JMIR Publications

Journal of Medical Internet Research

The leading peer-reviewed journal for health and healthcare in the Internet age.

JMIR's Thomson Reuter Impact Factor of 4.5 for 2015

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  • Barcode reading with smartphone. Image sourced and copyright owned by authors.

    Blood Culture Testing via a Mobile App That Uses a Mobile Phone Camera: A Feasibility Study


    Background: To evaluate patients with fever of unknown origin or those with suspected bacteremia, the precision of blood culture tests is critical. An inappropriate step in the test process or error in a parameter could lead to a false-positive result, which could then affect the direction of treatment in critical conditions. Mobile health apps can be used to resolve problems with blood culture tests, and such apps can hence ensure that point-of-care guidelines are followed and processes are monitored for blood culture tests. Objective: In this pilot project, we aimed to investigate the feasibility of using a mobile blood culture app to manage blood culture test quality. We implemented the app at a university hospital in South Korea to assess the potential for its utilization in a clinical environment by reviewing the usage data among a small group of users and by assessing their feedback and the data related to blood culture sampling. Methods: We used an iOS-based blood culture app that uses an embedded camera to scan the patient identification and sample number bar codes. A total of 4 medical interns working at 2 medical intensive care units (MICUs) participated in this project, which spanned 3 weeks. App usage and blood culture sampling parameters (including sampler, sampling site, sampling time, and sample volume) were analyzed. The compliance of sampling parameter entry was also measured. In addition, the participants’ opinions regarding patient safety, timeliness, efficiency, and usability were recorded. Results: In total, 356/644 (55.3%) of all blood culture samples obtained at the MICUs were examined using the app, including 254/356 (71.3%) with blood collection volumes of 5-7 mL and 256/356 (71.9%) with blood collection from the peripheral veins. The sampling volume differed among the participants. Sampling parameters were completely entered in 354/356 cases (99.4%). All the participants agreed that the app ensured good patient safety, disagreed on its timeliness, and did not believe that it was efficient. Although the bar code scanning speed was acceptable, the Wi-Fi environment required improvement. Moreover, the participants requested feedback regarding their sampling quality. Conclusions: Although this app could be used in the clinical setting, improvements in the app functions, environment network, and internal policy of blood culture testing are needed to ensure hospital-wide use.

  • How Veterans With Post-Traumatic Stress Disorder and Comorbid Health Conditions Utilize eHealth to Manage Their Health Care Needs: A Mixed-Methods Analysis


    Background: Mental health conditions are prevalent among US veterans and pose a number of self-management and health care navigation challenges. Post-Traumatic Stress Disorder (PTSD) with comorbid chronic medical conditions (CMCs) is especially common, in both returning Iraq or Afghanistan and earlier war-era veterans. Patient-facing electronic health (eHealth) technology may offer innovative strategies to support these individuals’ needs. Objective: This study was designed to identify the types of eHealth tools that veterans with PTSD and comorbid CMCs use, understand how they currently use eHealth technology to self-manage their unique health care needs, and identify new eHealth resources that veterans feel would empower them to better manage their health care. Methods: A total of 119 veterans with PTSD and at least one CMC who have used the electronic personal health record system of the US Department of Veterans Affairs (VA) responded to a mailed survey about their chronic conditions and preferences related to the use of technology. After the survey, 2 focus groups, stratified by sex, were conducted with a subgroup of patients to explore how veterans with PTSD and comorbid CMCs use eHealth technology to support their complex health care needs. Focus groups were transcribed verbatim and analyzed using standard content analysis methods for coding textual data, guided by the “Fit between Individual, Task, and Technology” framework. Results: Survey respondents had a mean age of 64.0 (SD 12.0) years, 85.1% (97/114) were male, 72.4% (84/116) were white, and 63.1% (70/111) had an annual household income of < US $50,000. Mean score on a measure of eHealth literacy was 27.7 (SD 9.8). Of the respondents, 44.6% (50/112) used health-related technology 1 to 3 times per month and 21.4% (24/112) used technology less than once per month. Veterans reported using technology most often to search for health information (78.9%, 90/114), communicate with providers (71.1%, 81/114), and track medications (64.9%, 74/114). Five major themes emerged that describe how eHealth technology influences veterans with PTSD and comorbid CMCs: (1) interactions with social support, (2) condition management, (3) access to and communication with providers, (4) information access, and (5) coordination of care. Conclusions: The “Fit between Individual, Task, and Technology” model provided a useful framework to examine the clinical tasks that arose for veterans and their resourceful adoption of eHealth tools. This study suggests that veterans who use the Web are eager to incorporate eHealth technology into their care and self-management activities. Findings illustrate a number of ways in which the VA and eHealth technology developers can refine existing applications, develop new resources, and better promote tools that address challenges experienced by veterans with PTSD and comorbid CMCs.

  • Fern image source (Licensed under Creative Commons Attribution 2.0).

    Participant Recruitment and Engagement in Automated eHealth Trial Registration: Challenges and Opportunities for Recruiting Women Who Experience Violence


    Background: Automated eHealth Web-based research trials offer people an accessible, confidential opportunity to engage in research that matters to them. eHealth trials may be particularly useful for sensitive issues when seeking health care may be accompanied by shame and mistrust. Yet little is known about people’s early engagement with eHealth trials, from recruitment to preintervention autoregistration processes. A recent randomized controlled trial that tested the effectiveness of an eHealth safety decision aid for New Zealand women in the general population who experienced intimate partner violence (isafe) provided the opportunity to examine recruitment and preintervention participant engagement with a fully automated Web-based registration process. The trial aimed to recruit 340 women within 24 months. Objective: The objective of our study was to examine participant preintervention engagement and recruitment efficiency for the isafe trial, and to analyze dropout through the registration pathway, from recruitment to eligibility screening and consent, to completion of baseline measures. Methods: In this case study, data collection sources included the trial recruitment log, Google Analytics reports, registration and program metadata, and costs. Analysis included a qualitative narrative of the recruitment experience and descriptive statistics of preintervention participant engagement and dropout rates. A Koyck model investigated the relationship between Web-based online marketing website advertisements (ads) and participant accrual. Results: The isafe trial was launched on September 17, 2012. Placement of ads in an online classified advertising platform increased the average number of recruited participants per month from 2 to 25. Over the 23-month recruitment period, the registration website recorded 4176 unique visitors. Among 1003 women meeting eligibility criteria, 51.55% (517) consented to participate; among the 501 women who enrolled (consented, validated, and randomized), 412 (82.2%) were accrued (completed baseline assessments). The majority (n=52, 58%) of the 89 women who dropped out between enrollment and accrual never logged in to the allocated isafe website. Of every 4 accrued women, 3 (314/412, 76.2%) identified the classified ad as their referral source, followed by friends and family (52/412, 12.6%). Women recruited through a friend or relative were more likely to self-identify as indigenous Māori and live in the highest-deprivation areas. Ads increased the accrual rate by a factor of 74 (95% CI 49–112). Conclusions: Print advertisements, website links, and networking were costly and inefficient methods for recruiting participants to a Web-based eHealth trial. Researchers are advised to limit their recruitment efforts to Web-based online marketplace and classified advertising platforms, as in the isafe case, or to social media. Online classified advertising in “Jobs–Other–volunteers” successfully recruited a diverse sample of women experiencing intimate partner violence. Preintervention recruitment data provide critical information to inform future research and critical analysis of Web-based eHealth trials. ClinicalTrial: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12612000708853; (Archived by WebCite at http://www.webcitation/6lMGuVXdK)

  • Snip from illness journey timeline. Image sourced and copyright owned by Annie T Chen et al.

    The Relationship Between Health Management and Information Behavior Over Time: A Study of the Illness Journeys of People Living With Fibromyalgia

    Authors List:


    Background: Over the course of a chronic illness, patients face many challenges, including understanding what is happening to them and developing an effective strategy for managing illness. While there is existing literature concerning how people seek health-related information and cope with chronic illnesses, there is a need for additional research on how information affects patients’ understandings of their illness, and how changes in this understanding affect their health management strategies over time. Objective: This study examined how health management, information seeking, and information consumption and use processes are related throughout an illness. Methods: A diversified recruitment strategy involving multiple media channels was used to recruit participants for an interview study. During the interviews, participants were asked to draw an “illness journey” timeline. The data were analyzed using a qualitative approach drawn from Interpretative Phenomenological Analysis and Grounded Theory. Results: The study identified four main health management features of illness journeys: onset, progression toward diagnosis, acceptance, and development of an effective management strategy. The study then focused on how information seeking changes over illness journeys, particularly in terms of a transition from active information seeking to monitoring with intermittent focused searching. Last, the paper describes the information consumption and use processes that patients engaged in throughout their journey. Conclusions: This study makes three important contributions to the field. First, it presents an integrated conceptualization of how health management and information behaviors are related on illness journeys. Second, it adds to our existing knowledge on health literacy and self-management of chronic illness. Third, the study has implications for health interface design.

  • Heat map showing average consumer satisfaction insurance scores of different plans by state. Image sourced and copyright owned by authors.

    Correlating Ratings of Health Insurance Plans to Their Providers' Attributes


    Background: There is a push towards quality measures in health care. As a consequence, the National Committee for Quality Assurance (NCQA) has been publishing insurance plan quality measures. Objective: The objective of this study was to examine the relationship between insurance plan quality measures and the participating providers (doctors). Methods: We collected and analyzed provider and insurance plan data from several online sources, including provider directories, provider referrals and awards, patient reviewing sites, and hospital rankings. The relationships between the provider attributes and the insurance plan quality measures were examined. Results: Our analysis yielded several findings: (1) there is a moderate Pearson correlation (r=.376) between consumer satisfaction insurance plan scores and review ratings of the member providers, (2) referral frequency and provider awards are negligibly correlated to consumer satisfaction plan scores (correlations of r=.031 and r=.183, respectively), (3) there is weak positive correlation (r=.266) between the cost charged for the same procedures and consumer satisfaction plan scores, and (4) there is no significant correlation between member specialists’ review ratings and specialty-specific insurance plan treatment scores for most specialties, except a surprising weak negative correlation for diabetes treatment (r=-.259). Conclusions: Our findings may be used by consumers to make informed choices about their insurance plans or by insurances to understand the relationship between patients’ satisfaction and their network of providers.

  • Escreening for children. Image sourced and copyright owned by authors.

    A Multimedia Child Developmental Screening Checklist: Design and Validation


    Background: Identifying disability early in life confers long-term benefits for children. The Taipei City Child Development Screening tool, second version (Taipei II) provides checklists for 13 child age groups from 4 months to 6 years. However, the usability of a text-based screening tool largely depends on the literacy level and logical reasoning ability of the caregivers, as well as language barriers caused by increasing numbers of immigrants. Objective: The objectives of this study were to (1) design and develop a Web-based multimedia version of the current Taipei II developmental screening tool, and (2) investigate the measurement equivalence of this multimedia version to the original paper-based version. Methods: To develop the multimedia version of Taipei II, a team of experts created illustrations, translations, and dubbing of the original checklists. The developmental screening test was administered to a total of 390 primary caregivers of children aged between 4 months and 6 years. Results: Psychometric testing revealed excellent agreement between the paper and multimedia versions of Taipei II. Good to excellent reliabilities were demonstrated for all age groups for both the cross-mode similarity (mode intraclass correlation range 0.85-0.96) and the test-retest reliability (r=.93). Regarding the usability, the mean score was 4.80 (SD 0.03), indicating that users were satisfied with their multimedia website experience. Conclusions: The multimedia tool produced essentially equivalent results to the paper-based tool. In addition, it had numerous advantages, such as it can facilitate active participation and promote early screening of target populations. ClinicalTrial: NCT02359591; (Archived by WebCite at

  • Two Illness Indicates Adult Onset Diabetes And Advertisement Stock Photo. Image source: Author: Stuart Miles. License: Free photo with attribution.

    Do Web-Based Interventions Improve Well-Being in Type 2 Diabetes? A Systematic Review and Meta-Analysis


    Background: Poor diabetes self-care can have a negative impact on psychological well-being and quality of life. Given the scarcity of traditional psychological support and the barriers to uptake of and attendance at face-to-face education programs, Web-based interventions are becoming a popular approach to provide an additional platform for psychological support in long-term conditions. However, there is limited evidence to assess the effect of Web-based psychological support in people with type 2 diabetes. Objective: This systematic review is the first review to critically appraise and quantify the evidence on the effect of Web-based interventions that aim to improve well-being in people with type 2 diabetes. Methods: Searches were carried out in the following electronic databases: MEDLINE, EMBASE, CINAHL, PsycINFO, and Cochrane Library. Reference lists were hand-searched. A meta-analysis was conducted for depression and distress outcomes. Results: A total of 16 randomized controlled studies met the inclusion criteria for the systematic review and 9 were included in the meta-analyses. Theories were applied to the majority of the interventions. The most common behavior change techniques were “General information” and “Tracking/monitoring.” Interventions with a duration of 2-6 months providing professional-led support with asynchronous and synchronous communication appeared to be associated with significant well-being outcomes. The pooled mean (95% confidence interval) difference between the intervention and control arms at follow-up on depression score was -0.31 (-0.73 to 0.11). The pooled mean difference on distress scores at follow-up was -0.11 (-0.38 to 0.16). No significant improvements in depression (P=.15) or distress (P=.43) were found following meta-analyses. Conclusions: While the meta-analyses demonstrated nonsignificant results for depression and distress scores, this review has shown that there is a potential for Web-based interventions to improve well-being outcomes in type 2 diabetes. Further research is required to confirm the findings of this review.

  • Prevail Splash Screen. Image created and copyright owned by authors.

    Using Intensive Longitudinal Data Collected via Mobile Phone to Detect Imminent Lapse in Smokers Undergoing a Scheduled Quit Attempt


    Background: Mobile phone‒based real-time ecological momentary assessments (EMAs) have been used to record health risk behaviors, and antecedents to those behaviors, as they occur in near real time. Objective: The objective of this study was to determine if intensive longitudinal data, collected via mobile phone, could be used to identify imminent risk for smoking lapse among socioeconomically disadvantaged smokers seeking smoking cessation treatment. Methods: Participants were recruited into a randomized controlled smoking cessation trial at an urban safety-net hospital tobacco cessation clinic. All participants completed in-person EMAs on mobile phones provided by the study. The presence of six commonly cited lapse risk variables (ie, urge to smoke, stress, recent alcohol consumption, interaction with someone smoking, cessation motivation, and cigarette availability) collected during 2152 prompted or self-initiated postcessation EMAs was examined to determine whether the number of lapse risk factors was greater when lapse was imminent (ie, within 4 hours) than when lapse was not imminent. Various strategies were used to weight variables in efforts to improve the predictive utility of the lapse risk estimator. Results: Participants (N=92) were mostly female (52/92, 57%), minority (65/92, 71%), 51.9 (SD 7.4) years old, and smoked 18.0 (SD 8.5) cigarettes per day. EMA data indicated significantly higher urges (P=.01), stress (P=.002), alcohol consumption (P<.001), interaction with someone smoking (P<.001), and lower cessation motivation (P=.03) within 4 hours of the first lapse compared with EMAs collected when lapse was not imminent. Further, the total number of lapse risk factors present within 4 hours of lapse (mean 2.43, SD 1.37) was significantly higher than the number of lapse risk factors present during periods when lapse was not imminent (mean 1.35, SD 1.04), P<.001. Overall, 62% (32/52) of all participants who lapsed completed at least one EMA wherein they reported ≥3 lapse risk factors within 4 hours of their first lapse. Differentially weighting lapse risk variables resulted in an improved risk estimator (weighted area=0.76 vs unweighted area=0.72, P<.004). Specifically, 80% (42/52) of all participants who lapsed had at least one EMA with a lapse risk score above the cut-off within 4 hours of their first lapse. Conclusions: Real-time estimation of smoking lapse risk is feasible and may pave the way for development of mobile phone‒based smoking cessation treatments that automatically tailor treatment content in real time based on presence of specific lapse triggers. Interventions that identify risk for lapse and automatically deliver tailored messages or other treatment components in real time could offer effective, low cost, and highly disseminable treatments to individuals who do not have access to other more standard cessation treatments.

  • Swordplay. Image source: Author: Xotatoman. License:CC0 Public Domain.

    The Narrative Impact of Active Video Games on Physical Activity Among Children: A Feasibility Study


    Background: Active video games (AVGs) capable of inducing physical activity offer an innovative approach to combating childhood obesity. Unfortunately, children’s AVG game play decreases quickly, underscoring the need to identify novel methods for player engagement. Narratives have been demonstrated to influence behaviors. Objective: The objective of this study was to test the hypothesis that a narrative would motivate increased AVG play, though a feasibility study that investigated the motivational effect of adding a previously developed narrative cutscene to an originally nonnarrative AVG, Nintendo Wii Sports Resort: Swordplay Showdown. Methods: A total of 40 overweight and obese 8- to 11-year-olds equally divided by sex played the AVG. Half (n=20) were randomly assigned to a narrative group that watched the narrative cutscene before game play. The other half played the game without watching it. Results: Children in the narrative group had significantly (P<.05) more steps per 10-second period (mean 3.2, SD 0.7) and overall (mean 523, SD 203) during game play compared with the nonnarrative group (10-second period: mean 2.7, SD 0.7; overall: mean 366, SD 172). Conclusions: The AVG with narrative induced increased physical activity. Additional research is needed to understand the mechanisms through which narrative increases physical activity during AVG game play.

  • Internet Security. Image Source: Author:TBIT. License:CC0 Public Domain.

    “I Always Vet Things”: Navigating Privacy and the Presentation of Self on Health Discussion Boards Among Individuals with Long-Term Conditions


    Background: The ethics of research into online communities is a long-debated issue, with many researchers arguing that open-access discussion groups are publically accessible data and do not require informed consent from participants for their use for research purposes. However, it has been suggested that there is a discrepancy between the perceived and actual privacy of user-generated online content by community members. Objective: There has been very little research regarding how privacy is experienced and enacted online. The objective of this study is to address this gap by qualitatively exploring the expectations of privacy on Internet forums among individuals with long-term conditions. Methods: Semistructured interviews were conducted with 20 participants with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and 21 participants with type 1 and 2 diabetes mellitus, and were analyzed using thematic analysis. Participants were recruited via online and offline routes, namely forums, email lists, newsletters, and face-to-face support groups. Results: The findings indicate that privacy online is a nebulous concept. Rather than individuals drawing a clear-cut distinction between what they would and would not be comfortable sharing online, it was evident that these situations were contextually dependent and related to a number of unique and individual factors. Conclusions: Interviewees were seen to carefully manage how they presented themselves on forums, filtering and selecting the information that they shared about themselves in order to develop and maintain a particular online persona, while maintaining and preserving an acceptable level of privacy.

  • Laptop usage. Image source: Author: License:CC0 License.

    Education-Based Gaps in eHealth: A Weighted Logistic Regression Approach

    Authors List:


    Background: Persons with a college degree are more likely to engage in eHealth behaviors than persons without a college degree, compounding the health disadvantages of undereducated groups in the United States. However, the extent to which quality of recent eHealth experience reduces the education-based eHealth gap is unexplored. Objective: The goal of this study was to examine how eHealth information search experience moderates the relationship between college education and eHealth behaviors. Methods: Based on a nationally representative sample of adults who reported using the Internet to conduct the most recent health information search (n=1458), I evaluated eHealth search experience in relation to the likelihood of engaging in different eHealth behaviors. I examined whether Internet health information search experience reduces the eHealth behavior gaps among college-educated and noncollege-educated adults. Weighted logistic regression models were used to estimate the probability of different eHealth behaviors. Results: College education was significantly positively related to the likelihood of 4 eHealth behaviors. In general, eHealth search experience was negatively associated with health care behaviors, health information-seeking behaviors, and user-generated or content sharing behaviors after accounting for other covariates. Whereas Internet health information search experience has narrowed the education gap in terms of likelihood of using email or Internet to communicate with a doctor or health care provider and likelihood of using a website to manage diet, weight, or health, it has widened the education gap in the instances of searching for health information for oneself, searching for health information for someone else, and downloading health information on a mobile device. Conclusion: The relationship between college education and eHealth behaviors is moderated by Internet health information search experience in different ways depending on the type of eHealth behavior. After controlling for college education, it was found that persons who experienced more fruitful Internet health information searches are generally less likely to engage in eHealth behaviors.

  • Patient Disability. Image Source: Copyright: Falco. License: CC Public Domain.

    The Effectiveness of Lower-Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: A Systematic Review


    Background: With advances in technology, the adoption of wearable devices has become a viable adjunct in poststroke rehabilitation. Regaining ambulation is a top priority for an increasing number of stroke survivors. However, despite an increase in research exploring these devices for lower limb rehabilitation, little is known of the effectiveness. Objective: This review aims to assess the effectiveness of lower limb wearable technology for improving activity and participation in adult stroke survivors. Methods: Randomized controlled trials (RCTs) of lower limb wearable technology for poststroke rehabilitation were included. Primary outcome measures were validated measures of activity and participation as defined by the International Classification of Functioning, Disability and Health. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, and the Cochrane Library. The Cochrane Risk of Bias Tool was used to assess the methodological quality of the RCTs. Results: In the review, we included 11 RCTs with collectively 550 participants at baseline and 474 participants at final follow-up including control groups and participants post stroke. Participants' stroke type and severity varied. Only one study found significant between-group differences for systems functioning and activity. Across the included RCTs, the lowest number of participants was 12 and the highest was 151 with a mean of 49 participants. The lowest number of participants to drop out of an RCT was zero in two of the studies and 19 in one study. Significant between-group differences were found across three of the 11 included trials. Out of the activity and participation measures alone, P values ranged from P=.87 to P ≤.001. Conclusions: This review has highlighted a number of reasons for insignificant findings in this area including low sample sizes, appropriateness of the RCT methodology for complex interventions, a lack of appropriate analysis of outcome data, and participant stroke severity.

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  • Characterising Measurements in Health Self Quantification: A Tools Review Study

    Date Submitted: Oct 27, 2016

    Open Peer Review Period: Oct 27, 2016 - Dec 22, 2016

    Background: Background: The use of wearable devices for health self-quantification (SQ) introduces new ways of thinking about one’s body and how to achieve the desired health outcomes. Measures rela...

    Background: Background: The use of wearable devices for health self-quantification (SQ) introduces new ways of thinking about one’s body and how to achieve the desired health outcomes. Measures related to heart rate, respiratory volume, skin temperature, blood volume pulse, sleep, mood, blood pressure, food consumed, quality of surrounding air – anything from mental, emotional, and physical to social and environmental aspects of daily life can be acquired, quantified, and aggregated in a holistic way that has never been possible before. However, health SQ lacks a formal common language or taxonomy for describing these measurements. Establishing such taxonomy is important because it enables systematic investigations which are needed to improve the use of wearable devices in health self-care, and contributes to provide evidence of sufficient quality to determine whether and how health SQ is a worthwhile healthcare paradigm. Objective: Objectives: This study aims to investigate a sample of wearable devices in order to build and test a taxonomy of measurements in health SQ. This is called the Classification of Data and Activity in Self-Quantification Systems (CDA-SQS). Methods: Methods: A sample of seven health SQ devices/services was selected to be examined in detail: 1) Zeo Sleep Manager, 2) Fitbit Ultra, 3) Fitlinxx Actipressure, 4) iBGStar, 5) Sensaris Senspod, 6) 23andMe, 7) uBiome. Open coding technique was followed to find all the themes that are related to our research aim. Results: Results: This study helped to distinguish between three types of measurements in health SQ: body structures and functions, body actions and activities, and around body. The CDA-SQS classification should be applicable to studying health SQ among people whatever their health objectives, health status and conditions are. Conclusions: Conclusion: CDA-SQS is a critical contribution to a much more consistent way of studying health SQ. It can be coupled to external taxonomies of tools, and models that describe the users’ health self-care activities and behaviours to facilitate a more rigorous analysis. This in turn may help in stratifying people into groups based on their health related measurements, wearable devices, health activities, etc. and ultimately enable the development of better personalised health interventions.

  • Linguistic Markers of Depression Severity Level: An Exploratory Study

    Date Submitted: Oct 26, 2016

    Open Peer Review Period: Oct 27, 2016 - Dec 22, 2016

    Background: Depression is a serious illness that affects millions of people globally. It is frequently undetected and commonly misdiagnosed. An objective marker of depression has the potential to dram...

    Background: Depression is a serious illness that affects millions of people globally. It is frequently undetected and commonly misdiagnosed. An objective marker of depression has the potential to dramatically improve current diagnostic approaches. Due to the ubiquity of smart phones and the popularity of social media, text is now a common form of communication, which could be very useful in monitoring linguistic patterns that might be indicative of symptoms of depression. Objective: The objective of this study was to explore the potential of using natural language processing and machine learning to automatically identify depression symptom severity. Methods: This study used the Distress Analysis Interview Corpus (DAIC), a multimodal collection of semi-structured clinical interviews. The interviews simulate the standard protocols for identifying people with major depression. The corpus contains audio and video recordings of participant interviews (N=688). In addition to manual transcriptions, automatic speech recognition (ASR) was performed to generate transcripts of the interviews. Semantic and syntactic linguistic features were extracted from the transcripts and then used to train linear regression models. Results: Using linguistic markers, we successfully train speaker-independent regression models that were able to predict depression severity (MAE=4.42, RMSE=5.06). We find a number of semantic and syntactic features to be significantly correlated with depression score (P<.001), including but not limited to: first person singular pronouns, words related to affective processes, word length, unique number of part-of-speech tags, attributes related to the syntactic dependency tree representation, and semantic coherence. Conclusions: Features extracted from unconstrained speech provided useful linguistics markers that were strongly related to depression. In addition, regression models trained with linguistic features were able to successfully predict depression level. These findings suggest that natural language processing and machine learning approaches offer numerous clinical opportunities, including an unobtrusive automatic assessment of depression severity, which could be used ubiquitously.

  • mHealth interventions for health system strengthening in China: a Systematic Review

    Date Submitted: Oct 26, 2016

    Open Peer Review Period: Oct 26, 2016 - Dec 21, 2016

    Background: With rapidly expanding infrastructure in China, mobile technology has been deemed to have the potential to revolutionise healthcare delivery. There is particular promise for mHealth to pos...

    Background: With rapidly expanding infrastructure in China, mobile technology has been deemed to have the potential to revolutionise healthcare delivery. There is particular promise for mHealth to positively influence health system reform, and confront the new challenges of chronic diseases. Objective: To systematically review existing mHealth initiatives in China, to characterise them and examine the extent to which mHealth contributes towards the health system strengthening in China. Also to identify gaps in mHealth development and evaluation. Methods: Systematically review of the literature from English and Chinese electronic database and trial registries, including PubMed, EMBASE, Cochrane, China National Knowledge of Infrastructure, and WHO International Clinical Trials Registry Platform. We used the English keywords of mHealth, eHealth, telemedicine, telehealth, mobile phone, cell phone, text messaging, and China, as well as their corresponding Chinese keywords. All articles using mobile technology for healthcare management were included in the study. Results: 1,704 articles were found using the search terms. and eventually 72 were included. Overall, few high quality interventions were identified. Most interventions were found to be insufficient in scope, and their evaluation was of inadequate rigour to generate scalable solutions and provide reliable evidence of effectiveness. Most interventions focused on text messaging for consumer education and behaviour change. There were a limited number of interventions that addressed health information management, health workforce issues, use of medicines and technologies, or leadership and governance from a health system perspective. Conclusions: We provide four recommendations for future mHealth interventions in China that include the need for the development, evaluation and trials examining integrated mHealth interventions in effort to guide the development of future mHealth interventions, target disadvantaged populations with mHealth interventions, and generate appropriate evidence for scalable and sustainable models of care.

  • A mobile health intervention to early detect exacerbation for older people with Heart Failure: Randomized Control Trial

    Date Submitted: Oct 25, 2016

    Open Peer Review Period: Oct 25, 2016 - Dec 20, 2016

    Background: Heart Failure is the most common cause of hospitalization amongst patients aged 65 years and over. There are no publications on the effectiveness of eHealth in the monitoring after dischar...

    Background: Heart Failure is the most common cause of hospitalization amongst patients aged 65 years and over. There are no publications on the effectiveness of eHealth in the monitoring after discharge focused on older people with Heart Failure and on the usefulness of non-classical, functional biomarkers in this population. Objective: To assess the effectiveness of a mobile intervention to early detect heart failure exacerbation, and to minimize readmissions and length of re-hospitalizations. Methods: We conducted a randomized non-blind controlled trial with a follow-up of 3 months after a hospitalization due to heart failure exacerbation. We remotely monitored functional status (i.e. gait speed and strength), vital signs (i.e. weight, oxygen saturation, heart rate and blood pressure) and symptoms after discharge from the Geriatric Acute Care Unit using a Smartphone connected to sensors. The main outcomes were the emergency visits rate, the readmissions and the length of stay of these readmissions. Effectiveness of the intervention was assessed through logistic models. Results: 90 patients were enrolled (median age, 86 years; females: 72.2%). 50 patients were randomly allocated to the intervention group-IG, (47 completed the study); and 40 to the control group-CG. Their characteristics were similar except for age (people in the IG is one year older). The adherence to the program was high, being the minimum rate of observations 70%. Patients in IG had a better clinical outcome measured as the risk for readmissions, which decreases more than 60% in comparison with CG. We did not find differences regarding visits to the emergency room. In addition, in those of the IG who were readmitted, 80% of the readmissions were shorter or equal than 7 days. In CG, this percentage was reached at 13th day. Median of stay differs between groups in 3.5 days (p= 0.02). The only biomarkers predicting the outcomes were the changes in the gait speed OR 1.34 (95% CI 1.04-1.72) and the oxygen saturation 0.743 (95% CI 0.566-0.976). Conclusions: Mobile systems are feasible and effective in this very old population of patients with heart failure. Functional variables as gait speed have predictive value, opening new ways of monitoring these patients. Clinical Trial: Identifier: NCT02506738

  • The feasibility and acceptability of a web-based alcohol management intervention in community sports clubs: a cross sectional study

    Date Submitted: Oct 20, 2016

    Open Peer Review Period: Oct 21, 2016 - Dec 16, 2016

    Background: The implementation of comprehensive alcohol management strategies can reduce excessive alcohol use and reduce the risk of alcohol related harm at sporting venues. Supporting sports venues...

    Background: The implementation of comprehensive alcohol management strategies can reduce excessive alcohol use and reduce the risk of alcohol related harm at sporting venues. Supporting sports venues to implement alcohol management strategies via the web may represent an effective and efficient means of reducing harm caused by alcohol in this setting. However, the feasibility and acceptability of such an approach is unknown. Objective: This study aimed to identify: (1) current access to and use of the web and electronic devices by sports clubs; (2) perceived usefulness, ease of use, and intention to use a web-based program to support implementation of alcohol management practices in sports clubs; (3) factors associated with intention to use such a web-based support program; and (4) the specific features of such a program that sports clubs would find useful. Methods: A cross-sectional survey was conducted with club administrators of community football clubs in the state of New South Wales, Australia. Perceived usefulness, ease of use and behavioural intention to use a hypothetical web-based alcohol management support program was assessed using the validated Technology Acceptance Model (TAM) instrument. Associations between intention to use a web-based program and club characteristics as well as perceived ease of use and usefulness was tested using Fisher’s exact test and represented using relative risk for high intention to use the program. Results: Of the 73 football clubs that were approached to participate in the study, 63 consented to participate, 46 were eligible and completed the survey. All participants reported having access to the web and 98% reported current use of electronic devices (e.g. computers, iPads/tablets, smartphones, laptops, televisions and smartboards). Mean scores (out of a possible 7) for the TAM constructs were high for: intention to use (Mean: 6.25, SD: 0.87), perceived ease of use (Mean: 6.00, SD: 0.99), and perceived usefulness (mean: 6.17, SD: 0.85). Intention to use the web-based alcohol management program was significantly associated with perceived ease of use (P=.02, RR: 1.4, CI: 1.0-2.9), perceived usefulness (P=.03, RR: 1.5, CI: 1.0-6.8) and club size (P=.02, RR: 0.8 CI: 0.5-0.9). The most useful features of such a program included the perceived ability to complete program requirements within users own time, complete program accreditation assessment and monitoring online, develop tailored action plans and receive email reminders and prompts to complete action. Conclusions: A web-based alcohol management approach to support sports clubs in the implementation of recommended alcohol management practices appears both feasible and acceptable. Future research should aim to determine if such intended use leads to actual use and club implementation of alcohol management practices. Clinical Trial: NA

  • An Inter-hospital 12-Lead Electrocardiography Teleconsultation System and Mobile Application Based on Users’ Experiences

    Date Submitted: Oct 20, 2016

    Open Peer Review Period: Oct 21, 2016 - Dec 16, 2016

    Background: More and more hospitals have formed hospital alliance to share medical resources with one another in Taiwan. Consequently, the need for developing a safe and convenient inter-hospital 12-l...

    Background: More and more hospitals have formed hospital alliance to share medical resources with one another in Taiwan. Consequently, the need for developing a safe and convenient inter-hospital 12-lead electrocardiography (ECG) and tele-consultation system arises. Objective: The major goal of this study is to develop a safe and effective mobile application (App) and ECG system to deliver inter-hospital 12-lead ECG tele-consultation. Methods: The design of this APP and system was based on the experiences of cardiologists as users and human factor consideration so to minimize misuse, misdiagnosis, and violation of patients’ privacy. In addition, this technology facilitated the interoperability of 12-lead ECG across hospitals, which integrates heterogeneous 12-lead ECG from different hospitals and various mobile phones of consulting cardiologists. Notably, the use of role-based certificates enhanced the safety of ECG delivery on internet. This App was evaluated by two senior cardiologists as with credible usability. Results: This technology allowed the practice of 12-lead ECG tele-consultation easier and more convenient. It also helped clinicians give proper diagnosis and disposition more efficiently based on more comprehensive ECG reports and consultation. Conclusions: In summary, this App can be applied easily in clinical settings and greatly improves the efficiency and quality of medical services.