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Journal Description

The Journal of Medical Internet Research (JMIR), now in its 21st year, is the pioneer open access eHealth journal and is the flagship journal of JMIR Publications. It is the leading digital health journal globally in terms of quality/visibility (Impact Factor 2018: 4.945, ranked #1 out of 26 journals in the medical informatics category) and in terms of size (number of papers published). The journal focuses on emerging technologies, medical devices, apps, engineering, and informatics applications for patient education, prevention, population health and clinical care. As a leading high-impact journal in its disciplines (health informatics and health services research), it is selective, but it is now complemented by almost 30 specialty JMIR sister journals, which have a broader scope. Peer-review reports are portable across JMIR journals and papers can be transferred, so authors save time by not having to resubmit a paper to different journals. 

As an open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as with all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).

We are also a leader in participatory and open science approaches, and offer the option to publish new submissions immediately as preprints, which receive DOIs for immediate citation (eg, in grant proposals), and for open peer-review purposes. We also invite patients to participate (eg, as peer-reviewers) and have patient representatives on editorial boards.

Be a widely cited leader in the digitial health revolution and submit your paper today!

 

Recent Articles:

  • Source: The Authors / Placeit; Copyright: JMIR Publications; URL: https://www.jmir.org/2020/4/e17251; License: Licensed by JMIR.
    Web-based and Mobile Health...

    Apr 3, 2020

    Effectiveness of Message Frame-Tailoring in a Web-Based Smoking Cessation Program: Randomized Controlled Trial

    Authors List:

    Abstract:

    Background: The content of online computer-tailored interventions is often determined to match an individual’s characteristics, beliefs, and behavioral factors. These content-tailored interventions lead to better message processing and a higher likelihood of behavior change such as smoking cessation. However, a meta-analysis of online computer-tailored interventions showed that effect sizes, albeit positive, remain small, suggesting room for improvement. A promising strategy to enhance the effectiveness of online computer-tailored interventions is to tailor the message frame (ie, how a message is communicated) based on the preferred communication style of the user in addition to content-tailoring. One factor that determines an individual’s communication style preference is the need for autonomy; some individuals prefer an autonomy-supportive communication style (offering choice and use of suggestive language), whereas others might prefer a directive communication style, which is replete with imperatives and does not provide choice. Tailoring how messages are presented (eg, based on the need for autonomy) is called message frame-tailoring. Objective: The aim of the present study was to test the effectiveness of message frame-tailoring based on the need for autonomy, in isolation and in combination with content-tailoring, within the context of an online computer-tailored smoking cessation intervention. The primary outcome measure was the 7-day point-prevalence of smoking abstinence. Secondary outcomes were perceived message relevance, self-determined motivation to quit smoking, and sociocognitive beliefs. Methods: A randomized controlled trial with a 2 (message frame-tailoring vs no message frame-tailoring) by 2 (content-tailoring vs no content-tailoring) design was conducted among adult smokers intending to quit smoking (N=273). Results: Structural equation modeling revealed that the content-tailored condition increased smoking abstinence rates 1 month after the start of the intervention (beta=.57, P=.02). However, neither message frame-tailoring nor its interaction with content-tailoring significantly predicted smoking abstinence. In our model, message frame-tailoring, content-tailoring, as well as their interaction significantly predicted perceived relevance of the smoking cessation messages, which consequently predicted self-determined motivation. In turn, self-determined motivation positively affected attitudes and self-efficacy for smoking cessation, but only self-efficacy consequently predicted smoking abstinence. Participants in the control condition perceived the highest level of message relevance (mean 4.78, SD 1.27). However, messages that were frame-tailored for individuals with a high need for autonomy in combination with content-tailored messages led to significantly higher levels of perceived message relevance (mean 4.83, SD 1.03) compared to those receiving content-tailored messages only (mean 4.24, SD 1.05, P=.003). Conclusions: Message frame-tailoring based on the need for autonomy seems to be an effective addition to conventional content-tailoring techniques in online smoking cessation interventions for people with a high need for autonomy; however, this is not effective in its current form for people with a low need for autonomy. Trial Registration: Dutch Trial Register (NL6512/NRT-6700); https://www.trialregister.nl/trial/6512

  • Source: The Authors / Creative Market; Copyright: The Authors / Dikarte Media; URL: https://www.jmir.org/2020/4/e16813; License: Licensed by JMIR.
    E-Health Policy and Health Systems...

    Apr 3, 2020

    Deploying Patient-Facing Application Programming Interfaces: Thematic Analysis of Health System Experiences

    Authors List:

    Abstract:

    Background: Health systems have recently started to activate patient-facing application programming interfaces (APIs) to facilitate patient access to health data and other interactions. Objective: This study sought to ascertain health systems’ understanding, strategies, governance, and organizational infrastructure around patient-facing APIs, as well as their business drivers and barriers, to facilitate national learning, policy, and progress toward adoption. Methods: We performed a content analysis of semistructured interviews with a convenience sample of 10 health systems known to be leading adopters of health technology, having either implemented or planning to implement patient-facing APIs. Results: Of the 10 health systems, eight had operational patient-facing APIs, with organizational strategy driven most by federal policy, the emergence of Health Records on iPhone, and feelings of ethical obligation. The two priority use cases identified were enablement of a patient’s longitudinal health record and digital interactions with the health system. The themes most frequently cited as barriers to the increased use of patient-facing APIs were security concerns, an immature app ecosystem that does not currently offer superior functionality compared with widely adopted electronic health record (EHR)–tethered portals, a lack of business drivers, EHR vendor hesitation toward data sharing, and immature technology and standards. Conclusions: Our findings reveal heterogeneity in health system understanding and approaches to the implementation and use of patient-facing APIs. Ongoing study, targeted policy interventions, and sharing of best practices appear necessary to achieve successful national implementation.

  • Source: The Authors/Placeit; Copyright: The Authors/Placeit; URL: https://placeit.net/c/mockups/stages/macbook-pro-mockup-featuring-people-at-a-meeting-2320-el1; License: Licensed by JMIR.
    New Methods

    Apr 3, 2020

    Re-Enactment as a Method to Reproduce Real-World Fall Events Using Inertial Sensor Data: Development and Usability Study

    Authors List:

    Abstract:

    Background: Falls are a common health problem, which in the worst cases can lead to death. To develop reliable fall detection algorithms as well as suitable prevention interventions, it is important to understand circumstances and characteristics of real-world fall events. Although falls are common, they are seldom observed, and reports are often biased. Wearable inertial sensors provide an objective approach to capture real-world fall signals. However, it is difficult to directly derive visualization and interpretation of body movements from the fall signals, and corresponding video data is rarely available. Objective: The re-enactment method uses available information from inertial sensors to simulate fall events, replicate the data, validate the simulation, and thereby enable a more precise description of the fall event. The aim of this paper is to describe this method and demonstrate the validity of the re-enactment approach. Methods: Real-world fall data, measured by inertial sensors attached to the lower back, were selected from the Fall Repository for the Design of Smart and Self-Adaptive Environments Prolonging Independent Living (FARSEEING) database. We focused on well-described fall events such as stumbling to be re-enacted under safe conditions in a laboratory setting. For the purposes of exemplification, we selected the acceleration signal of one fall event to establish a detailed simulation protocol based on identified postures and trunk movement sequences. The subsequent re-enactment experiments were recorded with comparable inertial sensor configurations as well as synchronized video cameras to analyze the movement behavior in detail. The re-enacted sensor signals were then compared with the real-world signals to adapt the protocol and repeat the re-enactment method if necessary. The similarity between the simulated and the real-world fall signals was analyzed with a dynamic time warping algorithm, which enables the comparison of two temporal sequences varying in speed and timing. Results: A fall example from the FARSEEING database was used to show the feasibility of producing a similar sensor signal with the re-enactment method. Although fall events were heterogeneous concerning chronological sequence and curve progression, it was possible to reproduce a good approximation of the motion of a person’s center of mass during fall events based on the available sensor information. Conclusions: Re-enactment is a promising method to understand and visualize the biomechanics of inertial sensor-recorded real-world falls when performed in a suitable setup, especially if video data is not available.

  • Source: freepik; Copyright: jcomp; URL: https://www.freepik.com/free-photo/woman-using-computer-mouse-with-laptop_3952295.htm#page=5&query=person+using+computer&position=26; License: Licensed by JMIR.
    Infodemiology and Infoveillance

    Apr 2, 2020

    Use of Rapid Online Surveys to Assess People's Perceptions During Infectious Disease Outbreaks: A Cross-sectional Survey on COVID-19

    Authors List:

    Abstract:

    Background: Given the extensive time needed to conduct a nationally representative household survey and the commonly low response rate of phone surveys, rapid online surveys may be a promising method to assess and track knowledge and perceptions among the general public during fast-moving infectious disease outbreaks. Objective: This study aimed to apply rapid online surveying to determine knowledge and perceptions of coronavirus disease 2019 (COVID-19) among the general public in the United States and the United Kingdom. Methods: An online questionnaire was administered to 3000 adults residing in the United States and 3000 adults residing in the United Kingdom who had registered with Prolific Academic to participate in online research. Prolific Academic established strata by age (18-27, 28-37, 38-47, 48-57, or ≥58 years), sex (male or female), and ethnicity (white, black or African American, Asian or Asian Indian, mixed, or “other”), as well as all permutations of these strata. The number of participants who could enroll in each of these strata was calculated to reflect the distribution in the US and UK general population. Enrollment into the survey within each stratum was on a first-come, first-served basis. Participants completed the questionnaire between February 23 and March 2, 2020. Results: A total of 2986 and 2988 adults residing in the United States and the United Kingdom, respectively, completed the questionnaire. Of those, 64.4% (1924/2986) of US participants and 51.5% (1540/2988) of UK participants had a tertiary education degree, 67.5% (2015/2986) of US participants had a total household income between US $20,000 and US $99,999, and 74.4% (2223/2988) of UK participants had a total household income between £15,000 and £74,999. US and UK participants’ median estimate for the probability of a fatal disease course among those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was 5.0% (IQR 2.0%-15.0%) and 3.0% (IQR 2.0%-10.0%), respectively. Participants generally had good knowledge of the main mode of disease transmission and common symptoms of COVID-19. However, a substantial proportion of participants had misconceptions about how to prevent an infection and the recommended care-seeking behavior. For instance, 37.8% (95% CI 36.1%-39.6%) of US participants and 29.7% (95% CI 28.1%-31.4%) of UK participants thought that wearing a common surgical mask was “highly effective” in protecting them from acquiring COVID-19, and 25.6% (95% CI 24.1%-27.2%) of US participants and 29.6% (95% CI 28.0%-31.3%) of UK participants thought it was prudent to refrain from eating at Chinese restaurants. Around half (53.8%, 95% CI 52.1%-55.6%) of US participants and 39.1% (95% CI 37.4%-40.9%) of UK participants thought that children were at an especially high risk of death when infected with SARS-CoV-2. Conclusions: The distribution of participants by total household income and education followed approximately that of the US and UK general population. The findings from this online survey could guide information campaigns by public health authorities, clinicians, and the media. More broadly, rapid online surveys could be an important tool in tracking the public’s knowledge and misperceptions during rapidly moving infectious disease outbreaks.

  • Source: Unsplash; Copyright: ROBIN WORRALL; URL: https://unsplash.com/photos/FPt10LXK0cg; License: Licensed by JMIR.
    Web-based and Mobile Health...

    Apr 2, 2020

    Optimizing Text Messages to Promote Engagement With Internet Smoking Cessation Treatment: Results From a Factorial Screening Experiment

    Authors List:

    Abstract:

    Background: Smoking remains a leading cause of preventable death and illness. Internet interventions for smoking cessation have the potential to significantly impact public health, given their broad reach and proven effectiveness. Given the dose-response association between engagement and behavior change, identifying strategies to promote engagement is a priority across digital health interventions. Text messaging is a proven smoking cessation treatment modality and a powerful strategy to increase intervention engagement in other areas of health, but it has not been tested as an engagement strategy for a digital cessation intervention. Objective: This study examined the impact of 4 experimental text message design factors on adult smokers’ engagement with an internet smoking cessation program. Methods: We conducted a 2×2×2×2 full factorial screening experiment wherein 864 participants were randomized to 1 of 16 experimental conditions after registering with a free internet smoking cessation program and enrolling in its automated text message program. Experimental factors were personalization (on/off), integration between the web and text message platforms (on/off), dynamic tailoring of intervention content based on user engagement (on/off), and message intensity (tapered vs abrupt drop-off). Primary outcomes were 3-month measures of engagement (ie, page views, time on site, and return visits to the website) as well as use of 6 interactive features of the internet program. All metrics were automatically tracked; there were no missing data. Results: Main effects were detected for integration and dynamic tailoring. Integration significantly increased interactive feature use by participants, whereas dynamic tailoring increased the number of features used and page views. No main effects were found for message intensity or personalization alone, although several synergistic interactions with other experimental features were observed. Synergistic effects, when all experimental factors were active, resulted in the highest rates of interactive feature use and the greatest proportion of participants at high levels of engagement. Measured in terms of standardized mean differences (SMDs), effects on interactive feature use were highest for Build Support System (SMD 0.56; 95% CI 0.27 to 0.81), Choose Quit Smoking Aid (SMD 0.38; 95% CI 0.10 to 0.66), and Track Smoking Triggers (SMD 0.33; 95% CI 0.05 to 0.61). Among the engagement metrics, the largest effects were on overall feature utilization (SMD 0.33; 95% CI 0.06 to 0.59) and time on site (SMD 0.29; 95% CI 0.01 to 0.57). As no SMD >0.30 was observed for main effects on any outcome, results suggest that for some outcomes, the combined intervention was stronger than individual factors alone. Conclusions: This factorial experiment demonstrates the effectiveness of text messaging as a strategy to increase engagement with an internet smoking cessation intervention, resulting in greater overall intervention dose and greater exposure to the core components of tobacco dependence treatment that can promote abstinence. Trial Registration: ClinicalTrials.gov NCT02585206; https://clinicaltrials.gov/ct2/show/NCT02585206.

  • Early tests of the eye-tracking device. Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2020/4/e15876/; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).
    Clinical Informatics

    Apr 2, 2020

    Leveraging Eye Tracking to Prioritize Relevant Medical Record Data: Comparative Machine Learning Study

    Authors List:

    Abstract:

    Background: Electronic medical record (EMR) systems capture large amounts of data per patient and present that data to physicians with little prioritization. Without prioritization, physicians must mentally identify and collate relevant data, an activity that can lead to cognitive overload. To mitigate cognitive overload, a Learning EMR (LEMR) system prioritizes the display of relevant medical record data. Relevant data are those that are pertinent to a context—defined as the combination of the user, clinical task, and patient case. To determine which data are relevant in a specific context, a LEMR system uses supervised machine learning models of physician information-seeking behavior. Since obtaining information-seeking behavior data via manual annotation is slow and expensive, automatic methods for capturing such data are needed. Objective: The goal of the research was to propose and evaluate eye tracking as a high-throughput method to automatically acquire physician information-seeking behavior useful for training models for a LEMR system. Methods: Critical care medicine physicians reviewed intensive care unit patient cases in an EMR interface developed for the study. Participants manually identified patient data that were relevant in the context of a clinical task: preparing a patient summary to present at morning rounds. We used eye tracking to capture each physician’s gaze dwell time on each data item (eg, blood glucose measurements). Manual annotations and gaze dwell times were used to define target variables for developing supervised machine learning models of physician information-seeking behavior. We compared the performance of manual selection and gaze-derived models on an independent set of patient cases. Results: A total of 68 pairs of manual selection and gaze-derived machine learning models were developed from training data and evaluated on an independent evaluation data set. A paired Wilcoxon signed-rank test showed similar performance of manual selection and gaze-derived models on area under the receiver operating characteristic curve (P=.40). Conclusions: We used eye tracking to automatically capture physician information-seeking behavior and used it to train models for a LEMR system. The models that were trained using eye tracking performed like models that were trained using manual annotations. These results support further development of eye tracking as a high-throughput method for training clinical decision support systems that prioritize the display of relevant medical record data.

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2020/4/e15863/; License: Creative Commons Attribution (CC-BY).
    Mobile Health (mhealth)

    Apr 2, 2020

    Effectiveness of One-Way Text Messaging on Attendance to Follow-Up Cervical Cancer Screening Among Human Papillomavirus–Positive Tanzanian Women...

    Authors List:

    Abstract:

    Background: Rapid human papillomavirus (HPV) DNA testing is an emerging cervical cancer screening strategy in resource-limited countries, yet it requires follow-up of women who test HPV positive. Objective: This study aimed to determine if one-way text messages improved attendance to a 14-month follow-up cervical cancer screening among HPV-positive women. Methods: This multicenter, parallel-group randomized controlled trial was conducted at 3 hospitals in Tanzania. Eligible participants were aged between 25 and 60 years, had tested positive to a rapid HPV test during a patient-initiated screening, had been informed of their HPV result, and had a private mobile phone with a valid number. Participants were randomly assigned in a 1:1 ratio to the intervention or control group through an incorporated algorithm in the text message system. The intervention group received one-way text messages, and the control group received no text messages. The primary outcome was attendance at a 14-month health provider-initiated follow-up screening. Participants were not blinded, but outcome assessors were. The analysis was based on intention to treat. Results: Between August 2015 and July 2017, 4080 women were screened for cervical cancer, of which 705 were included in this trial—358 women were allocated to the intervention group, and 347 women were allocated to the control group. Moreover, 16 women were excluded before the analysis because they developed cervical cancer or died (8 from each group). In the intervention group, 24.0% (84/350) women attended their follow-up screening, and in the control group, 23.8% (80/335) women attended their follow-up screening (risk ratio 1.02, 95% CI 0.79-1.33). Conclusions: Attendance to a health provider-initiated follow-up cervical cancer screening among HPV-positive women was strikingly low, and one-way text messages did not improve the attendance rate. Implementation of rapid HPV testing as a primary screening method at the clinic level entails the challenge of ensuring a proper follow-up of women. Trial Registration: ClinicalTrials.gov NCT02509702; https://clinicaltrials.gov/ct2/show/NCT02509702.

  • Source: Unsplash; Copyright: CDC; URL: https://unsplash.com/photos/GnLuuG9crEY; License: Licensed by JMIR.
    Clinical Informatics

    Apr 2, 2020

    Longitudinal Study of the Variation in Patient Turnover and Patient-to-Nurse Ratio: Descriptive Analysis of a Swiss University Hospital

    Authors List:

    Abstract:

    Background: Variations in patient demand increase the challenge of balancing high-quality nursing skill mixes against budgetary constraints. Developing staffing guidelines that allow high-quality care at minimal cost requires first exploring the dynamic changes in nursing workload over the course of a day. Objective: Accordingly, this longitudinal study analyzed nursing care supply and demand in 30-minute increments over a period of 3 years. We assessed 5 care factors: patient count (care demand), nurse count (care supply), the patient-to-nurse ratio for each nurse group, extreme supply-demand mismatches, and patient turnover (ie, number of admissions, discharges, and transfers). Methods: Our retrospective analysis of data from the Inselspital University Hospital Bern, Switzerland included all inpatients and nurses working in their units from January 1, 2015 to December 31, 2017. Two data sources were used. The nurse staffing system (tacs) provided information about nurses and all the care they provided to patients, their working time, and admission, discharge, and transfer dates and times. The medical discharge data included patient demographics, further admission and discharge details, and diagnoses. Based on several identifiers, these two data sources were linked. Results: Our final dataset included more than 58 million data points for 128,484 patients and 4633 nurses across 70 units. Compared with patient turnover, fluctuations in the number of nurses were less pronounced. The differences mainly coincided with shifts (night, morning, evening). While the percentage of shifts with extreme staffing fluctuations ranged from fewer than 3% (mornings) to 30% (evenings and nights), the percentage within “normal” ranges ranged from fewer than 50% to more than 80%. Patient turnover occurred throughout the measurement period but was lowest at night. Conclusions: Based on measurements of patient-to-nurse ratio and patient turnover at 30-minute intervals, our findings indicate that the patient count, which varies considerably throughout the day, is the key driver of changes in the patient-to-nurse ratio. This demand-side variability challenges the supply-side mandate to provide safe and reliable care. Detecting and describing patterns in variability such as these are key to appropriate staffing planning. This descriptive analysis was a first step towards identifying time-related variables to be considered for a predictive nurse staffing model.

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2020/4/e15841/; License: Creative Commons Attribution (CC-BY).
    Web-based and Mobile Health...

    Apr 1, 2020

    Efficacy of a Theory-Based Cognitive Behavioral Technique App-Based Intervention for Patients With Insomnia: Randomized Controlled Trial

    Authors List:

    Abstract:

    Background: Sleep hygiene is important for maintaining good sleep and reducing insomnia. Objective: This study examined the long-term efficacy of a theory-based app (including cognitive behavioral therapy [CBT], theory of planned behavior [TPB], health action process approach [HAPA], and control theory [CT]) on sleep hygiene among insomnia patients. Methods: The study was a 2-arm single-blind parallel-group randomized controlled trial (RCT). Insomnia patients were randomly assigned to a treatment group that used an app for 6 weeks (ie, CBT for insomnia [CBT-I], n=156) or a control group that received only patient education (PE, n=156) through the app. Outcomes were assessed at baseline and 1 month, 3 months, and 6 months postintervention. Primary outcomes were sleep hygiene, insomnia, and sleep quality. Secondary outcomes included attitudes toward sleep hygiene behavior, perceived behavioral control, behavioral intention, action and coping planning, self-monitoring, behavioral automaticity, and anxiety and depression. Linear mixed models were used to evaluate the magnitude of changes in outcomes between the two groups and across time. Results: Sleep hygiene was improved in the CBT-I group compared with the PE group (P=.02 at 1 month, P=.04 at 3 months, and P=.02 at 6 months) as were sleep quality and severity of insomnia. Mediation analyses suggested that perceived behavioral control on sleep hygiene as specified by TPB along with self-regulatory processes from HAPA and CT mediated the effect of the intervention on outcomes. Conclusions: Health care providers might consider using a CBT-I app to improve sleep among insomnia patients. Trial Registration: ClinicalTrials.gov NCT03605732; https://clinicaltrials.gov/ct2/show/NCT03605732

  • Source: freepik; Copyright: katemangostar; URL: https://www.freepik.com/free-photo/businesswoman-working-with-laptop-touchpad_1355538.htm#page=8&query=black+woman+using+tablet&position=45; License: Licensed by JMIR.
    Electronic/Mobile Data Capture,...

    Apr 1, 2020

    Use of Telephone and Digital Channels to Engage Socioeconomically Disadvantaged Adults in Health Disparities Research Within a Social Service Setting:...

    Authors List:

    Abstract:

    Background: Engaging socioeconomically disadvantaged populations in health research is vital to understanding and, ultimately, eliminating health-related disparities. Digital communication channels are increasingly used to recruit study participants, and recent trends indicate a growing need to partner with the social service sector to improve population health. However, few studies have recruited participants from social service settings using multiple digital channels. Objective: This study aimed to recruit and survey 3791 adult clients of a social service organization via telephone and digital channels. This paper aimed to describe recruitment outcomes across five channels and compare participant characteristics by recruitment channel type. Methods: The Cancer Communication Channels in Context Study recruited and surveyed adult clients of 2-1-1, a social service–focused information and referral system, using five channels: telephone, website, text message, web-based live chat, and email. Participants completed surveys administered either by phone (if recruited by phone) or on the web (if recruited from digital channels, ie, website, text message, Web-based live chat, or email). Measures for the current analysis included demographic and health characteristics. Results: A total of 3293 participants were recruited, with 1907 recruited by phone and 1386 recruited from digital channels. Those recruited by phone had a moderate study eligibility rate (42.23%) and the highest survey completion rate (91.24%) of all channels. Individuals recruited by text message had a high study eligibility rate (94.14%) yet the lowest survey completion rate (74.0%) of all channels. Sample accrual goals were achieved for phone, text message, and website recruitment. Multivariable analyses found differences in participant characteristics by recruitment channel type. Compared with participants recruited by phone, those recruited from digital channels were younger (adjusted odds ratio [aOR] 0.96, 95% CI 0.96-0.97) and more likely to be female (aOR 1.52, 95% CI 1.23-1.88), married (aOR 1.52, 95% CI 1.22-1.89), and other than non-Hispanic black (aOR 1.48, 95% CI 1.22-1.79). Those recruited via phone also were more likely to have more than a high school education (aOR 2.17, 95% CI 1.67-2.82), have a household income ≥US $25,000 a year (aOR 2.02, 95% CI 1.56-2.61), and have children living in the home (aOR 1.26, 95% CI 1.06-1.51). Additionally, participants recruited from digital channels were less likely than those recruited by phone to have public health insurance (aOR 0.75, 95% CI 0.62-0.90) and more likely to report better overall health (aOR 1.52, 95% CI 1.27-1.83 for good-to-excellent health). Conclusions: Findings indicate the feasibility and utility of recruiting socioeconomically disadvantaged adults from the social service sector using multiple communication channels, including digital channels. As social service–based health research evolves, strategic recruitment using a combination of traditional and digital channels may be warranted to avoid underrepresentation of highly medically vulnerable individuals, which could exacerbate disparities in health.

  • Source: freepik; Copyright: jcomp; URL: https://www.freepik.com/free-photo/working-office_908429.htm#page=2&query=person+using+laptop&position=42; License: Licensed by JMIR.
    Peer-to-Peer Support and Online...

    Apr 1, 2020

    Patients’ Willingness to Share Information in Online Patient Communities: Questionnaire Study

    Authors List:

    Abstract:

    Background: Online patient communities provide new channels for users to access and share medical information. In-depth study of users’ willingness to share information in online patient communities is of great significance for improving the level of information sharing among the patient community and the long-term development of communities. Objective: The aim of this study was to build a model of factors affecting patients’ willingness to share medical information from the perspective of both positive and negative utilities. Specifically, we aimed to determine the influence of online information support and privacy concerns, as well as the moderating effect of disease severity and information sensitivity of different patients on their willingness to share. Methods: Data from 490 users with experience in online patient communities were collected through a questionnaire survey, and structural equations were applied to empirically verify the model hypotheses. Results: Privacy concerns negatively affected the patients’ willingness to share information (P<.001), whereas online information support positively affected patients’ willingness to share information (P<.001), and information sensitivity negatively moderated the impact of online information support on sharing willingness (P=.01). Disease severity positively moderated the impact of privacy concerns on sharing willingness (P=.05). However, the hypotheses that information sensitivity is a negative moderator and disease severity is a positive moderator of the impact of privacy concerns on sharing willingness could not be supported. Conclusions: To improve the level of user information sharing, the online patient community should design a safe user registration process, ensure the confidentiality of information, reduce the privacy concerns of users, and accurately identify the information needs of patients to provide personalized support services.

  • Source: Fred van Diem Photography; Copyright: The Authors; URL: https://www.jmir.org/2020/4/e14549; License: Licensed by the authors.
    Innovations and Technology for...

    Apr 1, 2020

    Effectiveness of Serious Games to Increase Physical Activity in Children With a Chronic Disease: Systematic Review With Meta-Analysis

    Authors List:

    Abstract:

    Background: Physical activity (PA) is important for children with a chronic disease. Serious games may be useful to promote PA levels among these children. Objective: The primary purpose of this systematic review was to evaluate the effectiveness of serious games on PA levels in children with a chronic disease. Methods: PubMed, EMBASE, PsycINFO, ERIC, Cochrane Library, and CINAHL were systematically searched for articles published from January 1990 to May 2018. Both randomized controlled trials and controlled clinical trials were included to examine the effects of serious games on PA levels in children with a chronic disease. Two investigators independently assessed the intervention, methods, and methodological quality in all articles using the Cochrane risk of bias tool. Both qualitative and quantitative analyses were performed. Results: This systematic review included 9 randomized controlled trials (886 participants). In 2 of the studies, significant between-group differences in PA levels in favor of the intervention group were reported. The meta-analysis on PA levels showed a nonsignificant effect on moderate to vigorous PA (measured in minutes per day) between the intervention and control groups (standardized mean difference 0.30, 95% CI –0.15 to 0.75, P=.19). The analysis of body composition resulted in significantly greater reductions in BMI in the intervention group (standardized mean difference –0.24, 95% CI –0.45 to 0.04, P=.02). Conclusions: This review does not support the hypothesis that serious games improve PA levels in children with a chronic disease. The meta-analysis on body composition showed positive intervention effects with significantly greater reductions in BMI in favor of the intervention group. A high percentage of nonuse was identified in the study of serious games, and little attention was paid to behavior change theories and specific theoretical approaches to enhance PA in serious games. Small sample sizes, large variability between intervention designs, and limited details about the interventions were the main limitations. Future research should determine which strategies enhance the effectiveness of serious games, possibly by incorporating behavior change techniques.

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    Open Peer Review Period: Mar 31, 2020 - May 26, 2020

    Background: Digital health, which encompasses the use of information and communications technology in support of health, is a key driving force behind the cultural transformation of medicine towards p...

    Background: Digital health, which encompasses the use of information and communications technology in support of health, is a key driving force behind the cultural transformation of medicine towards people-centredness. Thus, eHealth literacy may support better experiences of care supported by innovative digital health solutions. Objective: To explore the relationship between eHealth literacy and patient-reported experience measures (PREMs) among users of outpatient care in Hungary. Methods: In early 2019, we conducted a cross-sectional survey on a large representative online sample recruited from the Hungarian general population. eHealth literacy was measured with the eHealth Literacy Scale (eHEALS) and PREMs with outpatient care with a set of questions recommended by the Organisation for Economic Co-operation and Development (OECD). Bivariate relationships were explored via polychoric correlation, the Kruskal-Wallis test and chi-square test. To capture non-linear associations, after controlling covariates, we analysed the relationship between eHEALS quartiles and PREMs using multivariate probit, OLS, ordered logit and logistic regression models. Results: 653 respondents (356 females, 54.5%) were included in the study with mean age of 49.2 (SD 17.5) and eHEALS score of 29.4 (SD 4.9). Respondents with higher eHEALS score were more likely to understand the healthcare professionals’ explanations (Chi-square(9)=25.6, P=.002) and to be involved in decision-making about care and treatment (Chi-square(9)=18.0, P=.03). In multivariate regression, respondents with lowest (1st quartile) and moderately high (3rd quartile) eHEALS scores differed significantly, where the latter were more likely to have an overall positive experience (P=.03) and experience fewer problems (P=.03). Also, those respondents had better experiences in terms of how easy it was to understand the healthcare professionals’ explanations (P=.002) and being able to ask questions during their last consultation (P=.03). Patient reported experiences of individuals with highest (4th quartile) and lowest (1st quartile) eHEALS levels did not differ significantly. Also, the relationship between eHealth literacy and self-reported unmet medical needs, and waiting times, was not significant. Conclusions: We demonstrated the association between eHealth literacy and PREMs. Individuals with the lowest self-reported eHealth literacy levels have a greater chance of a negative experiences with outpatient care, while those with moderately high eHealth literacy are more likely to have positive experiences. Actions should be taken to identify and support people with low eHealth literacy as they are at higher risk of experiencing problems in outpatient care, and hence, having difficulties to cope with medical treatments. The potential patient-, physician- and system-related factors explaining the negative experiences among people with highest levels of eHealth literacy warrant further investigation.

  • Using big data for effective surveillance and control of COVID-19: useful experiences from Hubei province of China

    Date Submitted: Mar 29, 2020

    Open Peer Review Period: Mar 29, 2020 - Apr 6, 2020

    Background: Background: COVID-19 has been an unprecedented challenge to the global healthcare system. Tools that can improve the focus of surveillance efforts and clinical decision support are of para...

    Background: Background: COVID-19 has been an unprecedented challenge to the global healthcare system. Tools that can improve the focus of surveillance efforts and clinical decision support are of paramount importance. Objective: Objective: New medical informatics technologies are needed to enable effective control of the pandemic. Methods: Methods: The Honghu Hybrid System (HHS) for COVID-19 collected, integrated, standardized and analyzed data from multiple sources, including the case reporting system, diagnostic labs, electronic medical records and social media on mobile devices. Results: Results: HHS was developed and successfully deployed within 72 hours in the city of Honghu in Hubei Province, China. Syndromic surveillance component in HHS covered over 95% of the population of over 900,000 people and provided near real-time evidence for the control of epidemic emergencies. Clinical decision support component in HHS was also provided to improve patient care and prioritize the limited medical resources. Conclusions: Conclusions: The facilitating factors and challenges are discussed to provide useful insights to other cities to build up suitable solutions based on big-data technologies. The HHS for COVID-19 proved to be feasible, sustainable and effective and can be migrated.

  • Text processing for detection of fungal ocular involvement in critical care patients: A cross-sectional study

    Date Submitted: Mar 23, 2020

    Open Peer Review Period: Mar 23, 2020 - May 18, 2020

    Background: Fungal ocular involvement can develop in patients with fungal bloodstream infections and can be vision-threatening. Ocular involvement has become less common in the current era of improved...

    Background: Fungal ocular involvement can develop in patients with fungal bloodstream infections and can be vision-threatening. Ocular involvement has become less common in the current era of improved anti-fungal therapies, with multiple studies reporting only a few cases over several years. However, manual retrospective record review to detect cases is time-consuming. Objective: To determine the prevalence of fungal ocular involvement in a critical care database using both structured and unstructured electronic health record (EHR) data. Methods: We queried microbiology data from 46,467 critical care patients over a twelve-year period (2000-2012) from the Medical Information Mart for Intensive Care III (MIMIC-III) to identify 265 patients with culture-proven fungemia. For each fungemic patient, demographic data, fungal species present in blood culture, and risk factors for fungemia (presence of indwelling catheters, recent major surgery, diabetes, immunosuppressed status, etc.) were ascertained. All structured diagnosis codes and free-text narrative notes associated with each patient’s hospitalization were also extracted. Screening for fungal endophthalmitis was performed using two approaches: (1) by querying a wide array of eye- and vision-related diagnosis codes, and (2) by utilizing a custom regular expression pipeline to identify and collate relevant text matches pertaining to fungal ocular involvement. Both approaches were validated using manual record review. The main outcome measure was documentation of any fungal ocular involvement. Results: 265 patients had culture-proven fungemia, with Candida albicans (43%) and Candida glabrata (28%) being the most common fungal species in blood culture. The in-hospital mortality rate was 41%. Seven patients were identified as having eye- or vision-related diagnosis codes, none of whom had fungal endophthalmitis based on record review. There were 26,830 free-text narrative notes associated with these 265 patients. A regular expression pipeline based on relevant terms yielded possible matches in 683 notes from 108 patients. Subsequent manual record review again demonstrated that no patients had fungal ocular involvement. Therefore, the prevalence of fungal ocular involvement in this cohort was 0%. Conclusions: MIMIC-III contained no cases of ocular involvement among fungemic patients. This supports prior studies reporting low rates of ocular involvement in fungemia. Additionally, it demonstrates an application of natural language processing to expedite review of narrative notes. This approach is highly relevant for ophthalmology, where diagnoses are often based on physical exam findings that are documented within clinical notes.

  • Socially Embodied AI: A Framework for Recognizing the Dynamic Sociality of Artificial Agents Within and Beyond Healthcare

    Date Submitted: Mar 25, 2020

    Open Peer Review Period: Mar 23, 2020 - May 18, 2020

    Modern forms of technology-augmented healthcare are focusing on personalization of the delivery of medical services. This trend is driven in part by the growing rhetoric around patient diversity, empo...

    Modern forms of technology-augmented healthcare are focusing on personalization of the delivery of medical services. This trend is driven in part by the growing rhetoric around patient diversity, empowerment, and choice as factors that impact the success of care. In parallel, there is a push for applying the latest advances in AI-based systems, especially intelligent agents (IA) or artificial agents (AA), as a way of autonomously carrying out and/or supporting interaction within healthcare service and personal health contexts. Robots, conversational agents, voice assistants, virtual characters—do these disparate forms of AI-based agents applied in care contexts have something in common? When and under what circumstances? Here we describe how they can manifest as “socially embodied AI,” which we define as the state an AI-based agent takes on when embedded within social and technologically nonpartisan “bodies” and contexts: a social form of human-AI interaction (HAII). We argue that this state is constructed by and dependent on human perception, arising when an embodied AI is perceived as having social characteristics and being socially interactive. Moreover, as a “circumstantial” category, we argue that if certain criteria are met, then any embodied AI can become socially embodied; however, this may not be true for all people at all times and in all situations. As a first step towards dealing with this complexity, we present an ontology for demarcating when embodied AI transition into socially embodied AI. We draw from theory and practice in human-machine communication (HMC), human-computer interaction (HCI), human-robot interaction (HRI), human-agent interaction (HAI), and social psychology. We reinforce our theoretical work with expert insights from a card sort workshop. We then propose an ontological heuristic for describing the dynamic threshold through which an AI-based agent becomes socially embodied: the Tepper line. We explore two case studies to illustrate the dynamic and contextual nature of this heuristic in healthcare contexts. We end by discussing possible implications of “crossing the Tepper line” from both AI- and human-centered viewpoints in person-centered care.

  • Do doctors care? Validating a tool for the assessment of health information security in Spanish-speaking countries

    Date Submitted: Mar 16, 2020

    Open Peer Review Period: Mar 20, 2020 - May 20, 2020

    Background: Healthcare has increased its use of information technology over the last few years. A trend followed higher usage of Electronic Health Record in low-and-middle-income countries where docto...

    Background: Healthcare has increased its use of information technology over the last few years. A trend followed higher usage of Electronic Health Record in low-and-middle-income countries where doctors use non-medical applications and websites for healthcare-related tasks. Information security awareness and practices are essential to reduce the risk of breaches. Objective: To assess the internal reliability of the Spanish translation of three areas of the Human Aspects of Information Security Questionnaire (HAIS-Q), and to assess the knowledge, attitudes, and practices of medical doctors around information security. Methods: This is a cross-sectional descriptive study designed as a questionnaire-based. We used focus areas (Password management, social media use, and mobile devices use) from the Human Aspects of Information Security Questionnaire (HAIS-Q). Medical doctors in Ecuador answered an online survey between December 2017 and January 2018. Results: A total of 434 health professionals (response rate: 0.65) completed all the questions in our study. Scores were 37.4 (SD 5.9) for Password Management, 35.4 (SD 5.0) for Social Media Use and 35.9 (SD 5.7) for Mobile Devices. Cronbach’s alpha coefficient (α) was 0.78 (95% CI: 0.75, 0.81) for password management, 0.73 (95%CI: 0.69, 0.77) for mobile devices and 0.77 (95% CI: 0.73, 0.78) for Social Media Use. Conclusions: Our study shows that three components of the Spanish translation of the HAIS-Q questionnaire were internally reliable when applied in medical doctors. Medical doctors with eagerness to receive infosec training scored higher in social media use and mobile device use categories.

  • Prevailing outcome themes reported by people with degenerative cervical myelopathy: findings from a semi-structured interview

    Date Submitted: Mar 19, 2020

    Open Peer Review Period: Mar 19, 2020 - May 14, 2020

    Background: Degenerative cervical myelopathy (DCM) arises when arthritic changes of the cervical spine cause compression and a progressive injury to the spinal cord. It is common and potentially disab...

    Background: Degenerative cervical myelopathy (DCM) arises when arthritic changes of the cervical spine cause compression and a progressive injury to the spinal cord. It is common and potentially disabling. People with DCM (PwCM) to have amongst the lowest quality of life scores (SF-36) of chronic disease, although the drivers for this are not entirely understood. DCM research faces a number of challenges, including the heterogenous reporting of study data. The AO Spine RECODE-DCM project is an international consensus process that aims improve research efficiency through formation of a core outcome set (COS). A key part of COS development process is organizing outcomes into domains which represent key aspects of the disease. Objective: To facilitate this, we sought to qualitatively explore the context and impact of patient reported outcomes in DCM on people with DCM (PwCM) and their supporters. The aim was to improve understanding of patient perspective and assist the organisation of outcomes into domains for the consensus process. Methods: A single focus group was hosted by Myelopathy.org, a charity and support group for PwCM. The 40 minute session was audio-recorded and transcribed verbatim. Data was familiarized and 2 authors performed data coding independently. Codes were grouped into themes and a thematic analysis was performed guided by Braun & Clarke’s six-phase approach. The themes were subsequently reviewed with an independent PwCM stakeholder (ES), assisting in the process of capturing the true context and importance of themes. Results: Five PwCM (three men and two women) and three supporters (all women) participated. The average PwCM age was 53 and the median mJOA was 11 (±IQR 2), indicating these PwCM had moderate to severe DCM. 54 codes were grouped into 10 themes that captured the impact of DCM on PwCM and their supporters. These themes included: acceptance of symptoms, anticipatory anxiety, coping mechanisms/resilience, feelings of helplessness, financial consequences, lack of recognition, mental health impact, loss of life control, social reclusiveness/isolation and social stigma Conclusions: This is the first study to undertake qualitative analysis of PwCM perspectives. It has highlighted a number of prevailing themes currently unmeasured in clinical research or care. The determinants of low quality of life in DCM are currently unknown, and these findings provide a novel and so far, unique perspective. These perspectives will be used to inform the development of a core outcome set for DCM which is inclusive of all relevant stakeholders, including PwCM.

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