Journal of Medical Internet Research

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ISSN / EISSN : 1438-8871 / 1438-8871
Current Publisher: JMIR Publications Inc. (10.2196)
Total articles ≅ 5,203
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Journal of Medical Internet Research, Volume 23; doi:10.2196/22698

Background Low-intensity self-guided mental health interventions that are delivered on the web may meet the needs and preferences of adults with mild to moderate symptoms. However, few clinical trials have examined the effectiveness of self-guided transdiagnostic interventions within a naturalistic setting. Objective This randomized controlled trial (RCT) tests the effectiveness of the video-based transdiagnostic intervention FitMindKit in reducing depression symptoms (primary outcome), anxiety symptoms, disability, and suicidal ideation, relative to an attention-matched control condition called HealthWatch. Methods The RCT was conducted with adults living in the Australian Capital Territory, Australia. Participants (n=1986) were recruited through the web using social media advertisements, screened for psychological distress, and then randomized to receive one of two 4-week programs: FitMindKit (12-module psychotherapy intervention) or HealthWatch (12-module program providing general health information). Participants were assessed at baseline and at 4 weeks postbaseline. To maintain the ecological validity of the trial, participants completed brief assessments and interventions without direct researcher contact or incentives. Results Mixed model repeated-measures analyses of variance demonstrated that FitMindKit significantly improved depression symptoms (F1,701.7=3.97; P=.047), along with panic symptoms (F1,706.5=5.59; P=.02) and social anxiety symptoms (F1,680.0=12.37; P
Florian Fischer , Sina Kleen
Journal of Medical Internet Research, Volume 23; doi:10.2196/17691

Background The broad availability of smartphones and the number of health apps in app stores have risen in recent years. Health apps have benefits for individuals (eg, the ability to monitor one’s health) as well as for researchers (eg, the ability to collect data in population-based, clinical, and observational studies). Although the number of health apps on the global app market is huge and the associated potential seems to be great, app-based questionnaires for collecting patient-related data have not played an important role in epidemiological studies so far. Objective This study aims to provide an overview of studies that have collected patient data using an app-based approach, with a particular focus on longitudinal studies. This literature review describes the current extent to which smartphones have been used for collecting (patient) data for research purposes, and the potential benefits and challenges associated with this approach. Methods We conducted a scoping review of studies that used data collection via apps. PubMed was used to identify studies describing the use of smartphone app questionnaires for collecting data over time. Overall, 17 articles were included in the summary. Results Based on the results of this scoping review, there are only a few studies that integrate smartphone apps into data-collection approaches. Studies dealing with the collection of health-related data via smartphone apps have mainly been developed with regard to psychosomatic, neurodegenerative, respiratory, and cardiovascular diseases, as well as malign neoplasm. Among the identified studies, the duration of data collection ranged from 4 weeks to 12 months, and the participants’ mean ages ranged from 7 to 69 years. Potential can be seen for real-time information transfer, fast data synchronization (which saves time and increases effectivity), and the possibility of tracking responses longitudinally. Furthermore, smartphone-based data-collection techniques might prevent biases, such as reminder bias or mistakes occurring during manual data transfers. In chronic diseases, real-time communication with physicians and early detection of symptoms enables rapid modifications in disease management. Conclusions The results indicate that using mobile technologies can help to overcome challenges linked with data collection in epidemiological research. However, further feasibility studies need to be conducted in the near future to test the applicability and acceptance of these mobile apps for epidemiological research in various subpopulations.
Ari Z Klein , Arjun Magge, Karen O'connor , Jesus Ivan Flores Amaro, Davy Weissenbacher , Graciela Gonzalez Hernandez
Journal of Medical Internet Research, Volume 23; doi:10.2196/25314

Background In the United States, the rapidly evolving COVID-19 outbreak, the shortage of available testing, and the delay of test results present challenges for actively monitoring its spread based on testing alone. Objective The objective of this study was to develop, evaluate, and deploy an automatic natural language processing pipeline to collect user-generated Twitter data as a complementary resource for identifying potential cases of COVID-19 in the United States that are not based on testing and, thus, may not have been reported to the Centers for Disease Control and Prevention. Methods Beginning January 23, 2020, we collected English tweets from the Twitter Streaming application programming interface that mention keywords related to COVID-19. We applied handwritten regular expressions to identify tweets indicating that the user potentially has been exposed to COVID-19. We automatically filtered out “reported speech” (eg, quotations, news headlines) from the tweets that matched the regular expressions, and two annotators annotated a random sample of 8976 tweets that are geo-tagged or have profile location metadata, distinguishing tweets that self-report potential cases of COVID-19 from those that do not. We used the annotated tweets to train and evaluate deep neural network classifiers based on bidirectional encoder representations from transformers (BERT). Finally, we deployed the automatic pipeline on more than 85 million unlabeled tweets that were continuously collected between March 1 and August 21, 2020. Results Interannotator agreement, based on dual annotations for 3644 (41%) of the 8976 tweets, was 0.77 (Cohen κ). A deep neural network classifier, based on a BERT model that was pretrained on tweets related to COVID-19, achieved an F1-score of 0.76 (precision=0.76, recall=0.76) for detecting tweets that self-report potential cases of COVID-19. Upon deploying our automatic pipeline, we identified 13,714 tweets that self-report potential cases of COVID-19 and have US state–level geolocations. Conclusions We have made the 13,714 tweets identified in this study, along with each tweet’s time stamp and US state–level geolocation, publicly available to download. This data set presents the opportunity for future work to assess the utility of Twitter data as a complementary resource for tracking the spread of COVID-19.
Sahr Wali , Milena Guessi Margarido , Amika Shah, Patrick Ware , Michael McDonald, Mary O'sullivan, Juan Duero Posada , Heather Ross , Emily Seto
Journal of Medical Internet Research, Volume 23; doi:10.2196/26165

Background To minimize the spread and risk of a COVID-19 outbreak, societal norms have been challenged with respect to how essential services are delivered. With pressures to reduce the number of in-person ambulatory visits, innovative models of telemonitoring have been used during the pandemic as a necessary alternative to support access to care for patients with chronic conditions. The pandemic has led health care organizations to consider the adoption of telemonitoring interventions for the first time, while others have seen existing programs rapidly expand. Objective At the Toronto General Hospital in Ontario, Canada, the rapid expansion of a telemonitoring program began on March 9, 2020, in response to COVID-19. The objective of this study was to understand the experiences related to the expanded role of a telemonitoring program under the changing conditions of the pandemic. Methods A single-case qualitative study was conducted with 3 embedded units of analysis. Semistructured interviews probed the experiences of patients, clinicians, and program staff from the Medly telemonitoring program at a heart function clinic in Toronto, Canada. Data were analyzed using inductive thematic analysis as well as Eakin and Gladstone’s value-adding approach to enhance the analytic interpretation of the study findings. Results A total of 29 participants were interviewed, including patients (n=16), clinicians (n=9), and operational staff (n=4). Four themes were identified: (1) providing care continuity through telemonitoring; (2) adapting telemonitoring operations for a more virtual health care system; (3) confronting virtual workflow challenges; and (4) fostering a meaningful patient-provider relationship. Beyond supporting virtual visits, the program’s ability to provide a more comprehensive picture of the patient’s health was valued. However, issues relating to the lack of system integration and alert-driven interactions jeopardized the perceived sustainability of the program. Conclusions With the reduction of in-person visits during the pandemic, virtual services such as telemonitoring have demonstrated significant value. Based on our study findings, we offer recommendations to proactively adapt and scale telemonitoring programs under the changing conditions of an increasingly virtual health care system. These include revisiting the scope and expectations of telemedicine interventions, streamlining virtual patient onboarding processes, and personalizing the collection of patient information to build a stronger virtual relationship and a more holistic assessment of patient well-being.
Jiska Cohen-Mansfield , Aline Muff, Guy Meschiany, Shahar Lev-Ari
Journal of Medical Internet Research, Volume 23; doi:10.2196/25848

Background Senior centers and other types of clubs provide activities for older adults to address boredom, social isolation, and loneliness. Due to the COVID-19 pandemic, most of these activities have been cancelled. A limited range of web-based activities have been offered as alternatives. However, the effectiveness of these web-based group activities for older adults has scarcely been researched. Objective We aimed to understand the extent to which web-based activities for older adults provide an adequate substitute for in-person activities. Methods In this telephone survey, we interviewed 105 older adults in Israel who had been offered the opportunity to participate in web-based activities after routine activities closed due to the COVID-19 pandemic. Of the total sample, 49/105 (46.7%) participated in the activities and 56/105 (53.3%) did not. We inquired about the respondents’ background characteristics, satisfaction with the activities, and reasons for participation or nonparticipation. Results The respondents who participated in the web-based activities tended to be highly satisfied with at least some of them. They rated the enjoyment derived from the content of the activity as the most important motivator, followed by maintaining a routine and by enjoying the group and the presence of others. Over 50% of the participants (28/49, 57%) wished to continue with the exercise programming after the end of the COVID-19 pandemic, and 41% (20/49) wished to continue with the web-based lectures. Participants were more likely to report partaking in alternative activities than nonparticipants (P=.04). The most common reasons cited by nonparticipants were being unaware of the web-based program (24/56, 43%) despite a notification having been sent to the entire sample, lack of interest in the content (18/56, 32%), and technical issues (13/56, 23%), such as not owning or being able to fully use a computer. Both participants and nonparticipants were interested in a wide range of topics, with many being very particular about the topics they wished to access. Approximately half expressed willingness to pay for access; those who were willing to pay tended to have more years of education (P=.03). Conclusions Our findings suggest a need for web-based activities for countering boredom and feelings of isolation. The main factors that influence the use, efficacy, and sustainability of online activities are access, motivational and need-fulfilling factors, and whether the activities are sufficiently tailored to individuals’ preferences and abilities. Challenges in substituting in-person services are promoting social relationships that are currently not sufficiently incorporated into most web-based programs, accommodating a wider range of topics, and increasing the accessibility of current programs to older adults, especially those who are homebound, both during and after the COVID-19 pandemic.
Atinkut Alamirrew Zeleke , Tolga Naziyok, Fleur Fritz , Lara Christianson , Rainer Röhrig
Journal of Medical Internet Research, Volume 23; doi:10.2196/21382

Background A population-level survey (PLS) is an essential and standard method used in public health research that supports the quantification of sociodemographic events, public health policy development, and intervention designs. Data collection mechanisms in PLS seem to be a significant determinant in avoiding mistakes. Using electronic devices such as smartphones and tablet computers improves the quality and cost-effectiveness of public health surveys. However, there is a lack of systematic evidence to show the potential impact of electronic data collection tools on data quality and cost reduction in interviewer-administered surveys compared with the standard paper-based data collection system. Objective This systematic review aims to evaluate the impact of the interviewer-administered electronic data collection methods on data quality and cost reduction in PLS compared with traditional methods. Methods We conducted a systematic search of MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit, Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and nonrandomized studies that examined data quality and cost reduction outcomes, as well as usability, user experience, and usage parameters. In total, 2 independent authors screened the title and abstract, and extracted data from selected papers. A third author mediated any disagreements. The review authors used EndNote for deduplication and Rayyan for screening. Results Our search produced 3817 papers. After deduplication, we screened 2533 papers, and 14 fulfilled the inclusion criteria. None of the studies were randomized controlled trials; most had a quasi-experimental design, for example, comparative experimental evaluation studies nested on other ongoing cross-sectional surveys. A total of 4 comparative evaluations, 2 pre-post intervention comparative evaluations, 2 retrospective comparative evaluations, and 4 one-arm noncomparative studies were included. Meta-analysis was not possible because of the heterogeneity in study designs, types, study settings, and level of outcome measurements. Individual paper synthesis showed that electronic data collection systems provided good quality data and delivered faster compared with paper-based data collection systems. Only 2 studies linked cost and data quality outcomes to describe the cost-effectiveness of electronic data collection systems. Field data collectors reported that an electronic data collection system was a feasible, acceptable, and preferable tool for their work. Onsite data error prevention, fast data submission, and easy-to-handle devices were the comparative advantages offered by electronic data collection systems. Challenges during implementation included technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems. Conclusions Although evidence exists of the comparative advantages of electronic data collection compared with paper-based methods, the included studies were not methodologically rigorous enough to combine. More rigorous studies are needed to compare paper and electronic data collection systems in public health surveys considering data quality, work efficiency, and cost reduction. International Registered Report Identifier (IRRID) RR2-10.2196/10678
Yonggang Xiao , Bin Xu, Wenhao Jiang, Yunjun Wu
Journal of Medical Internet Research, Volume 23; doi:10.2196/13556

Background Health care professionals are required to maintain accurate health records of patients. Furthermore, these records should be shared across different health care organizations for professionals to have a complete review of medical history and avoid missing important information. Nowadays, health care providers use electronic health records (EHRs) as a key to the implementation of these goals and delivery of quality care. However, there are technical and legal hurdles that prevent the adoption of these systems, such as concerns about performance and privacy issues. Objective This study aimed to build and evaluate an experimental blockchain for EHRs, named HealthChain, which overcomes the disadvantages of traditional EHR systems. Methods HealthChain is built based on consortium blockchain technology. Specifically, three organizations, namely hospitals, insurance providers, and governmental agencies, form a consortium that operates under a governance model, which enforces the business logic agreed by all participants. Every peer node hosts an instance of the distributed ledger consisting of EHRs and an instance of chaincode regulating the permissions of participants. Designated orderers establish consensus on the order of EHRs and then disseminate blocks to peers. Results HealthChain achieves functional and nonfunctional requirements. It can store EHRs in a distributed ledger and share them among different participants. Moreover, it demonstrates superior features, such as privacy preservation, security, and high throughput. These are the main reasons why HealthChain is proposed. Conclusions Consortium blockchain technology can help to build new EHR systems and solve the problems that prevent the adoption of traditional systems.
Journal of Medical Internet Research, Volume 23; doi:10.2196/24495

Background Although lockdown and mandatory quarantine measures have played crucial roles in the sharp decrease of the number of newly confirmed/suspected COVID-19 cases, concerns have been raised over the threat that these measures pose to mental health, especially the mental health of vulnerable groups, including pregnant women. Few empirical studies have assessed whether and how these control measures may affect mental health, and no study has investigated the prevalence and impacts of the use of eHealth resources among pregnant women during the COVID-19 outbreak. Objective This study investigated (1) the effects of lockdown and mandatory quarantine on mental health problems (ie, anxiety and depressive symptoms), (2) the potential mediation effects of perceived social support and maladaptive cognition, and (3) the moderation effects of eHealth-related factors (ie, using social media to obtain health information and using prenatal care services during the COVID-19 pandemic) on pregnant women in China. Methods An online cross-sectional survey was conducted among 19,515 pregnant women from all 34 Chinese provincial-level administrative regions from February 25 to March 10, 2020. Results Of the 19,515 participants, 12,209 (62.6%) were subjected to lockdown in their areas of residence, 737 (3.8%) were subjected to mandatory quarantine, 8712 (44.6%) had probable mild to severe depression, 5696 (29.2%) had probable mild to severe anxiety, and 1442 (7.4%) had suicidal ideations. Only 640 (3.3%) participants reported that they used online prenatal care services during the outbreak. Significant sociodemographic/maternal factors of anxiety/depressive symptoms included age, education, occupation, the area of residence, gestational duration, the number of children born, complication during pregnancy, the means of using prenatal care services, and social media use for obtaining health information. Multiple indicators multiple causes modeling (χ214=495.21; P
Romain Garnier , Jan R Benetka, John Kraemer, Shweta Bansal
Journal of Medical Internet Research, Volume 23; doi:10.2196/24591

Background Eliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic. Objective We aimed to assess how mobility patterns have varied across the United States during the COVID-19 pandemic and to identify associations with socioeconomic factors of populations. Methods We used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level in the United States between February and May 2020, the period during which social distancing was widespread in this country. Using linear mixed models, we assessed the associations between social distancing and socioeconomic variables, including the proportion of people in the population below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density. Results We found that the speed, depth, and duration of social distancing in the United States are heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; in contrast, we show that social distancing is intensely adopted in counties with higher population densities and larger Black populations. Conclusions Socioeconomic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of the COVID-19 pandemic in communities across the United States. These inequalities are likely to amplify existing health disparities and must be addressed to ensure the success of ongoing pandemic mitigation efforts.
Andy Wong, Rashaad Bhyat, Siddhartha Srivastava, Lysa Boissé Lomax, Ramana Appireddy
Journal of Medical Internet Research, Volume 23; doi:10.2196/20621

Virtual care, the use of videoconferencing technology to connect with patients, has become critical in providing continuing care for patients during the current COVID-19 pandemic. Virtual care has now been adopted by health care providers across the spectrum, including physicians, residents, nurse practitioners, nurses, and allied health care professionals. Virtual care is novel and nuanced compared to in-person care. Most of the health care providers who are delivering or expected to deliver virtual care have little to no prior experience with it. The nuances of virtual care involve regulatory standards, platforms, technology and troubleshooting, patient selection, etiquette, and workflow, all of which comprise critical points in the provision of health care. It is important to consistently deliver high-quality, equitable, and professional virtual care to inspire patients with the trust they need to continue follow-up of their care in these difficult times. We have been adopting virtual care in our clinical practice for over two years. In partnership with Canada Health Infoway, we have assembled a primer for virtual care that can serve as a guide for any health care provider in Canada and globally, with the goal of providing seamless transitions between in-person and virtual care.
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