adherence to laboratory testing.</p><p><strong>Conclusions: </strong>Telemedicine visits had decreased odds of no-shows without difference in laboratory testing adherence after adjustment for covariates. More research is needed to determine the clinical impact of telemedicine on patients with SLE.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":" ","pages":"e49065"},"PeriodicalIF":16.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11568399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141794069","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":"Blended Psychological Therapy for the Treatment of Psychological Disorders in Adult Patients: Systematic Review and Meta-Analysis.","authors":"Kelly Ferrao Nunes-Zlotkowski, Heather L Shepherd, Lisa Beatty, Phyllis Butow, Joanne Margaret Shaw","doi":"10.2196/49660","DOIUrl":"10.2196/49660","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Blended therapy (BT) combines digital with face-to-face psychological interventions. BT may improve access to treatment, therapy uptake, and adherence. However, research is scarce on the structure of BT models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We synthesized the literature to describe BT models used for the treatment of psychological disorders in adults. We investigated whether BT structure, content, and ratio affected treatment efficacy, uptake, and adherence. We also conducted meta-analyses to examine treatment efficacy in intervention-control dyads and associations between treatment outcomes versus BT model structure.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;PsycINFO, CINAHL, Embase, ProQuest, and MEDLINE databases were searched. Eligibility criteria included articles published in English till March 2023 that described digital and face-to-face elements as part of an intervention plan for treating psychological disorders in adult patients. We developed a coding framework to characterize the BT interventions. A meta-analysis was conducted to calculate effect size (ES; Cohen d and 95% CIs) regarding pre- and posttreatment outcomes in depression and anxiety versus BT structure. The review was registered with PROSPERO and followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Searches identified 8436 articles, and data were extracted from 29 studies. BT interventions were analyzed and classified according to mode of interaction between digital and face-to-face components (integrated vs sequential), role of the components (core vs supplementary), component delivery (alternate vs case-by-case), and digital materials assignment mode (standardized vs personalized). Most BT interventions (n=24) used a cognitive behavioral therapy approach for anxiety or depression treatment. Mean rates of uptake (91%) and adherence (81%) were reported across individual studies. BT interventions were more effective or noninferior to treatment as usual, with large spread in the data and a moderate to large ES in the treatment of depression (n=9; Cohen d=-1.1, 95% CI -0.6 to -1.6, P&lt;.001, and z score=-4.3). A small, nonsignificant ES was found for anxiety outcomes (n=5; Cohen d=-0.1, 95% CI -0.3 to 0.05, P=.17, and z score=-1.4). Higher ESs were found in blended interventions with supplementary design (depression: n=11, Cohen d=-0.75, 95% CI -0.56 to -0.95; anxiety: n=8, Cohen d=-0.9, 95% CI -0.6 to -1.2); fewer (≤6) face-to-face sessions (depression: n=9, Cohen d=-0.7, 95% CI -0.5 to -0.9; anxiety: n=7, Cohen d=-0.8, 95% CI -0.3 to -1.3); and a lower ratio (≤50%) of face-to-face versus digital sessions (depression: n=5, Cohen d=-0.8, 95% CI -0.6 to -1.1; anxiety: n=4, Cohen d=-0.8, 95% CI 0.006 to -1.6).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study confirmed integrated BT models as feasible to deliver. We found BT to be effective in depression treatment, but anxiety tre","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e49660"},"PeriodicalIF":1.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11558224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142523585","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":"Portuguese Version of the Oral Frailty Index-8: Instrument Validation Study.","authors":"Laura Corrêa, André Júdice, Robson Scoz, Vanessa Machado, José João Mendes, Luís Proença, João Botelho, Luciano Ferreira","doi":"10.2196/49975","DOIUrl":"10.2196/49975","url":null,"abstract":"<p><strong>Background: </strong>The concept of oral frailty has gained scientific and clinical relevance in recent years, and early detection can facilitate timely intervention to manage its progression. The Oral Frailty Index-8 (OFI-8) was developed to assess community-dwelling older adults at risk for oral frailty.</p><p><strong>Objective: </strong>This study aims to investigate the psychometric validity of the OFI-8 in the Portuguese population, named the Portuguese version of the OFI-8 (OFI-8-PT), which may serve as a reference for future studies related to longevity and oral function.</p><p><strong>Methods: </strong>This study included 2 main phases, involving patients aged 60 years or older, Portuguese speakers, and those who consented to participate in the study. First, the researchers translated and cross-culturally adapted the original questionnaire to make it suitable for native Portuguese speakers. The translated tool was then assessed for psychometric validation, which consisted of test-retest reliability, internal consistency, construct validity, and sex invariance measurement.</p><p><strong>Results: </strong>A total of 159 older adults participated in the baseline survey, with almost equal numbers of male (n=79, 49.7%) and female participants (n=80, 50.3%). The OFI-8-PT demonstrated good reliability (Cronbach α=0.95) and construct validity (goodness-of-fit index=0.96; comparative fit index=0.85; and root mean square error of approximation=0.05, 90% CI 0.00-0.09). The study found sex invariance, indicating that the OFI-8-PT is equally valid for male and female participants, and the tested-retest reliability of the OFI-8-PT was good, indicating consistent results over time.</p><p><strong>Conclusions: </strong>The OFI-8-PT showed psychometric validity and good reliability to be used in the Portuguese population.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e49975"},"PeriodicalIF":1.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11555463/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512734","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: Automated Psychotherapy in a Spaceflight Environment: Advantages, Drawbacks, and Unknowns.","authors":"Logan Smith","doi":"10.2196/67671","DOIUrl":"10.2196/67671","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.2196/58803.].</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e67671"},"PeriodicalIF":1.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11549575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512733","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}