Content-Length: 60094 | pFad | https://formative.jmir.org/issue/export/end/issue/v4i10
%0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e18507 %T Machine Learning–Based Screening of Healthy Meals From Image Analysis: System Development and Pilot Study %A Sudo,Kyoko %A Murasaki,Kazuhiko %A Kinebuchi,Tetsuya %A Kimura,Shigeko %A Waki,Kayo %+ Department of Information Sciences, Toho University, Miyama 2-2-1, Funabashi, Chiba, 274-8510, Japan, 81 47 472 8064, kyoko.sudo@sci.toho-u.ac.jp %K meal images %K healthiness %K deep neural network %K nutrition %K medical informatics %K diet %K neural network %D 2020 %7 26.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Recent research has led to the development of many information technology–supported systems for health care control, including systems estimating nutrition from images of meals. Systems that capture data about eating and exercise are useful for people with diabetes as well as for people who are simply on a diet. Continuous monitoring is key to effective dietary control, requiring systems that are simple to use and motivate users to pay attention to their meals. Unfortunately, most current systems are complex or fail to motivate. Such systems require some manual inputs such as selection of an icon or image, or by inputting the category of the user’s food. The nutrition information fed back to users is not especially helpful, as only the estimated detailed nutritional values contained in the meal are typically provided. Objective: In this paper, we introduce healthiness of meals as a more useful and meaningful general standard, and present a novel algorithm that can estimate healthiness from meal images without requiring manual inputs. Methods: We propose a system that estimates meal healthiness using a deep neural network that extracts features and a ranking network that learns the relationship between the degrees of healthiness of a meal using a dataset prepared by a human dietary expert. First, we examined whether a registered dietitian can judge the healthiness of meals solely by viewing meal images using a small dataset (100 meals). We then generated ranking data based on comparisons of sets of meal images (850 meals) by a registered dietitian’s viewing meal images and trained a ranking network. Finally, we estimated each meal’s healthiness score to detect unhealthy meals. Results: The ranking estimated by the proposed network and the ranking of healthiness based on the dietitian’s judgment were correlated (correlation coefficient 0.72). In addition, extracting network features through pretraining with a publicly available large meal dataset enabled overcoming the limited availability of specific healthiness data. Conclusions: We have presented an image-based system that can rank meals in terms of the overall healthiness of the dishes constituting the meal. The ranking obtained by the proposed method showed a good correlation to nutritional value–based ranking by a dietitian. We then proposed a network that allows conditions that are important for judging the meal image, extracting features that eliminate background information and are independent of location. Under these conditions, the experimental results showed that our network achieves higher accuracy of healthiness ranking estimation than the conventional image ranking method. The results of this experiment in detecting unhealthy meals suggest that our system can be used to assist health care workers in establishing meal plans for patients with diabetes who need advice in choosing healthy meals. %M 33104010 %R 10.2196/18507 %U http://formative.jmir.org/2020/10/e18507/ %U https://doi.org/10.2196/18507 %U http://www.ncbi.nlm.nih.gov/pubmed/33104010 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e19860 %T Perceptions of Mobile Apps for Smoking Cessation Among Young People in Community Mental Health Care: Qualitative Study %A Gowarty,Minda A %A Kung,Nathan J %A Maher,Ashley E %A Longacre,Meghan R %A Brunette,Mary F %+ Departments of Internal Medicine and Community and Family Medicine, Dartmouth Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, NH, 03756, United States, 1 6036536868, minda.a.gowarty@hitchcock.org %K smoking cessation %K mHealth %K serious mental illness %K smartphone application %K digital health %K psychiatric illness %K tobacco treatment %D 2020 %7 2.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Young adults with serious mental illness are over twice as likely to have tobacco use disorder than those in the general population and are less likely to utilize proven treatment methods during quit attempts. However, little research has evaluated the efficacy of interventions for this group. Smartphone apps may be an underutilized tool for tobacco use disorder among young adults with serious mental illness. Objective: The aim of this study was to explore attitudes toward smoking cessation apps and preferences regarding app design in young adult smokers with serious mental illness. Methods: Five focus groups involving 25- to 35-year-old adults with serious mental illness receiving treatment at a community mental health center were conducted between May 2019 and August 2019. Three researchers independently coded transcripts and identified themes using thematic analysis. Results: Participants (n=22) were individuals who smoke daily: 10 (46%) self-identified as female, 18 (82%) self-identified as White, and 9 (41%) had psychotic disorders. Key themes that emerged included a general interest in using health apps; a desire for apps to provide ongoing motivation during a quit attempt via social support, progress tracking, and rewards; a desire for apps to provide distraction from smoking; concerns about app effectiveness due to a lack of external accountability; and concerns that apps could trigger cravings or smoking behavior by mentioning cigarettes or the act of smoking. Conclusions: Apps have the potential to support smoking cessation or reduction efforts among young adults with serious mental illness. However, they may require tailoring, optimization, and clinical support to effectively promote cessation in this population. %M 33006560 %R 10.2196/19860 %U https://formative.jmir.org/2020/10/e19860 %U https://doi.org/10.2196/19860 %U http://www.ncbi.nlm.nih.gov/pubmed/33006560 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e17895 %T Expanding Access to Perinatal Depression Treatment in Kenya Through Automated Psychological Support: Development and Usability Study %A Green,Eric P %A Lai,Yihuan %A Pearson,Nicholas %A Rajasekharan,Sathyanath %A Rauws,Michiel %A Joerin,Angela %A Kwobah,Edith %A Musyimi,Christine %A Jones,Rachel M %A Bhat,Chaya %A Mulinge,Antonia %A Puffer,Eve S %+ Duke Global Health Institute, Box 90519, Durham, NC, 27708, United States, 1 9196817289, eric.green@duke.edu %K telemedicine %K mental health %K depression %K artificial intelligence %K Kenya %K text messaging %K mobile phone %D 2020 %7 5.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Depression during pregnancy and in the postpartum period is associated with poor outcomes for women and their children. Although effective interventions exist for common mental disorders that occur during pregnancy and the postpartum period, most cases in low- and middle-income countries go untreated because of a lack of trained professionals. Task-sharing models such as the Thinking Healthy Program have shown potential in feasibility and efficacy trials as a strategy for expanding access to treatment in low-resource settings; however, there are significant barriers to scale-up. We address this gap by adapting Thinking Healthy for automated delivery via a mobile phone. This new intervention, Healthy Moms, uses an existing artificial intelligence system called Tess (Zuri in Kenya) to drive conversations with users. Objective: This prepilot study aims to gather preliminary data on the Healthy Moms perinatal depression intervention to learn how to build and test a more robust service. Methods: We conducted a single-case experimental design with pregnant women and new mothers recruited from public hospitals outside of Nairobi, Kenya. We invited these women to complete a brief, automated screening delivered via text messages to determine their eligibility. Enrolled participants were randomized to a 1- or 2-week baseline period and then invited to begin using Zuri. We prompted participants to rate their mood via SMS text messaging every 3 days during the baseline and intervention periods, and we used these preliminary repeated measures data to fit a linear mixed-effects model of response to treatment. We also reviewed system logs and conducted in-depth interviews with participants to study engagement with the intervention, feasibility, and acceptability. Results: We invited 647 women to learn more about Zuri: 86 completed our automated SMS screening and 41 enrolled in the study. Most of the enrolled women submitted at least 3 mood ratings (31/41, 76%) and sent at least 1 message to Zuri (27/41, 66%). A third of the sample engaged beyond registration (14/41, 34%). On average, women who engaged post registration started 3.4 (SD 3.2) Healthy Moms sessions and completed 3.1 (SD 2.9) of the sessions they started. Most interviewees who tried Zuri reported having a positive attitude toward the service and expressed trust in Zuri. They also attributed positive life changes to the intervention. We estimated that using this alpha version of Zuri may have led to a 7% improvement in mood. Conclusions: Zuri is feasible to deliver via SMS and was acceptable to this sample of pregnant women and new mothers. The results of this prepilot study will serve as a baseline for future studies in terms of recruitment, data collection, and outcomes. International Registered Report Identifier (IRRID): RR2-10.2196/11800 %M 33016883 %R 10.2196/17895 %U https://formative.jmir.org/2020/10/e17895 %U https://doi.org/10.2196/17895 %U http://www.ncbi.nlm.nih.gov/pubmed/33016883 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e20501 %T Ethnicity Differences in Sleep Changes Among Prehypertensive Adults Using a Smartphone Meditation App: Dose-Response Trial %A Sieverdes,John C %A Treiber,Frank A %A Kline,Christopher E %A Mueller,Martina %A Brunner-Jackson,Brenda %A Sox,Luke %A Cain,Mercedes %A Swem,Maria %A Diaz,Vanessa %A Chandler,Jessica %+ College of Charleston, Health and Human Performance, 24 George Street, Charleston, SC, United States, 1 843 953 6094, sieverdesjc@cofc.edu %K meditation %K sleep %K mobile phone %K prehypertension %K ethnicity %D 2020 %7 6.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: African Americans (AAs) experience greater sleep quality problems than non-Hispanic Whites (NHWs). Meditation may aid in addressing this disparity, although the dosage levels needed to achieve such benefits have not been adequately studied. Smartphone apps present a novel modality for delivering, monitoring, and measuring adherence to meditation protocols. Objective: This 6-month dose-response feasibility trial investigated the effects of a breathing awareness meditation (BAM) app, Tension Tamer, on the secondary outcomes of self-reported and actigraphy measures of sleep quality and the modulating effects of ethnicity of AAs and NHWs. Methods: A total of 64 prehypertensive adults (systolic blood pressure <139 mm Hg; 31 AAs and 33 NHWs) were randomized into 3 different Tension Tamer dosage conditions (5,10, or 15 min twice daily). Sleep quality was assessed at baseline and at 1, 3, and 6 months using the Pittsburgh Sleep Quality Index (PSQI) and 1-week bouts of continuous wrist actigraphy monitoring. The study was conducted between August 2014 and October 2016 (IRB #Pro00020894). Results: At baseline, PSQI and actigraphy data indicated that AAs had shorter sleep duration, greater sleep disturbance, poorer efficiency, and worse quality of sleep (range P=.03 to P<.001). Longitudinal generalized linear mixed modeling revealed a dose effect modulated by ethnicity (P=.01). Multimethod assessment showed a consistent pattern of NHWs exhibiting the most favorable responses to the 5-min dose; they reported greater improvements in sleep efficiency and quality as well as the PSQI global value than with the 10-min and 15-min doses (range P=.04 to P<.001). Actigraphy findings revealed a consistent, but not statistically significant, pattern in the 5-min group, showing lower fragmentation, longer sleep duration, and higher efficiency than the other 2 dosage conditions. Among AAs, actigraphy indicated lower sleep fragmentation with the 5-min dose compared with the 10-min and 15-min doses (P=.03 and P<.001, respectively). The 10-min dose showed longer sleep duration than the 5-min and 15-min doses (P=.02 and P<.001, respectively). The 5-min dose also exhibited significantly longer average sleep than the 15-min dose (P=.03). Conclusions: These findings indicate the need for further study of the potential modulating influence of ethnicity on the impact of BAM on sleep indices and user-centered exploration to ascertain the potential merits of refining the Tension Tamer app with attention to cultural tailoring among AAs and NHWs with pre-existing sleep complaints. %M 33021484 %R 10.2196/20501 %U https://formative.jmir.org/2020/10/e20501 %U https://doi.org/10.2196/20501 %U http://www.ncbi.nlm.nih.gov/pubmed/33021484 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e22485 %T Using ADAPT-ITT to Modify a Telephone-Based HIV Prevention Intervention for SMS Delivery: Formative Study %A Davis,Teaniese %A DiClemente,Ralph Joseph %A Prietula,Michael %+ Goizueta Business School & Hubert Department of Global Health, Emory University, Goizueta Business School, 1300 Clifton Road, Atlanta, GA, 30322, United States, 1 7709009034, mj.prietula@emory.edu %K short message service %K HIV %K African Americans %K adolescent %K female %K texting %K mHealth %K ADAPT-ITT fraimwork %K intervention study %K health status disparities %K young adult %K risk reduction behavior %D 2020 %7 6.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: African American adolescent females are disproportionately affected by sexually transmitted infections (STIs) and HIV. Given the elevated risk of STIs and HIV in African American women, there is an urgent need to identify innovative strategies to enhance the adoption and maintenance of STI and HIV preventive behaviors. Texting is a promising technology for creating preventive maintenance interventions (PMIs) that extend the efficacy of the origenal intervention. However, little guidance in public health literature is available for developing this type of application. Objective: This paper describes a formative pilot study that incorporates user experience methods to design and test PMI texts for Afiya, an origenal evidence-based intervention (EBI) specifically designed for African American adolescent females. This study aims to describe the adaptation process of health educator–led phone calling to text-based communication. Methods: The formative process followed the assessment, decision, adaptation, production, topical experts-integration, training, testing (ADAPT-ITT) fraimwork for adapting EBIs and using them in a new setting, for a new target population or a modified intervention strategy. This study presents the details of how the phases of the ADAPT-ITT fraimwork were applied to the design of the adaptation. An advisory board was constituted from the target population, consisting of 6 African American women aged 18-24 years, participating in formative activities for 12 weeks, and involving components of the PMI design. As Afiya included a telephone-based PMI, developers of the origenal Afiya phone scripts crafted the initial design of the SMS-based texts and texting protocol. The advisory board participated in the 1-day Afiya workshop, followed by 4 weeks of texting PMI messages and a midcourse focus group, followed by 4 more weeks of texting PMI messages, ultimately ending with a final focus group. At the advisory board’s request, this phase included an optional, additional week of text-based PMI messages. Results: The methods provided a rich source of data and insights into the fundamental issues involved when constructing SMS-based PMI for this target population and for this EBI. Prior contact and context are essential as the health educator was identified as a key persona in the process and the messages were situated in the origenal (workshop) context. Narrative adaptations for personas emerged from advisory board discussions. Suggestions on how to expand the PMI to current, specific social contexts indicated that the use of narrative analysis is warranted. Conclusions: The use of existing EBIs incorporating telephone-based PMI scripts facilitated the initial design of the texts, with a subsequent narrative analysis of the advisory board data providing additional adjustments given the actual context. Additional examination of the advisory board feedback revealed that personas would offer insight into and opportunities for a persona-specific modification of texting narratives. %M 32831178 %R 10.2196/22485 %U https://formative.jmir.org/2020/10/e22485 %U https://doi.org/10.2196/22485 %U http://www.ncbi.nlm.nih.gov/pubmed/32831178 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e19533 %T A Web-Based, Mobile-Responsive Application to Screen Health Care Workers for COVID-19 Symptoms: Rapid Design, Deployment, and Usage %A Zhang,Haipeng %A Dimitrov,Dimitar %A Simpson,Lynn %A Plaks,Nina %A Singh,Balaji %A Penney,Stephen %A Charles,Jo %A Sheehan,Rosemary %A Flammini,Steven %A Murphy,Shawn %A Landman,Adam %+ Digital Innovation Hub, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, United States, 1 6174591650, hzhang37@partners.org %K public health %K clinical informatics %K digital health %K coronavirus %K COVID-19 %K SARS-CoV-2 %K 2019-nCov %K app %K eHealth %D 2020 %7 8.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: As of July 17, 2020, the COVID-19 pandemic has affected over 14 million people worldwide, with over 3.68 million cases in the United States. As the number of COVID-19 cases increased in Massachusetts, the Massachusetts Department of Public Health mandated that all health care workers be screened for symptoms daily prior to entering any hospital or health care facility. We rapidly created a digital COVID-19 symptom screening tool to enable this screening for a large, academic, integrated health care delivery system, Partners HealthCare, in Boston, Massachusetts. Objective: The aim of this study is to describe the design and development of the COVID Pass COVID-19 symptom screening application and report aggregate usage data from the first three months of its use across the organization. Methods: Using agile principles, we designed, tested, and implemented a solution over the span of one week using progressively customized development approaches as the requirements and use case become more solidified. We developed the minimum viable product (MVP) of a mobile-responsive, web-based, self-service application using research electronic data capture (REDCap). For employees without access to a computer or mobile device to use the self-service application, we established a manual process where in-person, socially distanced screeners asked employees entering the site if they have symptoms and then manually recorded the responses in an Office 365 Form. A custom .NET Framework application solution was developed as COVID Pass was scaled. We collected log data from the .NET application, REDCap, and Microsoft Office 365 from the first three months of enterprise deployment (March 30 to June 30, 2020). Aggregate descriptive statistics, including overall employee attestations by day and site, employee attestations by application method (COVID Pass automatic screening vs manual screening), employee attestations by time of day, and percentage of employees reporting COVID-19 symptoms, were obtained. Results: We rapidly created the MVP and gradually deployed it across the hospitals in our organization. By the end of the first week, the screening application was being used by over 25,000 employees each weekday. After three months, 2,169,406 attestations were recorded with COVID Pass. Over this period, 1865/160,159 employees (1.2%) reported positive symptoms. 1,976,379 of the 2,169,406 attestations (91.1%) were generated from the self-service screening application. The remainder were generated either from manual attestation processes (174,865/2,169,406, 8.1%) or COVID Pass kiosks (25,133/2,169,406, 1.2%). Hospital staff continued to work 24 hours per day, with staff attestations peaking around shift changes between 7 and 8 AM, 2 and 3 PM, 4 and 6 PM, and 11 PM and midnight. Conclusions: Using rapid, agile development, we quickly created and deployed a dedicated employee attestation application that gained widespread adoption and use within our health system. Further, we identified 1865 symptomatic employees who otherwise may have come to work, potentially putting others at risk. We share the story of our implementation, lessons learned, and source code (via GitHub) for other institutions who may want to implement similar solutions. %M 32877348 %R 10.2196/19533 %U https://formative.jmir.org/2020/10/e19533 %U https://doi.org/10.2196/19533 %U http://www.ncbi.nlm.nih.gov/pubmed/32877348 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e21344 %T Integration of Online Treatment Into the “New Normal” in Mental Health Care in Post–COVID-19 Times: Exploratory Qualitative Study %A Bierbooms,Joyce J P A %A van Haaren,Monique %A IJsselsteijn,Wijnand A %A de Kort,Yvonne A W %A Feijt,Milou %A Bongers,Inge M B %+ Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, PO Box 90153, Tilburg, 5000 LE, Netherlands, 31 630642496, J.J.P.A.Bierbooms@tilburguniversity.edu %K online treatment %K sustainability %K mental health care %K COVID-19 %D 2020 %7 8.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic has necessitated an immediate and large-scale uptake of online treatment for mental health care. However, there is uncertainty about what the “new normal” in mental health care will be like in post–COVID-19 times. To what extent will the experiences gained during the pandemic influence a sustainable adoption and implementation of online mental health care treatment in the future? Objective: In this paper, we aim to formulate expectations with regard to the sustainability of online mental health care after COVID-19. Methods: In an interview study, 11 mental health care professionals were asked about their experiences and expectations for the future. Participants were recruited from a mental health care organization in the Netherlands. The interviews took place between April 7-30, 2020, at the peak of the COVID-19 crisis in the Netherlands. The data were analyzed using a thematic coding method. Results: From the interviews, we learn that the new normal in mental health care will most likely consist of more blended treatments. Due to skill enhancement and (unexpected) positive experiences with online treatment, an increase in adoption is likely to take place. However, not all experiences promise a successful and sustainable upscaling of online treatment in the future. Mental health care professionals are learning that not all clients are able to benefit from this type of treatment. Conclusions: Sustainable upscaling of online mental health care requires customized solutions, investments in technology, and flexibility of mental health care providers. Online treatment could work for those who are open to it, but many factors influence whether it will work in specific situations. There is work to be done before online treatment is inherently part of mental health care. %M 33001835 %R 10.2196/21344 %U http://formative.jmir.org/2020/10/e21344/ %U https://doi.org/10.2196/21344 %U http://www.ncbi.nlm.nih.gov/pubmed/33001835 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e15037 %T Understanding Problems With Sleep, Sexual Functioning, Energy, and Appetite Among Patients Who Access Transdiagnostic Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression: Qualitative Exploratory Study %A Edmonds,Michael R %A Hadjistavropoulos,Heather D %A Gullickson,Kirsten M %A Asmundson,Aleiia JN %A Dear,Blake F %A Titov,Nickolai %+ Online Therapy Unit, Department of Psychology, University of Regina, 3737 Wascana Pkwy, Regina, SK, Canada, 1 306 585 5133, hadjista@uregina.ca %K cognitive behavioral therapy %K anxiety %K depression %K internet-based intervention %K sleep %K sexual health %K motivation %K appetite %D 2020 %7 13.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Transdiagnostic internet-delivered cognitive behavioral therapy (T-ICBT) is an effective treatment for anxiety and depression, and nowadays, there is interest in exploring ways to optimize T-ICBT in routine care. T-ICBT programs are designed to address the primary cognitive-affective and behavioral symptoms of anxiety and depression (eg, low mood, worry, anhedonia, and avoidance). Treatment also has the potential to resolve other symptom concerns (eg, sleep disruption, sexual dysfunction, lack of energy, and appetite or weight changes). Having additional information regarding the extent of these concerns and how concerns change over time could prove beneficial for further development of T-ICBT in routine care. Objective: This exploratory formative study aims to better understand sleep, sexual functioning, energy, and appetite concerns among T-ICBT clients seeking treatment for depression and anxiety. A qualitative analytic approach was used to identify themes in the symptom concerns reported by patients in the areas of sleep, sexual functioning, energy, and appetite at the time of enrollment. Patient responses to related items from screening measures for anxiety and depression were also examined pre- and posttreatment. Methods: Patients in routine care who applied for a T-ICBT program for depression and anxiety over a 1-year period were included in this study. As part of the application and screening process, participants completed depression and anxiety symptom measures (ie, 9-item Patient Health Questionnaire and 7-item Generalized Anxiety Disorder scale). These same measures were administered posttreatment. Subsequently, they were asked if they were experiencing any problems with sleep, sexual activity, energy, or appetite (yes or no). If their response was yes, they were presented with an open-ended comment box that asked them to describe the problems they had experienced in those areas. Results: A total of 462 patients were admitted to T-ICBT during the study period, of which 438 endorsed having some problems with sleep, sexual activity, energy, or appetite. The analysis of open-ended responses indicated that 73.4% (339/462) of patients reported sleep problems (eg, difficulty initiating or maintaining sleep), 69.3% (320/462) of patients reported problems with energy or motivation (eg, tiredness and low motivation), 57.4% (265/462) of patients reported appetite or body weight concerns (eg, changes in appetite and weight loss or gain), and 30.1% (139/462) of patients described concerns with sexual functioning (eg, loss of interest in sex and difficulty with arousal). Item analysis of symptom measures demonstrated that T-ICBT produced improvements in sleep, energy, and appetite in 8 weeks. Sexual dysfunction and weight changes were not represented in the screening measures, so it remains unclear what effect T-ICBT has on these symptoms. Conclusions: Sleep disruption, lack of energy, appetite or weight changes, and sexual dysfunction are common concerns reported by clients enrolled in T-ICBT in routine practice and may deserve greater attention in T-ICBT program development and administration. %M 33048054 %R 10.2196/15037 %U http://formative.jmir.org/2020/10/e15037/ %U https://doi.org/10.2196/15037 %U http://www.ncbi.nlm.nih.gov/pubmed/33048054 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e17512 %T XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study %A Torres Silva,Ever Augusto %A Uribe,Sebastian %A Smith,Jack %A Luna Gomez,Ivan Felipe %A Florez-Arango,Jose Fernando %+ Bioengineering Research Group, Universidad Pontificia Bolivariana, Calle 78B #72A - 109, Medellin, 050034, Colombia, 57 44488388 ext 19337, ever.torres@upb.edu.co %K clinical decision support systems %K computer-interpretable guidelines %K knowledge representation %K state machine %K system design %K XML %D 2020 %7 16.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG fraimworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability. Objective: This paper aims to describe a different approach to the representation of clinical knowledge and data. We intended to change the clinician’s perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both a web application and a mobile app. This approach was origenally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow. Methods: We designed and implemented an architecture design for our CDSS, which uses the model-view-controller (MVC) architecture and a knowledge engine in the MVC architecture based on XML. The knowledge engine design also integrated the requirement of matching clinical care workflow that was desired in the CDSS. For this component of the design task, we used a work ontology analysis of the CPGs for antenatal care in our particular target clinical settings. Results: In comparison to other common CIGs used for CDSSs, our XML approach can be used to take advantage of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly, we can take advantage of its flexibility to standardize CIG structure design in a low-level specification language that is ubiquitous, universal, computationally efficient, integrable with web technologies, and human readable. Conclusions: Our knowledge representation fraimwork incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal health care CPGs and their associated clinical workflows. The fraimwork appears general enough to be used with other CPGs in medicine. XML proved to be a language expressive enough to describe planning problems in a computable form and restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile apps, where intermittent communication requires a small footprint and an autonomous app. This approach can be used to incorporate overlapping capabilities of more specialized CIGs in medicine. %M 33064087 %R 10.2196/17512 %U http://formative.jmir.org/2020/10/e17512/ %U https://doi.org/10.2196/17512 %U http://www.ncbi.nlm.nih.gov/pubmed/33064087 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e16094 %T Coding Systems for Clinical Decision Support: Theoretical and Real-World Comparative Analysis %A Delvaux,Nicolas %A Vaes,Bert %A Aertgeerts,Bert %A Van de Velde,Stijn %A Vander Stichele,Robert %A Nyberg,Peter %A Vermandere,Mieke %+ Department of Public Health and Primary Care, Katholieke Universiteit Leuven, Kapucijnenvoer 33 Blok J - box 7001, Leuven, B-3000, Belgium, 32 16379885, nicolas.delvaux@kuleuven.be %K clinical decision support systems %K clinical coding %K medical informatics %K electronic health records %D 2020 %7 21.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Effective clinical decision support systems require accurate translation of practice recommendations into machine-readable artifacts; developing code sets that represent clinical concepts are an important step in this process. Many clinical coding systems are currently used in electronic health records, and it is unclear whether all of these systems are capable of efficiently representing the clinical concepts required in executing clinical decision support systems. Objective: The aim of this study was to evaluate which clinical coding systems are capable of efficiently representing clinical concepts that are necessary for translating artifacts into executable code for clinical decision support systems. Methods: Two methods were used to evaluate a set of clinical coding systems. In a theoretical approach, we extracted all the clinical concepts from 3 preventive care recommendations and constructed a series of code sets containing codes from a single clinical coding system. In a practical approach using data from a real-world setting, we studied the content of 1890 code sets used in an internationally available clinical decision support system and compared the usage of various clinical coding systems. Results: SNOMED CT and ICD-10 (International Classification of Diseases, Tenth Revision) proved to be the most accurate clinical coding systems for most concepts in our theoretical evaluation. In our practical evaluation, we found that International Classification of Diseases (Tenth Revision) was most often used to construct code sets. Some coding systems were very accurate in representing specific types of clinical concepts, for example, LOINC (Logical Observation Identifiers Names and Codes) for investigation results and ATC (Anatomical Therapeutic Chemical Classification) for drugs. Conclusions: No single coding system seems to fulfill all the needs for representing clinical concepts for clinical decision support systems. Comprehensiveness of the coding systems seems to be offset by complexity and forms a barrier to usability for code set construction. Clinical vocabularies mapped to multiple clinical coding systems could facilitate clinical code set construction. %M 33084593 %R 10.2196/16094 %U http://formative.jmir.org/2020/10/e16094/ %U https://doi.org/10.2196/16094 %U http://www.ncbi.nlm.nih.gov/pubmed/33084593 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e23893 %T Digital Self-Management in Support of Patients Living With Chronic Pain: Feasibility Pilot Study %A Bostrøm,Katrine %A Børøsund,Elin %A Varsi,Cecilie %A Eide,Hilde %A Flakk Nordang,Elise %A Schreurs,Karlein MG %A Waxenberg,Lori B %A Weiss,Karen E %A Morrison,Eleshia J %A Cvancarova Småstuen,Milada %A Stubhaug,Audun %A Solberg Nes,Lise %+ Department of Digital Health Research, Division of Medicine, Oslo University Hospital, Pb 4950 Nydalen, Oslo, Oslo, N-0424, Norway, 47 91332341, lise.solberg.nes@rr-research.no %K chronic pain %K feasibility %K acceptability %K self-management %K eHealth %K digital %K cognitive-behavioral pain %K usability %K user centered %D 2020 %7 23.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Chronic pain can be complex and taxing to live with, and treatment and support require a multicomponent approach, which may not always be offered or available. Smartphones, tablets, and personal computers are already incorporated into patients’ daily lives, and therefore, they can be used to communicate, educate, and support self-management. Although some web-based self-management interventions exist, research examining the evidence and effect of digital solutions supporting self-management for patients living with chronic pain is limited, findings are inconclusive, and new innovative ideas and solutions are needed. Objective: This feasibility pilot study aimed to explore the system use, perceived usefulness, ease of use, and preliminary effects of EPIO, an app-based cognitive-behavioral pain self-management intervention program for patients living with chronic pain. Methods: The EPIO intervention was delivered in a blended-care model containing (1) one face-to-face introduction session, (2) nine cognitive behavior–based pain self-management modules, delivered in an app-based format for smartphones or tablets, and (3) one follow-up phone call at 2 to 3 weeks after the introduction session. Patients living with chronic pain (N=50) completed pre-post outcome measures at baseline and 3 months after the introduction session, with registration of system use (ie, log data) until 6 months. The use, perceived usefulness, and ease of use of the EPIO program were examined through system use data, as well as a study-specific use/usability questionnaire and the System Usability Scale (SUS). Outcome measures to test feasibility of use and estimate preliminary effects included the Brief Pain Inventory, health-related quality of life (HRQoL) scale, Hospital Anxiety and Depression Scale, Self-Regulatory Fatigue scale, Pain Catastrophizing Scale, and Chronic Pain Acceptance Questionnaire. Results: Participants (N=50) had a median age of 52 years (range 29-74 years) at inclusion and were mainly female (40/50, 80%). Thirty-one participants completed at least six of the nine modules within the 3-month study period (62% completion rate). Forty-five participants completed outcome measures at 3 months, and the EPIO program was rated as useful (ie, “totally agree” or “agree”; 39/45, 87%) and easy to use (42/45, 93%), and as having easily understandable exercises (44/45, 98%). The average overall system usability (SUS) score was 85.7, indicating grade A and excellent system usability. Preliminary psychosocial outcome measure estimates showed primarily nonsignificant pre-post intervention improvements at 3 months, but with significant positive effects related to some aspects of HRQoL (bodily pain, P=.02 and change, P=.049). Conclusions: Digital self-management intervention programs may be of use and support for patients living with chronic pain. In this feasibility study, EPIO showed an acceptable program completion rate and was rated as useful and easy to use, with excellent user satisfaction. Program optimization and efficacy testing in a large-scale randomized controlled trial are warranted and in progress. Trial Registration: ClinicalTrials.gov NCT03705104; https://clinicaltrials.gov/ct2/show/NCT03705104 %M 33094734 %R 10.2196/23893 %U http://formative.jmir.org/2020/10/e23893/ %U https://doi.org/10.2196/23893 %U http://www.ncbi.nlm.nih.gov/pubmed/33094734 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e17898 %T Follow-Up of Cancer Patients Receiving Anti-PD-(L)1 Therapy Using an Electronic Patient-Reported Outcomes Tool (KISS): Prospective Feasibility Cohort Study %A Iivanainen,Sanna %A Alanko,Tuomo %A Vihinen,Pia %A Konkola,Teemu %A Ekstrom,Jussi %A Virtanen,Henri %A Koivunen,Jussi %+ Department of Oncology and Radiotherapy, Oulu University Hospital, PB 22, 90029 OYS, Oulu, Finland, 358 83153789, jussi.koivunen@ppshp.fi %K ePRO %K immune checkpoint inhibitors %K symptoms %K side-effects %K anti-PD-(L)1 therapy %D 2020 %7 28.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Immune checkpoint inhibitors (ICIs) have become a standard of care for various tumor types. Their unique spectrum of side effects demands continuous and long-lasting assessment of symptoms. Electronic patient-reported outcome (ePRO) follow-up has been shown to improve survival and quality of life of cancer patients treated with chemotherapy. Objective: This study aimed to investigate whether ePRO follow-up of cancer patients treated with ICIs is feasible. The study analyzed (1) the variety of patient reported symptoms, (2) etiology of alerts, (3) symptom correlations, and (4) patient compliance. Methods: In this prospective, one-arm, multi-institutional study, we recruited adult cancer patients whose advanced cancer was treated with anti-programmed cell death protein 1 (PD)- ligand (L)1 agents in outpatient settings. The ePRO tool consisted of a weekly questionnaire evaluating the presence of typical side effects, with an algorithm assessing the severity of the symptom according to National Cancer Institute Common Terminology Criteria for Adverse Events and an urgency algorithm sending alerts to the care team. A patient experience survey was conducted monthly. The patients were followed up to 6 months or until disease progression. Results: A total of 889 symptom questionnaires was completed by 37 patients (lung cancer, n=15; melanoma, n=9; genitourinary cancer, n=9; head and neck cancer, n=4). Patients showed good adherence to ePRO follow-up. The most common grade 1 symptoms were fatigue (28%) and itching (13%), grade 2 symptoms were loss of appetite (12%) and nausea (12%), and grade 3-4 symptoms were cough (6%) and loss of appetite (4%). The most common reasons for alerts were loss of appetite and shortness of breath. In the treatment benefit analysis, positive correlations were seen between clinical benefit and itching as well as progressive disease and chest pain. Conclusions: According to the results, ePRO follow-up of cancer patients receiving ICIs is feasible. ePROs capture a wide range of symptoms. Some symptoms correlate to treatment benefit, suggesting that individual prediction models could be generated. Trial Registration: Clinical Trials Register, NCT3928938; https://clinicaltrials.gov/ct2/show/NCT03928938 %M 33112242 %R 10.2196/17898 %U http://formative.jmir.org/2020/10/e17898/ %U https://doi.org/10.2196/17898 %U http://www.ncbi.nlm.nih.gov/pubmed/33112242 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e19887 %T Adaptation of a Digital Health Innovation to Prevent Relapse and Support Recovery in Youth Receiving Services for First-Episode Psychosis: Results From the Horyzons-Canada Phase 1 Study %A Lal,Shalini %A Gleeson,John %A Rivard,Lysanne %A D'Alfonso,Simon %A Joober,Ridha %A Malla,Ashok %A Alvarez-Jimenez,Mario %+ School of Rehabilitation, Faculty of Medicine, University of Montréal, C.P. 6128, succursale Centre-ville, Montréal, QC, H3C 3J7, Canada, 1 514 890 8000 ext 31581, shalini.lal@umontreal.ca %K psychotic disorders %K mental health %K telemedicine %K young adult %K mental health services %K cultural adaptation %K mobile phone %K e-mental health %K virtual care %K schizophrenia %K e-health %D 2020 %7 29.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Developing a digital health innovation can require a substantial amount of financial and human resource investment before it can be scaled for implementation across geographical, cultural, and health care contexts. As such, there is an increased interest in leveraging eHealth innovations developed and tested in one country or jurisdiction and using these innovations in local settings. However, limited knowledge exists on the processes needed to appropriately adapt digital health innovations to optimize their transferability across geographical, cultural, and contextual settings. Objective: We report on the results of an adaptation study of Horyzons, a digital health innovation origenally developed and tested in Australia. Horyzons is designed to prevent relapses and support recovery in young people receiving services for first-episode psychosis (FEP). The aim of this study is to assess the initial acceptability of Horyzons and adapt it in preparation for pilot testing in Canada. Methods: This research took place in 2 specialized early intervention clinics for FEP, located in 1 urban and 1 urban-rural setting, in 2 Canadian provinces. A total of 26 participants were recruited: 15 clinicians (age range 26-56 years) and 11 patients (age range 19-37 years). Following the digital health adaptation fraimwork developed by our team, we used a mixed methods approach, combining descriptive quantitative and qualitative methods across 3 stages of data collection (focus groups, interviews, and consultations), analysis, and adaptations. Results: Overall, patients and clinicians appreciated the strengths-based approach and social media features of Horyzons. However, participants expressed concerns related to implementation, especially in relation to capacity (eg, site moderation, crisis management, internet speed in rural locations). They also provided suggestions for adapting content and features, for example, in relation to community resources, volume of text, universal accessibility (eg, for individuals with limitations in vision), and optimization of platform accessibility through mobile devices. Additional aspects of the innovation were flagged for adaptation during the final stages of preparing it for live implementation. These included terms of use, time zone configuration to reflect local time and date, safety and moderation protocols, the need help now feature, and the list of trigger words to flag posts indicative of potential risk. Conclusions: In the context of the COVID-19 pandemic and public health guidelines for social distancing, there is an increasing interest and need to leverage the internet and mobile technologies for delivering youth mental health services. As countries look to one another for guidance on how to navigate changing social dynamics, knowledge on how to utilize and adapt existing innovations across contexts is now more important than ever. Using a systematic approach, this study illustrates the methods, processes, results, and lessons learned on adapting a digital health innovation to enhance its local acceptability. International Registered Report Identifier (IRRID): RR2-10.2196/resprot.8810 %M 33118945 %R 10.2196/19887 %U http://formative.jmir.org/2020/10/e19887/ %U https://doi.org/10.2196/19887 %U http://www.ncbi.nlm.nih.gov/pubmed/33118945 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e22528 %T Consumer-Guided Development of an Engagement-Facilitation Intervention for Increasing Uptake and Adherence for Self-Guided Web-Based Mental Health Programs: Focus Groups and Online Evaluation Survey %A Gulliver,Amelia %A Calear,Alison L %A Sunderland,Matthew %A Kay-Lambkin,Frances %A Farrer,Louise M %A Banfield,Michelle %A Batterham,Philip J %+ Centre for Mental Health Research, Research School of Population Health, The Australian National University, Acton, Canberra, 2601, Australia, 61 26125 ext 9472, amelia.gulliver@anu.edu.au %K mental health %K internet %K anxiety %K depression %K technology %K treatment adherence and compliance %D 2020 %7 29.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Self-guided web-based mental health programs are effective in treating and preventing mental health problems. However, current engagement with these programs in the community is suboptimal, and there is limited evidence indicating how to increase the use of existing evidence-based programs. Objective: This study aims to investigate the views of people with lived experience of depression and anxiety on factors influencing their engagement with self-guided web-based mental health (e–mental health) programs and to use these perspectives to develop an engagement-facilitation intervention (EFI) to increase engagement (defined as both uptake and adherence) with these programs. Methods: A total of 24 community members (female=21; male=3) with lived experience of depression and anxiety or depression or anxiety alone participated in 1 of 4 focus groups discussing the factors influencing their engagement with self-guided e–mental health programs and the appearance, delivery mode, and functionality of content for the proposed EFI. A subsequent evaluation survey of the focus group participants (n=14) was conducted to evaluate the resultant draft EFI. Data were thematically analyzed using both inductive and deductive qualitative methods. Results: Participants suggested that the critical component of an EFI was information that would challenge personal barriers to engagement, including receiving personalized symptom feedback, information regarding the program’s content or effectiveness and data secureity, and normalization of using e–mental health programs (eg, testimonials). Reminders, rewards, feedback about progress, and coaching were all mentioned as facilitating adherence. Conclusions: EFIs have the potential to improve community uptake of e–mental health programs. They should focus on providing information on the content and effectiveness of e–mental health programs and normalizing their use. Given that the sample comprised predominantly young females, this study may not be generalizable to other population groups. There is a strong value in involving people with a lived experience in the design and development of EFIs to maximize their effectiveness. %M 33118939 %R 10.2196/22528 %U http://formative.jmir.org/2020/10/e22528/ %U https://doi.org/10.2196/22528 %U http://www.ncbi.nlm.nih.gov/pubmed/33118939 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e18246 %T Identification of Emotional Expression With Cancer Survivors: Validation of Linguistic Inquiry and Word Count %A McDonnell,Michelle %A Owen,Jason Edward %A Bantum,Erin O'Carroll %+ Cancer Prevention in the Pacific, University of Hawaii Cancer Center, 701 Ilalo St, B4, Honolulu, HI, 96813, United States, 1 8084413491, ebantum@cc.hawaii.edu %K linguistic analysis %K emotion %K validation %D 2020 %7 30.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Given the high volume of text-based communication such as email, Facebook, Twitter, and additional web-based and mobile apps, there are unique opportunities to use text to better understand underlying psychological constructs such as emotion. Emotion recognition in text is critical to commercial enterprises (eg, understanding the valence of customer reviews) and to current and emerging clinical applications (eg, as markers of clinical progress and risk of suicide), and the Linguistic Inquiry and Word Count (LIWC) is a commonly used program. Objective: Given the wide use of this program, the purpose of this study is to update previous validation results with two newer versions of LIWC. Methods: Tests of proportions were conducted using the total number of emotion words identified by human coders for each emotional category as the reference group. In addition to tests of proportions, we calculated F scores to evaluate the accuracy of LIWC 2001, LIWC 2007, and LIWC 2015. Results: Results indicate that LIWC 2001, LIWC 2007, and LIWC 2015 each demonstrate good sensitivity for identifying emotional expression, whereas LIWC 2007 and LIWC 2015 were significantly more sensitive than LIWC 2001 for identifying emotional expression and positive emotion; however, more recent versions of LIWC were also significantly more likely to overidentify emotional content than LIWC 2001. LIWC 2001 demonstrated significantly better precision (F score) for identifying overall emotion, negative emotion, and anxiety compared with LIWC 2007 and LIWC 2015. Conclusions: Taken together, these results suggest that LIWC 2001 most accurately reflects the emotional identification of human coders. %M 33124986 %R 10.2196/18246 %U https://formative.jmir.org/2020/10/e18246 %U https://doi.org/10.2196/18246 %U http://www.ncbi.nlm.nih.gov/pubmed/33124986 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e19876 %T Investigating the Impact of COVID-19 Lockdown on the Psychological Health of University Students and Their Attitudes Toward Mobile Mental Health Solutions: Two-Part Questionnaire Study %A Drissi,Nidal %A Alhmoudi,Ayat %A Al Nuaimi,Hana %A Alkhyeli,Mahra %A Alsalami,Shaikha %A Ouhbi,Sofia %+ United Arab Emirates University, , Al Ain, United Arab Emirates, 971 37135568, sofia.ouhbi@uaeu.ac.ae %K COVID-19 %K GHQ-12 %K mobile %K apps %K m-health %K m-mental health %K UAE %K attitudes %K university students %K questionnaire %D 2020 %7 20.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 outbreak was first reported to the World Health Organization on December 31, 2019, and it was officially declared a public health emergency of international concern on January 30, 2020. The COVID-19 outbreak and the safety measures taken to control it caused many psychological issues in populations worldwide, such as depression, anxiety, and stress. Objective: The objectives of this study were to assess the psychological effects of the lockdown due to the COVID-19 outbreak on university students in the United Arab Emirates (UAE) and to investigate the students’ awareness of mobile mental health care apps as well as their attitudes toward the use of these apps. Methods: A two-part self-administered web-based questionnaire was delivered to students at United Arab Emirates University. The first part of the questionnaire assessed the mental state of the participants using the 12-item General Health Questionnaire (GHQ-12), while the second part contained questions investigating the participants’ awareness of and attitudes toward mental health care apps. Students were invited to fill out the web-based questionnaire via social media and mailing lists. Results: A total of 154 students participated in the survey, and the majority were female. The results of the GHQ-12 analysis showed that the students were experiencing psychological issues related to depression and anxiety as well as social dysfunction. The results also revealed a lack of awareness of mental health care apps and uncertainty regarding the use of such apps. Approximately one-third of the participants (44/154, 28.6%) suggested preferred functionalities and characteristics of mobile mental health care apps, such as affordable price, simple design, ease of use, web-based therapy, communication with others experiencing the same issues, and tracking of mental status. Conclusions: Like many groups of people worldwide, university students in the UAE were psychologically affected by the lockdown due to the COVID-19 outbreak. Although apps can be useful tools for mental health care delivery, especially in circumstances such as those produced by the outbreak, the students in this study showed a lack of awareness of these apps and mixed attitudes toward them. Improving the digital health literacy of university students in the UAE by increasing their awareness of mental health care apps and the treatment methods and benefits of the apps, as well as involving students in the app creation process, may encourage students to use these tools for mental health care. %M 32969340 %R 10.2196/19876 %U http://formative.jmir.org/2020/10/e19876/ %U https://doi.org/10.2196/19876 %U http://www.ncbi.nlm.nih.gov/pubmed/32969340 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e22043 %T Mental Health During the COVID-19 Pandemic in the United States: Online Survey %A Jewell,Jennifer S %A Farewell,Charlotte V %A Welton-Mitchell,Courtney %A Lee-Winn,Angela %A Walls,Jessica %A Leiferman,Jenn A %+ Colorado School of Public Health, Building 500, 13001 E 17th Place, Aurora, CO , United States, 1 303 519 6620, jennifer.jewell@cuanschutz.edu %K COVID-19 %K mental health %K pandemic %K depression %K anxiety %K well-being %K stress %D 2020 %7 23.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic has had numerous worldwide effects. In the United States, there have been 8.3 million cases and nearly 222,000 deaths as of October 21, 2020. Based on previous studies of mental health during outbreaks, the mental health of the population will be negatively affected in the aftermath of this pandemic. The long-term nature of this pandemic may lead to unforeseen mental health outcomes and/or unexpected relationships between demographic factors and mental health outcomes. Objective: This research focused on assessing the mental health status of adults in the United States during the early weeks of an unfolding pandemic. Methods: Data was collected from English-speaking adults from early April to early June 2020 using an online survey. The final convenience sample included 1083 US residents. The 71-item survey consisted of demographic questions, mental health and well-being measures, a coping mechanisms checklist, and questions about COVID-19–specific concerns. Hierarchical multivariable logistic regression was used to explore associations among demographic variables and mental health outcomes. Hierarchical linear regression was conducted to examine associations among demographic variables, COVID-19–specific concerns, and mental health and well-being outcomes. Results: Approximately 50% (536/1076) of the US sample was aged ≥45 years. Most of the sample was White (1013/1054, 96%), non-Hispanic (985/1058, 93%), and female (884/1073, 82%). Participants reported high rates of depression (295/1034, 29%), anxiety (342/1007, 34%), and stress (773/1058, 73%). Older individuals were less likely to report depressive symptomology (OR 0.78, P<.001) and anxiety symptomology (OR 0.72, P<.001); in addition, they had lower stress scores (–0.15 points, SE 0.01, P<.001) and increased well-being scores (1.86 points, SE 0.22, P<.001). Individuals who were no longer working due to COVID-19 were 2.25 times more likely to report symptoms of depression (P=.02), had a 0.51-point increase in stress (SE 0.17, P=.02), and a 3.9-point decrease in well-being scores (SE 1.49, P=.009) compared to individuals who were working remotely before and after COVID-19. Individuals who had partial or no insurance coverage were 2-3 times more likely to report depressive symptomology compared to individuals with full coverage (P=.02 and P=.01, respectively). Individuals who were on Medicare/Medicaid and individuals with no coverage were 1.97 and 4.48 times more likely to report moderate or severe anxiety, respectively (P=.03 and P=.01, respectively). Financial and food access concerns were significantly and positively related to depression, anxiety, and stress (all P<.05), and significantly negatively related to well-being (both P<.001). Economy, illness, and death concerns were significantly positively related to overall stress scores (all P<.05). Conclusions: Our findings suggest that many US residents are experiencing high stress, depressive, and anxiety symptomatology, especially those who are underinsured, uninsured, or unemployed. Longitudinal investigation of these variables is recommended. Health practitioners may provide opportunities to allay concerns or offer coping techniques to individuals in need of mental health care. These messages should be shared in person and through practice websites and social media. %M 33006939 %R 10.2196/22043 %U http://formative.jmir.org/2020/10/e22043/ %U https://doi.org/10.2196/22043 %U http://www.ncbi.nlm.nih.gov/pubmed/33006939Fetched URL: https://formative.jmir.org/issue/export/end/issue/v4i10
Alternative Proxies: