Generation WhatsApp: inter-brain synchrony during face-to-face and texting communication.

Texting has become one of the most prevalent ways to interact socially, particularly among youth; however, the effects of text messaging on social brain functioning are unknown. Guided by the biobehavioral synchrony frame, this pre-registered study utilized hyperscanning EEG to evaluate interbrain synchrony during face-to-face versus texting interactions. Participants included 65 mother-adolescent dyads observed during face-to-face conversation compared to texting from different rooms. Results indicate that both face-to-face and texting communication elicit significant neural synchrony compared to surrogate data, demonstrating for the first time brain-to-brain synchrony during texting. Direct comparison between the two interactions highlighted 8 fronto-temporal interbrain links that were significantly stronger in the face-to-face interaction compared to texting. Our findings suggest that partners co-create a fronto-temporal network of inter-brain connections during live social exchanges. The degree of improvement in the partners' right-frontal-right-frontal connectivity from texting to the live social interaction correlated with greater behavioral synchrony, suggesting that this well-researched neural connection may be specific to face-to-face communication. Our findings suggest that while technology-based communication allows humans to synchronize from afar, face-to-face interactions remain the superior mode of communication for interpersonal connection. We conclude by discussing the potential benefits and drawbacks of the pervasive use of texting, particularly among youth.

Mindfulness-based Interventions Across the Cancer Continuum in the United States: A Scoping Review.

OBJECTIVE: To review mindfulness-based interventions (MBIs) tested in randomized controlled trials (RCT) across the cancer continuum. DATA SOURCE: Articles identified in PubMed, CINAHL, Web of Science, PsycINFO, and Embase. STUDY INCLUSION AND EXCLUSION CRITERIA: Two independent reviewers screened articles for: (1) topic relevance; (2) RCT study design; (3) mindfulness activity; (4) text availability; (5) country (United States); and (6) mindfulness as the primary intervention component. DATA EXTRACTION: Twenty-eight RCTs met the inclusion criteria. Data was extracted on the following variables: publication year, population, study arms, cancer site, stage of cancer continuum, participant demographic characteristics, mindfulness definition, mindfulness measures, mindfulness delivery, and behavioral theory. DATA SYNTHESIS: We used descriptive statistics and preliminary content analysis to characterize the data and identify emerging themes. RESULTS: A definition of mindfulness was reported in 46% of studies and 43% measured mindfulness. Almost all MBIs were tested in survivorship (50%) or treatment (46%) stages of the cancer continuum. Breast cancer was the focus of 73% of cancer-site specific studies, and most participants were non-Hispanic white females. CONCLUSION: The scoping review identified 5 themes: (1) inconsistency in defining mindfulness; (2) differences in measuring mindfulness; (3) underrepresentation of racial/ethnic minorities; (4) underrepresentation of males and cancer sites other than breast; and (5) the lack of behavioral theory in the design, implementation, and evaluation of the MBI.

Implementing a text message-based intervention to support type 2 diabetes medication adherence in primary care: a qualitative study with general practice staff.

BACKGROUND: The Support through Mobile Messaging and digital health Technology for Diabetes (SuMMiT-D) project has developed, and is evaluating, a mobile phone-based intervention delivering brief messages targeting identified behaviour change techniques promoting medication use to people with type 2 diabetes in general practice. The present study aimed to inform refinement and future implementation of the SuMMiT-D intervention by investigating general practice staff perceptions of how a text message-based intervention to support medication adherence should be implemented within current and future diabetes care. METHODS: Seven focus groups and five interviews were conducted with 46 general practice staff (including GPs, nurses, healthcare assistants, receptionists and linked pharmacists) with a potential role in the implementation of a text message-based intervention for people with type 2 diabetes. Interviews and focus groups were audio-recorded, transcribed and analysed using an inductive thematic analysis approach. RESULTS: Five themes were developed. One theme 'The potential of technology as a patient ally' described a need for diabetes support and the potential of technology to support medication use. Two themes outlined challenges to implementation, 'Limited resources and assigning responsibility' and 'Treating the patient; more than diabetes medication adherence'. The final two themes described recommendations to support implementation, 'Selling the intervention: what do general practice staff need to see?' and 'Fitting the mould; complementing current service delivery'. CONCLUSIONS: Staff see the potential for a text message-based support intervention to address unmet needs and to enhance care for people with diabetes. Digital interventions, such as SuMMiT-D, need to be compatible with existing systems, demonstrate measurable benefits, be incentivised and be quick and easy for staff to engage with. Interventions also need to be perceived to address general practice priorities, such as taking a holistic approach to care and having multi-cultural reach and relevance. Findings from this study are being combined with parallel work with people with type 2 diabetes to ensure stakeholder views inform further refinement and implementation of the SuMMiT-D intervention.

Acute Effects of Coffee Consumption on Health among Ambulatory Adults.

BACKGROUND: Coffee is one of the most commonly consumed beverages in the world, but the acute health effects of coffee consumption remain uncertain. METHODS: We conducted a prospective, randomized, case-crossover trial to examine the effects of caffeinated coffee on cardiac ectopy and arrhythmias, daily step counts, sleep minutes, and serum glucose levels. A total of 100 adults were fitted with a continuously recording electrocardiogram device, a wrist-worn accelerometer, and a continuous glucose monitor. Participants downloaded a smartphone application to collect geolocation data. We used daily text messages, sent over a period of 14 days, to randomly instruct participants to consume caffeinated coffee or avoid caffeine. The primary outcome was the mean number of daily premature atrial contractions. Adherence to the randomization assignment was assessed with the use of real-time indicators recorded by the participants, daily surveys, reimbursements for date-stamped receipts for coffee purchases, and virtual monitoring (geofencing) of coffee-shop visits. RESULTS: The mean (±SD) age of the participants was 39±13 years; 51% were women, and 51% were non-Hispanic White. Adherence to the random assignments was assessed to be high. The consumption of caffeinated coffee was associated with 58 daily premature atrial contractions as compared with 53 daily events on days when caffeine was avoided (rate ratio, 1.09; 95% confidence interval [CI], 0.98 to 1.20; P = 0.10). The consumption of caffeinated coffee as compared with no caffeine consumption was associated with 154 and 102 daily premature ventricular contractions, respectively (rate ratio, 1.51; 95% CI, 1.18 to 1.94); 10,646 and 9665 daily steps (mean difference, 1058; 95% CI, 441 to 1675); 397 and 432 minutes of nightly sleep (mean difference, 36; 95% CI, 25 to 47); and serum glucose levels of 95 mg per deciliter and 96 mg per deciliter (mean difference, -0.41; 95% CI, -5.42 to 4.60). CONCLUSIONS: In this randomized trial, the consumption of caffeinated coffee did not result in significantly more daily premature atrial contractions than the avoidance of caffeine. (Funded by the University of California, San Francisco, and the National Institutes of Health; CRAVE ClinicalTrials.gov number, NCT03671759.).

Patient engagement in a mobile health intervention to improve preparedness for prostate biopsy.

OBJECTIVE: We designed and implemented a peri-procedural text message (SMS) program for patients undergoing transrectal prostate biopsy and aimed to evaluate predictors of patient enrollment and engagement with the SMS program. METHODS: We designed an SMS-based program with 8 messages containing web-based modules with educational content and reminders confirming MRI for fusion biopsy, antibiotic adherence, enema use, and anticoagulation cessation. Data on patient demographics, enrollment, and engagement with modules were collected from June 1, 2018 to February 28, 2021. Engagement was defined as a patient clicking a link delivered via SMS to access modules. We made multivariable models to identify predictors of patient enrollment and engagement. RESULTS: Of the 1,760 prostate biopsies between June 2018 and March 2021, 1,383 (78.6%) were enrolled in SMS, 182 (10.3%) in email, 106 (6.0%) in both, and 240 (13.6%) were not enrolled. Of 1418 patients enrolled, 1,270 (89.6%) engaged with at least one module. African American patients had 50% lower odds of being enrolled (OR = 0.50, 95% CI 0.28-0.96; P = 0.03), but once enrolled there were no differences in engagement. Patients for whom English was not listed as their primary language had 60% lower odds of engagement (OR = 0.40, 95% CI 0.17-1.00, P = .04) and patients who were single or divorced had a 40% lower odds of engagement (OR = 0.60, 95% CI 0.41-0.91, P = 0.01). CONCLUSIONS: A cohort of older men undergoing prostate biopsy were able to engage with a text message-based education and reminder program. Future efforts must address barriers to enrollment for Black or African American men and improve accessibility to non-English speaking patients.

Randomized Study of Survey Recruitment Strategies for Parents of Autistic Children.

INTRODUCTION: This study aimed to compare phone, email, or text message recruitment strategies for engaging parents of autistic children in an online survey. METHOD: In this randomized study, a sample of 1,624 parents of autistic children spectrum disorder (autism) from an integrated health system in Southern California were sent an initial mailed letter and email simultaneously for baseline survey outreach. Then, participants were randomly assigned to one of three follow-up recruitment groups: phone, email, or text message. We compared the efficacy of recruitment strategies in multivariate models. RESULTS: All three follow-up methods were equally effective for eliciting a survey response. Parents of girls were less likely to respond to survey outreach attempts than parents of boys. DISCUSSION: Multiple modalities of survey recruitment, including digital and mobile approaches, effectively recruit parents of children in research.

Delivering Mindfulness-Based Interventions for Insomnia, Pain, and Dysfunctional Eating Through a Text Messaging App: Three Randomized Controlled Trials Investigating the Effectiveness and Mediating Mechanisms.

BACKGROUND: Although text messaging has the potential to be the core intervention modality, it is often used as an adjunct only. To improve health and alleviate the distress related to insomnia, pain, and dysregulated eating of people living in urban areas, text messaging-based mindfulness-based interventions were designed and evaluated in 3 randomized controlled trials. OBJECTIVE: This study investigated the effectiveness and mediating mechanisms of text messaging-based mindfulness-based interventions for people with distress related to insomnia, pain, or dysregulated eating. METHODS: In these trials, 333, 235, and 351 participants were recruited online and randomized to intervention and wait-list control conditions for insomnia, pain, and dysregulated eating, respectively. Participants experienced 21 days of intervention through WhatsApp Messenger. Participants completed pre-, post-, 1-month follow-up, and 3-month follow-up self-report questionnaires online. The retention rates at postmeasurements were 83.2% (139/167), 77.1% (91/118), and 72.9% (129/177) for intervention groups of insomnia, pain, and dysregulated eating, respectively. Participants' queries were answered by a study technician. Primary outcomes included insomnia severity, presleep arousal, pain intensity, pain acceptance, and eating behaviors. Secondary outcomes included mindfulness, depression, anxiety, mental well-being, and functional impairments. Mindfulness, dysfunctional beliefs and attitudes about sleep, pain catastrophizing, and reactivity to food cues were hypothesized to mediate the relationship between the intervention and outcomes. RESULTS: For all 3 studies, the intervention groups showed significant improvement on most outcomes at 1-month follow-up compared to their respective wait-list control groups; some primary outcomes (eg, insomnia, pain, dysregulated eating indicators) and secondary outcomes (eg, depression, anxiety symptoms) were sustained at 3-month follow-up. Medium-to-large effect sizes were found at postassessments in most outcomes in all studies. In the intervention for insomnia, mediation analyses showed that dysfunctional beliefs and attitudes about sleep mediated the effect of the intervention on all primary outcomes and most secondary outcomes at both 1-month and 3-month follow-ups, whereas mindfulness mediated the intervention effect on presleep arousal at 1-month and 3-month follow-ups. In the intervention for pain, pain catastrophizing mediated the effect of intervention on pain intensity and functioning at both 1-month and 3-month follow-ups, whereas mindfulness only mediated the effect of intervention on anxiety and depressive symptoms. In the intervention for dysregulated eating, power of food mediated the effect of intervention on both uncontrolled and emotional eating at both 1-month and 3-month follow-ups and mindfulness was found to mediate the effect on depressive symptoms at both 1-month and 3-month follow-ups. CONCLUSIONS: These 3 studies converged and provided empirical evidence that mindfulness-based interventions delivered through text messaging are effective in improving distress related to sleep, pain, and dysregulated eating. Text messaging has the potential to be a core intervention modality to improve various common health outcomes for people living a fast-paced lifestyle. TRIAL REGISTRATION: Clinical Research and Biostatistics Clinical Trials Registry CUHK_CCRB00559; https://tinyurl.com/24rkwarz.

Design and Preliminary Realization of a Screening and Early Warning Health Management System for Populations at High Risk for Depression.

Depression has a high incidence in the world. Based on the concept of preventive treatment of disease of traditional Chinese medicine, timely screening and early warning of depression in populations at high risk for this condition can avoid, to a certain extent, the dysfunctions caused by depression. This work studied a method to collect information on depression, generate a database of depression features, design algorithms for screening populations at high risk for depression and creating an early warning model, develop an early warning short-message service (SMS) platform, and implement a scheme of depression screening and an early warning health management system. The implementation scheme included mobile application (app), cloud form, screening and early warning model, cloud platform, and computer software. Multiple modules jointly realized the screening, early warning, and management of the health functions of individuals at high risk for depression. At the same time, function modules such as mobile app and cloud form for collecting depression health information, early warning SMS platform, and health management software were designed, and the functions of the modules were preliminarily developed. Finally, the black-box test and white-box test were used to assess the system's functions and ensure the reliability of the system. Through the integration of mobile app and computer software, this study preliminarily realized the screening and early warning health management of a population at high risk for depression.

Exploring context specific anti-smoking warning labels on cigarette packs: A quasi-experiment.

OBJECTIVE: To evaluate the impact of introducing newly-designed warning labels in relation to the available conventional cigarette packs. METHODS: The quasi-experimental study was conducted at four co-educational academic institutions selected using cluster random sampling technique in Gulshan-e-Iqbal town of Karachi from September 2016 to October 2017. The respondents, aged 16-24 years, were exposed with an experimental condition using five graphic cards; each comprising of two separate labels; label 1 being a cigarette pack currently rotated, and label 2 being the newly designed graphic and text warning label. Each participant responded over efficacy measures for each label separately. The difference in the efficacy scores between the two labels was assessed using repeated measure ANOVA with Bonferroni correction in analysis. RESULTS: Of the 388 students, 256(66%) were males and 132(34%) were females. The overall mean age was 18±2.76 years. Also, 188(48.5%) subjects were studying in higher secondary, 179(46.1%) undergraduate and 21(5.4%) postgraduate level. Of them, 104(26.8%) were ever-smokers and 284(73.2%) reported to be never-smokers. A difference was observed in the efficacy of the newly designed label "poverty" compared with current cigarette pack on the measure of not to start smoking(p=0.006). Never-smoking males perceived newly-designed label element 'dead person' as fear-arousing (p=0.045), while never-smoking females considered 'look after family' as efficacious (p=0.024). CONCLUSIONS: There was some evidence of variation in efficacy scores after stratifying on gender and smoking status. A more holistic approach is needed in this regard.

Mental imagery-based self-regulation: Effects on physical activity behaviour and its cognitive and affective precursors over time.

OBJECTIVES: (1) Test whether a mental imagery-based self-regulation intervention increases physical activity behaviour over 90 days; (2) Examine cognitive and affective precursors of change in physical activity behaviour. DESIGN: A randomized control trial with participants (N = 500) randomized to one of six intervention conditions in a 3 (risk communication format: bulleted list, table, risk ladder) x 2 (mental imagery behaviour: physical activity, active control [sleep hygiene]) factorial design. METHODS: After receiving personalized risk estimates via a website on a smartphone, participants listened to an audiorecording that guided them through a mental imagery activity related to improving physical activity (intervention group) or sleep hygiene behaviour (active control). Participants received text message reminders to complete the imagery for 3 weeks post-intervention, 4 weekly text surveys to assess behaviour and its cognitive and affective precursors, and a mailed survey 90 days post-baseline. RESULTS: Physical activity increased over 90 days by 19.5 more minutes per week (95%CI: 2.0, 37.1) in the physical activity than the active control condition. This effect was driven by participants in the risk ladder condition, who exercised 54.8 more minutes (95%CI 15.6, 94.0) in the physical activity condition than participants in the active control sleep hygiene group. Goal planning positively predicted physical activity behaviour (b = 12.2 minutes per week, p = 0.002), but self-efficacy, image clarity, and affective attitudes towards behaviours did not (p > 0.05). CONCLUSIONS: Mental imagery-based self-regulation interventions can increase physical activity behaviour, particularly when supported by personalized disease risk information presented in an easy-to-understand format.

Effects of a cannabis use disorder text message-delivered treatment on young adult alcohol misuse: Differential effects by gender.

Alcohol misuse is more prevalent, frequent, and severe among young adults who use cannabis. Treatment of dual alcohol and cannabis users may have mixed results, with some studies reporting that alcohol misuse increases when cannabis use decreases (substance substitution), while others report that alcohol misuse decreases along with decreasing cannabis use (treatment spillover), and others report no association. Additionally, little research tests whether gender differences are found in treatment of dual alcohol and cannabis users, which may be expected given previous alcohol-focused treatments showing larger effects for females. In the current study, we present a secondary analysis of a randomized clinical trial testing a text message-delivered cannabis use disorder (CUD) treatment (peer network counseling text or "PNC-txt"). The trial included 101 young adults ages 18-25 who met criteria for CUD. We tested whether alcohol use and binge drinking frequency (4+/5+ drinks for women/men) decreased in response to the PNC-txt treatment, which has previously shown effectiveness in reducing cannabis use days. Latent growth models tested PNC-txt effects on the monthly rate of change in alcohol use and binge drinking across three months. In the full sample, we found no evidence of significant treatment effects on alcohol use (d = -0.07) or binge drinking (d = -0.10). Moderation analyses, however, indicated the PNC-txt effect on both alcohol use and binge drinking differed significantly by gender. PNC-txt led to significantly larger decreases in alcohol use (d = -0.53) and binge drinking days (d = -0.43) across the three months for females, whereas the study saw opposite (but nonsignificant) effects for males (d = 0.30 and 0.16 for alcohol use and binge drinking, respectively). We found no evidence that reductions in alcohol use and binge drinking were associated with cannabis use decreases, arguing against direct substitution or spillover effects. These results provide evidence that treatments focused on cannabis use may have secondary beneficial effects for young-adult alcohol misuse, although such effects may be limited to women.

Text Messages to Curb Sugar-Sweetened Beverage Consumption among Pregnant Women and Mothers: A Mobile Health Randomized Controlled Trial.

Racial, ethnic, and socioeconomic disparities in childhood obesity in the United States (U.S.) originate in early life. Maternal sugar-sweetened beverage (SSB) consumption is an early life risk factor for later offspring obesity. The goal of this study was to test the effects of policy-relevant messages delivered by text messages mobile devices (mHealth) on maternal SSB consumption. In this three-arm 1-month randomized controlled trial (RCT), pregnant women or mothers of infants in predominantly Hispanic/Latino New York City neighborhoods were randomized to receive one of three text message sets: graphic beverage health warning labels, beverage sugar content information, or attention control. The main outcome was change in maternal self-reporting of average daily SSB consumption from baseline to one month. Among 262 participants, maternal SSB consumption declined over the 1-month period in all three arms. No intervention effect was detected in primary analyses. In sensitivity analyses accounting for outliers, graphic health warning labels reduced maternal SSB consumption by 28 kcal daily (95% CI: -56, -1). In this mHealth RCT among pregnant women and mothers of infants, graphic health warning labels and beverage sugar content information did not reduce maternal SSB consumption.

The NUDGE trial pragmatic trial to enhance cardiovascular medication adherence: study protocol for a randomized controlled trial.

BACKGROUND: Nearly half of patients do not take their cardiovascular medications as prescribed, resulting in increased morbidity, mortality, and healthcare costs. Mobile and digital technologies for health promotion and disease self-management offer an opportunity to adapt behavioral "nudges" using ubiquitous mobile phone technology to facilitate medication adherence. The Nudge pragmatic clinical trial uses population-level pharmacy data to deliver nudges via mobile phone text messaging and an artificial intelligent interactive chat bot with the goal of improving medication adherence and patient outcomes in three integrated healthcare delivery systems. METHODS: The Theory of mHealth, the Expanded RE-AIM/PRISM, and the PRECIS-2 frameworks were used for program planning, implementation, and evaluation, along with a focus on dissemination and cost considerations. During the planning phase, the Nudge study team developed and piloted a technology-based nudge message and chat bot of optimized interactive content libraries for a range of diverse patients. Inclusion criteria are very broad and include patients in one of three diverse health systems who take medications to treat hypertension, atrial fibrillation, coronary artery disease, diabetes, or hyperlipidemia. A target of approximately 10,000 participants will be randomized to one of 4 study arms: usual care (no intervention), generic nudge (text reminder), optimized nudge, and optimized nudge plus interactive AI chat bot. The PRECIS-2 tool indicated that the study protocol is very pragmatic, although there is variability across PRECIS-2 dimensions. DISCUSSION: The primary effectiveness outcome is medication adherence defined by the proportion of days covered (PDC) using pharmacy refill data. Implementation outcomes are assessed using the RE-AIM framework, with a particular focus on reach, consistency of implementation, adaptations, cost, and maintenance/sustainability. The project has limitations including limited power to detect some subgroup effects, medication complications (bleeding), and longer-term outcomes (myocardial infarction). Strengths of the study include the diverse healthcare systems, a feasible and generalizable intervention, transparent reporting using established pragmatic research and implementation science frameworks, strong stakeholder engagement, and planning for dissemination and sustainment. TRIAL REGISTRATION: ClinicalTrials.gov NCT03973931 . Registered on 4 June 2019. The study was funded by the NIH; grant number is 4UH3HL144163-02 issued 4/5/19.

Using Wearable Cameras to Assess Foods and Beverages Omitted in 24 Hour Dietary Recalls and a Text Entry Food Record App.

Technology-enhanced methods of dietary assessment may still face common limitations of self-report. This study aimed to assess foods and beverages omitted when both a 24 h recall and a smartphone app were used to assess dietary intake compared with camera images. For three consecutive days, young adults (18-30 years) wore an Autographer camera that took point-of-view images every 30 seconds. Over the same period, participants reported their diet in the app and completed daily 24 h recalls. Camera images were reviewed for food and beverages, then matched to the items reported in the 24 h recall and app. ANOVA (with post hoc analysis using Tukey Honest Significant Difference) and paired t-test were conducted. Discretionary snacks were frequently omitted by both methods (p < 0.001). Water was omitted more frequently in the app than in the camera images (p < 0.001) and 24 h recall (p < 0.001). Dairy and alternatives (p = 0.001), sugar-based products (p = 0.007), savoury sauces and condiments (p < 0.001), fats and oils (p < 0.001) and alcohol (p = 0.002) were more frequently omitted in the app than in the 24 h recall. The use of traditional self-report methods of assessing diet remains problematic even with the addition of technology and finding new objective methods that are not intrusive and are of low burden to participants remains a challenge.

Addressing logistical barriers to childhood vaccination using an automated reminder system and online resource intervention: A randomized controlled trial.

BACKGROUND: As the rates of vaccination decline in children with logistical barriers to vaccination, new strategies to increase vaccination are needed. The goal of this study was to develop and evaluate the effectiveness of the Vaccines For Babies (VFB) intervention, an automated reminder system with online resources to address logistical barriers to vaccination in caregivers of children enrolled in an integrated healthcare system. Effectiveness was evaluated in a randomized controlled trial. METHODS: Qualitative interviews were conducted with parents of children less than two years old to identify logistical barriers to vaccination that were used to develop the VFB intervention. VFB included automated reminders to schedule the 6- and 12-month vaccine visit linking caregivers to resources to address logistic barriers, sent to the preferred mode of outreach (text, email, and/or phone). Parents of children between 3 and 10 months of age with indicators of logistical barriers to vaccination were randomized to receive VFB or usual well child care (UC). The primary outcome was percentage of days undervaccinated at 2 years of life. A difference in differences analysis was conducted. RESULTS: Qualitative interviews with 6 parents of children less than 2 years of age identified transportation, scheduling challenges, and knowledge of vaccine timing as logistical barriers to vaccination. We enrolled 250 participants in the trial, 45% were loss to follow-up. There were no significant differences in vaccination uptake between those enrolled in UC or the VFB intervention (0.51%, p = 0.86). In Medicaid enrolled participants, there was a modest decrease in percentage of days undervaccinated in the VFB intervention compared to UC (6.3%, p = 0.07). CONCLUSION: Automated Reminders and with links to heath system resources was not shown to increase infant vaccination uptake demonstrating additional resources are needed to address the needs of caregivers experiencing logistical barriers to vaccination.

KeMRE: Knowledge-enhanced medical relation extraction for Chinese medicine instructions.

Medicine instructions usually contain rich medical relations, and extracting them is very helpful for many downstream tasks such as medicine knowledge graph construction and medicine side-effect prediction. Existing relation extraction (RE) methods usually predict relations between entities from their contexts and do not consider medical knowledge. However, understanding a part of medical relations may need some expert knowledge in the medical field, making it challenging for existing methods to achieve satisfying performances of medical RE. In this paper, we propose a knowledge-enhanced framework for medical RE, which can exploit medical knowledge of medicines to better conduct medical RE on Chinese medicine instructions. We first propose a BERT-CNN-LSTM based framework for text modeling and learn representations of characters from their contexts. Then we learn representations of each entity by aggregating representations of their characters. Besides, we propose a CNN-LSTM based framework for entity modeling and learn entity representations from their relatedness. In addition, there are usually many different instructions for the same medicine, which usually share general knowledge on this medicine. Thus, to obtain medical knowledge of medicines, we annotate relations on a randomly-sampled instruction of each medicine. Then we build knowledge embeddings to represent potential relations between entities from knowledge of medicines. Finally, we use an MLP network to predict relations between entities from their representations and knowledge embeddings. Extensive experiments on a real-world dataset show that our method can significantly outperform existing methods.

Patients' and Clinicians' Visions of a Future Internet-of-Things System to Support Asthma Self-Management: Mixed Methods Study.

BACKGROUND: Supported self-management for asthma reduces acute attacks and improves control. The internet of things could connect patients to health care providers, community services, and their living environments to provide overarching support for self-management. OBJECTIVE: We aimed to identify patients' and clinicians' preferences for a future internet-of-things system and explore their visions of its potential to support holistic self-management. METHODS: In an exploratory sequential mixed methods study, we recruited patients from volunteer databases and charities' social media. We purposively sampled participants to interview them about their vision of the design and utility of the internet of things as a future strategy for supporting self-management. Respondents who were not invited to participate in the interviews were invited to complete a web-based questionnaire to prioritize the features suggested by the interviewees. Clinicians were recruited from professional networks. Interviews were transcribed and analyzed thematically using PRISMS self-management taxonomy. RESULTS: We interviewed 12 patients and 12 clinicians in the United Kingdom, and 140 patients completed the web-based questionnaires. Patients expressed mostly wanting a system to log their asthma control status automatically; provide real-time advice to help them learn about their asthma, identify and avoid triggers, and adjust their treatment. Peak flow (33/140, 23.6%), environmental (pollen, humidity, air temperature) (33/140, 23.6%), and asthma symptoms (25/140, 17.9%) were the specific data types that patient most wanted. Information about asthma and text or email access to clinical advice provided a feeling of safety for patients. Clinicians wanted automated objective data about the patients' condition that they could access during consultations. The potential reduction in face-to-face consultations was appreciated by clinicians which they perceived could potentially save patients' travel time and health service resources. Lifestyle logs of fitness regimes or weight control were valued by some patients but were of less interest to clinicians. CONCLUSIONS: An automated internet-of-things system that requires minimal input from the user and provides timely advice in line with an asthma action plan agreed by the patient with their clinician was preferred by most respondents. Links to asthma information and the ability to connect with clinicians by text or email were perceived by patients as features that would provide a sense of safety. Further studies are needed to evaluate the usability and effectiveness of internet-of-things systems in routine clinical practice.

Factors Associated With Opting Out of Automated Text and Telephone Messages Among Adult Members of an Integrated Health Care System.

Importance: Health care systems deliver automated text or telephone messages to remind patients of appointments and to provide health information. Patients who receive multiple messages may demonstrate message fatigue by opting out of future messages. Objective: To assess whether the volume of automated text or interactive voice response (IVR) telephone messages is associated with the likelihood of patients requesting to opt out of future messages. Design, Setting, and Participants: This retrospective cohort study was conducted at Kaiser Permanente Colorado (KPCO), an integrated health care system. All adult members who received 1 or more automated text or IVR message between October 1, 2018, and September 30, 2019, were included. Exposures: Receipt of automated text or IVR messages. Main Outcomes and Measures: Message volume and opt-out rates obtained from messaging systems over 1 year. Results: Of the 428 242 adults included in this study, 59.7% were women, and 66.5% were White; the mean (SD) age was 52.3 (17.7) years. During the study period, 84.1% received 1 or more text messages (median, 4 messages; interquartile range, 2-8 messages) and 67.8% received 1 or more IVR messages (median, 3 messages; interquartile range, 1-6 messages). A total of 8929 individuals (2.5%) opted out of text messages, and 4392 (1.5%) opted out of IVR messages. In multivariable analyses, individuals who received 10 to 19.9 or 20 or more text messages per year had higher opt-out rates for text messages compared with those who received fewer than 2 messages per year (adjusted odds ratio [aOR]: 10-19.9 vs <2 messages, 1.27 [95% CI, 1.17-1.38]; ≥20 vs <2 messages, 3.58 [95% CI, 3.28-3.91]), whereas opt-out rates increased progressively in association with IVR message volume, with the highest rates among individuals who received 10.0 to 19.9 messages (aOR, 11.11; 95% CI, 9.43-13.08) or 20.0 messages or more (aOR, 49.84; 95% CI, 42.33-58.70). Individuals opting out of text messages were more likely to opt out of IVR messages (aOR, 4.07; 95% CI, 3.65-4.55), and those opting out of IVR messages were more likely to opt out of text messages (aOR, 5.92; 95% CI, 5.29-6.61). Conclusions and Relevance: In this cohort study among adult members of an integrated health care system, requests to discontinue messages were associated with greater message volume. These findings suggest that, to preserve the benefits of automated outreach, health care systems should use these messages judiciously to reduce message fatigue.

Traditional Chinese medicine symptom normalization approach leveraging hierarchical semantic information and text matching with attention mechanism.

Traditional Chinese medicine (TCM) symptom normalization is difficult because the challenges of the symptoms having different literal descriptions, one-to-many symptom descriptions and different symptoms sharing a similar literal description. We propose a novel two-step approach utilizing hierarchical semantic information that represents the functional characteristics of symptoms and develop a text matching model that integrates hierarchical semantic information with an attention mechanism to solve these problems. In this study, we constructed a symptom normalization dataset and a TCM normalization symptom dictionary containing normalization symptom words, and assigned symptoms into 24 classes of functional characteristics. First, we built a multi-label text classifier to isolate the hierarchical semantic information from each symptom description and count the corresponding normalization symptoms and filter the candidate set. Then we designed a text matching model of mixed multi-granularity language features with an attention mechanism that utilizes the hierarchical semantic information to calculate the matching score between the symptom description and the normalization symptom words. We compared our approach with other baselines on real-world data. Our approach gives the best performance with a Hit@ 1, 3, and 10 of 0.821, 0.953, and 0.993, respectively, and a MeanRank of 1.596, thus outperforming significantly regarding the symptom normalization task. We developed an approach for the TCM symptom normalization task and demonstrated its superior performance compared with other baselines, indicating the promise of this research direction.