https://mhealth.jmir.org/issue/feed 2024-01-05T10:15:04-05:00 JMIR Publications editor@jmir.org Open Journal Systems Unless stated otherwise, all articles are open-access distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work ("first published in JMIR mHealth and uHealth...") is properly cited with original URL and bibliographic citation information. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. JMIR mhealth and uhealth is a new journal focussing on mobile and ubiquitous health technologies, including smartphones, augmented reality (Google Glasses), intelligent domestic devices, implantable devices, and other technologies designed to maintain health and improve life. https://mhealth.jmir.org/2025/1/e59660/ 2025-03-06T14:30:04-05:00 Simon Woll Dennis Birkenmaier Gergely Biri Rebecca Nissen Luisa Lutz Marc Schroth Ulrich W Ebner-Priemer Marco Giurgiu

<strong>Background:</strong> Wearable technology is used by consumers worldwide for continuous activity monitoring in daily life but more recently also for classifying or predicting mental health parameters like stress or depression levels. Previous studies identified, based on traditional approaches, that physical activity is a relevant factor in the prevention or management of mental health. However, upcoming artificial intelligence methods have not yet been fully established in the research field of physical activity and mental health. <strong>Objective:</strong> This systematic review aims to provide a comprehensive overview of studies that integrated passive monitoring of physical activity data measured via wearable technology in machine learning algorithms for the detection, prediction, or classification of mental health states and traits. <strong>Methods:</strong> We conducted a review of studies processing wearable data to gain insights into mental health parameters. Eligibility criteria were (1) the study uses wearables or smartphones to acquire physical behavior and optionally other sensor measurement data, (2) the study must use machine learning to process the acquired data, and (3) the study had to be published in a peer-reviewed English language journal. Studies were identified via a systematic search in 5 electronic databases. <strong>Results:</strong> Of 11,057 unique search results, 49 published papers between 2016 and 2023 were included. Most studies examined the connection between wearable sensor data and stress (n=15, 31%) or depression (n=14, 29%). In total, 71% (n=35) of the studies had less than 100 participants, and 47% (n=23) had less than 14 days of data recording. More than half of the studies (n=27, 55%) used step count as movement measurement, and 44% (n=21) used raw accelerometer values. The quality of the studies was assessed, scoring between 0 and 18 points in 9 categories (maximum 2 points per category). On average, studies were rated 6.47 (SD 3.1) points. <strong>Conclusions:</strong> The use of wearable technology for the detection, prediction, or classification of mental health states and traits is promising and offers a variety of applications across different settings and target groups. However, based on the current state of literature, the application of artificial intelligence cannot realize its full potential mostly due to a lack of methodological shortcomings and data availability. Future research endeavors may focus on the following suggestions to improve the quality of new applications in this context: first, by using raw data instead of already preprocessed data. Second, by using only relevant data based on empirical evidence. In particular, crafting optimal feature sets rather than using many individual detached features and consultation with in-field professionals. Third, by validating and replicating the existing approaches (ie, applying the model to unseen data). Fourth, depending on the research aim (ie, generalization vs personalization) maximizing the sample size or the duration over which data are collected.

2025-03-06T14:30:04-05:00 https://mhealth.jmir.org/2025/1/e63805/ 2025-03-06T11:15:04-05:00 Xiaorong Jin Yimei Zhang Min Zhou Qian Mei Yangjuan Bai Qiulan Hu Wei Wei Xiong Zhang Fang Ma

Background: Chronic heart failure has become a serious threat to the health of the global population. Self-management is the key to treating chronic heart failure, and the emergence of mHealth has provided new ideas for self-management of chronic heart failure. Despite the many potential benefits of mHealth, public utilization of mHealth apps is low, and poor health literacy is a key barrier to mHealth use. However, the mechanism of the influence is unclear. Objective: To explore the dyadic associations between health literacy and mHealth usage intentions in dyads of patients with chronic heart failure and their caregivers, and the mediating role of mHealth perceived usefulness and perceived ease of use in these associations. Methods: This study was a cross-sectional research design, with a sample of 312 dyads of chronic heart failure patients and their caregivers who had been hospitalized in the cardiology departments of two tertiary care hospitals in China from March to October 2023. A general information questionnaire, the Chinese version of the Heart Failure-Specific Health Literacy Scale, and the mHealth Intention to Use Scale were used to conduct the survey; the data were analyzed using the actor-partner interdependence mediation model. Results: The results of the actor-partner interdependent mediation analysis of health literacy, perceived usefulness of mHealth, and mHealth use intention among patients with chronic heart failure and their caregivers showed that all of the model's actor effects were valid (β = 0.26-0.45, P < 0.001), the partner effects were partially valid (β = 0.08-0.20, P < 0.05), and the mediation effects were valid (β = 0.002-0.242, the 95% CI = 0.003-0.321, P < 0.05); actor-partner interdependent mediation analyses of health literacy, perceived ease of use of mHealth, and mHealth use intention among patients and caregivers with chronic heart failure showed that the model's actor effect partially held (β = 0.17-0.71, P < 0.01), and the partner effect partially held (β = 0.15, P < 0.01), the mediation effect partially held (β = 0.355-0.584, 95% CI = 0.234-0.764, P < 0.001). Conclusions: Our study proposes that the health literacy of patients with chronic heart failure and their caregivers positively contributes to their own intention to use mHealth, suggesting that the use of mHealth by patients with chronic heart failure can be promoted by improving the health literacy of patients and caregivers as well. Our findings also suggest that the perceived usefulness of patients with chronic heart failure and caregivers affects patients' mHealth use intention, and therefore chronic heart failure patients and their caregivers should be involved throughout the mHealth development process to improve the usability of mHealth for both patients and caregivers. This study emphasizes the key role of chronic heart failure patients' perception that mHealth is easy to use in facilitating their use of mHealth. Therefore, it is recommended that the development of mHealth should focus on simplifying the operational procedures and providing relevant operational training according to the needs of the patients when necessary.

2025-03-06T11:15:04-05:00 https://mhealth.jmir.org/2025/1/e60811/ 2025-03-03T11:00:07-05:00 Mara Anna Franke Anne Neumann Kim Nordmann Daniela Suleymanova Onja Gabrielle Ravololohanitra Julius Valentin Emmrich Samuel Knauss

Background: Mobile money-based cash transfer interventions are becoming increasingly utilised, especially in humanitarian settings. The South of Madagascar constituted a humanitarian emergency in 2021/2022 when the second wave of the COVID-19 pandemic and a severe famine affected the fragile region simultaneously. Objective: This mixed-methods study aims to analyse the impact and factors influencing the success of a mobile-money-based conditional cash transfer intervention for healthcare utilisation at four primary and eleven secondary facilities in Madagascar. Methods: We drew on quantitative data from eleven facility registers, detailing patient numbers per month, divided by categories (maternity care, surgical care, paediatric care, outpatient care, and inpatient care). We conducted an interrupted time series analysis, without a control group, using the end of the intervention in July 2022 as the cut-off point. For qualitative data, we drew on data from 63 in-depth interviews conducted with healthcare providers, NGO staff, policymakers beneficiaries, and non-beneficiaries of the intervention, interpreted by four different researchers using reflexive thematic analysis. For the qualitative component, we conducted 63 in-depth interviews with healthcare providers, NGO staff, policymakers, beneficiaries, and non-beneficiaries, analysed by four independent researchers through reflexive thematic analysis to identify facilitators and barriers to implementation. Results: The interrupted time series analysis showed a significant, negative impact of the end of the intervention on healthcare utilisation, indicating a reduction in healthcare seeking after the end of the cash transfer intervention. The effect was stronger on the slope change of patient numbers per month, which significantly decreased in 39 out of 55 (70%) of models (P-value <.05) compared to the step change at the end of the intervention, which only showed a significant change (P-value <.05) in 40% (22/55) of models. The changes were most pronounced for surgical and paediatric care. The key factors that influenced the success of the implementation were grouped across three levels. At the community level, outreach conducted to inform potential beneficiaries about the project by community health workers and the radio was a decisive success factor. At participating facilities, high intrinsic staff motivation and high digital literacy of facility staff positively influenced the intervention. Confusion about previous activities of the same implementing NGO and a perception that the bonus payments for healthcare providers included in the project were unfair negatively affected the intervention. Lastly, on the side of the implementing NGO, the NGO staff present at each facility and the speed and ease of the intervention’s administrative processes emerged as decisive factors that influenced the intervention. Conclusions: The conditional cash transfer intervention was overarchingly successful in increasing healthcare utilisation in Southern Madagascar in a humanitarian setting. However, this success was conditional on key implementation factors at the community, facility, and NGO level. Future, similar interventions should proactively consider the key factors identified.

2025-03-03T11:00:07-05:00 https://mhealth.jmir.org/2025/1/e60115/ 2025-02-25T16:00:26-05:00 Guangqi Li Xueyan Zhou Junyue Deng Jiao Wang Ping Ai Jingyuan Zeng Xuelei Ma Hu Liao

<strong>Background:</strong> Lung cancer ranks as the leading cause of cancer-related deaths. For lung cancer survivors, cardiopulmonary fitness is a strong independent predictor of survival, while surgical interventions impact both cardiovascular and pulmonary function. Home-based cardiac telerehabilitation through wearable devices and mobile apps is a substitution for traditional, center-based rehabilitation with equal efficacy and a higher completion rate. However, it has not been widely used in clinical practice. <strong>Objective:</strong> The objective of this study was to broaden the use of digital health care in the cardiopulmonary rehabilitation of lung cancer survivors and to assess its impact on cardiopulmonary fitness and quality of life (QOL). <strong>Methods:</strong> Early-stage nonsmall cell lung cancer survivors aged 18-70 years were included. All the participants received surgery 1-2 months before enrollment and did not require further antitumor therapy. Participants were randomly assigned to receive cardiac telerehabilitation or usual care for 5 months. Artificial intelligence–driven exercise prescription with a video guide and real-time heart rate (HR) monitoring was generated based on cardiopulmonary exercise testing. Aerobic exercise combining elastic band–based resistance exercises were recommended with a frequency of 3-5 d/wk and a duration of 90-150 min/wk. The effective exercise duration was recorded when patients’ HR reached the target zone (HR_resting + [HR_max – HR_resting] × [≈40%-60%]), representing the duration under the target intensity. The prescription used a gradual progression in duration and action intensity based on the exercise data and feedback. Outcome measurements included cardiopulmonary fitness; lung function; cardiac function; tumor marker; safety; compliance; and scales assessing symptoms, psychology, sleep, fatigue, and QOL. <strong>Results:</strong> A total of 40 (85%) out of 47 patients finished the trial. The average prescription compliance rate of patients in the telerehabilitation group reached 101.2%, with an average exercise duration of 151.4 min/wk and an average effective exercise duration of 92.3 min/wk. The cardiac telerehabilitation was associated with higher improvement of maximal oxygen uptake peak (3.66, SD 3.23 mL/Kg/min vs 1.09, SD 3.23 mL/Kg/min; <i>P=.</i>02) and global health status or QOL (16.25, SD 23.02 vs 1.04, SD 13.90; <i>P=.</i>03) compared with usual care. Better alleviation of affective interference (–0.88, SD 1.50 vs 0.21, SD 1.22; <i>P=.</i>048), fatigue (–8.89, SD 15.96 vs 1.39, SD 12.09; <i>P=.</i>02), anxiety (–0.31, SD 0.44 vs –0.05, SD 0.29; <i>P=.</i>048), and daytime dysfunction (–0.55, SD 0.69 vs 0.00, SD 0.52; <i>P=.</i>02) was also observed in the telerehabilitation group. No exercise-related adverse events were identified during the intervention period. <strong>Conclusions:</strong> The 5-month, digital therapeutics–based telerehabilitation improved cardiorespiratory fitness in lung cancer survivors with good compliance and safety. Patients receiving telerehabilitation also reported improved QOL with reduced levels of fatigue, anxiety, and daytime dysfunction. <strong>Trial Registration:</strong> Chinese Clinical Trial Registry ChiCTR2200064000; https://www.chictr.org.cn/showproj.html?proj=180594

2025-02-25T16:00:26-05:00 https://mhealth.jmir.org/2025/1/e64527/ 2025-02-25T14:45:04-05:00 Kyung-In Joung Sook Hee An Joon Seok Bang Kwang Joon Kim

Background: Mobile health technologies show promise in addressing metabolic syndrome, but their comparative effectiveness in large-scale public health interventions remains unclear. Objective: To compare the effectiveness of wearable devices (wearable activity tracker) and mobile app-based activity trackers (built-in step counters) in promoting walking practice, improving health behaviors, and reducing metabolic syndrome risk within a national mobile healthcare program operated by the Korea Health Promotion Institute (KHPI). Methods: This retrospective cohort study analyzed data from 46,579 participants in South Korea's national mobile healthcare program (2020-2022). Participants used wearable devices for 12 weeks, after which some switched to built-in step counters. Outcomes included changes in walking practice, health behaviors, and metabolic syndrome risk factors. Multivariate logistic regression and propensity score matching were used to assess the association between device type and outcomes. Results: Both device types showed substantial improvements across all indicators. After full adjustment, wearable devices showed a non-significant advantage in promoting walking practice (OR 0.83, 95% CI 0.66-1.06). No significant differences were found in overall health behavior improvements (OR 0.94, 95% CI 0.84-1.04). Notably, built-in step counter users demonstrated greater reductions in metabolic syndrome risk (OR 1.15, 95% CI 1.03-1.30). Age-specific subgroup analyses revealed that the association between built-in step counters and metabolic syndrome risk reduction was more pronounced in young adults (OR 1.21, 95% CI 1.01-1.45). Conclusions: Both wearable devices and built-in step counters effectively reduced metabolic syndrome risk in a large-scale public health intervention. The findings suggest that personalized device recommendations based on individual characteristics may enhance the effectiveness of mobile health interventions.

2025-02-25T14:45:04-05:00 https://mhealth.jmir.org/2025/1/e56533/ 2025-02-12T13:45:04-05:00 Abigail R Smith Elizabeth R Mueller Cora E Lewis Alayne Markland Caroline Smerdon Ariana L Smith Siobhan Sutcliffe Jean F Wyman Lisa Kane Low Janis M Miller The Prevention of Lower Urinary Tract Symptoms (PLUS) Research C

Background: Little is known about women’s decisions around toileting for urination and how those decisions influence moment-to-moment behaviors to manage bladder needs. The new smartphone application Where I Go captures such nuanced and granular data in real-world environments. Objective: Describe participant engagement with Where I Go, variation in novel parameters collected, and readiness for the data collection tool’s use in population-based studies. Methods: Where I Go has three components: a) real-time, b) short look-back periods (3-4 hours), and c) event location (GPS recorded at each interaction). Sample size was forty-four women. Recording of real-time toileting events and responding to look-back questions was measured over 2-days of data collection. The participant’s self-entered location descriptions and the automatic GPS recordings were compared. Results: Forty-four women with an average age of 44 years interacted with the application.: Real-time reporting of at least one toileting event per day was high (38/44 [86%] day 1, 40/44 [91%] day 2) with median of 5 toileting events recorded each day. Toileting most commonly occurred at home (85/140 [61%] day 1, 129/171 [75%] day 2) due to a need to go (114/140 [66%] day 1, 153/171 [74%] day 2). The most common reasons for delaying toileting were “work duties” (33/140 [21%] day 1, 21/171 [11%] day 2) and “errands or traveling” (19/140 [12%] day 1, 19/171 [10%] day 2). Response to at least one look-back notification was similarly high (41/44 [93%] day 1, 42/44 [95%] day 2), with number of responses higher on average on day 2 compared to day 1 (mean day 1=3.2, mean day 2=4.3, P<.001). Median additional toileting events reported on the look-back survey was one and two on days 1 and 2, respectively. Overall concordance between self-reported location recording and GPS was 76% (188/247). Participants reported lower urge ratings when at home versus away when reporting real time toileting (median rating 61 vs. 72), and daily fluid intake showed small to medium positive correlation with toileting frequency (day 1 r=0.3, day 2 r=0.24). Toileting frequency reported in Where I Go showed small positive correlation with the frequency item from the International Consultation on Incontinence Questionnaire (ICIQ) (r=0.31 with day 1 toileting frequency and r=0.21 with day 2 toileting frequency). Conclusions: Where I Go has potential to increase understanding of factors that affect women’s toileting decisions and potentially long-term bladder health. We anticipate its use as a data collection tool in population-based studies. Clinical Trial: Not applicable.

2025-02-12T13:45:04-05:00 https://mhealth.jmir.org/2025/1/e51271/ 2025-02-11T16:00:08-05:00 Robin De Croon Daniela Segovia-Lizano Paul Finglas Vero Vanden Abeele Katrien Verbert

Background: User acceptance and trust play a critical role in decision-making, particularly in domains such as personalized nutrition. This paper investigates the design and implementation of a food recommender system and explanation interfaces that provide insights into individualized food recommendations. Objective: The objective of this study is to examine the significance of user acceptance and trust in supporting decision-making and explore the effectiveness of explaining food recommendations in a retail-controlled service environment. Methods: A mixed method, user-centered design approach was employed, involving 26 participants and expert feedback from 2 professional dietitians. The proof-of-concepts were tested through deployments at 2 large companies with 45 and 16 participants, respectively. An updated demonstrator was deployed at a third large company over a 7-week study duration with 136 participants. Results: Despite a mismatch between participants’ food preferences and their individual healthy recommendations, the mobile application successfully explained the reasons behind the recommended meals with clear and adequate explanations. This explanation process led to an increase in trust in the recommendations. The paper discusses the design goals of the food recommender system, the challenges faced during real-life deployment in a retail-controlled service environment, and provides reflections for future food recommender systems. Conclusions: The study highlights the importance of explaining food recommendations in fostering user trust, even when there is a discrepancy between user preferences and healthy recommendations. The system effectively provided clear and adequate explanations, resulting in increased trust in the recommendations. The paper also discusses design goals, deployment challenges, and offers recommendations for future food recommender systems.

2025-02-11T16:00:08-05:00 https://mhealth.jmir.org/2025/1/e52887/ 2025-02-11T13:00:25-05:00 Shirlene Wang Chih-Hsiang Yang Denver Brown Alan Cheng Matthew Y W Kwan

Background: Adolescence through emerging adulthood represents a critical period associated with changes in lifestyle behaviors. Understanding the dynamic relationships between cognitive, social, and environmental contexts is informative for the development of interventions aiming to help youth sustain physical activity and limit sedentary time during this life stage. Ecological momentary assessment (EMA) is an innovative method involving real-time assessment of individuals’ experiences and behaviors in their naturalistic or everyday environments; however, EMA compliance can be problematic due to high participant burdens. Objective: This systematic review synthesized existing evidence pertaining to compliance in EMA studies that investigated wake-time movement behaviors among adolescent and emerging adult populations. Differences in EMA delivery scheme or protocol, EMA platforms, prompting schedules, and compensation methods—all of which can affect participant compliance and overall study quality—were examined. Methods: An electronic literature search was conducted in PubMed, PsycINFO, and Web of Science databases to select relevant papers that assessed movement behaviors among the population using EMA and reported compliance information for inclusion (n=52) in October 2022. Study quality was assessed using a modified version of the Checklist for Reporting of EMA Studies (CREMAS). Results: Synthesizing the existing evidence revealed several factors that influence compliance. The platform used for EMA studies could affect compliance and data quality in that studies using smartphones or apps might lessen additional burdens associated with delivering EMAs, yet most studies used web-based formats (n=18, 35%). Study length was not found to affect EMA compliance rates, but the timing and frequency of prompts may be critical factors associated with missingness. For example, studies that only prompted participants once per day had higher compliance (91% vs 77%), but more frequent prompts provided more comprehensive data for researchers at the expense of increased participant burden. Similarly, studies with frequent prompting within the day may provide more representative data but may also be perceived as more burdensome and result in lower compliance. Compensation type did not significantly affect compliance, but additional motivational strategies could be applied to encourage participant response. Conclusions: Ultimately, researchers should consider the best strategies to limit burdens, balanced against requirements to answer the research question or phenomena being studied. Findings also highlight the need for greater consistency in reporting and more specificity when explaining procedures to understand how EMA compliance could be optimized in studies examining physical activity and sedentary time among youth. Clinical Trial: PROSPERO CRD42021282093; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=282093

2025-02-11T13:00:25-05:00 https://mhealth.jmir.org/2025/1/e55298/ 2025-02-10T16:00:05-05:00 Sara Fatima Faqar Uz Zaman Svenja Sliwinski Lisa Mohr-Wetzel Julia Dreilich Natalie Filmann Charlotte Detemble Dora Zmuc Felix Chun Wojciech Derwich Waldemar Schreiner Wolf Bechstein Johannes Fleckenstein Andreas A Schnitzbauer

<strong>Background:</strong> Major surgery is associated with significant morbidity and a reduced quality of life, particularly among older adults and individuals with frailty and impaired functional capacity. Multimodal prehabilitation can enhance functional recovery after surgery and reduce postoperative complications. Digital prehabilitation has the potential to be a resource-sparing and patient-empowering tool that improves patients’ preoperative status; however, little remains known regarding their safety and accuracy as medical devices. <strong>Objective:</strong> This study aims to test the accuracy and validity of a new software in comparison to the gold-standard electrocardiogram (ECG)-based heart rate measurement. <strong>Methods:</strong> The PROTEGO MAXIMA trial was a prospective interventional pilot trial assessing the validity, accuracy, and safety of an app-based exercise program. The Prehab App calculates a personalized, risk-stratified aerobic interval training plan based on individual risk factors and utilizes wearables to monitor heart rate. Healthy students and patients undergoing major surgery were enrolled. A structured risk assessment was conducted, followed by a 6-minute walking test and a 37-minute supervised interval session. During the exercise, patients wore app-linked wearables for heart rate and distance measurements, which were compared with standard ECG and treadmill measurements. Safety, accuracy, and usability assessments included testing alarm signals, while the occurrence of adverse events served as the primary and secondary outcome measures. <strong>Results:</strong> A total of 75 participants were included. The mean heart rate differences between wearables and standard ECG were ≤5 bpm (beats per minute) with a mean absolute percentage error of ≤5%. Regression analysis revealed a significant impact of the BMI (odds ratio 0.90, 95% CI 0.82-0.98, <i>P</i>=.02) and Timed Up and Go Test score (odds ratio 0.12, 95% CI 0.03-0.55, <i>P</i>=.006) on the accuracy of heart rate measurement; 29 (39%) patients experienced adverse events: pain (5/12, 42%), ECG electrode–related skin irritations (2/42, 17%), dizziness (2/42, 17%), shortness of breath (2/42, 17%), and fatigue (1/42, 8%). No cardiovascular or serious adverse events were reported, and no serious device deficiency was detected. There were no indications of clinically meaningful overexertion based on laboratory values measured before and after the 6-minute walking test and exercise. The differences in means and ranges were as follows: lactate (mmol/l), mean 0.04 (range –3 to 6; <i>P</i>=.47); creatinine kinase (U/l), mean 12 (range –7 to 43; <i>P</i>&lt;.001); and sodium (mmol/l), mean –2 (range –11 to 12; <i>P</i>&lt;.001). <strong>Conclusions:</strong> The interventional trial demonstrated the high safety of the exercise program and the accuracy of heart rate measurements using commercial wearables in patients before major surgery, paving the way for potential remote implementation in the future. <strong>Trial Registration:</strong> German Clinical Trials Register DRKS00026985; https://drks.de/search/en/trial/DRKS00026985 and European Database on Medical Devices (EUDAMED) CIV-21-07-0307311.

2025-02-10T16:00:05-05:00 https://mhealth.jmir.org/2025/1/e56185/ 2025-02-05T19:00:06-05:00 Zixu Yang Creighton Heaukulani Amelia Sim Thisum Buddhika Nur Amirah Abdul Rashid Xuancong Wang Shushan Zheng Yue Feng Quek Sutapa Basu Kok Wei Lee Charmaine Tang Swapna Verma Robert J T Morris Jimmy Lee

Background: Digital phenotyping provides insights into an individual’s digital behaviours and has potential clinical utility. Objective: In this observational study, we explore the digital biomarkers collected from both a wrist wearable device and a smartphone and their associations with clinical symptoms and functioning in patients with schizophrenia. Methods: 100 outpatients with schizophrenia spectrum disorder were recruited, and various digital data from a commercially available wrist wearable and a smartphone were collected over a six-month period. In this report, we analyse the first one week of digital data on heart rate, sleep, and physical activity (from the wrist wearable) and travel distance, sociability, touchscreen tapping speed and screen time (from the smartphone). We analyse the relationship between these digital measures and patient baseline measurements of clinical symptoms, assessed with the Positive and Negative Syndrome Scale (PANSS), Brief Negative Symptoms Scale (BNSS), Calgary Depression Scale for Schizophrenia (CDSS), as well as functioning as assessed with the Social and Occupational Functioning Assessment Scale (SOFAS). Linear regression was performed for each digital and clinical measure, independently, with the digital measures being treated as predictors. Results: Digital data was successfully collected from both the wearable and smartphone throughout the study, with 91% of the total possible data successfully collected from the wearable and 82% from the smartphone during the first week of the trial - the period under analysis in this report. Among the clinical outcomes, negative symptoms were associated with the greatest number of digital measures (10 of the 12 studied here), followed by overall measures of psychopathology symptoms, functioning, and positive symptoms, which were each associated with at least three digital measures. Cognition and cognitive/disorganization symptoms were each associated with one or two digital measures. Conclusions: We have found significant associations between nearly all digital measures and a wide range of symptoms and functioning in a community sample of individuals with schizophrenia. These findings provide insights into the digital behaviours of individuals with schizophrenia and highlight the potential of using commercially available wrist wearables and smartphones for passive monitoring in schizophrenia.

2025-02-05T19:00:06-05:00