JMIR Publications

Journal of Medical Internet Research

The leading peer-reviewed journal for digital medicine, and health & healthcare in the Internet age.

JMIR's Thomson Reuter Impact Factor of 4.5 for 2015

Recent Articles:

  • Web-based medical appointment. Source: Image created by the authors; Copyright: The authors;

    Web-Based Medical Appointment Systems: A Systematic Review


    Background: Health care is changing with a new emphasis on patient-centeredness. Fundamental to this transformation is the increasing recognition of patients' role in health care delivery and design. Medical appointment scheduling, as the starting point of most non-urgent health care services, is undergoing major developments to support active involvement of patients. By using the Internet as a medium, patients are given more freedom in decision making about their preferences for the appointments and have improved access. Objective: The purpose of this study was to identify the benefits and barriers to implement Web-based medical scheduling discussed in the literature as well as the unmet needs under the current health care environment. Methods: In February 2017, MEDLINE was searched through PubMed to identify articles relating to the impacts of Web-based appointment scheduling. Results: A total of 36 articles discussing 21 Web-based appointment systems were selected for this review. Most of the practices have positive changes in some metrics after adopting Web-based scheduling, such as reduced no-show rate, decreased staff labor, decreased waiting time, and improved satisfaction, and so on. Cost, flexibility, safety, and integrity are major reasons discouraging providers from switching to Web-based scheduling. Patients’ reluctance to adopt Web-based appointment scheduling is mainly influenced by their past experiences using computers and the Internet as well as their communication preferences. Conclusions: Overall, the literature suggests a growing trend for the adoption of Web-based appointment systems. The findings of this review suggest that there are benefits to a variety of patient outcomes from Web-based scheduling interventions with the need for further studies.

  • Source: Image created by the authors; Copyright: The authors;

    Compliance With Mobile Ecological Momentary Assessment Protocols in Children and Adolescents: A Systematic Review and Meta-Analysis


    Background: Mobile device-based ecological momentary assessment (mobile-EMA) is increasingly used to collect participants' data in real-time and in context. Although EMA offers methodological advantages, these advantages can be diminished by participant noncompliance. However, evidence on how well participants comply with mobile-EMA protocols and how study design factors associated with participant compliance is limited, especially in the youth literature. Objective: To systematically and meta-analytically examine youth’s compliance to mobile-EMA protocols and moderators of participant compliance in clinical and nonclinical settings. Methods: Studies using mobile devices to collect EMA data among youth (age ≤18 years old) were identified. A systematic review was conducted to describe the characteristics of mobile-EMA protocols and author-reported factors associated with compliance. Random effects meta-analyses were conducted to estimate the overall compliance across studies and to explore factors associated with differences in youths’ compliance. Results: This review included 42 unique studies that assessed behaviors, subjective experiences, and contextual information. Mobile phones were used as the primary mode of EMA data collection in 48% (20/42) of the reviewed studies. In total, 12% (5/42) of the studies used wearable devices in addition to the EMA data collection platforms. About half of the studies (62%, 24/42) recruited youth from nonclinical settings. Most (98%, 41/42) studies used a time-based sampling protocol. Among these studies, most (95%, 39/41) prompted youth 2-9 times daily, for a study length ranging from 2-42 days. Sampling frequency and study length did not differ between studies with participants from clinical versus nonclinical settings. Most (88%, 36/41) studies with a time-based sampling protocol defined compliance as the proportion of prompts to which participants responded. In these studies, the weighted average compliance rate was 78.3%. The average compliance rates were not different between studies with clinical (76.9%) and nonclinical (79.2%; P=.29) and studies that used only a mobile-EMA platform (77.4%) and mobile platform plus additional wearable devices (73.0%, P=.36). Among clinical studies, the mean compliance rate was significantly lower in studies that prompted participants 2-3 times (73.5%) or 4-5 times (66.9%) compared with studies with a higher sampling frequency (6+ times: 89.3%). Among nonclinical studies, a higher average compliance rate was observed in studies that prompted participants 2-3 times daily (91.7%) compared with those that prompted participants more frequently (4-5 times: 77.4%; 6+ times: 75.0%). The reported compliance rates did not differ by duration of EMA period among studies from either clinical or nonclinical settings. Conclusions: The compliance rate among mobile-EMA studies in youth is moderate but suboptimal. Study design may affect protocol compliance differently between clinical and nonclinical participants; including additional wearable devices did not affect participant compliance. A more consistent compliance-related result reporting practices can facilitate understanding and improvement of participant compliance with EMA data collection among youth.

  • Source: Flickr; Copyright: US Department of Agriculture; URL:; License: Creative Commons Attribution (CC-BY).

    Impact of Information and Communication Technologies on Nursing Care: Results of an Overview of Systematic Reviews


    Background: Information and communication technologies (ICTs) are becoming an impetus for quality health care delivery by nurses. The use of ICTs by nurses can impact their practice, modifying the ways in which they plan, provide, document, and review clinical care. Objective: An overview of systematic reviews was conducted to develop a broad picture of the dimensions and indicators of nursing care that have the potential to be influenced by the use of ICTs. Methods: Quantitative, mixed-method, and qualitative reviews that aimed to evaluate the influence of four eHealth domains (eg, management, computerized decision support systems [CDSSs], communication, and information systems) on nursing care were included. We used the nursing care performance framework (NCPF) as an extraction grid and analytical tool. This model illustrates how the interplay between nursing resources and the nursing services can produce changes in patient conditions. The primary outcomes included nurses’ practice environment, nursing processes, professional satisfaction, and nursing-sensitive outcomes. The secondary outcomes included satisfaction or dissatisfaction with ICTs according to nurses’ and patients’ perspectives. Reviews published in English, French, or Spanish from January 1, 1995 to January 15, 2015, were considered. Results: A total of 5515 titles or abstracts were assessed for eligibility and full-text papers of 72 articles were retrieved for detailed evaluation. It was found that 22 reviews published between 2002 and 2015 met the eligibility criteria. Many nursing care themes (ie, indicators) were influenced by the use of ICTs, including time management; time spent on patient care; documentation time; information quality and access; quality of documentation; knowledge updating and utilization; nurse autonomy; intra and interprofessional collaboration; nurses’ competencies and skills; nurse-patient relationship; assessment, care planning, and evaluation; teaching of patients and families; communication and care coordination; perspectives of the quality of care provided; nurses and patients satisfaction or dissatisfaction with ICTs; patient comfort and quality of life related to care; empowerment; and functional status. Conclusions: The findings led to the identification of 19 indicators related to nursing care that are impacted by the use of ICTs. To the best of our knowledge, this was the first attempt to apply NCPF in the ICTs’ context. This broad representation could be kept in mind when it will be the time to plan and to implement emerging ICTs in health care settings. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews: CRD42014014762; (Archived by WebCite at

  • Fotografy Gianni Pauciello
Department of ORL, Head and Neck Surgery
University Hospital of Bern, Switzerland, 2017.

    Influence of Telecommunication Modality, Internet Transmission Quality, and Accessories on Speech Perception in Cochlear Implant Users


    Background: Telecommunication is limited or even impossible for more than one-thirds of all cochlear implant (CI) users. Objective: We sought therefore to study the impact of voice quality on speech perception with voice over Internet protocol (VoIP) under real and adverse network conditions. Methods: Telephone speech perception was assessed in 19 CI users (15-69 years, average 42 years), using the German HSM (Hochmair-Schulz-Moser) sentence test comparing Skype and conventional telephone (public switched telephone networks, PSTN) transmission using a personal computer (PC) and a digital enhanced cordless telecommunications (DECT) telephone dual device. Five different Internet transmission quality modes and four accessories (PC speakers, headphones, 3.5 mm jack audio cable, and induction loop) were compared. As a secondary outcome, the subjective perceived voice quality was assessed using the mean opinion score (MOS). Results: Speech telephone perception was significantly better (median 91.6%, P<.001) with Skype compared with PSTN (median 42.5%) under optimal conditions. Skype calls under adverse network conditions (data packet loss > 15%) were not superior to conventional telephony. In addition, there were no significant differences between the tested accessories (P>.05) using a PC. Coupling a Skype DECT phone device with an audio cable to the CI, however, resulted in higher speech perception (median 65%) and subjective MOS scores (3.2) than using PSTN (median 7.5%, P<.001). Conclusions: Skype calls significantly improve speech perception for CI users compared with conventional telephony under real network conditions. Listening accessories do not further improve listening experience. Current Skype DECT telephone devices do not fully offer technical advantages in voice quality.

  • Source: Created by Ben Schonewille.; Copyright: via; URL:; License: Licensed by the authors.

    Analyzing and Predicting User Participations in Online Health Communities: A Social Support Perspective


    Background: Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with similar peers to seek, receive, and provide different types of social support, such as informational support, emotional support, and companionship. As active participations in an OHC are beneficial to both the OHC and its users, it is important to understand factors related to users’ participations and predict user churn for user retention efforts. Objective: This study aimed to analyze OHC users’ Web-based interactions, reveal which types of social support activities are related to users’ participation, and predict whether and when a user will churn from the OHC. Methods: We collected a large-scale dataset from a popular OHC for cancer survivors. We used text mining techniques to decide what kinds of social support each post contained. We illustrated how we built text classifiers for 5 different social support categories: seeking informational support (SIS), providing informational support (PIS), seeking emotional support (SES), providing emotional support (PES), and companionship (COM). We conducted survival analysis to identify types of social support related to users’ continued participation. Using supervised machine learning methods, we developed a predictive model for user churn. Results: Users’ behaviors to PIS, SES, and COM had hazard ratios significantly lower than 1 (0.948, 0.972, and 0.919, respectively) and were indicative of continued participations in the OHC. The churn prediction model based on social support activities offers accurate predictions on whether and when a user will leave the OHC. Conclusions: Detecting different types of social support activities via text mining contributes to better understanding and prediction of users’ participations in an OHC. The outcome of this study can help the management and design of a sustainable OHC via more proactive and effective user retention strategies.

  • Source:; Copyright: Mic445; URL:; License: Creative Commons Attribution (CC-BY).

    Usability, Acceptability, and Adherence to an Electronic Self-Monitoring System in Patients With Major Depression Discharged From Inpatient Wards


    Background: Patients suffering from depression have a high risk of relapse and readmission in the weeks following discharge from inpatient wards. Electronic self-monitoring systems that offer patient-communication features are now available to offer daily support to patients, but the usability, acceptability, and adherence to these systems has only been sparsely investigated. Objective: We aim to test the usability, acceptability, adherence, and clinical outcome of a newly developed computer-based electronic self-assessment system (the Daybuilder system) in patients suffering from depression, in the period from discharge until commencing outpatient treatment in the Intensive Outpatient Unit for Affective Disorders. Methods: Patients suffering from unipolar major depression that were referred from inpatient wards to an intensive outpatient unit were included in this study before their discharge, and were followed for four weeks. User satisfaction was assessed using semiqualitative questionnaires and the System Usability Scale (SUS). Patients were interviewed at baseline and at endpoint with the Hamilton depression rating scale (HAM-D17), the Major Depression Inventory (MDI), and the 5-item World Health Organization Well-Being Index (WHO-5). In this four-week period patients used the Daybuilder system to self-monitor mood, sleep, activity, and medication adherence on a daily basis. The system displayed a graphical representation of the data that was simultaneously displayed to patients and clinicians. Patients were phoned weekly to discuss their data entries. The primary outcomes were usability, acceptability, and adherence to the system. The secondary outcomes were changes in: the electronically self-assessed mood, sleep, and activity scores; and scores from the HAM-D17, MDI, and WHO-5 scales. Results: In total, 76% of enrolled patients (34/45) completed the four-week study. Five patients were readmitted due to relapse. The 34 patients that completed the study entered data for mood on 93.8% of the days (872/930), sleep on 89.8% of the days (835/930), activity on 85.6% of the days (796/930), and medication on 88.0 % of the days (818/930). SUS scores were 86.2 (standard deviation [SD] 9.7) and 79% of the patients (27/34) found that the system lived up to their expectations. A significant improvement in depression severity was found on the HAM-D17 from 18.0 (SD 6.5) to 13.3 (SD 7.3; P<.01), on the MDI from 27.1 (SD 13.1) to 22.1 (SD 12.7; P=.006), and in quality of life on the WHO-5 from 31.3 (SD 22.9) to 43.4 (SD 22.1; P<.001) scales, but not on self-assessed mood (P=.08). Mood and sleep parameters were highly variable from day-to-day. Sleep-offset was significantly delayed from baseline, averaging 48 minutes (standard error 12 minutes; P<.001). Furthermore, when estimating delay of sleep-onset (with sleep quality included in the model) during the study period, this showed a significant negative effect on mood (P=.03) Conclusions: The Daybuilder systems performed well technically, and patients were satisfied with the system and had high adherence to self-assessments. The dropout rate and the gradual delay in sleep emphasize the need for continued clinical support for these patients, especially when considering sleep guidance.

  • Books on ADHD. Source: Pete Quily via; Copyright: Pete Quily; URL:; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Seeking Web-Based Information About Attention Deficit Hyperactivity Disorder: Where, What, and When


    Background: Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder, prevalent among 2-10% of the population. Objective: The objective of this study was to describe where, what, and when people search online for topics related to ADHD. Methods: Data were collected from Microsoft’s Bing search engine and from the community question and answer site, Yahoo Answers. The questions were analyzed based on keywords and using further statistical methods. Results: Our results revealed that the Internet indeed constitutes a source of information for people searching the topic of ADHD, and that they search for information mostly about ADHD symptoms. Furthermore, individuals personally affected by the disorder made 2.0 more questions about ADHD compared with others. Questions begin when children reach 2 years of age, with an average age of 5.1 years. Most of the websites searched were not specifically related to ADHD and the timing of searches as well as the query content were different among those prediagnosis compared with postdiagnosis. Conclusions: The study results shed light on the features of ADHD-related searches. Thus, they may help improve the Internet as a source of reliable information, and promote improved awareness and knowledge about ADHD as well as quality of life for populations dealing with the complex phenomena of ADHD.

  • Source: iStock by Getty Images; Copyright: Pekic via www.gettyimages; URL:; License: Licensed by the authors.

    Toward Game-Based Digital Mental Health Interventions: Player Habits and Preferences


    Background: Designers of digital interventions for mental health often leverage interactions from games because the intrinsic motivation that results from game-based interventions may increase participation and translate into improved treatment efficacy. However, there are outstanding questions about the suitability (eg, are desktop or mobile interventions more appropriate?) and intervention potential (eg, do people with depression activate enough to play?) of games for mental health. Objective: In this paper, we aimed to describe the presently unknown relationship between gaming activity and indicators of well-being so that designers make informed choices when designing game-based interventions for mental health. Methods: We gathered validated scales of well-being (Beck’s Depression Inventory [BDI-II], Patient Health Questionnaire [PHQ-9], trait anxiety [TA], and basic psychological needs satisfaction [BPNS]), play importance (control over game behavior: control; gamer identity: identity), and play behavior (play frequency, platform preferences, and genre preferences) in a Web-based survey (N=491). Results: The majority of our participants played games a few times a week (45.3%, 222/490) or daily (34.3%, 168/490). In terms of depression, play frequency was associated with PHQ-9 (P=.003); PHQ-9 scores were higher for those who played daily than for those who played a few times a week or less. Similarly, for BDI-II (P=.01), scores were higher for those who played daily than for those who played once a week or less. Genre preferences were not associated with PHQ-9 (P=.32) or BDI-II (P=.68); however, platform preference (ie, mobile, desktop, or console) was associated with PHQ-9 (P=.04); desktop-only players had higher PHQ-9 scores than those who used all platforms. Platform preference was not associated with BDI-II (P=.18). In terms of anxiety, TA was not associated with frequency (P=.23), platform preference (P=.07), or genre preference (P=.99). In terms of needs satisfaction, BPNS was not associated with frequency (P=.25) or genre preference (P=.53), but it was associated with platform preference (P=.01); desktop-only players had lower needs satisfaction than those who used all platforms. As expected, play frequency was associated with identity (P<.001) and control (P<.001); those who played more had identified more as a gamer and had less control over their gameplay. Genre preference was associated with identity (P<.001) and control (P<.001); those who played most common genres had higher control over their play and identified most as gamers. Platform preference was not associated with control (P=.80), but was with identity (P=.001); those who played on all devices identified more as a gamer than those who played on mobiles or consoles only. Conclusions: Our results suggest that games are a suitable approach for mental health interventions as they are played broadly by people across a range of indicators of mental health. We further unpack the platform preferences and genre preferences of players with varying levels of well-being.

  • Screenshots from the virtual coach prototype showing the homepage and a reminder. Source: Figure 1 from; Copyright: the authors; License: Creative Commons Attribution (CC-BY).

    Using Persuasive Technology to Increase Physical Activity in People With Chronic Obstructive Pulmonary Disease by Encouraging Regular Walking: A...


    Background: People with chronic obstructive pulmonary disease (PwCOPD) often experience breathlessness and fatigue, making physical activity challenging. Although many persuasive technologies (such as mobile phone apps) have been designed to support physical activity among members of the general population, current technologies aimed at PwCOPD are underdeveloped and only use a limited range of persuasive technology design principles. Objective: The aim of this study was to explore how acceptable different persuasive technology design principles were considered to be in supporting and encouraging physical activity among PwCOPD. Methods: Three prototypes for mobile apps using different persuasive technology design principles as defined by the persuasive systems design (PSD) model—namely, dialogue support, primary task support, and social support—were developed. Opinions of these prototypes were explored through 28 interviews with PwCOPD, carers, and the health care professionals (HCPs) involved in their care and questionnaires completed by 87 PwCOPD. Participants also ranked how likely individual techniques (eg, competition) would be to convince them to use a technology designed to support physical activity. Data were analyzed using framework analysis, Friedman tests, and Wilcoxon signed rank tests and a convergent mixed methods design was used to integrate findings. Results: The prototypes for mobile apps were received positively by participants. The prototype that used a dialogue support approach was identified as the most likely to be used or recommended by those interviewed, and was perceived as more persuasive than both of the other prototypes (Z=−3.06, P=.002; Z=−5.50, P<.001) by those who completed the questionnaire. PwCOPD identified dialogue support and primary task support techniques as more likely to convince them to use a technology than social support techniques (Z=−5.00, P<.001; Z=−4.92, P<.001, respectively). Opinions of social support techniques such as competition and collaboration were divided. Conclusions: Dialogue support and primary task support approaches are considered to be both acceptable and likely to be persuasive by PwCOPD, carers, and HCPs. In the future, these approaches should be considered when designing apps to encourage physical activity by PwCOPD.

  • Runner consulting fitness app. Source: via; URL:; License: Public Domain (CC0).

    Who Uses Mobile Phone Health Apps and Does Use Matter? A Secondary Data Analytics Approach


    Background: Mobile phone use and the adoption of healthy lifestyle software apps (“health apps”) are rapidly proliferating. There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions to change, and actual health behaviors. Objective: The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended guidelines for fruit and vegetable intake and physical activity. Methods: Data on users of mobile devices and health apps were analyzed from the National Cancer Institute’s 2015 Health Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss. Results: From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+ years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a mobile device, especially if that person was a college graduate (OR 3.30). Individuals with apps were significantly more likely to report intentions to improve fruit (63.8% with apps vs 58.5% without apps, P=.01) and vegetable (74.9% vs 64.3%, P<.01) consumption, physical activity (83.0% vs 65.4%, P<.01), and weight loss (83.4% vs 71.8%, P<.01). Individuals with apps were also more likely to meet recommendations for physical activity compared with those without a device or health apps (56.2% with apps vs 47.8% without apps, P<.01). Conclusions: The main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income. Although differences persist for gender, age, and educational attainment, many individual sociodemographic factors are becoming less potent in influencing engagement with mobile devices and health app use. App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations.

  • The pronator drift test: (a) the degree of drift in the weak arm and counter-arm of a patient was measured by the drift angle from the horizontal plane, and (b) the degree of pronation was assessed in front of the patient. Source: Figure 2 from; Copyright: the authors; License: Creative Commons Attribution (CC-BY).

    Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients


    Background: The pronator drift test (PDT), a neurological examination, is widely used in clinics to measure motor weakness of stroke patients. Objective: The aim of this study was to develop a PDT tool with machine learning classifiers to detect stroke symptoms based on quantification of proximal arm weakness using inertial sensors and signal processing. Methods: We extracted features of drift and pronation from accelerometer signals of wearable devices on the inner wrists of 16 stroke patients and 10 healthy controls. Signal processing and feature selection approach were applied to discriminate PDT features used to classify stroke patients. A series of machine learning techniques, namely support vector machine (SVM), radial basis function network (RBFN), and random forest (RF), were implemented to discriminate stroke patients from controls with leave-one-out cross-validation. Results: Signal processing by the PDT tool extracted a total of 12 PDT features from sensors. Feature selection abstracted the major attributes from the 12 PDT features to elucidate the dominant characteristics of proximal weakness of stroke patients using machine learning classification. Our proposed PDT classifiers had an area under the receiver operating characteristic curve (AUC) of .806 (SVM), .769 (RBFN), and .900 (RF) without feature selection, and feature selection improves the AUCs to .913 (SVM), .956 (RBFN), and .975 (RF), representing an average performance enhancement of 15.3%. Conclusions: Sensors and machine learning methods can reliably detect stroke signs and quantify proximal arm weakness. Our proposed solution will facilitate pervasive monitoring of stroke patients.

  • Permanent Snooze. Source: via; URL:; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles


    Background: Sleep is a critical aspect of people’s well-being and as such assessing sleep is an important indicator of a person’s health. Traditional methods of sleep assessment are either time- and resource-intensive or suffer from self-reporting biases. Recently, researchers have started to use mobile phones to passively assess sleep in individuals’ daily lives. However, this work remains in its early stages, having only examined relatively small and homogeneous populations in carefully controlled contexts. Thus, it remains an open question as to how well mobile device-based sleep monitoring generalizes to larger populations in typical use cases. Objective: The aim of this study was to assess the ability of machine learning algorithms to detect the sleep start and end times for the main sleep period in a 24-h cycle using mobile devices in a diverse sample. Methods: We collected mobile phone sensor data as well as daily self-reported sleep start and end times from 208 individuals (171 females; 37 males), diverse in age (18−66 years; mean 39.3), education, and employment status, across the United States over 6 weeks. Sensor data consisted of geographic location, motion, light, sound, and in-phone activities. No specific instructions were given to the participants regarding phone placement. We used random forest classifiers to develop both personalized and global predictors of sleep state from the phone sensor data. Results: Using all available sensor features, the average accuracy of classifying whether a 10-min segment was reported as sleep was 88.8%. This is somewhat better than using the time of day alone, which gives an average accuracy of 86.9%. The accuracy of the model considerably varied across the participants, ranging from 65.1% to 97.3%. We found that low accuracy in some participants was due to two main factors: missing sensor data and misreports. After correcting for these, the average accuracy increased to 91.8%, corresponding to an average median absolute deviation (MAD) of 38 min for sleep start time detection and 36 min for sleep end time. These numbers are close to the range reported by previous research in more controlled situations. Conclusions: We find that mobile phones provide adequate sleep monitoring in typical use cases, and that our methods generalize well to a broader population than has previously been studied. However, we also observe several types of data artifacts when collecting data in uncontrolled settings. Some of these can be resolved through corrections, but others likely impose a ceiling on the accuracy of sleep prediction for certain subjects. Future research will need to focus more on the understanding of people’s behavior in their natural settings in order to develop sleep monitoring tools that work reliably in all cases for all people.

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  • Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients with Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial

    Date Submitted: Apr 25, 2017

    Open Peer Review Period: Apr 25, 2017 - Jun 20, 2017

    Background: Depression is a significant challenge for safety-net primary care systems. Collaborative depression care is effective, but complex system factors impede adoption and result in persistent d...

    Background: Depression is a significant challenge for safety-net primary care systems. Collaborative depression care is effective, but complex system factors impede adoption and result in persistent disparities in depression outcomes. A care delivery model was evaluated that harnesses information and communication technologies to automate routine screening and monitoring of patient depressive symptoms and treatment adherence and to allow timely communication with providers. Objective: The aim of the study was to compare 6-month outcomes of the technology-facilitated care management (TC) model to usual care (UC) and a supported care (SC) model that involved team-based care management practice for safety-net primary care adult patients with type 2 diabetes. Methods: The Diabetes-Depression Care-Management Adoption Technologies Trial is a translational study in collaboration with Los Angeles County Department of Health Services, the second-largest safety-net care system in the United States. A comparative effectiveness study with quasi-experimental design was conducted in three groups of adult patients with type 2 diabetes to compare three delivery models: UC, SC, and TC. Six-month outcomes included depression and diabetes care measures and patient-reported outcomes. Comparative treatment effects were estimated by linear or logistic regression models that used generalized propensity scores to adjust for sampling bias inherent in the nonrandomized design. Results: A sample of 1,406 patients (484 in UC, 480 in SC, 442 in TC) was enrolled. A majority of the patients were Hispanic or Latino and female. Compared to UC, both SC and TC groups experienced significantly reduced depressive symptoms measured by scores on the 9-item Patient Health Questionnaire (least squares estimate [LSE]: UC=6.35, SC=5.05, TC=5.16; P: SC vs. UC=.02, TC vs. UC=.02); decreased prevalence of major depression (odds ratio [OR]: SC vs. UC=0.45, TC vs. UC=0.33; P: SC vs. UC=.02, TC vs. UC=.007); and improved functional disability as measured by Sheehan Disability Scale scores (LSE: UC=3.21, SC=2.61, TC=2.59; P: SC vs. UC=.04, TC vs. UC=.03). Only TC, not SC, significantly improved depression remission (TC vs. UC: OR=2.98, P=.04); increased satisfaction with care for emotional problems among depressed patients (LSE: UC=3.20, TC=3.70; P=.05); reduced total cholesterol level (LSE: UC=176.40, TC=160.46; P=.01); improved satisfaction with diabetes care (LSE: UC=4.01, TC=4.20; P=.05); and increased the odds of taking an A1c test (TC vs. UC: OR=3.40, P<.001). Conclusions: Both the TC and SC delivery models can improve 6-month depression outcomes. Nevertheless, the TC model is more effective in improving depression remission, patient satisfaction, and diabetes care quality. Clinical Trial: NCT01781013

  • Use of the Internet to Communicate with Providers from 2003 to 2013: 10 years of Patient Engagement according to the Health Information National Trends Surveys (HINTS)

    Date Submitted: Apr 24, 2017

    Open Peer Review Period: Apr 25, 2017 - Jun 20, 2017

    Background: Communication is key in chronic disease management, and the Internet has altered the manner in which patient and providers can communicate. It is an additional avenue by which providers c...

    Background: Communication is key in chronic disease management, and the Internet has altered the manner in which patient and providers can communicate. It is an additional avenue by which providers can engage patients. Adoption of secure messaging differs among patients due to the digital divide (i.e., disparities in technology access based on socio-economic factors). Objective: To examine the current state of online patient-provider communication, exploring longitudinal trends over time in the use of online patient-provider communication. Methods: A three part analytic process was used: 1) reanalysis, 2) close replication across years, and 3) trend analysis extension. During the reanalysis stage, the publicly available HINTS 1 and 2 data was used with the goal of identifying the precise analytic methodology used by in the original 2007 paper. The original analysis was extended to add additional data years (i.e., 2008, 2011, and 2013) using the same analytic approach with the purpose of identifying trends over time. Multivariate logistic regression was used to analyze pooled data across all years with year as an added predictor in addition to a model for each individual data year. Results: The odds of Internet users to communicate online with health care providers was significantly and increasingly higher by year compared to 2003 (2005 OR=1.32, 2008 OR=2.14, 2011 OR=2.92, and 2013 OR=5.75). Statistically significant socio-economic factors found to decrease the likelihood of Internet users communicating online with providers included: age, no insurance, no history of cancer, and non-urban area of residence. Conclusions: The proportion of Internet users communicating online with their healthcare providers has significantly increased since 2003, and though these trends are encouraged to continue through health care policy (e.g., HITECH Act), access challenges remain making it difficult to use this means of communication to engage all patients in all areas.

  • A Medical Student–Delivered Smoking Prevention Program, Education Against Tobacco, for Secondary Schools in Germany: Randomized Controlled Trial

    Date Submitted: Apr 23, 2017

    Open Peer Review Period: Apr 23, 2017 - May 2, 2017

    Background: More than 8,5 Million Germans suffer from chronic diseases attributable to smoking. Education Against Tobacco (EAT) is a multinational network of medical students who volunteer for school-...

    Background: More than 8,5 Million Germans suffer from chronic diseases attributable to smoking. Education Against Tobacco (EAT) is a multinational network of medical students who volunteer for school-based prevention in the classroom setting amongst other activities. EAT is implemented in 28 medical schools in Germany and present in 13 additional countries around the globe. A recent quasi-experimental study showed significant short-term smoking cessation effects on 11- to 15-year-old adolescents. Objective: The aim of this study was to provide the first randomized long-term evaluation of the optimized 2014 EAT curriculum involving a photoaging software for its effectiveness to reduce the smoking prevalence among 11- to 15-year-old pupils in German secondary schools. Methods: A randomized controlled trial was enrolled among 1.504 adolescents aged 11-15 years in grades 6-8 of 9 secondary schools in Germany of which 718 (47,7%) were identifiable for the prospective sample at one year follow-up. The experimental study design included measurements at baseline and at 6 and 12 months postintervention via questionnaire. The study groups consisted of 40 randomized classes receiving the standardized EAT intervention (two medical student-led interactive modules taking 120 minutes total) and 34 control classes within the same schools (no intervention). The primary end point was the difference of the cigarette smoking prevalence in the intervention group versus the difference in the control group at 12 months of follow-up. The differences in smoking behavior (smoking onset, quitting) between the 2 groups as well as effects on the different genders were studied as secondary outcomes. Results: None of the effects were significant with reference to a high loss-to-follow-up effect (52,3%). The smoking prevalence increased from 3,1% to 5,2% to 7,2% in the control group and from 3% to 5,4% to 5,8% in the intervention group (NNT: 68) with notable differences between the groups for the female gender (4,2% to 9,5% for controls vs. 4% to 5,2%; NNT: 24 vs. NNT: 207 for males), low educational background (7,3% to 12% for controls vs. 6,1% to 8,7%; NNT: 30), and migrational background at endline. The intervention appears to prevent smoking onset (NNT: 63) but does not appear to initiate quitting. Conclusions: The intervention appears to prevent smoking especially in females and students with a low educational background.

  • The effect of text messaging interventions on cancer screening rates: a systematic review.

    Date Submitted: Apr 20, 2017

    Open Peer Review Period: Apr 22, 2017 - Jun 17, 2017

    Background: Despite high quality evidence that demonstrates screening reduces mortality from breast, cervical, colorectal, and lung cancer, a substantial portion of the population remains inadequately...

    Background: Despite high quality evidence that demonstrates screening reduces mortality from breast, cervical, colorectal, and lung cancer, a substantial portion of the population remains inadequately screened. There is a critical need to identify interventions that increase the uptake and adoption of evidence-based screening guidelines for preventable cancers at the community practice level. Text messaging has been effective in promoting behavioral change in various clinical settings, but the overall impact and reach of text messaging interventions on cancer screening is unknown. Objective: We performed a systematic review to assess the effect of text messaging interventions on screening for breast, cervical, colorectal, and lung cancer. Methods: We searched multiple databases for studies published between the years 2000-2017, including Pubmed, EMBASE, and the Cochrane Database of Systematic Reviews, to identify controlled trials that measured the effect of text messaging on screening for breast, cervical, colorectal, or lung cancer. Study quality was evaluated using the Cochrane risk of bias tool. Results: Our search yielded 2,238 citations, of which 31 underwent full review and nine met inclusion criteria. Five studies examined screening for breast cancer, one for cervical cancer, and three for colorectal cancer. No studies were found for lung cancer screening. Absolute screening rates for individuals who received text message interventions were 0.6% to 15.0% higher than for controls. Unadjusted relative screening rates for text message recipients were 4% to 63% higher compared to controls. Conclusions: Text messaging interventions appear to moderately increase screening rates for breast and cervical cancer and may have a small effect on colorectal cancer screening. Benefit was observed in various countries, including resource-poor and non-English speaking populations. Given the paucity of data, additional research is needed to better quantify the effectiveness of this promising intervention.

  • A proof of concept study evaluating the variability and accuracy among scribes’ transcribed notes using EHR integrated simulation and qualitative evaluation of scribe simulation

    Date Submitted: Apr 21, 2017

    Open Peer Review Period: Apr 22, 2017 - Jun 17, 2017

    Background: Background: The increasing adoption of Electronic Health Records (EHRs) has been associated with a number of unintended negative consequences with provider efficiency and job satisfaction....

    Background: Background: The increasing adoption of Electronic Health Records (EHRs) has been associated with a number of unintended negative consequences with provider efficiency and job satisfaction. To address this, there has been a dramatic increase in the use of medical scribes to perform many of the required EHR functions. In spite of this rapid growth, little has been published on the training or assessment tools to appraise the safety and efficacy of scribe related EHR activities. Given the number of reports documenting that other professional groups suffer from a number of performance errors in EHR interface and data gathering, scribes likely suffer from similar challenges. This highlights the need for new assessment tools for medical scribes. Objective: To develop a virtual, video based simulation to demonstrate and quantify the variability and accuracy of scribes’ transcribed notes in the EHR. Methods: We created 3 simulated patient-provider scenarios. Each scenario contained a corresponding medical record in our simulation instance of our EHR. For each scenario, we video recorded a standardized patient-provider encounter. 5 scribes with at least 6 months experience both with our EHR and in the specialty of the simulated cases were recruited. Each scribe watched the simulated encounter and transcribed notes into a simulated electronic health record (EHR) environment. Transcribed notes were evaluated for inter-scribe variability and compared to a gold-standard for accuracy. Results: All scribes completed all simulated cases. There was significant inter-scribe variability in note structure and content. Overall, only 26% of all data elements were unique to the scribe writing them. Note length varied by 55, 85, and 115 fold differences between the 3 cases and word economy ranged between 23-71%. Overall, there was a wide inter- and intra-scribe variation in accuracy for each section of the notes with ranges from 50-76%. This resulting in an overall positive predictive value for each note between 38-81%. Conclusions: We created a high fidelity, video based EHR simulation, capable of assessing multiple performance indicators in medical scribes. In this cohort, we demonstrate significant variability both in terms of structure and accuracy in clinical documentation. This form of simulation can provide a valuable tool for future development of scribe curriculum and assessment of competency.

  • Telemedicine and mobile health solutions in oncology: an opinion poll of representatives of Polish medical societies

    Date Submitted: Apr 19, 2017

    Open Peer Review Period: Apr 21, 2017 - Jun 16, 2017

    Background: Telemedicine, or diagnosis/treatment of patients via telecommunications technology, and mobile health (mHealth) is increasingly gaining acceptance across numerous medical fields worldwide....

    Background: Telemedicine, or diagnosis/treatment of patients via telecommunications technology, and mobile health (mHealth) is increasingly gaining acceptance across numerous medical fields worldwide. Indeed, the World Health Organization strongly recommends that mHealth technologies should be implemented in health care systems across all Member States of the European Union. However, in Poland, the public health system has not yet implemented the institutional framework, including legislation, to facilitate an mHealth model. Objective: This study aimed to obtain the opinion from management representatives of Polish medical societies on the use and possibilities of telemedicine and mHealth solutions in Poland, particularly those relating to cancer. Methods: Eleven Polish medical societies, whose members perform tasks related to prevention, diagnosis, or treatment of cancer, were invited to participate in this study. A total of nine experts from seven medical societies accepted the invitation. The study was conducted using partially structured individual interviews, lasting 45 to 70 minutes. A qualitative analysis of the experts’ responses was performed. Results: We found telemedicine is currently more widely known and used among the oncology experts than mHealth technologies. According to the experts, widespread dissemination of telemedicine is expected across all medical fields, including oncology, in future; however, the use of mHealth applications (apps) may not be as easily accepted in the clinic. The biggest advantages of telemedicine stated by the respondents were its ability to save time and to improve the quality of health care. Challenges to mHealth solutions in clinical practice in Poland include low technological literacy, the threat to data security, and insufficient scientific evidence of efficacy and safety. Conclusions: Telemedicine and mHealth solutions can offer many advantages to both patients and health care professionals. However, there is a necessity to create a system of financing telemedicine and mHealth to achieve more widespread use of these technologies in Poland. We must also create a legal framework to support the health care professionals and to protect patients’ personal data. Patients must be educated prior to the implementation of mHealth apps to ensure an adequate use. App developers should involve health care professionals in their development process and consider the needs of older people and those with poor technology literacy. Finally, there should be more scientific validation of mHealth apps.