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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: Flickr; Copyright: David Stewart; URL: https://www.flickr.com/photos/141436406@N04/30411910658; License: Creative Commons Attribution + Noncommercial (CC-BY-NC).

    Effectiveness and Parental Acceptability of Social Networking Interventions for Promoting Seasonal Influenza Vaccination Among Young Children: Randomized...


    Background: Seasonal influenza vaccination (SIV) coverage among young children remains low worldwide. Mobile social networking apps such as WhatsApp Messenger are promising tools for health interventions. Objective: This was a preliminary study to test the effectiveness and parental acceptability of a social networking intervention that sends weekly vaccination reminders and encourages exchange of SIV-related views and experiences among mothers via WhatsApp discussion groups for promoting childhood SIV. The second objective was to examine the effect of introducing time pressure on mothers’ decision making for childhood SIV for vaccination decision making. This was done using countdowns of the recommended vaccination timing. Methods: Mothers of child(ren) aged 6 to 72 months were randomly allocated to control or to one of two social networking intervention groups receiving vaccination reminders with (SNI+TP) or without (SNI–TP) a time pressure component via WhatsApp discussion groups at a ratio of 5:2:2. All participants first completed a baseline assessment. Both the SNI–TP and SNI+TP groups subsequently received weekly vaccination reminders from October to December 2017 and participated in WhatsApp discussions about SIV moderated by a health professional. All participants completed a follow-up assessment from April to May 2018. Results: A total of 84.9% (174/205), 71% (57/80), and 75% (60/80) who were allocated to the control, SNI–TP, and SNI+TP groups, respectively, completed the outcome assessment. The social networking intervention significantly promoted mothers’ self-efficacy for taking children for SIV (SNI–TP: odds ratio [OR] 2.69 [1.07-6.79]; SNI+TP: OR 2.50 [1.13-5.55]), but did not result in significantly improved children’s SIV uptake. Moreover, after adjusting for mothers’ working status, introducing additional time pressure reduced the overall SIV uptake in children of working mothers (OR 0.27 [0.10-0.77]) but significantly increased the SIV uptake among children of mothers without a full-time job (OR 6.53 [1.87-22.82]). Most participants’ WhatsApp posts were about sharing experience or views (226/434, 52.1%) of which 44.7% (101/226) were categorized as negative, such as their concerns over vaccine safety, side effects and effectiveness. Although participants shared predominantly negative experience or views about SIV at the beginning of the discussion, the moderator was able to encourage the discussion of more positive experience or views and more knowledge and information. Most intervention group participants indicated willingness to receive the same interventions (110/117, 94.0%) and recommend the interventions to other mothers (102/117, 87.2%) in future Conclusions: Online information support can effectively promote mothers’ self-efficacy for taking children for SIV but alone it may not sufficient to address maternal concerns over SIV to achieve a positive vaccination decision. However, the active involvement of health professionals in online discussions can shape positive discussions about vaccination. Time pressure on decision making interacts with maternal work status, facilitating vaccination uptake among mothers who may have more free time, but having the opposite effect among busier working mothers. Trial Registration: Hong Kong University Clinical Trials Registry HKUCTR-2250; https://tinyurl.com/vejv276

  • Child engaged with a communication device. Source: Image created by the Authors; Copyright: Heidi Holmen; URL: http://www.jmir.org/2020/2/e16248/; License: Licensed by JMIR.

    Home-Based Pediatric Palliative Care and Electronic Health: Systematic Mixed Methods Review


    Background: Children and families in pediatric palliative care depend on close contact with health care personnel, and electronic health (eHealth) is suggested to support care at home by facilitating their remote interactions. Objective: This study aimed to identify and review the use of eHealth to communicate and support home-based pediatric palliative care and appraise the methodological quality of the published research. Methods: We conducted a convergent, systematic mixed methods review and searched Medical Literature Analysis and Retrieval System Online (Medline), EMBASE, PsycINFO, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and Scopus for eligible papers. Studies evaluating 2-way communication technology for palliative care for children aged ≤18 years and applying quantitative, qualitative, or mixed methods from 2012 to 2018 were eligible for inclusion. Quantitative and qualitative studies were equally valued during the search, screening, extraction, and analysis. Quantitative data were transformed into qualitative data and analyzed using a thematic analysis. Overall, 2 independent researchers methodologically appraised all included studies. Results: We identified 1277 citations. Only 7 papers were eligible for review. Evaluating eHealth interventions in pediatric palliative care poses specific methodological and ethical challenges. eHealth to facilitate remote pediatric palliative care was acknowledged both as an intrusion and as a support at home. Reluctance toward eHealth was mainly identified among professionals. Conclusions: The strengths of the conclusions are limited by the studies’ methodological challenges. Despite the limitless possibilities held by new technologies, research on eHealth in home-based pediatric palliative care is scarce. The affected children and families appeared to hold positive attitudes toward eHealth, although their views were less apparent compared with those of the professionals. Trial Registration: PROSPERO CRD42018119051; https://tinyurl.com/rtsw5ky

  • SMART Mental health screening by ASHA. Source: The George Institute for Global Health; Copyright: The George Institute for Global Health; URL: http://www.jmir.org/2020/2/e15553/; License: Licensed by the authors.

    The Systematic Medical Appraisal Referral and Treatment Mental Health Project: Quasi-Experimental Study to Evaluate a Technology-Enabled Mental Health...


    Background: Although around 10% of Indians experience depression, anxiety, or alcohol use disorders, very few receive adequate mental health care, especially in rural communities. Stigma and limited availability of mental health services contribute to this treatment gap. The Systematic Medical Appraisal Referral and Treatment Mental Health project aimed to address this gap. Objective: This study aimed to evaluate the effectiveness of an intervention in increasing the use of mental health services and reducing depression and anxiety scores among individuals at high risk of common mental disorders. Methods: A before-after study was conducted from 2014 to 2019 in 12 villages in Andhra Pradesh, India. The intervention comprised a community antistigma campaign, with the training of lay village health workers and primary care doctors to identify and manage individuals with stress, depression, and suicide risk using an electronic clinical decision support system. Results: In total, 900 of 22,046 (4.08%) adults screened by health workers had increased stress, depression, or suicide risk and were referred to a primary care doctor. At follow-up, 731 out of 900 (81.2%) reported visiting the doctor for their mental health symptoms, compared with 3.3% (30/900) at baseline (odds ratio 133.3, 95% CI 89.0 to 199.7; P<.001). Mean depression and anxiety scores were significantly lower postintervention compared with baseline from 13.4 to 3.1 (P<.001) and from 12.9 to 1.9 (P<.001), respectively. Conclusions: The intervention was associated with a marked increase in service uptake and clinically important reductions in depression and anxiety symptom scores. This will be further evaluated in a large-scale cluster randomized controlled trial.

  • Remote monitoring of poststroke patients with a smartphone-based management system. Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2020/2/e15377/; License: Licensed by JMIR.

    Remote Management of Poststroke Patients With a Smartphone-Based Management System Integrated in Clinical Care: Prospective, Nonrandomized, Interventional Study


    Background: Advances in mobile health (mHealth) have enabled systematic and continuous management of patients with chronic diseases. Objective: We developed a smartphone-based mHealth system and aimed to evaluate its effects on health behavior management and risk factor control in stroke patients. Methods: With a multifaceted stroke aftercare management system that included exercise, medication, and educational materials, we performed a 12-week single-arm intervention among eligible poststroke patients in the stroke clinic from September to December 2016. The intervention consisted of (1) regular blood pressure (BP), blood glucose, and physical activity measurements; (2) stroke education; (3) an exercise program; (4) a medication program; and (5) feedback on reviewing of records by clinicians. Clinical assessments consisted of the stroke awareness score, Beck Depression Inventory-II (BDI), EuroQol-5 Dimensions (EQ-5D), and BP at visit 1 (baseline), visit 2 (4 weeks), and visit 3 (12 weeks). Temporal differences in the parameters over 12 weeks were investigated with repeated-measures analysis of variance. Changes in medication adherence at visit 1-2 (from visit 1 to visit 2) and visit 2-3 (from visit 2 to visit 3) were compared. System satisfaction was evaluated with a self-questionnaire using a 5-point Likert scale at visit 3. Results: The study was approved by the Institutional Review Board in September 2016, and participants were enrolled from September to December 2016. Among the 110 patients enrolled for the study, 99 were included in our analyses. The mean stroke awareness score (baseline: 59.6 [SD 18.1]; 4 weeks: 67.6 [SD 16.0], P<.001; 12 weeks: 74.7 [SD 14.0], P<.001) and BDI score (baseline: 12.7 [SD 10.1]; 4 weeks: 11.2 [SD 10.2], P=.01; 12 weeks: 10.7 [SD 10.2], P<.001) showed gradual improvement; however, no significant differences were found in the mean EQ-5D score (baseline: 0.66 [SD 0.33]; 4 weeks: 0.69 [SD 0.34], P=.01; 12 weeks: 0.69 [SD 0.34], P<.001). Twenty-six patients who had uncontrolled BP at baseline had −13.92 mmHg (P=.001) and −6.19 mmHg (P<.001) reductions on average in systolic and diastolic BP, respectively, without any antihypertensive medication change. Medication compliance was better at visit 2-3 (60.9% [SD 37.2%]) than at visit 1-2 (47.8% [SD 38.7%], P<.001). Conclusions: Awareness of stroke, depression, and BP was enhanced when using the smartphone-based mHealth system. Emerging mHealth techniques have potential as new nonpharmacological secondary prevention methods because of their ubiquitous access, near real-time responsiveness, and comparatively lower cost.

  • Source: Unsplash; Copyright: Gras Grun; URL: https://unsplash.com/photos/iCHacuW8BcI; License: Licensed by the authors.

    Locating Medical and Recreational Cannabis Outlets for Research Purposes: Online Methods and Observational Study


    Background: An increasing number of states have laws for the legal sale of recreational and medical cannabis out of brick-and-mortar storefront locations. Given the proliferation of cannabis outlets and their potential for impact on local economies, neighborhood structures, and individual patterns of cannabis use, it is essential to create practical and thorough methods to capture the location of such outlets for research purposes. However, methods used by researchers vary greatly between studies and often do not include important information about the retailer’s license status and storefront signage. Objective: The aim of this study was to find methods for locating and observing cannabis outlets in Los Angeles County after the period when recreational cannabis retailers were granted licenses and allowed to be open for business. Methods: The procedures included searches of online cannabis outlet databases, followed by methods to verify each outlet’s name, address, license information, and open status. These procedures, conducted solely online, resulted in a database of 531 outlets. To further verify each outlet’s information and collect signage data, we conducted direct observations of the 531 identified outlets. Results: We found that 80.9% (430/531) of these outlets were open for business, of which 37.6% (162/430) were licensed to sell cannabis. Unlicensed outlets were less likely to have signage indicating the store sold cannabis, such as a green cross, which was the most prevalent form of observed signage. Co-use of cannabis and tobacco/nicotine has been found to be a substantial health concern, and we observed that 40.6% (175/430) of cannabis outlets had a tobacco/nicotine outlet within sight of the cannabis outlet. Most (350/430, 81.4%) cannabis outlets were located within the City of Los Angeles, and these outlets were more likely to be licensed than outlets outside the city. Conclusions: The findings of this study suggest that online searches and observational methods are both necessary to best capture accurate and detailed information about cannabis outlets. The methods described here can be applied to other metropolitan areas to more accurately capture the availability of cannabis in an area.

  • Source: Unsplash; Copyright: Anton Darius; URL: https://unsplash.com/photos/5S9elyjB_sU; License: Licensed by JMIR.

    Promoting Reproducible Research for Characterizing Nonmedical Use of Medications Through Data Annotation: Description of a Twitter Corpus and Guidelines


    Background: Social media data are being increasingly used for population-level health research because it provides near real-time access to large volumes of consumer-generated data. Recently, a number of studies have explored the possibility of using social media data, such as from Twitter, for monitoring prescription medication abuse. However, there is a paucity of annotated data or guidelines for data characterization that discuss how information related to abuse-prone medications is presented on Twitter. Objective: This study discusses the creation of an annotated corpus suitable for training supervised classification algorithms for the automatic classification of medication abuse–related chatter. The annotation strategies used for improving interannotator agreement (IAA), a detailed annotation guideline, and machine learning experiments that illustrate the utility of the annotated corpus are also described. Methods: We employed an iterative annotation strategy, with interannotator discussions held and updates made to the annotation guidelines at each iteration to improve IAA for the manual annotation task. Using the grounded theory approach, we first characterized tweets into fine-grained categories and then grouped them into 4 broad classes—abuse or misuse, personal consumption, mention, and unrelated. After the completion of manual annotations, we experimented with several machine learning algorithms to illustrate the utility of the corpus and generate baseline performance metrics for automatic classification on these data. Results: Our final annotated set consisted of 16,443 tweets mentioning at least 20 abuse-prone medications including opioids, benzodiazepines, atypical antipsychotics, central nervous system stimulants, and gamma-aminobutyric acid analogs. Our final overall IAA was 0.86 (Cohen kappa), which represents high agreement. The manual annotation process revealed the variety of ways in which prescription medication misuse or abuse is discussed on Twitter, including expressions indicating coingestion, nonmedical use, nonstandard route of intake, and consumption above the prescribed doses. Among machine learning classifiers, support vector machines obtained the highest automatic classification accuracy of 73.00% (95% CI 71.4-74.5) over the test set (n=3271). Conclusions: Our manual analysis and annotations of a large number of tweets have revealed types of information posted on Twitter about a set of abuse-prone prescription medications and their distributions. In the interests of reproducible and community-driven research, we have made our detailed annotation guidelines and the training data for the classification experiments publicly available, and the test data will be used in future shared tasks.

  • Source: Freepik; Copyright: jcomp; URL: https://www.freepik.com/free-photo/doctor-is-working-with-tablet-white-background_3763235.htm#page=2&query=doctor+computer&position=4; License: Licensed by JMIR.

    Dose-Response Effect of a Digital Health Intervention During Cardiac Rehabilitation: Subanalysis of Randomized Controlled Trial


    Background: Previous data have validated the benefit of digital health interventions (DHIs) on weight loss in patients following acute coronary syndrome entering cardiac rehabilitation (CR). Objective: The primary purpose of this study was to test the hypothesis that increased DHI use, as measured by individual log-ins, is associated with improved weight loss. Secondary analyses evaluated the association between log-ins and activity within the platform and exercise, dietary, and medication adherence. Methods: We obtained DHI data including active days, total log-ins, tasks completed, educational modules reviewed, medication adherence, and nonmonetary incentive points earned in patients undergoing standard CR following acute coronary syndrome. Linear regression followed by multivariable models were used to evaluate associations between DHI log-ins and weight loss or dietary adherence. Results: Participants (n=61) were 79% male (48/61) with mean age of 61.0 (SD 9.7) years. We found a significant positive association of total log-ins during CR with weight loss (r2=.10, P=.03). Educational modules viewed (r2=.11, P=.009) and tasks completed (r2=.10, P=.01) were positively significantly associated with weight loss, yet total log-ins were not significantly associated with differences in dietary adherence (r2=.05, P=.12) or improvements in minutes of exercise per week (r2=.03, P=.36). Conclusions: These data extend our previous findings and demonstrate increased DHI log-ins portend improved weight loss in patients undergoing CR after acute coronary syndrome. DHI adherence can potentially be monitored and used as a tool to selectively encourage patients to adhere to secondary prevention lifestyle modifications. Trial Registration: ClinicalTrials.gov (NCT01883050); https://clinicaltrials.gov/ct2/show/NCT01883050

  • Source: freepik; Copyright: pch.vector; URL: https://www.freepik.com/free-photo/cropped-shot-thoughtful-woman-working-with-laptop-library_6882266.htm#page=1&query=woman%20using%20laptop&position=9; License: Licensed by JMIR.

    Equipping Learners to Evaluate Online Health Care Resources: Longitudinal Study of Learning Design Strategies in a Health Care Massive Open Online Course


    Background: The digital revolution has led to a boom in the number of available online health care resources. To navigate these resources successfully, digital literacy education is required. Learners who can evaluate the reliability and validity of online health care information are likely to be more effective at avoiding potentially dangerous misinformation. In addition to providing health care education, massive open online courses (MOOCs) are well positioned to play a role in providing digital literacy education in this context. Objective: This study focused on learners enrolled in a MOOC on cancer genomics. The aim of this study was to evaluate the efficacy of a series of digital literacy–related activities within this course. This was an iterative study, with changes made to digital literacy–related activities in 4 of the 8 runs of the course. Methods: This mixed methods study focused on learner engagement with the digital literacy–related activities, including the final course written assignment. Quantitative data including the number of references listed in each written assignment were compared between successive runs. Qualitative data in the form of learner comments on discussion forums for digital literacy–related tasks were evaluated to determine the impact of these educational activities. Results: Using the number of references included for each final course assignment as an indicator of digital literacy skills, the digital literacy–related activities in the final 2 runs were judged to be the most successful. We found a statistically significant increase in the number of references cited by learners in their final written assignments. The average number of references cited in Run 8 was significantly higher (3.5) than in Run 1 (1.8) of the MOOC (P=.001). Learner comments in Runs 7 and 8 showed that a poll in which learners were asked to select which of 4 online resources was reliable was effective in stimulating learner discussion about how to evaluate resource reliability. Conclusions: Similar to many health care MOOCs, the course studied here had a heterogeneous group of learners, including patients (and their families), the public, health care students, and practitioners. Carefully designing a range of digital literacy–related activities that would be beneficial to this heterogenous group of learners enabled learners to become more effective at evaluating and citing appropriate online resources within their written assignments. Trial Registration:

  • Source: freepik; Copyright: freepik; URL: https://www.freepik.com/free-photo/doctors-doing-research-laptop_5480806.htm#page=1&query=doctor%20doing%20research&position=10; License: Licensed by JMIR.

    Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis


    Background: With the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The development of cloud health care provides a more convenient and effective solution for health. Studying the evolution of knowledge and research hotspots in the field of cloud health care is increasingly important for medical informatics. Scholars in the medical informatics community need to understand the extent of the evolution of and possible trends in cloud health care research to inform their future research. Objective: Drawing on the cloud health care literature, this study aimed to describe the development and evolution of research themes in cloud health care through a knowledge map and common word analysis. Methods: A total of 2878 articles about cloud health care was retrieved from the Web of Science database. We used cybermetrics to analyze and visualize the keywords in these articles. We created a knowledge map to show the evolution of cloud health care research. We used co-word analysis to identify the hotspots and their evolution in cloud health care research. Results: The evolution and development of cloud health care services are described. In 2007-2009 (Phase I), most scholars used cloud computing in the medical field mainly to reduce costs, and grid computing and cloud computing were the primary technologies. In 2010-2012 (Phase II), the security of cloud systems became of interest to scholars. In 2013-2015 (Phase III), medical informatization enabled big data for health services. In 2016-2017 (Phase IV), machine learning and mobile technologies were introduced to the medical field. Conclusions: Cloud health care research has been rapidly developing worldwide, and technologies used in cloud health research are simultaneously diverging and becoming smarter. Cloud–based mobile health, cloud–based smart health, and the security of cloud health data and systems are three possible trends in the future development of the cloud health care field.

  • Untitled. Source: freepik; Copyright: Nensuria; URL: https://www.freepik.com/free-photo/doctor-her-patient-choosing-mammary-prosthesis-office_1624913.htm#page=1&query=doctor%20patient&position=17; License: Creative Commons Attribution (CC-BY).

    Characteristics of Patients Using Different Patient Portal Functions and the Impact on Primary Care Service Utilization and Appointment Adherence:...


    Background: Patient portals are now widely available and increasingly adopted by patients and providers. Despite the growing research interest in patient portal adoption, there is a lack of follow-up studies describing the following: whether patients use portals actively; how frequently they use distinct portal functions; and, consequently, what the effects of using them are, the understanding of which is paramount to maximizing the potential of patient portals to enhance care delivery. Objective: To investigate the characteristics of primary care patients using different patient portal functions and the impact of various portal usage behaviors on patients’ primary care service utilization and appointment adherence. Methods: A retrospective, observational study using a large dataset of 46,544 primary care patients from University of Florida Health was conducted. Patient portal users were defined as patients who adopted a portal, and adoption was defined as the status that a portal account was opened and kept activated during the study period. Then, users were further classified into different user subgroups based on their portal usage of messaging, laboratory, appointment, and medication functions. The intervention outcomes were the rates of primary care office visits categorized as arrived, telephone encounters, cancellations, and no-shows per quarter as the measures of primary care service utilization and appointment adherence. Generalized linear models with a panel difference-in-differences study design were then developed to estimate the rate ratios between the users and the matched nonusers of the four measurements with an observational window of up to 10 quarters after portal adoption. Results: Interestingly, a high propensity to adopt patient portals does not necessarily imply more frequent use of portals. In particular, the number of active health problems one had was significantly negatively associated with portal adoption (odds ratios [ORs] 0.57-0.86, 95% CIs 0.51-0.94, all P<.001) but was positively associated with portal usage (ORs 1.37-1.76, 95% CIs 1.11-2.22, all P≤.01). The same was true for being enrolled in Medicare for portal adoption (OR 0.47, 95% CI 0.41-0.54, P<.001) and message usage (OR 1.44, 95% CI 1.03-2.03, P=.04). On the impact of portal usage, the effects were time-dependent and specific to the user subgroup. The most salient change was the improvement in appointment adherence, and patients who used messaging and laboratory functions more often exhibited a larger reduction in no-shows compared to other user subgroups. Conclusions: Patients differ in their portal adoption and usage behaviors, and the portal usage effects are heterogeneous and dynamic. However, there exists a lack of match in the patient portal market where patients who benefit the most from patient portals are not active portal adopters. Our findings suggest that health care delivery planners and administrators should remove the barriers of adoption for the portal beneficiaries; in addition, they should incorporate the impact of portal usage into care coordination and workflow design, ultimately aligning patients’ and providers’ needs and functionalities to effectively deliver patient-centric care.

  • Untitled. Source: freepik; Copyright: katemangostar; URL: https://www.freepik.com/free-photo/positive-senior-lady-showing-photos-daughter-laptop_4167026.htm#page=1&query=elderly%20computer&position=15; License: Licensed by JMIR.

    Online Self-Management Support for Family Caregivers Dealing With Behavior Changes in Relatives With Dementia (Part 2): Randomized Controlled Trial


    Background: Online contacts with a health professional have the potential to support family caregivers of people with dementia. Objective: The goal of the research was to study the effects of an online self-management support intervention in helping family caregivers deal with behavior changes of a relative with dementia. The intervention—involving among others personal email contacts with a dementia nurse—was compared with online interventions without these email contacts. Methods: A randomized controlled trial was conducted with 81 family caregivers of people with dementia who live at home. Participants were randomly assigned to a (1) major self-management support intervention consisting of personal email contacts with a specialist dementia nurse, online videos, and e-bulletins; (2) medium intervention consisting only of online videos and e-bulletins; or (3) minor intervention consisting of only the e-bulletins. The primary outcome was family caregivers’ self-efficacy in dealing with behavior changes of the relative with dementia. Secondary outcomes were family caregivers’ reports of behavior problems in the people with dementia and the quality of the relationship between the family caregiver and the person with dementia. Measurements were performed at the baseline and at 6 (T1) and 12 weeks (T2) after the baseline. A mixed-model analysis was conducted to compare the outcomes of the 3 intervention arms. Results: Family caregivers participating in the major intervention involving email contacts showed no statistically significant differences in self-efficacy after the intervention compared with the minor intervention involving only e-bulletins (difference –0.02, P=.99). In the adjusted analysis, the medium intervention (involving videos and e-bulletins) showed a negative trend over time (difference –4.21, P=.09) and at T1 (difference –4.71, P=.07) compared with the minor intervention involving only e-bulletins. No statistical differences were found between the intervention arms in terms of the reported behavior problems and the quality of the relationship between the family caregiver and the person with dementia. Conclusions: The expectation that an online self-management support intervention involving email contacts would lead to positive effects and be more effective than online interventions without personal email contacts was not borne out. One explanation might be related to the fact that not all family caregivers who were assigned to that intervention actually made use of the opportunity for personal email contact. The online videos were also not always viewed. To obtain more definite conclusions, future research involving extra efforts to reach higher use rates is required. Trial Registration: Netherlands Trial Registry NTR6237; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=6237 (Archived by WebCite at http://www.webcitation.org/6v0S4fxTC)

  • Source: Pixabay; Copyright: 27707; URL: https://pixabay.com/ko/photos/%EA%B3%B5%EB%B6%80-%EC%8B%9C%ED%97%98-%EC%A4%80%EB%B9%84-%EC%A7%80%EC%8B%9D-951818/; License: Licensed by the authors.

    Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study


    Background: Methylphenidate, a stimulant used to treat attention deficit hyperactivity disorder, has the potential to be used nonmedically, such as for studying and recreation. In an era when many people actively use social networking services, experience with the nonmedical use or side effects of methylphenidate might be shared on Twitter. Objective: The purpose of this study was to analyze tweets about the nonmedical use and side effects of methylphenidate using a machine learning approach. Methods: A total of 34,293 tweets mentioning methylphenidate from August 2018 to July 2019 were collected using searches for “methylphenidate” and its brand names. Tweets in a randomly selected training dataset (6860/34,293, 20.00%) were annotated as positive or negative for two dependent variables: nonmedical use and side effects. Features such as personal noun, nonmedical use terms, medical use terms, side effect terms, sentiment scores, and the presence of a URL were generated for supervised learning. Using the labeled training dataset and features, support vector machine (SVM) classifiers were built and the performance was evaluated using F1 scores. The classifiers were applied to the test dataset to determine the number of tweets about nonmedical use and side effects. Results: Of the 6860 tweets in the training dataset, 5.19% (356/6860) and 5.52% (379/6860) were about nonmedical use and side effects, respectively. Performance of SVM classifiers for nonmedical use and side effects, expressed as F1 scores, were 0.547 (precision: 0.926, recall: 0.388, and accuracy: 0.967) and 0.733 (precision: 0.920, recall: 0.609, and accuracy: 0.976), respectively. In the test dataset, the SVM classifiers identified 361 tweets (1.32%) about nonmedical use and 519 tweets (1.89%) about side effects. The proportion of tweets about nonmedical use was highest in May 2019 (46/2624, 1.75%) and December 2018 (36/2041, 1.76%). Conclusions: The SVM classifiers that were built in this study were highly precise and accurate and will help to automatically identify the nonmedical use and side effects of methylphenidate using Twitter.

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    Background: Caring for the growing dementia patient population with complex healthcare needs in West Virginia has been challenging due to its large, sizably rural-dwelling geriatric population and lim...

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    Open Peer Review Period: Feb 22, 2020 - Apr 22, 2020

    Background: In December 2019, novel coronavirus broke out in Wuhan, Hubei with an impact spreading to the whole of China. Under this condition, many WeChat official accounts have posted articles daily...

    Background: In December 2019, novel coronavirus broke out in Wuhan, Hubei with an impact spreading to the whole of China. Under this condition, many WeChat official accounts have posted articles daily to transmit health information about the epidemic. We found that the number of followers in many official accounts has soared, whereas that in several accounts has remained stable or decreased. Moreover, the numbers and classifications of essays posted have varied amongst accounts. Objective: This study aims to explore the impact factors of health information dissemination on users’ behaviours in WeChat. Methods: We adopted the uses and gratifications theory to reveal the principle in information dissemination of the official accounts. Two-wave data, comprising the number of followers from the top 200 official accounts on 21 January 2020 and 27 January 2020, were used to calculate the increase. We selected them during the seven-day period as the first dependent variable. The total number of likes from headlines on the epidemic in this period was selected as the second dependent variable. The number of each type of articles and headlines about the coronavirus served as the independent variables. The above data were used to develop multiple and simple linear regression models. We used content analysis to explore other factors affecting users’ behaviour. Results: The top 200 official accounts can be classified to institution, medicine and individual groups. For institution and medicine groups, the adjusted R2 value in the multiple linear regression model were 0.355 and 0.452, respectively. For the institution group, the adjusted R2 value in the simple linear regression model was 0.317. The other results were insignificant, and we could not develop an ideal model for them. However, the above R2 value indicated a good fit. For the institution group, report and story types of articles were significant for the multiple linear regression model (B=2.724, P=.007; B=14.875, P=.003), and both were identified positive effects. For the simple linear regression model, the number of headlines on coronavirus was identified positive effect (B=3.084, P<.001). For the medicine group, report and science types were significant for the multiple linear regression model (B=4.381, P=.009; B=31.564, P<.001) and had a positive effect. Conclusions: Different factors in health information dissemination contribute to users’ behaviour. Through content analysis, we concluded that articles with multiform information and certain types are considerably more popular than their counterpart.

  • Effects of Incentives on Adherence to a Web-based Intervention Promoting Physical Activity: An Ecological Study

    Date Submitted: Feb 20, 2020

    Open Peer Review Period: Feb 20, 2020 - Apr 16, 2020

    Background: Despite many advantages of web-based health behavior interventions such as wide accessibility or low costs, these interventions are often accompanied by high attrition rates, particularly...

    Background: Despite many advantages of web-based health behavior interventions such as wide accessibility or low costs, these interventions are often accompanied by high attrition rates, particularly in usage under real-life conditions. It would therefore be helpful to implement strategies such as the use of financial incentives to motivate program participation and increase adherence. Objective: This ecological study examined program adherence to a 12-week web-based physical activity (PA) intervention (Fitness Coach) among insurants who participated in an additional incentive program (IP group) and those who did not use the incentive program (No IP group). IP users had the perspective of receiving 30 € cash back at the end of the intervention. Methods: Registration and usage data of the Fitness Coach were analyzed between September 2016 and June 2018. Depending on the duration of use and the weekly recording of tasks, four adherence groups (low, occasional, strong, complete adherence) were defined. Demographic characteristics were collected by a self-reported questionnaire at registration. We analyzed baseline predictors and moderators of complete adherence such as participation in the IP, age, gender, and BMI using binary logistic regressions. Results: A total of 18.613 eligible persons registered for the intervention with 15.482 users choosing to participate in the incentive program (IP; Mage = 42.4 years; MBMI = 24.5 kg/m2; 65.1% female) and 3.131 users deciding not to use the incentive program (No IP; Mage = 40.7 years; MBMI = 26.2 kg/m2; 72.2% female). At the end of the intervention, participants of the IP group showed 4.8 times higher complete adherence rates than the No IP group (39.2% vs 8.1%), also yielding significantly higher odds to complete the intervention (Odds Ratio [OR] = 12.638) for the IP users. Gender significantly moderated the effect with men in the IP group showing higher odds to be completely adherent than women overall and men in the No IP group (OR = 1.761). Furthermore, older age, as well as male gender were significant predictors of complete adherence for all participants whereas BMI did not predict intervention completion. Conclusions: This is the first naturalistic sample study in the field of web-based PA interventions that shows the potential of even small financial incentives to increase program adherence. Male users in particular seem to be strongly motivated by incentives to complete the intervention. Based on these findings, healthcare providers can use differentiated incentive systems to increase the regular participation in web-based PA interventions.

  • Evaluation of digital technologies tailored to support young people’s self-management of musculoskeletal pain: a mixed-methods design

    Date Submitted: Feb 20, 2020

    Open Peer Review Period: Feb 19, 2020 - Apr 15, 2020

    Background: Digital technologies connect young people with health services and resources supporting their self-care. The lack of accessible, reliable digital resources tailored to young people with pe...

    Background: Digital technologies connect young people with health services and resources supporting their self-care. The lack of accessible, reliable digital resources tailored to young people with persistent musculoskeletal pain, is a significant health services gap in Australia. Recognising the intense resourcing required to develop and implement effective eHealth interventions, adaptation of extant, proven digital technologies may support better access to pain care with cost- and time-efficiencies. Objective: To test the acceptability and need for adaptation of extant digital technologies, the painHEALTH website and iCanCope with Pain app, for use by young Australians with musculoskeletal pain. Methods: A 3-phased, mixed-methods evaluation was undertaken in Australia May 2019 to August 2019. Young people aged 15 to 25 years with musculoskeletal pain > 3-months duration were recruited. Phases were sequential: Phase 1. Remote participant testing (3 groups, each of n=5) of website prototype(s) co-designed with young people compared to a control website (painHEALTH), with user tasks mapped to eHealth quality and engagement criteria; Phase 2, participant week-long use of iCanCope with Pain app with engagement data captured using a real-time analytic platform (daily check-ins for pain, interference, sleep, mood, physical activity and energy levels; goal setting; accessing resources); for Phase 3, semi-structured interviews were conducted to gain insights into participants’ experiences of using these digital technologies. Results: Fifteen young people (80% female; mean age 20.5 (SD 3.3), range 15-25 years) participated in all 3 phases. Phase 1 aggregated group data informed recommendations used to guide rapid cycles of prototype iteration (3 cycles), moving from 2 initial prototypes (group 1) to a final version (group 3). Adaptations included optimizing navigation, improving usability (functionality) and enhancing content to better promote user engagement and acceptability. In Phase 2, all participants checked-in, with the highest frequency of full check-ins attributed by pain intensity (n=183; 100%), pain interference (n=175; 95.6%) and mood (n=152; 83.1%), respectively. Individual variability was evident for monitoring progress with highest frequency of history views for pain intensity (n=51; 32.3%), followed by pain interference (n=24; 15.2%). For the ‘goals set’ feature, thirteen participants (86.7%) set a total of 42 goals covering 5 areas, most frequently for activity (n=35; 83.3%). For Phase 3, meta-synthesis of qualitative data highlighted that these digital tools were perceived as youth-focused and acceptable. Four meta-themes emerged: 1. importance of user-centred design to leverage user engagement; 2. website design (features) promoting user acceptability and engagement; 3. app functionality supporting self-management; and 4. the role for wider promotion, health professional ‘digital prescriptions’ and strategies to ensure longer-term engagement. Conclusions: Leveraging extant digital tools, with appropriate user-informed adaptations, can help to build capacity tailored to support young people’s self-management of musculoskeletal pain.

  • The Effect of Chronic Stress on Heart Rate over Time modulated by Gender: Cross-sectional Study using Wearable Technologies

    Date Submitted: Feb 14, 2020

    Open Peer Review Period: Feb 14, 2020 - Apr 10, 2020

    Background: Chronic stress is increasing in prevalence and it is associated with several physical and mental disorders. Assessment of chronic stress is mostly performed by administrating questionnaire...

    Background: Chronic stress is increasing in prevalence and it is associated with several physical and mental disorders. Assessment of chronic stress is mostly performed by administrating questionnaires. Despite being convenient and valid tools, questionnaires do not inform on the detrimental effects of chronic stress on physiological functioning, which could be relevant for better characterization of stress and for tailoring stress management. Continuous measurement of vital signs in daily life and chronic stress detection algorithms could serve to this purpose. To this aim, it is paramount to model the effects of chronic stress on human physiology and include other cofounders, such as demographics, enabling to enrich population wide approach with individual variations. Objective: The main objectives of this study are to investigate the effect of chronic stress on the heart rate (HR) over time and test a possible modulation effect by gender and age in a healthy cohort. Methods: Chronic stress was assessed with the Perceived Stress Scale (PSS) inquiring on the degree to which situations in one’s life are appraised as stressful during the last month. Hourly heart rate (HR) was measured as the average HR derived from an electrocardiogram (ECG) signal, continuously measured over five days using a wearable health patch device. Models are compared including a trigonometric fit over time with four harmonics, gender, age, the PSS score and whether it was a workday or weekend-day as predictors. Results: As main effects, gender, the hour of the day and the four harmonics over time had a significant effect on the HR. Two three-way interaction effects were found. The interaction of age, whether it is a work- or weekend day and the circadian harmonic over time was significantly correlated to the HR (χ22 = 7.13, P = .028) as well as the interaction of gender, PSS score and the circadian harmonic over time (χ22 = 7.59, P = .023). Conclusions: The results of this study indicate that both baseline HR and daily fluctuations of HR are individual and time-dependent, and that although chronic stress does not relate to the average HR of an individual, it does influence the HR circadian pattern. This correlation of chronic stress with the HR over time is gender specific and possibly related to the evolution-based energy utilization strategies, as suggested in related literature studies. More research , including daily cortisol, longer recordings and wider population, should be done to confirm this interpretation. This would enable the development of more complete and personalized models of chronic stress.

  • Delivering Perinatal Health Information via a Voice Interactive App: A Mixed Method Study

    Date Submitted: Feb 13, 2020

    Open Peer Review Period: Feb 13, 2020 - Apr 9, 2020

    Background: Perinatal healthcare is critically important to maternal infant health outcomes. The U.S. fares considerably worse than comparable countries for maternal and infant mortality rates. As suc...

    Background: Perinatal healthcare is critically important to maternal infant health outcomes. The U.S. fares considerably worse than comparable countries for maternal and infant mortality rates. As such, alternative models of care or engagement are warranted. Ubiquitous digital devices and increased utilization of digital health tools have the potential to extend the reach to women and infants in their everyday lives and make positive impacts to their health outcomes. As voice-enabled devices become more mainstream, research is prudent to establish evidence-based practice on how to best leverage voice interaction to promote maternal infant health. Objective: Our primary aim was to assess the feasibility and usability of voice technology in perinatal health education. A secondary aim was to explore perceptions and attitudes of pregnant women towards perinatal health content delivered through voice. Methods: The study was a mixed method design. Study activities included completing baseline surveys, using a voice interactive app for two-weeks, and participating in exit interviews. Through the intervention, SMILE, users were able listen to perinatal health content delivered through mini-podcasts and provide immediate verbal feedback. Descriptive analysis was performed on quantitative survey data. Podcast feedback was analyzed using sentiment and thematic analysis. Interview data was analyzed using thematic analysis. Results: 19 pregnant women (ranging 17-36 weeks pregnant) were consented. Themes identified as important for perinatal health information include: establishing routines, expected norms and realistic expectations, and providing key takeaways. Themes identified important for voice interaction include: customization and user preferences, privacy, family and friends, and context and convenience. Qualitative analysis suggested that perinatal health promotion content delivered by voice should be accurate, succinctly delivered, and highlight key takeaways. Perinatal health interventions with voice-interaction delivery should provide users with the ability to customize the intervention, but also provide opportunities to engage family members, particularly spouses. To leverage the convenience of voice technology, solution must consider user contexts (e.g. timing or ability to listen/talk versus non-voice interaction with the system) in designing intervention activities. Conclusions: Findings from this research inform future content, design, and delivery considerations of perinatal digital health interventions and contribute to an evolving domain of digital health intervention research using voice interactive technology. Clinical Trial: n/a