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Journal Description

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

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

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

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

 

Recent Articles:

  • Source: flickr; Copyright: Marco Verch; URL: https://flickr.com/photos/30478819@N08/48719741971/; License: Creative Commons Attribution (CC-BY).

    The Use of Technology for Communicating With Clinicians or Seeking Health Information in a Multilingual Urban Cohort: Cross-Sectional Survey

    Abstract:

    Background: Technology is being increasingly used to communicate health information, but there is limited knowledge on whether these strategies are effective for vulnerable populations, including non–English speaking or low-income individuals. Objective: This study assessed how language preferences (eg, English, Spanish, or Chinese), smartphone ownership, and the type of clinic for usual source of care (eg, no usual source of care, nonintegrated safety net, integrated safety net, private or community clinic, academic tertiary medical center, or integrated payer-provider) affect technology use for health-related communication. Methods: From May to September 2017, we administered a nonrandom, targeted survey to 1027 English-, Spanish-, and Chinese-speaking San Francisco residents and used weighted multivariable logistic regression analyses to assess predictors of five technology use outcomes. The three primary predictors of interest—language preference, smartphone ownership, and type of clinic for usual care—were adjusted for age, gender, race or ethnicity, limited English proficiency, educational attainment, health literacy, and health status. Three outcomes focused on use of email, SMS text message, or phone apps to communicate with clinicians. The two other outcomes were use of Web-based health videos or online health support groups. Results: Nearly one-third of participants watched Web-based health videos (367/1027, 35.74%) or used emails to communicate with their clinician (318/1027, 30.96%). In adjusted analyses, individuals without smartphones had significantly lower odds of texting their clinician (adjusted odds ratio [aOR] 0.27, 95% CI 0.13-0.56), using online health support groups (aOR 0.14, 95% CI 0.04-0.55), or watching Web-based health videos (aOR 0.31, 95% CI 0.15-0.64). Relative to English-speaking survey respondents, individuals who preferred Chinese had lower odds of texting their clinician (aOR 0.25, 95% CI 0.08-0.79), whereas Spanish-speaking survey respondents had lower odds of using apps to communicate with clinicians (aOR 0.34, 95% CI 0.16-0.75) or joining an online support group (aOR 0.30, 95% CI 0.10-0.92). Respondents who received care from a clinic affiliated with the integrated safety net, academic tertiary medical center, or integrated payer-provider systems had higher odds than individuals without a usual source of care at using emails, SMS text messages, or apps to communicate with clinicians. Conclusions: In vulnerable populations, smartphone ownership increases the use of many forms of technology for health purposes, but device ownership itself is not sufficient to increase the use of all technologies for communicating with clinicians. Language preference impacts the use of technology for health purposes even after considering English proficiency. Health system factors impact patients’ use of technology-enabled approaches for communicating with clinicians. No single factor was associated with higher odds of using technology for all health purposes; therefore, existing disparities in the use of digital health tools among diverse and vulnerable populations can only be addressed using a multipronged approach.

  • Source: National Cancer Institute; Copyright: Daniel Sone; URL: https://visualsonline.cancer.gov/details.cfm?imageid=9713; License: Public Domain (CC0).

    Social Media Strategies for Health Promotion by Nonprofit Organizations: Multiple Case Study Design

    Abstract:

    Background: Nonprofit organizations have always played an important role in health promotion. Social media is widely used in health promotion efforts. However, there is a lack of evidence on how decisions regarding the use of social media are undertaken by nonprofit organizations that want to increase their impact in terms of health promotion. Objective: The aim of this study was to understand why and how nonprofit health care organizations put forth social media strategies to achieve health promotion goals. Methods: A multiple case study design, using in-depth interviews and a content analysis of each social media strategy, was employed to analyze the use of social media tools by six North American nonprofit organizations dedicated to cancer prevention and management. Results: The resulting process model demonstrates how social media strategies are enacted by nonprofit organizations to achieve health promotion goals. They put forth three types of social media strategies relative to their use of existing information and communication technologies (ICT)—replicate, transform, or innovate—each affecting the content, format, and delivery of the message differently. Organizations make sense of the social media innovation in complementarity with existing ICT. Conclusions: For nonprofit organizations, implementing a social media strategy can help achieve health promotion goals. The process of social media strategy implementation could benefit from understanding the rationale, the opportunities, the challenges, and the potentially complementary role of existing ICT strategies.

  • Source: Unsplash; Copyright: jeshoots; URL: https://unsplash.com/photos/LtNvQHdKkmw; License: Licensed by JMIR.

    Influence of Health Literacy on Effects of Patient Rating Websites: Survey Study Using a Hypothetical Situation and Fictitious Doctors

    Abstract:

    Background: Physician rating websites (PRWs) are a device people use actively and passively, although their objective capabilities are insufficient when it comes to judging the medical performance and qualification of physicians. PRWs are an innovation born of the potential of the Internet and boosted very much by the longstanding policy of improving and encouraging patient participation in medical decision-making. A mismatch is feared between patient motivations to participate and their capabilities of doing so well. Awareness of such a mismatch might contribute to some skepticism of patient-written physician reviews on PRWs. Objective: We intend to test whether health literacy is able to dampen the effects that a patient-written review of a physician’s performance might have on physician choice. Methods: An experiment was conducted within a survey interview. Participants were put into a fictitious decision situation in which they had to choose between two physicians on the basis of their profiles on a PRW. One of the physician profiles contained the experimental stimulus in the form of a friendly and a critical written review. The dependent variable was physician choice. An attitude differential, trust differential, and two measures of health literacy, the newest vital sign as an example of a performance-based measure and eHealth Literacy Scale as an example of a perception-based measure, were tested for roles as intermediary variables. Analysis traced the influence of the review tendency on the dependent variables and a possible moderating effect of health literacy on these influences. Results: Reviews of a physician’s competence and medical skill affected participant choice of a physician. High health literacy dampened these effects only in the case of the perception-based measure and only for the negative review. Correspondingly, the effect of the review tendency appeared to be stronger for the positive review. Attitudes and trust only affected physician choice when included as covariants, considerably increasing the variance explained by regression models. Conclusions: Findings sustain physician worries that even one negative PRW review can affect patient choice and damage doctors’ reputations. Hopes that health literacy might raise awareness of the poor basis of physician reviews and ratings given by patients have some foundation.

  • Source: Pexels; Copyright: bongkarn thanyakij; URL: https://www.pexels.com/photo/young-woman-holding-a-stethoscope-3758765/; License: Licensed by JMIR.

    Adoption of an Electronic Patient Record Sharing Pilot Project: Cross-Sectional Survey

    Abstract:

    Background: The Public Private Interface–Electronic Patient Record (PPI-ePR) system was implemented as a new electronic platform to facilitate collaboration between the public and private sectors in Hong Kong. However, its barriers to participate and benefits have not been comprehensively assessed. Objective: This study aimed to evaluate the awareness, acceptance, perceived benefits, and obstacles to participation among private doctors and the general public. Methods: From December 2012 to January 2013, 2435 telephone interviews were performed by trained interviewers to survey randomly selected patients who were enrolled or not enrolled in the PPI-ePR system. In addition, self-administered surveys were sent by postal mail to 4229 registered doctors in Hong Kong. The questionnaires for both patients and doctors contained questions on subjects’ awareness, acceptance, and perceptions of the PPI-ePR, perceived benefits and obstacles of participating in the program, reasons for not using the system after enrolling, and perceived areas for service improvement of the system. Results: More than 53.1% (266/501) of enrolled patients believed that the PPI-ePR system would improve health care quality by reducing duplicate tests and treatments, while more than 76.8% (314/409) of enrolled doctors emphasized timely access to patients’ medical records as the biggest benefit of their enrollment. Among nonenrolled patients, unawareness of the project was the most popular obstacle to enrolling in the PPI-ePR system (483/1200, 40.3%). Regarding nonenrolled doctors, the complicated registration process hindered them from participating in the program the most (95/198, 48.0%). Television, newspaper, and magazine advertisements and medical profession newsletters or journals were suggested as the most effective means to encourage participation in the program among surveyed patients (1297/1701, 76.2%) and doctors (428/610, 70.2%), respectively. Lack of clinical indication requiring data extraction from other hospitals was the main reason for low level of PPI-ePR use. Conclusions: This study comprehensively assessed the popularity, perceived benefits, and hindering factors of enrolling in the PPI-ePR system in Hong Kong. Low levels of awareness, few privacy concerns, and inactive use of the PPI-ePR system were among the key features for patients and physicians. Public promotions, simplified logistics, and a user-friendly online interface were suggested to improve the coverage and effectiveness of health information exchange between private and public health care sectors.

  • Source: The Authors / Placeit; Copyright: JMIR Publications; URL: https://www.jmir.org/2020/4/e17251; License: Licensed by JMIR.

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

    Abstract:

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

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

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

    Abstract:

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

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

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

    Abstract:

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

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

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

    Authors List:

    Abstract:

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

  • Source: Unsplash; Copyright: ROBIN WORRALL; URL: https://unsplash.com/photos/FPt10LXK0cg; License: Licensed by JMIR.

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

    Abstract:

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

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

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

    Abstract:

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

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

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

    Abstract:

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

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

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

    Abstract:

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

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  • Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: A Digital Topic Modeling Approach

    Date Submitted: Apr 4, 2020

    Open Peer Review Period: Apr 3, 2020 - Apr 14, 2020

    Background: In December 2019, a few COVID-19 cases were first reported in Wuhan, Hubei, China. Soon after, increasing cases were detected in other parts of China and soon the disease broke out in Chin...

    Background: In December 2019, a few COVID-19 cases were first reported in Wuhan, Hubei, China. Soon after, increasing cases were detected in other parts of China and soon the disease broke out in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, and prevention/containment. Objective: This study collected media reports on COVID-19 and investigated the patterns of media-directed health communications as well as the role of media in this ongoing COVID-19 crisis in China. Methods: We adopted the Huike database to extract related news articles about coronavirus from major press media, between January 1st, 2020, to February 20th, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated Latent Dirichlet Allocation (LDA) topic modeling with the suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into two-dimensional plane via multidimensional scaling. Results: After removing duplicates, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as our number of topics, and the generated topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three popular themes were prevention and control procedures, medical treatment and research, global/local social/economic influences, accounting for 32.6%, 16.6%, 11.8% of the collected reports respectively. Conclusions: Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles each day and the outbreak development, we note that mass media news reports in China lag behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society than on individuals. The COVID-19 crisis has become a global issue, and society has also become concerned about donation and support as well as mental health. We recommend that future work should address the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

  • Facebook Ads Manager as a Recruitment Tool for an Online Health and Safety Survey

    Date Submitted: Apr 1, 2020

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

    Background: Social media websites have unprecedented levels of growth and usage over the past decade, with Facebook.com hosting 2.5 billion active users worldwide and over 200 million Americans. This...

    Background: Social media websites have unprecedented levels of growth and usage over the past decade, with Facebook.com hosting 2.5 billion active users worldwide and over 200 million Americans. This population has been underutilized and understudied by the academic community as a resource for participant recruitment. Objective: We explore the efficacy of Facebook.com recruitment for an online agricultural health and safety survey Methods: We undertook a pilot study lasting one week on Facebook utilizing their integrated, targeted advertising platform – Facebook Ads Manager. We posted three advertisements depicting varying levels of agricultural safety adoption leading to a brief survey on farm demographics and safety attitudes. We targeted our advertisements towards farm mothers aged 21-50 in the United States and determined cost-effectiveness and potential biases. Results: Three, one-week advertisements were listed concurrently for $294 USD, total. We reached over 40,000 users and gathered 318 clicks. There were 29 participants who consented to the survey, with 24 completions. Our cost per completed survey was $12.25. Compared to the distribution of farms in the US, advertisements were disproportionately posted to users living in Ohio, California, and Michigan and were under-posted in Texas and Iowa. Conclusions: Social media recruitment is limited by geographic and response bias and by self-selection, which needs to be addressed. However, Facebook represents a potentially cost-effective and timely method to recruit participants for online health and safety research when targeting a specific population.

  • eHealth Literacy and Patient-Reported Experiences with Outpatient Care in the Hungarian General Adult Population: A Cross-Sectional Survey Study

    Date Submitted: Mar 31, 2020

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

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

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

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

    Date Submitted: Mar 23, 2020

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

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

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

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

    Date Submitted: Mar 25, 2020

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

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

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

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

    Date Submitted: Mar 19, 2020

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

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

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

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