Seizure forecasting and cyclic control of seizures.

Epilepsy is a unique neurologic condition characterized by recurrent seizures, where causes, underlying biomarkers, triggers, and patterns differ across individuals. The unpredictability of seizures can heighten fear and anxiety in people with epilepsy, making it difficult to take part in day-to-day activities. Epilepsy researchers have prioritized developing seizure prediction algorithms to combat episodic seizures for decades, but the utility and effectiveness of prediction algorithms has not been investigated thoroughly in clinical settings. In contrast, seizure forecasts, which theoretically provide the probability of a seizure at any time (as opposed to predicting the next seizure occurrence), may be more feasible. Many advances have been made over the past decade in the field of seizure forecasting, including improvements in algorithms as a result of machine learning and exploration of non-EEG-based measures of seizure susceptibility, such as physiological biomarkers, behavioral changes, environmental drivers, and cyclic seizure patterns. For example, recent work investigating periodicities in individual seizure patterns has determined that more than 90% of people have circadian rhythms in their seizures, and many also experience multiday, weekly, or longer cycles. Other potential indicators of seizure susceptibility include stress levels, heart rate, and sleep quality, all of which have the potential to be captured noninvasively over long time scales. There are many possible applications of a seizure-forecasting device, including improving quality of life for people with epilepsy, guiding treatment plans and medication titration, optimizing presurgical monitoring, and focusing scientific research. To realize this potential, it is vital to better understand the user requirements of a seizure-forecasting device, continue to advance forecasting algorithms, and design clear guidelines for prospective clinical trials of seizure forecasting.

Wearable Devices Are Well Accepted by Patients in the Study and Management of Inflammatory Bowel Disease: A Survey Study.

BACKGROUND: Wearable devices are designed to capture health-related and physiological data. They may be able to improve inflammatory bowel disease management and address evolving research needs. Little is known about patient perceptions for their use in the study and management of inflammatory bowel disease. AIMS: The aim of this survey study is to understand patient preferences and interest in wearable technology. METHODS: Consecutive adult patients who self-reported having inflammatory bowel disease were approached at the Susan and Leonard Feinstein Inflammatory Bowel Disease Center at the Mount Sinai Hospital to complete a 28-question survey. Reponses were analyzed with descriptive statistics. The Pearson Chi-square test and Fischer's exact test were used to determine the association between demographic and disease-related features and survey responses. RESULTS: Four hundred subjects completed the survey. 42.7% of subjects reported prior or current use of wearable devices. 89.0% of subjects believed that wearable devices can provide important information about their health, while 93.8% reported that they would use a wearable device if it could help their doctor manage their IBD. Subjects identified wrist-worn devices as the preferred device type and a willingness to wear these devices at least daily. CONCLUSIONS: Patients with inflammatory bowel disease believe that wearable devices can provide important information about their health and report a willingness to wear them frequently in research studies and as part the routine management of inflammatory bowel disease.

Willingness to use a wearable device capable of detecting and reversing overdose among people who use opioids in Philadelphia.

BACKGROUND: The incidence of opioid-related overdose deaths has been rising for 30 years and has been further exacerbated amidst the COVID-19 pandemic. Naloxone can reverse opioid overdose, lower death rates, and enable a transition to medication for opioid use disorder. Though current formulations for community use of naloxone have been shown to be safe and effective public health interventions, they rely on bystander presence. We sought to understand the preferences and minimum necessary conditions for wearing a device capable of sensing and reversing opioid overdose among people who regularly use opioids. METHODS: We conducted a combined cross-sectional survey and semi-structured interview at a respite center, shelter, and syringe exchange drop-in program in Philadelphia, Pennsylvania, USA, during the COVID-19 pandemic in August and September 2020. The primary aim was to explore the proportion of participants who would use a wearable device to detect and reverse overdose. Preferences regarding designs and functionalities were collected via a questionnaire with items having Likert-based response options and a semi-structured interview intended to elicit feedback on prototype designs. Independent variables included demographics, opioid use habits, and previous experience with overdose. RESULTS: A total of 97 adults with an opioid use history of at least 3 months were interviewed. A majority of survey participants (76%) reported a willingness to use a device capable of detecting an overdose and automatically administering a reversal agent upon initial survey. When reflecting on the prototype, most respondents (75.5%) reported that they would wear the device always or most of the time. Respondents indicated discreetness and comfort as important factors that increased their chance of uptake. Respondents suggested that people experiencing homelessness and those with low tolerance for opioids would be in greatest need of the device. CONCLUSIONS: The majority of people sampled with a history of opioid use in an urban setting were interested in having access to a device capable of detecting and reversing an opioid overdose. Participants emphasized privacy and comfort as the most important factors influencing their willingness to use such a device. TRIAL REGISTRATION: NCT04530591.

Seizure detection devices and health-related quality of life: A patient- and caregiver-centered evaluation.

INTRODUCTION: The unpredictability of epilepsy has a severe impact on health-related quality of life (HR-QOL) for people with epilepsy. Seizure detection devices have the potential to improve HR-QOL by improving seizure safety, reducing caregiver hypervigilance, and reducing seizure anxiety. Emerging data have led to an improved understanding of characteristics that promote acceptability of detection devices for people with epilepsy and caregivers. However, whether usage of seizure detection devices is associated with clinically meaningful improvement in anxiety and HR-QOL remains poorly understood. METHODS: We analyzed cross-sectional survey data collected first-hand from 371 people with epilepsy and caregivers on seizure detection device and HR-QOL using an enriched population of electronic seizure diary users. Metrics related to quality of life and anxiety reduction were compared between users and nonusers of seizure detection devices. RESULTS: Compared with nonusers of seizure detection devices, device users were significantly more likely to have been impacted by epilepsy in multiple HR-QOL domains, including anxiety, mood, emotional regulation/aggression, speech/language, sleep quality, social life, activities of daily living, independence, and education/academic potential. The majority (80.2%) of people using seizure detection devices experienced moderate or greater anxiety reduction from seizure detection device usage, while 11.1% reported that detection devices did not help at all with anxiety. Despite potential benefit, seizure detection devices were used only by a minority (21.8%) of people with epilepsy surveyed, and usage tended to be skewed toward younger patient age, higher income, and caregivers. There was no significant difference in overall HR-QOL between users and nonusers. CONCLUSIONS: Seizure detection devices provide moderate or greater anxiety reduction among the majority of people with epilepsy and their caregivers, but current translatability into improvements in overall HR-QOL may be limited. Affordability and technological support are potential barriers to maximizing benefit equally among the epilepsy community. These considerations may be useful to help guide future device development and inform patient-clinician discussions on device usage and HR-QOL.

Feasibility and acceptability of a novel tool for the study of interpersonal processes in psychotherapy.

Psychotherapy process research methods often require extensive time and resources. Technology innovations, such as wearable sensors, have the potential to increase the efficiency of process data collection and processing. One such tool is the Sociometric Badge (SB), which is a portable, palm-sized device that can simultaneously record raw audio and data on social signals (e.g., speech patterns, body movement) in real-time and in varied contexts. In addition to describing the nature and implications of wearable sensing devices for psychotherapy research, this article reports results from a pilot study that examined the feasibility and acceptance of these assessment devices in comparison with traditional audio recording equipment. Undergraduate students (N = 306; Mage = 19.16 years, SD = 1.44; 50.3% female) were randomly placed into 153 dyads to mimic a psychotherapy dyad. Each dyad was randomly assigned to either a SB condition (n = 75 dyads) or a standard recording device condition (n = 78 dyads), and engaged in a conversation task. Participants completed self-report items assessing perceived relationship quality and experience with the respective recording device. Between-condition tests showed that perceived relationship quality did not differ between conditions. Participants in the audio recorder (vs. SB) condition reported more awareness of the device in the room. These findings reveal comparable acceptability and feasibility of SBs to traditional audio recorders in a simulated dyad, suggesting that wearable sensing devices may be suitable for research and practice in routine psychotherapy contexts. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Social Processes: What Determines Industrial Workers' Intention to Use Exoskeletons?

OBJECTIVE: The aim of this study is to test the unified theory of acceptance and use of technology (UTAUT) model for explaining the intention to use exoskeletons among industrial workers. BACKGROUND: Exoskeletons could help reduce physical workload and risk for injuries among industrial workers. Therefore, it is crucial to understand which factors play a role in workers' intention to use such exoskeletons. METHOD: Industrial workers (N = 124) completed a survey on their attitudes regarding the use of exoskeletons at their workplace. Using partial least squares (PLS) path modeling, the UTAUT model and a revised version of the UTAUT model were fitted to these data. RESULTS: The adapted UTAUT model of Dwivedi et al. (2017) was able to explain up to 75.6% of the variance in intention to use exoskeletons, suggesting a reasonable model fit. CONCLUSION: The model fit suggests that effort expectancy (how easy it seems to use an exoskeleton) plays an important role in predicting the intention to use exoskeletons. Social influence (whether others think workers should use exoskeletons) and performance expectancy (how useful exoskeletons seem to be for work) play a smaller role in predicting the intention to use. APPLICATIONS: This research informs companies about the optimal implementation of exoskeletons by improving the determinants of acceptance among their workers.

Perceived acceptability of wearable devices for the treatment of mental health problems.

OBJECTIVE: This study examined the potential acceptability of wearable devices (e.g., smart headbands, wristbands, and watches) aimed at treating mental health disorders, relative to conventional approaches. METHODS: A questionnaire assessed perceptions of wearable and nonwearable treatments, along with demographic and psychological information. Respondents (N = 427) were adults from a community sample (Mage = 44.6, SDage = 15.3) which included current (30.2%) and former (53.9%) mental health help-seekers. RESULTS: Perceived effectiveness of wearables was a strong predictor of interest in using them as adjuncts to talk therapies, or as an alternative to self-help options (e.g., smartphone applications). Devices were more appealing to those with negative evaluations of psychological therapy and less experience in help-seeking. CONCLUSIONS: Interest in using wearable devices was strong, particularly when devices were seen as effective. Clients with negative attitudes to conventional therapies may be more responsive to using wearable devices as a less directive treatment approach.

Sensor technology implementation for research, treatment, and assessment of eating disorders.

Sensor technology has made huge technological advances in the past decade. Many sensor technologies (e.g., wearable wristbands) have been integrated into health research with the ability to substantially improve health outcomes and reduce health care costs. Despite the rapid technological developments in sensor technology, little research has examined sensor technology in eating disorders (EDs). The overarching aim of the current article is to briefly review the literature on sensor technology and health outcomes, including EDs, and discuss several potential ideas for the application of sensor technology in the treatment, assessment, and diagnosis of EDs. We will also present data from a feasibility case study with an ED participant and healthy control providing a brief example of how wearable sensor technology might be implemented in ED research. Overall, we will discuss how sensor technology could be used to improve treatment and assessment of EDs and represents an idea in need of more research in the ED field.

Feasibility of smart wristbands for continuous monitoring during pregnancy and one month after birth.

BACKGROUND: Smart wristbands enable the continuous monitoring of health parameters, for example, in maternity care. Understanding the feasibility and acceptability of these devices in an authentic context is essential. The aim of this study was to evaluate the feasibility of using a smart wristband to collect continuous activity, sleep and heart rate data from the beginning of the second trimester until one month postpartum. METHODS: The feasibility of a smart wristband was tested prospectively through pregnancy in nulliparous women (n = 20). The outcomes measured were the wear time of the device and the participants' experiences with the smart wristband. The data were collected from the wristbands, phone interviews, questionnaires, and electronic patient records. The quantitative data were analyzed with hierarchical linear mixed models for repeated measures, and qualitative data were analyzed using content analysis. RESULTS: Participants (n = 20) were recruited at a median of 12.9 weeks of gestation. They used the smart wristbands for an average of 182 days during the seven-month study period. The daily use of the devices was similar during the second (17.9 h, 95% CI 15.2 to 20.7) and third trimesters (16.7 h, 95% CI 13.8 to 19.5) but decreased during the postpartum period (14.4 h, 95% CI 11.4 to 17.4, p = 0.0079). Participants who could not wear smart wristbands at work used the device 300 min less per day than did those with no use limitations. Eight of the participants did not wear the devices or wore them only occasionally after giving birth. Nineteen participants reported that the smart wristband did not have any permanent effects on their behavior. Problems with charging and synchronizing the devices, perceiving the devices as uncomfortable, or viewing the data as unreliable, and the fear of scratching their babies with the devices were the main reasons for not using the smart wristbands. CONCLUSIONS: A smart wristband is a feasible tool for continuous monitoring during pregnancy. However, the daily use decreased after birth. The results of this study may support the planning of future studies and help with overcoming barriers related to the use of smart wristbands on pregnant women.

Using Digital Phenotyping to Accurately Detect Depression Severity.

Development of digital biomarkers holds promise for enabling scalable, time-sensitive, and cost-effective strategies to monitor symptom severity among those with major depressive disorder (MDD). The current study examined the use of passive movement and light data from wearable devices to assess depression severity in 15 patients with MDD. Using over 1 week of movement data, we were able to significantly assess depression severity with high precision for self-reported (r = 0.855; 95% confidence interval [CI], 0.610-0.950; p = 4.95 × 10) and clinician-rated (r = 0.604; 95% CI, 0.133-0.894; p = 0.017) symptom severity. Pending replication, the present data suggest that the use of passive wearable sensors to inform healthcare decisions holds considerable promise.

Acceptability of a lifelogging wearable camera in older adults with mild cognitive impairment: a mixed-method study.

BACKGROUND: The main objective of this research was to evaluate the acceptance of technology based on a wearable lifelogging camera in a sample of older adults diagnosed with mild cognitive impairment (MCI). METHODS: A mixed-method design was used, consisting of a self-report questionnaire, numerous images taken by users, and a series of focus group discussions. The patients were involved in an individualized training programme. RESULTS: Nine MCI patients and their caregiver relatives were included. They showed good acceptance of the camera and downloaded an appropriate number of images on a daily basis. Perceived severity and ease of use were the main factors associated with the intention to use the device. CONCLUSIONS: Older adults with MCI can become competent users of lifelogging wearable cameras with a good level of acceptance. Privacy concerns are outweighed by the potential benefits for memory. Limitations, strengths and implications for future research are discussed.

Willingness to adopt wearable devices with behavioral and economic incentives by health insurance wellness programs: results of a US cross-sectional survey with multiple consumer health vignettes.

BACKGROUND: The number of health-related wearable devices is growing but it is not clear if Americans are willing to adopt health insurance wellness programs based on wearables and the incentives with which they would be more willing to adopt. METHODS: In this cross-sectional study we used a survey methodology, usage vignettes and a dichotomous scale to examine U.S. residents' willingness to adopt wearables (WTAW) in six use-cases where it was mandatory to use a wearable device and share the resulting data with a health insurance company. Each use-case was tested also for the influence of additional economic incentives on WTAW. RESULTS: A total of 997 Americans across 46 states participated in the study. Most of them were 25 to 34 years old (40.22%), 57.27% were female, and 74.52% were white. On average, 69.5% of the respondents were willing to adopt health-insurance use-cases based on wearable devices, though 77.8% of them were concerned about issues related to economic benefits, data privacy and to a lesser extent, technological accuracy. WTAW was 11-18% higher among consumers in use-cases involving health promotion and disease prevention. Furthermore, additional economic incentives combined with wearables increased WTAW overall. Notably, financial incentives involving providing healthcare credits, insurance premium discount, and/or wellness product discounts had particularly greater effectiveness for increasing WTAW in the consumer use-cases involving participation: for health promotion (RR = 1.06 for financial incentive, 95% CI: 1.01-1.11; P = 0.018); for personalized products and services (RR = 1.11 for financial incentive, 95% CI: 1.01-1.21; P = 0.018); and for automated underwriting discount at annual renewal (RR = 1.28 for financial incentive, 95% CI: 1.20-1.37; P < 0.001). CONCLUSIONS: Under the adequate economic, data privacy and technical conditions, 2 out of 3 Americans would be willing to adopt health insurance wellness programs based on wearable devices, particularly if they have benefits related to health promotion and disease prevention, and particularly with financial incentives.

Making sense with numbers. Unravelling ethico-psychological subjects in practices of self-quantification.

Prevention enthusiasts show great optimism about the potential of health apps to modify peoples' lifestyles through the tracking and quantification of behaviours and bodily signs. Critical sociologists warn for the disciplining effects of self-tracking. In this paper we use an empirical ethics approach to study the characteristics and strivings of the various types of 'ethico-psychological subjects' that emerge in practices of self-quantification by analysing how people and numbers relate in three cases of self-quantification: in prevention discourse, in testimonies from the quantified self (QS) movement and in empirical work we did with people with Diabetes type I and with 'every day self-trackers'. We show that a free subject that needs support to enact its will is crucial to understand the optimism about prevention. In the QS-movement the concern is with a lack of objective and personalised knowledge about imperceptible processes in the body. These subjects are decentered and multiplied when we trace how numbers in their turn act to make sense of people in our empirical study. We conclude that there are many different types of ethico-psychological subjects in practices of self-tracking that need to be explored in order to establish what good these practices of self-quantification might do.

Patient acceptability of wearable vital sign monitoring technologies in the acute care setting: A systematic review.

AIMS AND OBJECTIVES: To examine patient acceptability of wearable vital sign monitoring devices in the acute setting. BACKGROUND: Wearable vital sign monitoring devices may improve patient safety, yet hospital patients' acceptability of these devices is largely unreported. DESIGN: A systematic review. METHODS: Cumulative Index to Nursing and Allied Health Literature Complete, MEDLINE Complete and EMBASE were searched, supplemented by reference list hand searching. Studies were included if they involved adult hospital patients (≥18 years), a wearable monitoring device capable of assessing ≥1 vital sign, and measured patient acceptability, satisfaction or experience of wearing the device. No date restrictions were enforced. Quality assessments of quantitative and qualitative studies were undertaken using the Downs and Black Checklist for Measuring Study Quality and the Critical Appraisal Skills Programme Qualitative Research Checklist, respectively. Meta-analyses were not possible given data heterogeneity and low research quality. Reporting adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and a Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was completed. RESULTS: Of the 427 studies screened, seven observational studies met the inclusion criteria. Six studies were of low quality and one was of high quality. In two studies, patient satisfaction was investigated. In the remaining studies, patient experience, patient opinions and experience, patient perceptions and experience, device acceptability, and patient comfort and concerns were investigated. In four studies, patients were mostly accepting of the wearable devices, reporting positive experiences and satisfaction relating to their use. In three studies, findings were mixed. CONCLUSION: There is limited high-quality research examining patient acceptability of wearable vital sign monitoring devices as an a priori focus in the acute setting. Further understanding of patient perspectives of these devices is required to inform their continued use and development. RELEVANCE TO CLINICAL PRACTICE: The provision of patient-centred nursing care is contingent on understanding patients' preferences, including their acceptability of technology use.

Sham sleep feedback delivered via actigraphy biases daytime symptom reports in people with insomnia: Implications for insomnia disorder and wearable devices.

This study investigated whether providing sham feedback about sleep to individuals with insomnia influenced daytime symptom reports, sleep-related attentional bias and psychomotor vigilance. Sixty-three participants meeting DSM-5 criteria for insomnia disorder were recruited from the community. Following baseline assessments and actigraphy briefing, participants were randomised to receive next-day sham feedback on sleep quality ("positive" vs. "negative" sleep efficiency condition). Feedback was delivered at habitual rise-time using an integrated actigraphy-diary watch to simulate wearable device behaviour. Participants completed symptom reports immediately before receiving feedback, and at 12:00 and 15:00 hr, using the experience sampling method. Following this they returned to the laboratory in the evening to complete symptom reports and computerised tests of sleep-related attentional bias and basic psychomotor vigilance. Participants randomised to negative feedback (n = 32) evidenced impaired daytime function (decreased alert cognition [d = 0.79], increased sleepiness/fatigue [d = 0.55]) in the evening compared with those given positive feedback (n = 31). Within-day trajectories revealed that the positive-feedback group, relative to the negative-feedback group, displayed a significantly greater increase in positive mood and alert cognition (from rise-time to 12:00 hr), and significantly greater decrease in sleepiness/fatigue. There were no significant between-group differences on measures of sleep-related attentional bias [d = 0.20] or psychomotor vigilance [d = 0.12]. This controlled experiment shows that sham feedback about sleep biases appraisal of daytime symptoms, highlighting a pathway connecting sleep misperception with daytime features of insomnia. Findings have important implications for wearable devices that claim to measure "objective" sleep yet may provide inaccurate data relative to gold-standard measurement.

Accuracy, satisfaction and usability of a flash glucose monitoring system among children and adolescents with type 1 diabetes attending a summer camp.

BACKGROUND: The study aimed to assess accuracy, satisfaction and usability of a flash glucose monitoring system (FGM) in children and adolescents with type 1 diabetes mellitus (T1DM) attending a diabetes summer camp. METHODS: Sixty-six children and adolescents with T1DM aged 6 to 17 years participating in a 7-day medically supervised summer camp were enrolled. Capillary blood glucose (BG) and flash glucose (FG) values were measured simultaneously at breakfast, lunch, and dinner and for any given FG value <72 mg/dL (<4.0 mmol/L) during daytime, <108 mg/dL (<6.0 mmol/L) at nighttime, >270 mg/dL (>15.0 mmol/L) or when patient symptoms were discordant with sensor readings. Sensor-related issues were documented and patients' and healthcare professionals' (HCPs) satisfaction was evaluated. RESULTS: FGM demonstrated satisfactory clinical accuracy compared to reference capillary BG values with 98.8% of values falling within the clinically acceptable zones (A and B) of the consensus error grid. Overall mean absolute relative difference (MARD) was 16.7% ± 16.1%. Specific calculations of mean absolute difference (MAD), mean relative difference (MRD), and mean difference (MD) demonstrated that FGM overestimated BG values across all glycemic ranges. Overall satisfaction with the FGM was high in 91.7% participants and 95.0% HCPs, although confidence in the system was low in 18.0% participants and 40.0% HCPs. CONCLUSIONS: The FGM exhibited satisfactory clinical accuracy. However, based on the present data, we conclude that no decision should be taken on the basis of a single, non-verified, FGM value alone. Our study highlights the need for revised therapeutic education for patients/families and further investigation on the integration of sensor readings in clinical decision-making.

Wearable technology in epilepsy: The views of patients, caregivers, and healthcare professionals.

PURPOSE: In recent years, digital technology and wearable devices applied to seizure detection have progressively become available. In this study, we investigated the perspectives of people with epilepsy (PWE), caregivers (CG), and healthcare professionals (HP). We were interested in their current use of digital technology as well as their willingness to use wearables to monitor seizures. We also explored the role of factors influencing engagement with technology, including demographic and clinical characteristics, data confidentiality, need for technical support, and concerns about strain or increased workload. METHODS: An online survey drawing on previous data collected via focus groups was constructed and distributed via a web link. Using logistic regression analyses, demographic, clinical, and other factors identified to influence engagement with technology were correlated with reported use and willingness to use digital technology and wearables for seizure tracking. RESULTS: Eighty-seven surveys were completed, fifty-two (59.7%) by PWE, 13 (14.4%) by CG, and 22 (25.3%) by HP. Responders were familiar with multiple digital technologies, including the Internet, smartphones, and personal computers, and the use of digital services was similar to the UK average. Moreover, age and disease-related factors did not influence access to digital technology. The majority of PWE were willing to use a wearable device for long-term seizure tracking. However, only a limited number of PWE reported current regular use of wearables, and nonusers attributed their choice to uncertainty about the usefulness of this technology in epilepsy care. People with epilepsy envisaged the possibility of understanding their condition better through wearables and considered, with caution, the option to send automatic emergency calls. Despite concerns around accuracy, data confidentiality, and technical support, these factors did not limit PWE's willingness to use digital technology. Caregivers appeared willing to provide support to PWE using wearables and perceived a reduction of their workload and anxiety. Healthcare professionals identified areas of application for digital technologies in their clinical practice, pending an appropriate reorganization of the clinical team to share the burden of data reviewing and handling. CONCLUSIONS: Unlike people who have other chronic health conditions, PWE appeared not to be at risk of digital exclusion. This study highlighted a great interest in the use of wearable technology across epilepsy service users, carers, and healthcare professionals, which was independent of demographic and clinical factors and outpaced data security and technology usability concerns.

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study.

BACKGROUND: Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being. OBJECTIVE: We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions. METHODS: We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures. RESULTS: We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification. CONCLUSIONS: New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping.

Using Wearables to Study Biopsychosocial Dynamics in Couples Who Cope With a Chronic Health Condition: Ambulatory Assessment Study.

BACKGROUND: Technology has become an integral part of our everyday life, and its use to manage and study health is no exception. Romantic partners play a critical role in managing chronic health conditions as they tend to be a primary source of support. OBJECTIVE: This study tests the feasibility of using commercial wearables to monitor couples' unique way of communicating and supporting each other and documents the physiological correlates of interpersonal dynamics (ie, heart rate linkage). METHODS: We analyzed 617 audio recordings of 5-minute duration (384 with concurrent heart rate data) and 527 brief self-reports collected from 11 couples in which 1 partner had type II diabetes during the course of their typical daily lives. Audio data were coded by trained raters for social support. The extent to which heart rate fluctuations were linked among couples was quantified using cross-correlations. Random-intercept multilevel models explored whether cross-correlations might differ by social contexts and exchanges. RESULTS: Sixty percent of audio recordings captured speech between partners and partners reported personal contact with each other in 75% of self-reports. Based on the coding, social support was found in 6% of recordings, whereas at least 1 partner self-reported social support about half the time (53%). Couples, on average, showed small to moderate interconnections in their heart rate fluctuations (r=0.04-0.22). Couples also varied in the extent to which there was lagged linkage, that is, meaning that changes in one partner's heart rate tended to precede changes in the other partner's heart rate. Exploratory analyses showed that heart rate linkage was stronger (1) in rater-coded partner conversations (vs moments of no rater-coded partner conversations: rdiff=0.13; P=.03), (2) when partners self-reported interpersonal contact (vs moments of no self-reported interpersonal contact: rdiff=0.20; P<.001), and (3) when partners self-reported social support exchanges (vs moments of no self-reported social support exchange: rdiff=0.15; P=.004). CONCLUSIONS: Our study provides initial evidence for the utility of using wearables to collect biopsychosocial data in couples managing a chronic health condition in daily life. Specifically, heart rate linkage might play a role in fostering chronic disease management as a couple. Insights from collecting such data could inform future technology interventions to promote healthy lifestyle engagement and adaptive chronic disease management. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13685.