JMIR Publications

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  Artificial Intelligence

  Dec 4, 2020

  Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study

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  • Aleksandar Ćirković  

  Abstract:

  Background: Consumer-oriented mobile self-diagnosis apps have been developed using undisclosed algorithms, presumably based on machine learning and other artificial intelligence (AI) technologies. The US Food and Drug Administration now discerns apps with learning AI algorithms from those with stable ones and treats the former as medical devices. To the author’s knowledge, no self-diagnosis app testing has been performed in the field of ophthalmology so far. Objective: The objective of this study was to test apps that were previously mentioned in the scientific literature on a set of diagnoses in a deliberate time interval, comparing the results and looking for differences that hint at “nonlocked” learning algorithms. Methods: Four apps from the literature were chosen (Ada, Babylon, Buoy, and Your.MD). A set of three ophthalmology diagnoses (glaucoma, retinal tear, dry eye syndrome) representing three levels of urgency was used to simultaneously test the apps’ diagnostic efficiency and treatment recommendations in this specialty. Two years was the chosen time interval between the tests (2018 and 2020). Scores were awarded by one evaluating physician using a defined scheme. Results: Two apps (Ada and Your.MD) received significantly higher scores than the other two. All apps either worsened in their results between 2018 and 2020 or remained unchanged at a low level. The variation in the results over time indicates “nonlocked” learning algorithms using AI technologies. None of the apps provided correct diagnoses and treatment recommendations for all three diagnoses in 2020. Two apps (Babylon and Your.MD) asked significantly fewer questions than the other two (P<.001). Conclusions: “Nonlocked” algorithms are used by self-diagnosis apps. The diagnostic efficiency of the tested apps seems to worsen over time, with some apps being more capable than others. Systematic studies on a wider scale are necessary for health care providers and patients to correctly assess the safety and efficacy of such apps and for correct classification by health care regulating authorities.

  • J Med Internet Res 2020;22(12):e18097

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  JMIR Theme Issue 2020: COVID-19...

  Dec 3, 2020

  Dynamic Public Health Surveillance to Track and Mitigate the US COVID-19 Epidemic: Longitudinal Trend Analysis Study

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  Authors List:

  • Lori Ann Post  
  • Tariq Ziad Issa  
  • Michael J Boctor  
  • Charles B Moss  
  • Robert L Murphy  
  • Michael G Ison  
  • Chad J Achenbach  
  • Danielle Resnick  
  • Lauren Nadya Singh  
  • Janine White  
  • Joshua Marco Mitchell Faber  
  • Kasen Culler  
  • Cynthia A Brandt  
  • James Francis Oehmke  

  Abstract:

  Background: The emergence of SARS-CoV-2, the virus that causes COVID-19, has led to a global pandemic. The United States has been severely affected, accounting for the most COVID-19 cases and deaths worldwide. Without a coordinated national public health plan informed by surveillance with actionable metrics, the United States has been ineffective at preventing and mitigating the escalating COVID-19 pandemic. Existing surveillance has incomplete ascertainment and is limited by the use of standard surveillance metrics. Although many COVID-19 data sources track infection rates, informing prevention requires capturing the relevant dynamics of the pandemic. Objective: The aim of this study is to develop dynamic metrics for public health surveillance that can inform worldwide COVID-19 prevention efforts. Advanced surveillance techniques are essential to inform public health decision making and to identify where and when corrective action is required to prevent outbreaks. Methods: Using a longitudinal trend analysis study design, we extracted COVID-19 data from global public health registries. We used an empirical difference equation to measure daily case numbers for our use case in 50 US states and the District of Colombia as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results: Examination of the United States and state data demonstrated that most US states are experiencing outbreaks as measured by these new metrics of speed, acceleration, jerk, and persistence. Larger US states have high COVID-19 caseloads as a function of population size, density, and deficits in adherence to public health guidelines early in the epidemic, and other states have alarming rates of speed, acceleration, jerk, and 7-day persistence in novel infections. North and South Dakota have had the highest rates of COVID-19 transmission combined with positive acceleration, jerk, and 7-day persistence. Wisconsin and Illinois also have alarming indicators and already lead the nation in daily new COVID-19 infections. As the United States enters its third wave of COVID-19, all 50 states and the District of Colombia have positive rates of speed between 7.58 (Hawaii) and 175.01 (North Dakota), and persistence, ranging from 4.44 (Vermont) to 195.35 (North Dakota) new infections per 100,000 people. Conclusions: Standard surveillance techniques such as daily and cumulative infections and deaths are helpful but only provide a static view of what has already occurred in the pandemic and are less helpful in prevention. Public health policy that is informed by dynamic surveillance can shift the country from reacting to COVID-19 transmissions to being proactive and taking corrective action when indicators of speed, acceleration, jerk, and persistence remain positive week over week. Implicit within our dynamic surveillance is an early warning system that indicates when there is problematic growth in COVID-19 transmissions as well as signals when growth will become explosive without action. A public health approach that focuses on prevention can prevent major outbreaks in addition to endorsing effective public health policies. Moreover, subnational analyses on the dynamics of the pandemic allow us to zero in on where transmissions are increasing, meaning corrective action can be applied with precision in problematic areas. Dynamic public health surveillance can inform specific geographies where quarantines are necessary while preserving the economy in other US areas.

  • J Med Internet Res 2020;22(12):e24286

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  JMIR Theme Issue 2020: COVID-19...

  Dec 3, 2020

  Tweets by People With Arthritis During the COVID-19 Pandemic: Content and Sentiment Analysis

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  Authors List:

  • Danielle Berkovic  
  • Ilana Ackerman  
  • Andrew M Briggs  
  • Darshini Ayton  

  Abstract:

  Background: Emerging evidence suggests that people with arthritis are reporting increased physical pain and psychological distress during the COVID-19 pandemic. At the same time, Twitter’s daily usage has surged by 23% throughout the pandemic period, presenting a unique opportunity to assess the content and sentiment of tweets. Individuals with arthritis use Twitter to communicate with peers, and to receive up-to-date information from health professionals and services about novel therapies and management techniques. Objective: The aim of this research was to identify proxy topics of importance for individuals with arthritis during the COVID-19 pandemic, and to explore the emotional context of tweets by people with arthritis during the early phase of the pandemic. Methods: From March 20 to April 20, 2020, publicly available tweets posted in English and with hashtag combinations related to arthritis and COVID-19 were extracted retrospectively from Twitter. Content analysis was used to identify common themes within tweets, and sentiment analysis was used to examine positive and negative emotions in themes to understand the COVID-19 experiences of people with arthritis. Results: In total, 149 tweets were analyzed. The majority of tweeters were female and were from the United States. Tweeters reported a range of arthritis conditions, including rheumatoid arthritis, systemic lupus erythematosus, and psoriatic arthritis. Seven themes were identified: health care experiences, personal stories, links to relevant blogs, discussion of arthritis-related symptoms, advice sharing, messages of positivity, and stay-at-home messaging. Sentiment analysis demonstrated marked anxiety around medication shortages, increased physical symptom burden, and strong desire for trustworthy information and emotional connection. Conclusions: Tweets by people with arthritis highlight the multitude of concurrent concerns during the COVID-19 pandemic. Understanding these concerns, which include heightened physical and psychological symptoms in the context of treatment misinformation, may assist clinicians to provide person-centered care during this time of great health uncertainty.

  • J Med Internet Res 2020;22(12):e24550

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  Viewpoint

  Dec 3, 2020

  COVID-19 Contact-Tracing Apps: Analysis of the Readability of Privacy Policies

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  Authors List:

  • Melvyn Zhang  
  • Aloysius Chow  
  • Helen Smith  

  Abstract:

  Apps that enable contact-tracing are instrumental in mitigating the transmission of COVID-19, but there have been concerns among users about the data collected by these apps and their management. Contact tracing is of paramount importance when dealing with a pandemic, as it allows for rapid identification of cases based on the information collected from infected individuals about other individuals they may have had recent contact with. Advances in digital technology have enabled devices such as mobile phones to be used in the contract-tracing process. However, there is a potential risk of users’ personal information and sensitive data being stolen should hackers be in the near vicinity of these devices. Thus, there is a need to develop privacy-preserving apps. Meanwhile, privacy policies that outline the risk associated with the use of contact-tracing apps are needed, in formats that are easily readable and comprehensible by the public. To our knowledge, no previous study has examined the readability of privacy policies of contact-tracings apps. Therefore, we performed a readability analysis to evaluate the comprehensibility of privacy policies of 7 contact-tracing apps currently in use. The contents of the privacy policies of these apps were assessed for readability using Readability Test Tool, a free web-based reliability calculator, which computes scores based on a number of statistics (ie, word count and the number of complex words) and indices (ie, Flesch Reading Ease, Flesch-Kincaid Reading Grade Level, Gunning Fog Index, and Simplified Measure of Gobbledygook index). Our analysis revealed that explanations used in the privacy policies of these apps require a reading grade between 7 and 14, which is considerably higher than the reading ability of the average individual. We believe that improving the readability of privacy policies of apps could be potentially reassuring for users and may help facilitate the increased use of such apps.

  • J Med Internet Res 2020;22(12):e21572

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  JMIR Theme Issue 2020: COVID-19...

  Dec 3, 2020

  The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets

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  Authors List:

  • Paiheng Xu  
  • Mark Dredze  
  • David A Broniatowski  

  Abstract:

  Background: Social distancing is an important component of the response to the COVID-19 pandemic. Minimizing social interactions and travel reduces the rate at which the infection spreads and “flattens the curve” so that the medical system is better equipped to treat infected individuals. However, it remains unclear how the public will respond to these policies as the pandemic continues. Objective: The aim of this study is to present the Twitter Social Mobility Index, a measure of social distancing and travel derived from Twitter data. We used public geolocated Twitter data to measure how much users travel in a given week. Methods: We collected 469,669,925 tweets geotagged in the United States from January 1, 2019, to April 27, 2020. We analyzed the aggregated mobility variance of a total of 3,768,959 Twitter users at the city and state level from the start of the COVID-19 pandemic. Results: We found a large reduction (61.83%) in travel in the United States after the implementation of social distancing policies. However, the variance by state was high, ranging from 38.54% to 76.80%. The eight states that had not issued statewide social distancing orders as of the start of April ranked poorly in terms of travel reduction: Arkansas (45), Iowa (37), Nebraska (35), North Dakota (22), South Carolina (38), South Dakota (46), Oklahoma (50), Utah (14), and Wyoming (53). We are presenting our findings on the internet and will continue to update our analysis during the pandemic. Conclusions: We observed larger travel reductions in states that were early adopters of social distancing policies and smaller changes in states without such policies. The results were also consistent with those based on other mobility data to a certain extent. Therefore, geolocated tweets are an effective way to track social distancing practices using a public resource, and this tracking may be useful as part of ongoing pandemic response planning.

  • J Med Internet Res 2020;22(12):e21499

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  Infodemiology and Infoveillance

  Dec 3, 2020

  Dimensions of Misinformation About the HPV Vaccine on Instagram: Content and Network Analysis of Social Media Characteristics

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  Authors List:

  • Philip M Massey  
  • Matthew D Kearney  
  • Michael K Hauer  
  • Preethi Selvan  
  • Emmanuel Koku  
  • Amy E Leader  

  Abstract:

  Background: The human papillomavirus (HPV) vaccine is a major advancement in cancer prevention and this primary prevention tool has the potential to reduce and eliminate HPV-associated cancers; however, the safety and efficacy of vaccines in general and the HPV vaccine specifically have come under attack, particularly through the spread of misinformation on social media. The popular social media platform Instagram represents a significant source of exposure to health (mis)information; 1 in 3 US adults use Instagram. Objective: The objective of this analysis was to characterize pro- and anti-HPV vaccine networks on Instagram, and to describe misinformation within the anti-HPV vaccine network. Methods: From April 2018 to December 2018, we collected publicly available English-language Instagram posts containing hashtags #HPV, #HPVVaccine, or #Gardasil using Netlytic software (n=16,607). We randomly selected 10% of the sample and content analyzed relevant posts (n=580) for text, image, and social media features as well as holistic attributes (eg, sentiments, personal stories). Among antivaccine posts, we organized elements of misinformation within four broad dimensions: 1) misinformation theoretical domains, 2) vaccine debate topics, 3) evidence base, and 4) health beliefs. We conducted univariate, bivariate, and network analyses on the subsample of posts to quantify the role and position of individual posts in the network. Results: Compared to provaccine posts (324/580, 55.9%), antivaccine posts (256/580, 44.1%) were more likely to originate from individuals (64.1% antivaccine vs 25.0% provaccine; P<.001) and include personal narratives (37.1% vs 25.6%; P=.003). In the antivaccine network, core misinformation characteristics included mentioning #Gardasil, purporting to reveal a lie (ie, concealment), conspiracy theories, unsubstantiated claims, and risk of vaccine injury. Information/resource posts clustered around misinformation domains including falsification, nanopublications, and vaccine-preventable disease, whereas personal narrative posts clustered around different domains of misinformation, including concealment, injury, and conspiracy theories. The most liked post (6634 likes) in our full subsample was a positive personal narrative post, created by a non-health individual; the most liked post (5604 likes) in our antivaccine subsample was an informational post created by a health individual. Conclusions: Identifying characteristics of misinformation related to HPV vaccine on social media will inform targeted interventions (eg, network opinion leaders) and help sow corrective information and stories tailored to different falsehoods.

  • J Med Internet Res 2020;22(12):e21451

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  Review

  Dec 3, 2020

  Effectiveness, Acceptability, and Feasibility of Digital Health Interventions for LGBTIQ+ Young People: Systematic Review

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  Authors List:

  • Dylan Gilbey  
  • Helen Morgan  
  • Ashleigh Lin  
  • Yael Perry  

  Abstract:

  Background: Young people (aged 12-25 years) with diverse sexuality, gender, or bodily characteristics, such as those who identify as lesbian, gay, bisexual, transgender, intersex, or queer (LGBTIQ+), are at substantially greater risk of a range of mental, physical, and sexual health difficulties compared with their peers. Digital health interventions have been identified as a potential way to reduce these health disparities. Objective: This review aims to summarize the characteristics of existing evidence-based digital health interventions for LGBTIQ+ young people and to describe the evidence for their effectiveness, acceptability, and feasibility. Methods: A systematic literature search was conducted using internet databases and gray literature sources, and the results were screened for inclusion. The included studies were synthesized qualitatively. Results: The search identified 38 studies of 24 unique interventions seeking to address mental, physical, or sexual health–related concerns in LGBTIQ+ young people. Substantially more evidence-based interventions existed for gay and bisexual men than for any other population group, and there were more interventions related to risk reduction of sexually transmitted infections than to any other health concern. There was some evidence for the effectiveness, feasibility, and acceptability of these interventions overall; however, the quality of evidence is often lacking. Conclusions: There is sufficient evidence to suggest that targeted digital health interventions are an important focus for future research aimed at addressing health difficulties in LGBTIQ+ young people. Additional digital health interventions are needed for a wider range of health difficulties, particularly in terms of mental and physical health concerns, as well as more targeted interventions for same gender–attracted women, trans and gender-diverse people, and people with intersex variations. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020128164; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=128164

  • J Med Internet Res 2020;22(12):e20158

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  Review

  Dec 3, 2020

  Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review

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  Authors List:

  • Jawad Ahmed Chishtie  
  • Jean-Sebastien Marchand  
  • Luke A Turcotte  
  • Iwona Anna Bielska  
  • Jessica Babineau  
  • Monica Cepoiu-Martin  
  • Michael Irvine  
  • Sarah Munce  
  • Sally Abudiab  
  • Marko Bjelica  
  • Saima Hossain  
  • Muhammad Imran  
  • Tara Jeji  
  • Susan Jaglal  

  Abstract:

  Background: Visual analytics (VA) promotes the understanding of data with visual, interactive techniques, using analytic and visual engines. The analytic engine includes automated techniques, whereas common visual outputs include flow maps and spatiotemporal hot spots. Objective: This scoping review aims to address a gap in the literature, with the specific objective to synthesize literature on the use of VA tools, techniques, and frameworks in interrelated health care areas of population health and health services research (HSR). Methods: Using the 2018 PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, the review focuses on peer-reviewed journal articles and full conference papers from 2005 to March 2019. Two researchers were involved at each step, and another researcher arbitrated disagreements. A comprehensive abstraction platform captured data from diverse bodies of the literature, primarily from the computer and health sciences. Results: After screening 11,310 articles, findings from 55 articles were synthesized under the major headings of visual and analytic engines, visual presentation characteristics, tools used and their capabilities, application to health care areas, data types and sources, VA frameworks, frameworks used for VA applications, availability and innovation, and co-design initiatives. We found extensive application of VA methods used in areas of epidemiology, surveillance and modeling, health services access, use, and cost analyses. All articles included a distinct analytic and visualization engine, with varying levels of detail provided. Most tools were prototypes, with 5 in use at the time of publication. Seven articles presented methodological frameworks. Toward consistent reporting, we present a checklist, with an expanded definition for VA applications in health care, to assist researchers in sharing research for greater replicability. We summarized the results in a Tableau dashboard. Conclusions: With the increasing availability and generation of big health care data, VA is a fast-growing method applied to complex health care data. What makes VA innovative is its capability to process multiple, varied data sources to demonstrate trends and patterns for exploratory analysis, leading to knowledge generation and decision support. This is the first review to bridge a critical gap in the literature on VA methods applied to the areas of population health and HSR, which further indicates possible avenues for the adoption of these methods in the future. This review is especially important in the wake of COVID-19 surveillance and response initiatives, where many VA products have taken center stage.

  • J Med Internet Res 2020;22(12):e17892

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  Review

  Dec 3, 2020

  Involvement of People With Dementia in the Development of Technology-Based Interventions: Narrative Synthesis Review and Best Practice Guidelines

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  Authors List:

  • Harleen Kaur Rai  
  • Aline Cavalcanti Barroso  
  • Lauren Yates  
  • Justine Schneider  
  • Martin Orrell  

  Abstract:

  Background: Technology can be helpful in supporting people with dementia in their daily lives. However, people with dementia are often not fully involved in the development process of new technology. This lack of involvement of people with dementia in developing technology-based interventions can lead to the implementation of faulty and less suitable technology. Objective: This systematic review aims to evaluate current approaches and create best practice guidelines for involving people with dementia in developing technology-based interventions. Methods: A systematic search was conducted in January 2019 in the following databases: EMBASE (Excerpta Medica database), PsycINFO, MEDLINE (Medical Literature Analysis and Retrieval System Online), CINAHL (Cumulated Index to Nursing and Allied Health Literature), and Web of Science. The search strategy included search terms in 3 categories: dementia, technology, and involvement in development. Narrative synthesis wove the evidence together in a structured approach. Results: A total of 21 studies met the inclusion criteria. Most studies involved people with dementia in a single phase, such as development (n=10), feasibility and piloting (n=7), or evaluation (n=1). Only 3 studies described involvement in multiple phases. Frequently used methods for assessing involvement included focus groups, interviews, observations, and user tests. Conclusions: Most studies concluded that it was both necessary and feasible to involve people with dementia, which can be optimized by having the right prerequisites in place, ensuring that technology meets standards of reliability and stability, and providing a positive research experience for participants. Best practice guidelines for the involvement of people with dementia in developing technology-based interventions are described.

  • J Med Internet Res 2020;22(12):e17531

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  Web-based and Mobile Health...

  Dec 3, 2020

  Effectiveness of WeChat for Improving Exclusive Breastfeeding in Huzhu County China: Randomized Controlled Trial

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  Authors List:

  • Qiong Wu  
  • Yiwen Huang  
  • Zijun Liao  
  • Michelle Helena van Velthoven  
  • Wei Wang  
  • Yanfeng Zhang  

  Abstract:

  Background: The benefits of breastfeeding for both infants and mothers have been well recognized. However, the exclusive breastfeeding rate in China is low and decreasing. Mobile technologies have rapidly developed; communication apps such as WeChat (one of the largest social networking platforms in China) are widely used and have the potential to conveniently improve health behaviors. Objective: This study aimed to assess the effectiveness of using WeChat to improve breastfeeding practices. Methods: This 2-arm randomized controlled trial was conducted among pregnant women from May 2019 to April 2020 in Huzhu County, Qinghai Province, China. Pregnant women were eligible to participate if they were aged 18 years or older, were 11 to 37 weeks pregnant with a singleton fetus, had no known illness that could limit breastfeeding after childbirth, used WeChat through their smartphone, and had access to the internet. A total of 344 pregnant women were recruited at baseline, with 170 in the intervention group and 174 in the control group. Women in the intervention group received breastfeeding knowledge and promotion information weekly through a WeChat official account from their third month of pregnancy to 6 months postpartum. The primary outcome of exclusive and predominant breastfeeding rate was measured 0-1 month, 2-3 months, and 4-5 months postpartum. Results: At 0-1 month postpartum, the exclusive breastfeeding rate was significantly higher in the intervention group than that in the control group (81.1% vs 63.3%; odds ratio [OR] 2.75, 95% CI 1.58-4.78; P<.001). Similarly, mothers in the intervention group were more likely to provide predominantly breast milk (OR 2.77, 95% CI 1.55-4.96; P<.001) and less likely to give dairy products to their children (OR 0.40, 95% CI 0.21-0.75; P=.005). There was no statistically significant difference for exclusive breastfeeding rate 2-3 months (P=.09) and 4-5 months postpartum (P=.27), though more children in the intervention group were exclusively breastfed than those in the control group 2-3 months postpartum (intervention: 111/152, 73.0%; control: 96/152, 63.2%) and 4-5 months postpartum(intervention: 50/108, 46.3%; control: 46/109, 42.2%). Conclusions: This study is the first effort to promote exclusive breastfeeding through WeChat in China, which proved to be an effective method of promoting exclusive breastfeeding in early life. WeChat health education can be used in addition to local breastfeeding promotion programs. Trial Registration: Chinese Clinical Trial Registry ChiCTR1800017364; http://www.chictr.org.cn/showproj.aspx?proj=29325

  • J Med Internet Res 2020;22(12):e23273

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  New Methods

  Dec 3, 2020

  Patient Interaction Phenotypes With an Automated Remote Hypertension Monitoring Program and Their Association With Blood Pressure Control: Observational Study

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  Authors List:

  • Anahita Davoudi  
  • Natalie S Lee  
  • Corey Chivers  
  • Timothy Delaney  
  • Elizabeth L Asch  
  • Catherine Reitz  
  • Shivan J Mehta  
  • Krisda H Chaiyachati  
  • Danielle L Mowery  

  Abstract:

  Background: Automated texting platforms have emerged as a tool to facilitate communication between patients and health care providers with variable effects on achieving target blood pressure (BP). Understanding differences in the way patients interact with these communication platforms can inform their use and design for hypertension management. Objective: Our primary aim was to explore the unique phenotypes of patient interactions with an automated text messaging platform for BP monitoring. Our secondary aim was to estimate associations between interaction phenotypes and BP control. Methods: This study was a secondary analysis of data from a randomized controlled trial for adults with poorly controlled hypertension. A total of 201 patients with established primary care were assigned to the automated texting platform; messages exchanged throughout the 4-month program were analyzed. We used the k-means clustering algorithm to characterize two different interaction phenotypes: program conformity and engagement style. First, we identified unique clusters signifying differences in program conformity based on the frequency over time of error alerts, which were generated to patients when they deviated from the requested text message format (eg, ###/## for BP). Second, we explored overall engagement styles, defined by error alerts and responsiveness to text prompts, unprompted messages, and word count averages. Finally, we applied the chi-square test to identify associations between each interaction phenotype and achieving the target BP. Results: We observed 3 categories of program conformity based on their frequency of error alerts: those who immediately and consistently submitted texts without system errors (perfect users, 51/201), those who did so after an initial learning period (adaptive users, 66/201), and those who consistently submitted messages generating errors to the platform (nonadaptive users, 38/201). Next, we observed 3 categories of engagement style: the enthusiast, who tended to submit unprompted messages with high word counts (17/155); the student, who inconsistently engaged (35/155); and the minimalist, who engaged only when prompted (103/155). Of all 6 phenotypes, we observed a statistically significant association between patients demonstrating the minimalist communication style (high adherence, few unprompted messages, limited information sharing) and achieving target BP (P<.001). Conclusions: We identified unique interaction phenotypes among patients engaging with an automated text message platform for remote BP monitoring. Only the minimalist communication style was associated with achieving target BP. Identifying and understanding interaction phenotypes may be useful for tailoring future automated texting interactions and designing future interventions to achieve better BP control.

  • J Med Internet Res 2020;22(12):e22493

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  JMIR Theme Issue 2020: COVID-19...

  Dec 2, 2020

  Mental Health Burden in Different Professions During the Final Stage of the COVID-19 Lockdown in China: Cross-sectional Survey Study

  View Authors View Abstract

  Authors List:

  • Junfeng Du  
  • Gwendolyn Mayer  
  • Svenja Hummel  
  • Neele Oetjen  
  • Nadine Gronewold  
  • Ali Zafar  
  • Jobst-Hendrik Schultz  

  Abstract:

  Background: COVID-19 resulted in considerable mental health burden in the Chinese general population and among health care workers at the beginning and peak of the pandemic. However, little is known about potentially vulnerable groups during the final stage of the lockdown. Objective: The aim of this survey study was to assess the mental health burden of different professions in China in order to find vulnerable groups, possible influencing factors, and successful ways of coping during the last 4 weeks of the lockdown in Hubei Province. Methods: A cross-sectional online survey asked participants about current residence, daily working hours, exposure to COVID-19 at work, and media preferences. We used a shortened version of the Depression, Anxiety and Stress Scale (DASS-21) to assess mental health. Further assessments included perceived stress (Simplified Chinese version of the 14-item Perceived Stress Scale), coping strategies for all participants, and specific stressors for health care workers. We followed the reporting guidelines of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement for observational studies. Results: The sample (N=687) consisted of 158 doctors, 221 nurses, 24 other medical staff, 43 students, 60 teachers/government staff, 135 economy staff, 26 workers/farmers, and 20 professions designated under the “other” category. We found increased depression (n=123, 17.9%), anxiety (n=208, 30.3%), and stress (n=94, 13.7%) in our sample. Professions that were vulnerable to depression were other medical staff and students. Doctors, nurses, and students were vulnerable to anxiety; and other medical staff, students, and economy staff were vulnerable to stress. Coping strategies were reduced to three factors: active, mental, and emotional. Being female and emotional coping were independently associated with depression, anxiety, or stress. Applying active coping strategies showed lower odds for anxiety while mental coping strategies showed lower odds for depression, anxiety, and stress. Age, being inside a lockdown area, exposure to COVID-19 at work, and having a high workload (8-12 hours per day) were not associated with depression, anxiety, or stress. WeChat was the preferred way of staying informed across all groups. Conclusions: By the end of the lockdown, a considerable part of the Chinese population showed increased levels of depression and anxiety. Students and other medical staff were the most affected, while economy staff were highly stressed. Doctors and nurses need support regarding potential anxiety disorders. Future work should focus on longitudinal results of the pandemic and develop targeted preventive measures. Trial Registration:

  • J Med Internet Res 2020;22(12):e24240

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