Wearable Devices and Smartphones for Activity Tracking Among People with Serious Mental Illness

Efficacy of a Wearable Activity Tracker With Step-by-Step Goal-Setting on Older Adults' Physical Activity and Sarcopenia Indicators: Clustered Trial

BACKGROUND

Smart wearable technology has potential benefits for promoting physical activity and preventing sarcopenia.

OBJECTIVE

The purpose of this study was to explore the efficacy of a wearable activity tracker with 2-stage goal-setting for daily steps on older adults' physical activity and sarcopenia indicators.

METHODS

The study used a clustered trial design and was conducted in March to June 2022. Participants were community-dwelling adults older than 60 years who were recruited from 4 community centers in Taipei City. The intervention was designed with 2-stage goals set to 5000 steps/day in the first 4 weeks and 7500 steps/day in the final 4 weeks while wearing a commercial wearable activity tracker. Data were collected by self-reported questionnaires, a body composition analyzer, a handle grip tester, and 5 sit-to-stand tests.

RESULTS

All 27 participants in the experimental group and 31 participants in the control group completed the 8-week intervention. Total and light-intensity physical activities, skeletal muscle index, and muscle strength increased, while sedentary time, BMI, and the waist circumference of participants decreased in the experimental group, with significant group-by-time interactions compared to the control group.

CONCLUSIONS

A wearable activity tracker with gradual goal-setting is an efficient approach to improve older adults' physical activity and sarcopenia indicators. Smart wearable products with behavioral change techniques are recommended to prevent sarcopenia in older adult populations.

Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture

Unlabelled

The integration of health and activity data from various wearable devices into research studies presents technical and operational challenges. The Awesome Data Acquisition Method (ADAM) is a versatile, web-based system that was designed for integrating data from various sources and managing a large-scale multiphase research study. As a data collecting system, ADAM allows real-time data collection from wearable devices through the device's application programmable interface and the mobile app's adaptive real-time questionnaires. As a clinical trial management system, ADAM integrates clinical trial management processes and efficiently supports recruitment, screening, randomization, data tracking, data reporting, and data analysis during the entire research study process. We used a behavioral weight-loss intervention study (SMARTER trial) as a test case to evaluate the ADAM system. SMARTER was a randomized controlled trial that screened 1741 participants and enrolled 502 adults. As a result, the ADAM system was efficiently and successfully deployed to organize and manage the SMARTER trial. Moreover, with its versatile integration capability, the ADAM system made the necessary switch to fully remote assessments and tracking that are performed seamlessly and promptly when the COVID-19 pandemic ceased in-person contact. The remote-native features afforded by the ADAM system minimized the effects of the COVID-19 lockdown on the SMARTER trial. The success of SMARTER proved the comprehensiveness and efficiency of the ADAM system. Moreover, ADAM was designed to be generalizable and scalable to fit other studies with minimal editing, redevelopment, and customization. The ADAM system can benefit various behavioral interventions and different populations.

A systematic review of users experiences of using digital interventions within psychosis: a thematic synthesis of qualitative research

PURPOSE

Although the development of digital mental health support for people with psychosis has been increasing, the development and opportunities to access this have been more limited compared to other mental health conditions. Qualitative research exploring the experiences of using digital interventions amongst people with psychosis is even less well developed; however, such research is crucial in capturing the experiences of using digital interventions to ensure they are meeting the needs of people with psychosis. This paper aimed to synthesise qualitative data related to the experiences of people with psychosis who have used digital interventions.

METHODS

A systematic literature search was conducted of articles published between 1992 and October 2023 using PubMed, MBase, PsycINFO, & OVID Medline. Two reviewers independently reviewed and screened 268 papers. Papers that met inclusion criteria were quality assessed using The Critical Appraisal Skills Programme (CASP) qualitative studies checklist. The Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) checklist was used to guide the structure of the report.

RESULTS

A thematic synthesis of 19 studies revealed six overarching themes which related to different aspects and features of the digital interventions: participants' relationship with technology; the accessibility of the interventions; how the interventions could impact on individuals' awareness and management of mental health; enhanced communication and relationships; and opportunities for reflection.

CONCLUSIONS

Benefits of using digital interventions are discussed. Areas for development and improvements are highlighted. Finally, recommendations for stakeholders who develop and implement digital interventions for psychosis are made.

Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review

BACKGROUND

Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users' acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential.

OBJECTIVE

This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations.

METHODS

We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords "wearable devices," "mobile apps," "mHealth apps," "physiological data," "usability," "user experience," and "user evaluation" were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist.

RESULTS

A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation.

CONCLUSIONS

Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.

Perceptions of adult patients with cancer towards telemedicine: A qualitative meta-synthesis

Objective

This study aims to systematically identify, evaluate, and synthesize published qualitative research on the views and attitudes of adult cancer patients toward telemedicine and, consequently to better inform the future development of telemedicine technology and interventions.

Methods

A meta-synthesis review was conducted to identify qualitative studies that reported adult cancer patients' perceptions toward telemedicine applications using nine electronic databases, including PubMed, MEDLINE, Web of Science, the Cochrane Library, PsycINFO, CINAHL, Wan Fang, VIP, and CNKI, from inception to November 2022. Quality appraisal was guided by the Joanna Briggs Institute's (JBI) Critical Appraisal Checklist for Qualitative Research. Data were synthesized using "thematic synthesis" to identify themes and concepts.

Results

A total of 3518 articles were retrieved, of which 23 met the inclusion and exclusion criteria. These studies identified three key meta-themes and 11 key sub-themes: (1) Benefits of telemedicine: obtaining information and social support, maintaining the continuity of treatment, receiving professional assistance, having greater flexibility, and promoting physical and mental health; (2) Limitations of telemedicine: interference with normal life, privacy and security issues, auxiliary function issues, and increased psychological burden; (3) Expectations for future telemedicine: more personalized intervention, more specific and diverse information.

Conclusions

The study showed that the benefits and limitations coexisted in the process of telemedicine application among adult cancer patients. It is necessary to develop personalized applications that are better suited to the needs and characteristics of adult cancer patients. Future telemedicine interventions should focus on information diversification and provide patients with more diverse and effective information.

Systematic review registration

PROSPERO, CRD42022324528.

Digital health behaviour change interventions in severe mental illness: a systematic review

The use of digital technologies as a method of delivering health behaviour change (HBC) interventions is rapidly increasing across the general population. However, the role in severe mental illness (SMI) remains overlooked. In this study, we aimed to systematically identify and evaluate all of the existing evidence around digital HBC interventions in people with an SMI. A systematic search of online electronic databases was conducted. Data on adherence, feasibility, and outcomes of studies on digital HBC interventions in SMI were extracted. Our combined search identified 2196 titles and abstracts, of which 1934 remained after removing duplicates. Full-text screening was performed for 107 articles, leaving 36 studies to be included. From these, 14 focused on physical activity and/or cardio-metabolic health, 19 focused on smoking cessation, and three concerned other health behaviours. The outcomes measured varied considerably across studies. Although over 90% of studies measuring behavioural changes reported positive changes in behaviour/attitudes, there were too few studies collecting data on mental health to determine effects on psychiatric outcomes. Digital HBC interventions are acceptable to people with an SMI, and could present a promising option for addressing behavioural health in these populations. Feedback indicated that additional human support may be useful for promoting adherence/engagement, and the content of such interventions may benefit from more tailoring to specific needs. While the literature does not yet allow for conclusions regarding efficacy for mental health, the available evidence to date does support their potential to change behaviour across various domains.

Association Between the Use of Wearable Devices and Physical Activity Among US Adults With Depression and Anxiety: Evidence From the 2019 and 2020 Health Information National Trends Survey

Objective The objective of this study was to examine the relationship between wearable device (WD) use and physical activity (PA) levels among US adults with self-reported depression and anxiety. Methods Data were pooled from 2026 adults who self-reported depression and anxiety from the 2019 and 2020 Health Information National Trends Survey. The explanatory variable was WD use, and the outcomes were weekly PA levels and resistance strength training. Logistic regression was conducted to investigate the association between WD and PA parameters. Results About 33% of adults with self-reported depression/anxiety reported WD use. Only 32.5% and 34.2% of the population reported meeting the weekly recommended levels of physical activity (≥150 minutes/week) and strength and resistance exercise (≥2 times weekly), respectively. In adjusted analyses, the use of WD was not associated with meeting the national weekly recommendation for physical activity (OR 1.38, 95% CI (0.94, 2.04); p=0.10) or resistance strength training (OR 1.31, 95% CI (0.82, 2.08); p=0.26). Further exploratory analysis also showed that physical activity levels did not differ with the frequency of WD use. Conclusion Despite the popularity of WD use among people with mental disorders, we found that use of WD was not associated with increased physical activity measures, suggesting that although there is a promise for these tools to augment mental health, their real-world effectiveness in promoting physical activity in people with mental disorders remains to be proven.

Use of new technologies for the promotion of physical activity in patients with mental illness: A systematic review

BACKGROUND

Physical exercise is an underutilized tool for the management of mental disorders. New technologies have made a breakthrough in health care, and one of its possible applications (apps) could be that of customizing exercise programs for special populations, such as patients with mental disorders. However, the app of the so-called e-health to mental health care is still limited.

AIM

To know the efficacy of apps to promote physical activity in patients with mental disorders.

METHODS

We conducted a systematic review of the PubMed and Embase databases with the aim of exploring the use of new technologies for the enhancement of physical exercise in patients with a psychiatric illness. Following the selection process, 10 articles were included in the review.

RESULTS

The most commonly used devices in this type of intervention are wearable devices and web platforms. Good results in terms of effectiveness and acceptability were obtained in most of the studies.

CONCLUSION

Our findings suggest that the use of new technologies in mental health represents a feasible strategy with great potential in clinical practice.

Are remote psychotherapy/remediation efforts accessible and feasible in patients with schizophrenia? A narrative review

Background

Cognitive remediation (CR) therapy provides an effective way to improve cognitive impairments in schizophrenia. With the advent of telehealth services, especially during COVID 19 pandemic, a suitable alternative can be found in computer and cell phone-based mental health interventions. Previous studies have proven that remote mental health interventions have by and large been successful. Remote psychotherapy/CR services can now be accessed through smartphone apps, iPads, laptops and wearable devices. This has the advantage of reaching a wider population in resource-limited settings. The lack of access to technology, difficulty in using these online interventions and lack of privacy provide impediments to the delivery of care through these online platforms. Further, as some previous studies have shown, there may be a high rate of dropout in people using remote mental health resources. We aim to look at the factors, which influence the accessibility of remote mental health interventions in schizophrenia. Additionally, we test the feasibility of these interventions and look at how they compare and the potential they hold for implementation in future clinical settings.

Results

We found remote cognitive remediation to be both accessible and feasible. Concerning features, however, are the high attrition rates and the concentration of the studies in Western populations.

Conclusions

Remote interventions are a viable alternative to in-person psychotherapy when in-person resources may not always be present. They are efficacious in improving health outcomes among patients with schizophrenia. Further research into the widespread implementation of remote CR will be beneficial in informing clinical decision-making.

Decision support system for the differentiation of schizophrenia and mood disorders using multiple deep learning models on wearable devices data

In the modern world, with so much inherent stress, mental health disorders (MHDs) are becoming more common in every country around the globe, causing a significant burden on society and patients' families. MHDs come in many forms with various severities of symptoms and differing periods of suffering, and as a result it is difficult to differentiate between them and simple to confuse them with each other. Therefore, we propose a support system that employs deep learning (DL) with wearable device data to provide physicians with an objective reference resource by which to make differential diagnoses and plan treatment. We conducted experiments on open datasets containing activity motion signal data from wearable devices to identify schizophrenia and mood disorders (bipolar and unipolar), the datasets being named Psykose and Depresjon. The results showed that, in both workflow approaches, the proposed framework performed well in comparison with the traditional machine learning (ML) and DL methods. We concluded that applying DL models using activity motion signal data from wearable devices represents a prospective objective support system for MHD differentiation with a good performance.

Attitudes toward innovative mental health treatment approaches in Germany: E-mental health and home treatment

E-mental health and home treatment are treatment approaches that have proven to be effective, but are only slowly implemented in the German health care system. This paper explores the attitudes toward these innovative treatment approaches. Data was collected in two large, non-clinical samples representative of the German population in spring 2020 (N = 2,503) and winter 2020/2021 (N = 2,519). Statistical associations between variables were examined using two-tailed tests. Binary and multinomial logistic regressions were performed to predict attitudes toward online-based treatment concepts and home treatment approaches. Only few (<20%) people preferred online-based treatment approaches, while a larger proportion (~50%) could imagine being treated at home. Overall, younger subjects were more open to online-therapy approaches, while people with lower education preferred more often a traditional therapy setting. Acceptance of online-therapy did not raise significantly during the first months of the COVID-19 pandemic. When different online-based treatment options were available, the probability of accepting home treatment significantly increased with increasing levels of therapeutic support. Further promotion of acceptance for online-therapy and home treatment seems to be necessary. In the future, more information on innovative treatment approaches should be actively provided.

Automated classification of hand gestures using a wristband and machine learning for possible application in pill intake monitoring

BACKGROUND

Thanks to the increased interest towards health and lifestyle, a larger adoption in wearable devices for activity tracking is present among the general population. Wearable devices such as smart wristbands integrate inertial units, including accelerometers and gyroscopes, which can be utilised to perform automatic classification of hand gestures. This technology could also find an important application in automatic medication adherence monitoring. Accordingly, this study aims at comparing the performance of several Machine-Learning (ML) and Deep-Learning (DL) approaches for the automatic identification of hand gestures, with a specific focus on the drinking gesture, commonly associated to the action of oral intake of a pill-packed medication.

METHODS

A method to automatically recognize hand gestures in daily living is proposed in this work. The method relies on a commercially available wristband sensor (MetaMotionR, MbientLab Inc.) integrating tri-axial accelerometer and gyroscope. Both ML and DL algorithms were evaluated for both multi-gesture (drinking, eating, pouring water, opening a bottle, typing, answering a phone, combing hair, and cutting) and binary gesture (drinking versus other gestures) classification from wristband sensor signals. Twenty-two participants were involved in the experimental analysis, performing a 10 min acquisition in a laboratory setting. Leave-one-subject-out cross validation was performed for robust performance assessment.

RESULTS

The highest performance was achieved using a convolutional neural network with long- short term memory (CNN-LSTM), with a median f1-score of 90.5 [first quartile: 84.5; third quartile: 92.5]% and 92.5 [81.5;98.0]% for multi-gesture and binary classification, respectively.

CONCLUSIONS

Experimental results showed that hand gesture classification with ML/DL from wrist accelerometers and gyroscopes signals can be performed with reasonable accuracy in laboratory settings, paving the way for a new generation of medical devices for monitoring medical adherence.

Group Lifestyle Intervention With Mobile Health for Young Adults With Serious Mental Illness: A Randomized Controlled Trial

OBJECTIVE

Evidence-based lifestyle interventions tailored to young adults with serious mental illness are needed to reduce their cardiometabolic risk. This study evaluated the effectiveness of a group lifestyle intervention ("PeerFIT") enhanced with mobile health (mHealth) compared with one-on-one mHealth coaching (basic education supported by activity tracking [BEAT]) for young adults with serious mental illness who were overweight or obese.

METHODS

Participants were young adults ages 18-35 years with serious mental illness and a body mass index ≥25 kg/m2, who were randomly assigned to PeerFIT or BEAT. Research staff collected data at baseline and at 6 and 12 months. Main outcomes were clinically significant changes from baseline in weight (≥5% weight loss), cardiorespiratory fitness (CRF; increase of >50 m on the 6-minute walk test), and cardiovascular disease (CVD) risk reduction (clinically significant weight loss or CRF improvement).

RESULTS

Participants were 150 young adults with a mean ± SD body mass index of 37.1±7.4. Intent-to-treat analyses revealed no significant between-group difference for weight-loss, CRF, or CVD outcomes at 6 and 12 months. Participants in both conditions achieved clinically significant CVD risk reduction, weight loss, and CRF from baseline to 6 and 12 months, and all these improvements were statistically significant (p<0.01).

CONCLUSION

The PeerFIT group lifestyle intervention was not superior to one-on-one mHealth coaching in achieving clinically significant changes in weight, CRF, and CVD risk reduction. Although both interventions improved outcomes, low-intensity mHealth coaching may be a more scalable approach for addressing modifiable cardiometabolic risk factors among young adults with serious mental illness.

Use of smartphones, mobile apps and wearables for health promotion by people with anxiety or depression: An analysis of a nationally representative survey data

People with mental illness have increased cardiovascular risk factors, which contributes significantly to mortality in this population. Digital interventions have emerged as promising models to promote physical health, although their potential for use in mental health populations is relatively unexplored. We examined the potential for using digital tools for health promotion by people with common mental disorders like anxiety or depression. Using data from the 2019 edition of the Health Information National Trends Survey (HINTS 5), we evaluated differences between individuals with self-reported history of diagnosed depression/anxiety and the general population with respect to ownership, usage, and perceived usefulness of digital tools for managing their health. Overall, individuals with anxiety or depression were as likely as the general population to use digital devices for their care. Those with anxiety or depression who had health apps were more likely to report intentions to lose weight than those without health apps. Significant sociodemographic predictors of digital tools usage included gender, age, income, and education level. People with anxiety or depression own and use digital health tools at similarly high rates to the general population, suggesting that these tools present a novel opportunity for health promotion among people with these disorders.

Exploring the Association Between Electronic Wearable Device Use and Levels of Physical Activity Among Individuals With Depression and Anxiety: A Population Level Study

Aim: The present study aimed to investigate the cross-sectional association between self-reported use of electronic wearable devices (EWDs) and the levels of physical activity among a representative sample of adults with depression and anxiety in the United States. Methods: For this cross-sectional study, data were pooled from the Health Information National Trends Survey 2019. A sample of 1,139 adults with self-reported depression and anxiety (60.9% women; mean age of 52.5 years) was analyzed. The levels of physical activity and prevalence of EWD utilization were self-reported. The chi-square tests were used to compare individual characteristics through the use of EWDs. Multivariable logistic regression was employed to investigate the association between EWDs and physical activity levels while adjusting for sociodemographic and health-related factors. Results: From the 1,139 adults with self-reported depression and anxiety, 261 (weighted percentage 28.1%) endorsed using EWD in the last year. After adjusting for covariates, the use of EWDs was only significantly associated with a higher odds of reporting intention to lose weight (OR 2.12; 95% CI 1.04, 4.35; p = 0.04). We found no association between the use of EWDs and meeting the national weekly recommendation for physical activity or resistance/strength exercise training. Conclusion: About three in 10 adults suffering from depression and anxiety in the United States reported using EWDs in the last year. The current study findings indicate that among people living with mental illness, EWD use is associated with higher odds of weight loss intent suggesting that EWDs may serve as an opening for the clinical interactions around physical health through identifying patients primed for behavior change. Further large-scale studies using randomized trial designs are needed to examine the causal relationships between EWDs and the physical activity of people with mental health conditions.

Smart Wearable Device Users' Behavior Is Essential for Physical Activity Improvement

BACKGROUNDS

This study aimed to explore the effect on physical activity and sedentary behavior of users of wearable devices, and understand the association between physical activity and behavior.

METHODS

This study conducted a three-arm, randomized controlled trial for 12 weeks. Healthy adults without experience of using a wearable device were recruited and were randomly assigned to a control group with a mobile app and two experimental groups with different smart wearable devices. Data were collected through questionnaires.

RESULTS

No significant effect of group, time, or group-by-time interaction among groups for physical activity, sedentary time, or sleep quality was found. Wearing duration significantly positively predicted changes in low-intensity and total physical activity. The number of times the device was checked negatively predicted a change in sedentary time.

CONCLUSIONS

The behavior of wearable device users is an essential factor for successfully increasing physical activity and decreasing sedentary time.

Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Background

Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user’s uptake and sustained interactions with these interventions.

Objective

This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs.

Methods

A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included.

Results

A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one’s own health.

Conclusions

Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions.

Comparisons of physical activity and sedentary behavior between owners and non-owners of commercial wearable devices

AIMS

Wearable devices are a new strategy for promoting physical activity in a free-living condition that utilizes self-monitoring, self-awareness, and self-determination. The main purpose of this study was to explore health benefits of commercial wearable devices by comparing physical activity, sedentary time, sleep quality, and other health outcomes between individuals who used and those that did not use commercial wearable devices.

METHODS

The research design was a cross-sectional study using an Internet survey in Taiwan. Self-administered questionnaires included the International Physical Activity Questionnaire-Short Form, Pittsburgh Sleep Quality Index, Health-Promoting Lifestyle Profile, and World Health Organization Quality-of-Life Scale.

RESULTS

In total, 781 participants were recruited, including 50% who were users of wearable devices and 50% non-users in the most recent 3 months. Primary outcomes revealed that wearable device users had significantly higher self-reported walking, moderate physical activity, and total physical activity, and significantly lower sedentary time than non-users. Wearable device users had significantly better sleep quality than non-users.

CONCLUSION

Wearable devices inspire users' motivation, engagement, and interest in physical activity through habit formation. Wearable devices are recommended to increase physical activity and decrease sedentary behavior for promoting good health.

Real world sedentary behavior and activity levels in patients with schizophrenia and controls: An ecological momentary assessment study

BACKGROUND

People with schizophrenia often experience poor health, leading to shortened lifespans. The health of people with schizophrenia may be further exacerbated by increased sedentary behavior, which independently predicts health risk in the general population. However, the prevalence and patterns of objectively measured sedentary behavior in schizophrenia have not been studied extensively on a momentary basis.

METHODS

Activity of 100 patients with schizophrenia was compared to that of healthy controls (HC; n=71) using ecological momentary assessment (EMA). EMA provides real-time, real-world monitoring of behavior. We sampled behavior seven times per day for seven days, quantifying active versus inactive behaviors and four different movement patterns (recumbent, seated, standing, and moving). Due to different employment rates between samples, we focused on surveys completed at home.

RESULTS

Four of the five most commonly reported activities for participants with schizophrenia involved sitting or lying down. When considering activity during the last hour, participants with schizophrenia were more likely to be sitting or pacing and less likely to be standing than HC. If participants with schizophrenia only did one thing in the last hour, it was more likely to involve sitting and less likely to involve standing compared to HC.

DISCUSSION

People with schizophrenia were significantly more likely to be seated and less likely to be standing or active during the past hour than HC, despite high frequencies of seated behaviors in the HC as well. The adverse health consequences of sitting for extended periods may be especially relevant for people with schizophrenia and likely contribute to premature mortality in this population.

Physical Activity Can Enhance Life (PACE-Life): results from a 10-week walking intervention for individuals with schizophrenia spectrum disorders

BACKGROUND

Premature mortality in individuals with schizophrenia spectrum disorders (SSDs) is largely due to high rates of chronic health conditions. Although exercise has been shown to improve health in this population, scalable and accessible interventions are limited.

AIM

To examine the impact of Physical Activity Can Enhance Life (PACE-Life), a novel walking intervention, on physical activity, and on secondary outcomes of cardiorespiratory fitness (CRF), physical health, autonomous motivation, social support, and quality of life.

METHOD

Sixteen individuals with SSDs were enrolled in a 10-week open trial. The intervention included walking groups, home-based walks, Fitbit use, and goal-setting and if-then plans. Within-group effect sizes were calculated to represent changes from baseline to post-test and 1-month follow-up.

RESULTS

Participants increased self-reported weekly walking minutes and decreased daily hours spent sitting; however, Fitbit-recorded exercise behavior changed only minimally. There were also improvements in secondary outcomes including autonomous motivation and hip circumference. CRF improved only minimally, and findings were relatively unchanged with outliers removed from the full sample.

CONCLUSIONS

This open trial demonstrates modest improvements in key parameters of exercise behavior and physical health from participating in PACE-Life. Future research should assess the efficacy of this intervention in a randomized controlled trial.

Sensor, Wearable, and Remote Patient Monitoring Competencies for Clinical Care and Training: Scoping Review

Sensor, wearable, and remote patient monitoring technologies are typically used in conjunction with video and/or in-person care for a variety of interventions and care outcomes. This scoping review identifies clinical skills (i.e., competencies) needed to ensure quality care and approaches for organizations to implement and evaluate these technologies. The literature search focused on four concept areas: (1) competencies; (2) sensors, wearables, and remote patient monitoring; (3) mobile, asynchronous, and synchronous technologies; and (4) behavioral health. From 2846 potential references, two authors assessed abstracts for 2828 and, full text for 521, with 111 papers directly relevant to the concept areas. These new technologies integrate health, lifestyle, and clinical care, and they contextually change the culture of care and training-with more time for engagement, continuity of experience, and dynamic data for decision-making for both patients and clinicians. This poses challenges for users (e.g., keeping up, education/training, skills) and healthcare organizations. Based on the clinical studies and informed by clinical informatics, video, social media, and mobile health, a framework of competencies is proposed with three learner levels (novice/advanced beginner, competent/proficient, advanced/expert). Examples are provided to apply the competencies to care, and suggestions are offered on curricular methodologies, faculty development, and institutional practices (e-culture, professionalism, change). Some academic health centers and health systems may naturally assume that clinicians and systems are adapting, but clinical, technological, and administrative workflow-much less skill development-lags. Competencies need to be discrete, measurable, implemented, and evaluated to ensure the quality of care and integrate missions.

Remote CBT for Psychosis During the COVID-19 Pandemic: Challenges and Opportunities

The COVID pandemic is now leading to the emergence of a secondary mental health pandemic. Clients with psychosis are at increased risk of poorer medium- and long-term psychosocial and clinical outcomes. In response to the pressing need to flexibly deliver high-quality care to individuals with psychosis, this brief report proposes high yield cognitive behavioral techniques for psychosis (HY-CBt-p) facilitated by task sharing and digital enhancements. HY-CBt-p is delivered over fewer sessions than formulation-based Cognitive Behavioral Therapy for psychosis (CBTp), can be learned by a range of providers, and includes techniques such as developing a normalizing explanation; techniques to reduce anxiety, depression, and insomnia, which perpetuate psychotic symptoms; self-monitoring; reality testing; and wellness planning. Previous research suggests that effect sizes will be lower than that of 16-session formulation-driven CBTp, but additional research is needed to test the feasibility, acceptability, efficacy, and comparative effectiveness of different forms of remote-delivered CBTp.

Collecting, exploring and sharing personal data: Why, how and where

New, multi-channel personal data sources (like heart rate, sleep patterns, travel patterns, or social activities) are enabled by ever increased availability of miniaturised technologies embedded within smartphones and wearables. These data sources enable personal self-management of lifestyle choices (e.g., exercise, move to a bike-friendly area) and, on a large scale, scientific discoveries to improve health and quality of life. However, there are no simple and reliable ways for individuals to securely collect, explore and share these sources. Additionally, much data is also wasted, especially when the technology provider ceases to exist, leaving the users without any opportunity to retrieve own datasets from “dead” devices or systems. Our research reveals evidence of what we term human data bleeding and offers guidance on how to address current issues by reasoning upon five core aspects, namely technological, financial, legal, institutional and cultural factors. To this end, we present preliminary specifications of an open platform for personal data storage and quality of life research. The Open Health Archive (OHA) is a platform that would support individual, community and societal needs by facilitating collecting, exploring and sharing personal health and QoL data.

Smart wearable devices as a psychological intervention for healthy lifestyle and quality of life: a randomized controlled trial

PURPOSE

Creating a healthy lifestyle is important across different life stages. Commercial smart wearable devices are an innovative and interesting approach as an early psychological intervention for modifying health-related behaviors. Therefore, the purpose of this study was to explore the effects of smart wearable devices on health-promoting lifestyles and quality of life.

METHODS

The study design was a three-parallel randomized controlled trial with a 3-month intervention. Two commercial smart wearable devices (smartwatches and smart bracelets) with different levels of complicated functions were applied as a psychological intervention in comparison with a smartphone app as the control group. Participants were healthy young adults with a median age of 26 years. Outcome measurements were conducted by self-administered questionnaires. Chi-square tests and ANOVA were performed for testing the difference of participants at baseline, and generalized estimating equations were performed for testing the effect of the intervention.

RESULTS

At the beginning, 81 participants were recruited and 73 participants completed the study. Results of a healthy lifestyle demonstrated significant group effects of exercise and a significant effect of the interaction for self-actualization and stress management in the experimental group with a smartwatch (Self-actualization: MD = 0.35[- 0.10,0.80]; Exercise: MD = 0.21[- 0.33 0.75]; Stress management: MD = 0.36[- 0.04,0.76]) by comparing with only using mobile app (Self-actualization: MD =  - 0.03[- 0.25,0.18]; Exercise: MD =  - 0.12[- 0.38,0.14]; Stress management, MD =  - 0.28[- 0.55,0.00]). The significant effect of group-by-time interaction for self-actualization was found in the experimental group with a smart bracelet (MD = 0.05[- 0.30,0.20]) by comparing with the control group. The GEE-adjusted model indicated significant effects of the interaction on the comprehensive, physical, and mental quality of life in the experimental group with the smartwatch (Comprehensive: MD = 0.24[- 0.04,0.52]; Physical: MD = 0.67[0.26,1.09]; Mental: MD = 0.72[0.29,1.16]) by comparing with the control group (Comprehensive: MD =  - 1.57[- 2.55, - 0.59]; Physical: MD = 0.25[0.00,0.50]; Mental: MD = 0.08[- 0.11,0.27]).

CONCLUSION

From a psychological perspective, smart wearable devices have potential benefits of shaping a healthy lifestyle and improving the quality of life. Enhancing the utility of commercial well-designed smart wearable devices is an innovative and effective strategy for promoting public health.

Using a mobile health device to manage severe mental illness in the community: What is the potential and what are the challenges?

There has been a revolution in the use of mobile health devices for monitoring physical health. There is more recent interest in whether these devices can also be used for monitoring symptoms of mental illness. This paper considers how stress increases risk of mental deterioration and individuals with mental illness are sensitive to the effects of stress. It discusses how an inexpensive mobile health device could be used for detecting physiological signs of stress: deviations in biometrics such as sleep, activity and arousal may reflect a stress response and increased risk of relapse. These biometrics can allow patients to self-monitor and clinicians to detect early warning signs. This paper reviews the measurement of electrodermal activity, actigraphy and heart rate to predict mental deterioration. It considers the advantages of continuous measurement and reviews studies using mobile health devices to monitor stress and psychosis. It describes the potential for using a mobile health device to manage and monitor severe mental illness in young adults. Finally, this paper considers challenges associated with this approach, particularly with regard to correctly interpreting the physiological data and integrating the mobile health device into clinical practice. This paper concludes a mobile health device has the potential to enhance care by improving detection of early warning signs and increasing the connection between clinicians and their patients.

Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review

BACKGROUND

Despite the prevalence of mobile health (mHealth) technologies and observations of their impacts on patients' health, there is still no consensus on how best to evaluate these tools for patient self-management of chronic conditions. Researchers currently do not have guidelines on which qualitative or quantitative factors to measure or how to gather these reliable data.

OBJECTIVE

This study aimed to document the methods and both qualitative and quantitative measures used to assess mHealth apps and systems intended for use by patients for the self-management of chronic noncommunicable diseases.

METHODS

A scoping review was performed, and PubMed, MEDLINE, Google Scholar, and ProQuest Research Library were searched for literature published in English between January 1, 2015, and January 18, 2019. Search terms included combinations of the description of the intention of the intervention (eg, self-efficacy and self-management) and description of the intervention platform (eg, mobile app and sensor). Article selection was based on whether the intervention described a patient with a chronic noncommunicable disease as the primary user of a tool or system that would always be available for self-management. The extracted data included study design, health conditions, participants, intervention type (app or system), methods used, and measured qualitative and quantitative data.

RESULTS

A total of 31 studies met the eligibility criteria. Studies were classified as either those that evaluated mHealth apps (ie, single devices; n=15) or mHealth systems (ie, more than one tool; n=17), and one study evaluated both apps and systems. App interventions mainly targeted mental health conditions (including Post-Traumatic Stress Disorder), followed by diabetes and cardiovascular and heart diseases; among the 17 studies that described mHealth systems, most involved patients diagnosed with cardiovascular and heart disease, followed by diabetes, respiratory disease, mental health conditions, cancer, and multiple illnesses. The most common evaluation method was collection of usage logs (n=21), followed by standardized questionnaires (n=18) and ad-hoc questionnaires (n=13). The most common measure was app interaction (n=19), followed by usability/feasibility (n=17) and patient-reported health data via the app (n=15).

CONCLUSIONS

This review demonstrates that health intervention studies are taking advantage of the additional resources that mHealth technologies provide. As mHealth technologies become more prevalent, the call for evidence includes the impacts on patients' self-efficacy and engagement, in addition to traditional measures. However, considering the unstructured data forms, diverse use, and various platforms of mHealth, it can be challenging to select the right methods and measures to evaluate mHealth technologies. The inclusion of app usage logs, patient-involved methods, and other approaches to determine the impact of mHealth is an important step forward in health intervention research. We hope that this overview will become a catalogue of the possible ways in which mHealth has been and can be integrated into research practice.

Wearable activity trackers and health awareness: Nursing implications

Purpose

Wearable devices are commonly used to measure physical activity. However, it remains unclear the effect of wearing these devices on health awareness. Our aim was to provide evidence related to wearing physical activity trackers and health awareness.

Methods

A quantitative comparison study design was used comparing participants who wore physical activity tracking devices (n = 108) and those who did not (n = 112). A paper-based Physical Health Knowledge survey designed for the purpose of this research was used for data collection in 2018.

Results

A difference between participants who wore physical activity tracking devices and those that did not was identified in relation to activity levels and physical health awareness. Wearable devices are suggested as an opportunity for nurses to engage people in physical activity with the potential to improve their health awareness.

Conclusions

Nurses are well placed in the healthcare landscape to work with patients who own an activity tracker device concerning increasing activity self-monitoring. This information the patient has from the device can also form the basis of health discussions between nurses and the people in their care.

Internet of Things-Enabled Technologies for Weight Management in Children and Adolescents: Protocol for a Systematic Review

BACKGROUND

Childhood obesity is a serious global issue, leading to increased medical spending on obesity-related diseases such as cardiovascular diseases and diabetes. There is a need for health care services that link health behavior to risk factors, such as diet and physical activity, and that provide better advice and feedback to users, which Internet of Things-enabled technologies could facilitate.

OBJECTIVE

The objective of the systematic review will be to identify available Internet of Things-enabled technologies for weight management of children and adolescents (users younger than 18 years). It will also aim to understand the use, effectiveness, and feasibility of these technologies.

METHODS

We will search the Medline, PubMed, Web of Science, Scopus, ProQuest Central, and IEEE Xplore Digital Library databases for studies published after 2010, using a combination of keywords and subject headings related to health activity tracking, youth, and Internet of Things. In addition, a Google search to identify grey literature will be conducted. Two authors will independently screen the titles and abstracts identified from the search and accept or reject the studies according to the study inclusion criteria. Any discrepancies will then be discussed and resolved. The quality of the included studies will be assessed using the Critical Appraisal Skills Programme (CASP) checklists. Data from included studies will be extracted into a predesigned form to identify the types of devices or apps, Internet of Things applications, and health outcomes related to weight management.

RESULTS

A preliminary search on Medline returned 484 results. The publication of the final systematic review is expected in mid-2020.

CONCLUSIONS

The effectiveness and feasibility of physical activity trackers and consumer wearables for different patient groups have been well reviewed, but there are currently no published reviews that look into these technologies in the wider Internet of Things context. This review aims to address this gap by examining Internet of Things-enabled technologies that are designed for youth weight management and thus inform further research and clinical studies to reduce childhood obesity.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/16930.

Digital Opportunities for Outcomes in Recovery Services (DOORS): A Pragmatic Hands-On Group Approach Toward Increasing Digital Health and Smartphone Competencies, Autonomy, Relatedness, and Alliance for Those With Serious Mental Illness

Digital health technologies such as smartphones present the potential for increased access to care and on-demand services. However, many patients with serious mental illnesses (eg, schizophrenia) have not been offered the digital health training necessary to fully utilize these innovative approaches. To bridge this digital divide in knowledge and skills, we created a hands-on and interactive training program grounded in self-determination theory, technology use cases, and the therapeutic alliance. This article introduces the need and theoretical foundation for and the experience of running the resulting Digital Opportunities for Outcomes in Recovery Services (DOORS) group in the setting of 2 programs: a first-episode psychosis program and a clubhouse for individuals with serious mental illness. The experience of running these 2 DOORS groups resulted in 2 publicly available, free training manuals to empower others to run such groups and adapt them for local needs. Future work on DOORS will expand the curriculum to best support digital health needs and increase equity of access to and knowledge and skills related to technology use in serious mental illness.

Perspectives of People Who Are Overweight and Obese on Using Wearable Technology for Weight Management: Systematic Review

BACKGROUND

Obesity is a large contributor to preventable chronic diseases and health care costs. The efficacy of wearable devices for weight management has been researched; however, there is limited knowledge on how these devices are perceived by users.

OBJECTIVE

This study aimed to review user perspectives on wearable technology for weight management in people who are overweight and obese.

METHODS

We searched the online databases Pubmed, Scopus, Embase, and the Cochrane library for literature published from 2008 onward. We included all types of studies using a wearable device for delivering weight-loss interventions in adults who are overweight or obese, and qualitative data were collected about participants' perspectives on the device. We performed a quality assessment using criteria relevant to different study types. The Cochrane risk of bias tool was used for randomized controlled trials. The Risk of Bias in Non-randomized Studies - of Interventions (ROBINS-I) was used for nonrandomized studies. The Oxman and Guyatt Criteria were used for systematic reviews. We used the critical appraisal checklist for qualitative studies. Data were extracted into a data extraction sheet and thematically analyzed.

RESULTS

We included 19 studies: 5 randomized controlled trials, 6 nonrandomized studies, 5 qualitative studies, and 3 reviews. Mixed perceptions existed for different constructs of wearable technologies, which reflects the differences in the suitability of wearable technology interventions for different individuals in different contexts. This also indicates that interventions were not often tailored to participants' motivations. In addition, very few wearable technology interventions included a thorough qualitative analysis of the participants' view on important features of the intervention that made it successful.

CONCLUSIONS

This study highlights the importance of determining the type of intervention most suitable for an individual before the intervention is used. Our findings could help participants find a suitable intervention that is most effective for them. Further research needs to develop a user-centered tool for obtaining comprehensive user feedback.

TRIAL REGISTRATION

PROSPERO CRD42018096932; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=96932.

A Scale to Assess the Methodological Quality of Studies Assessing Usability of Electronic Health Products and Services: Delphi Study Followed by Validity and Reliability Testing

BACKGROUND

The usability of electronic health (eHealth) and mobile health apps is of paramount importance as it impacts the quality of care. Methodological quality assessment is a common practice in the field of health for different designs and types of studies. However, we were unable to find a scale to assess the methodological quality of studies on the usability of eHealth products or services.

OBJECTIVE

This study aimed to develop a scale to assess the methodological quality of studies assessing usability of mobile apps and to perform a preliminary analysis of of the scale's feasibility, reliability, and construct validity on studies assessing usability of mobile apps, measuring aspects of physical activity.

METHODS

A 3-round Delphi panel was used to generate a pool of items considered important when assessing the quality of studies on the usability of mobile apps. These items were used to write the scale and the guide to assist its use. The scale was then used to assess the quality of studies on usability of mobile apps for physical activity, and it assessed in terms of feasibility, interrater reliability, and construct validity.

RESULTS

A total of 25 experts participated in the Delphi panel, and a 15-item scale was developed. This scale was shown to be feasible (time of application mean 13.10 [SD 2.59] min), reliable (intraclass correlation coefficient=0.81; 95% CI 0.55-0.93), and able to discriminate between low- and high-quality studies (high quality: mean 9.22 [SD 0.36]; low quality: mean 6.86 [SD 0.80]; P=.01).

CONCLUSIONS

The scale that was developed can be used both to assess the methodological quality of usability studies and to inform its planning.

E-mental health: Promising advancements in policy, research, and practice

The increasing need for mental health services in the population is posing significant challenges for the health system. It is therefore important to identify new approaches to delivering care that are sustainable and scalable in terms of reach and impact. E-mental health is one approach that shows promise in addressing the treatment gap in mental healthcare. E-mental health involves leveraging the Internet and related technologies such as smartphone apps, web sites, and social media to deliver mental health services. Over the past decade, this field has made significant advancements in Canada and internationally. In this article, the author introduces the e-mental health field and provides an overview of promising Canadian developments in relation to policy, research, and practice. In addition, the article discusses some of the challenges facing the wide-scale implementation of e-mental health and identifies priority areas of focus for health leaders to advance the field.

Experiences of mobile health in promoting physical activity: A qualitative systematic review and meta-ethnography

OBJECTIVE

Despite evidence supporting physical activity in primary and secondary prevention, many individuals do not meet recommended levels. Mobile health is a field with a growing evidence base and is proposed as a convenient method for delivering health interventions. Despite qualitative exploration of stakeholder perspectives, there is a lack of synthesis to inform evidence-based design. This study aims to resolve this by identifying and synthesising qualitative research on the experience of using mobile health applications to promote physical activity.

METHOD

A systematic review focused on qualitative research, mobile health and physical activity was conducted in October 2017 using CINAHL, ERIC, EMBASE, MEDLINE and PsycINFO databases. The protocol was registered with the Prospero database (Registration: CRD42018080610). Results were synthesised as a meta-ethnography.

RESULTS

Fifteen studies were included, covering a variety of populations, including people with diabetes, obesity, and serious mental illness. Five themes emerged: (a) personal factors and the experience of using mobile health, (b) mobile health and changes in thinking that support physical activity, (c) the experience of mobile health features, including prompts, goal setting and gamification, (d) the experience of personalised mobile health and physical activity, (e) technical and user issues in mobile health and their effect on experience.

CONCLUSION

Personal factors and features of the device influenced the experience of using mobile health to support physical activity. The two mechanisms through which mobile health use facilitated physical activity were strengthening of motivation and changes in self-awareness and strategising. Experiences were not entirely unproblematic as technical issues and adverse effects related to self-monitoring were noted. This synthesis provides insight into the experience of mobile health and is useful for researchers and healthcare practitioners interested in designing user-informed mobile health interventions for promoting physical activity.

Peer support and mobile health technology targeting obesity-related cardiovascular risk in young adults with serious mental illness: Protocol for a randomized controlled trial

BACKGROUND

Individuals with serious mental illness (SMI) such as schizophrenia and bipolar disorder face a higher risk of early death due to cardiovascular disease and other preventable chronic illnesses. Young adulthood is a critical window of development for lifestyle interventions to improve the long-term health and quality of life in this population. Fit Forward is an NIH-funded randomized clinical trial examining the effectiveness of a group lifestyle intervention (PeerFIT) enhanced with mobile health technology compared to one-on-one mobile lifestyle coaching with Basic Education in fitness and nutrition supported by a wearable Activity Tracking device (BEAT) in achieving clinically significant weight loss and improved cardiorespiratory fitness in young adults with SMI.

METHODS

Fit Forward targets 144 young adults (18 to 35 years) with SMI and a body mass index (BMI) of ≥25 receiving public mental health services. In a two-arm randomized clinical trial, participants will be randomly assigned with equal probability to PeerFIT or BEAT, stratified by birth sex and psychiatric diagnosis. Participants will be assessed at baseline, 6, and 12 months. The primary outcome is cardiovascular risk reduction indicated by either clinically significant weight loss (5% or greater) or increased fitness (>50 m on the 6-Minute Walk Test). Secondary outcomes include change in BMI, lipids, and hemoglobin A1c. Perceived self-efficacy for exercise and peer support will be evaluated as mechanisms underlying intervention effects.

CONCLUSION

If effective, PeerFIT will provide a potentially scalable approach to addressing health risks among young adults with SMI in mental health settings.

TRIALS REGISTRATION

ClinicalTrials.gov, NCT02815813.

The WorkingWell Mobile Phone App for Individuals With Serious Mental Illnesses: Proof-of-Concept, Mixed-Methods Feasibility Study

BACKGROUND

The disparities in employment for individuals with serious mental illnesses have been well documented, as have the benefits of work. Mobile technology can provide accessible in-the-moment support for these individuals. The WorkingWell mobile app was developed to meet the need for accessible follow-along supports for individuals with serious mental illnesses in the workplace.

OBJECTIVE

We explore the usability, usage, usefulness, and overall feasibility of the WorkingWell mobile app with individuals with serious mental illnesses who are actively employed and receiving community-based services.

METHODS

In this proof-of-concept, mixed-methods, 2-month feasibility study (N=40), employed individuals with serious mental illnesses were recruited in mental health agencies. Participants completed surveys regarding background characteristics and cellphone use at enrollment and responded to interview items regarding app usability, usage, and usefulness in technical assistance calls at 1, 2, 4, and 6 weeks of participation and in the exit interview at 8 weeks. Data on the frequency of app usage were downloaded on a daily basis. A version of the System Usability Scale (SUS) was administered in the exit interview. Overall feasibility was determined by the percent of users completing the study, responses to an interview item regarding continued use, and findings on usability, usage, and usefulness. General impressions were obtained from users regarding user support materials, technical assistance, and study procedures.

RESULTS

Most participants were male (60%, 24/40), aged 55 or younger (70%, 28/40), white (80%, 32/40), had less than a 4-year college education (78%, 31/40), were employed part-time (98%, 39/40), had been working more than 6 months (60%, 24/40), and indicated a diagnosis of bipolar, schizoaffective, or depressive disorder (84%, 16/25). The majority of participants owned cellphones (95%, 38/40) and used them multiple times per day (83%, 33/40). Their average rating on SUS usability items was 3.93 (SD 0.77, range 1.57-5.00), reflecting positive responses. In general, participants indicated WorkingWell was "very easy," "straightforward," "simple," and "user friendly." Usability challenges were related to personal issues (eg, memory) or to difficulties with the phone or app. Data on app usage varied considerably. The most frequent navigations were to the home screen, followed by Rate My Day and My Progress, and then by Manage the Moment and Remind Me. The app was described as useful by most participants; 86% (30/35) agreed the app would help them manage better on the job. Of the 40 original participants, 35 (87%) completed the study.

CONCLUSIONS

The WorkingWell app is a feasible approach to providing accessible, as-needed employment support for individuals with serious mental illnesses. The app would benefit from modifications to address recommendations from feasibility testing. Controlled research with larger samples, more diverse in individual characteristics and workplace settings, is essential to demonstrating the effectiveness of the app.

How college students diagnosed with anxiety disorders and/or depression use everyday technology

Anxiety disorders and/or depression are the most frequently diagnosed mental health problems (MHP) among American college students. Everyday technology (EDT) is being used with those who have MHP to help them cope with the mental/cognitive disabilities arising from having anxiety and/or depression. Deveau investigated the types of EDT students with MHP use to manage their roles as college students. While this research indicated that individuals with MHP were open to learning about EDT they can use, the author recommended further investigation of the topic. This qualitative study further investigated what types of EDT college students use to manage their anxiety disorder and/or depression. Our research found that while college students with anxiety and depression are familiar with and willing to use EDT to help compensate for some of the issues they have resulting from their anxiety and depression, some reported that the use of EDT contributes to their problems. Implications for further investigation include continuing to examine the use of EDT amongst a larger group of college students. Future research should also investigate creating a peer run technology group, taught by interested student such as occupational therapy, psychology or computer science students to name a few, to inform students about apps to manage scheduling, routines, medication management and symptoms management. Additionally, the positive and negative aspects of social media and how to manage ones use of it use would be a relevant topic for group discussion.Implications for rehabilitationWhile most college students currently use everyday technology as a part of their lives, it has positive and negative meanings to college students who have anxiety and/or depression.Finding out what a user wants to do with technology and the meaning it has for them is a critical part of insuring the right match between a person and an assistive technology intervention.Consider a full range of no to high technology options when working with college students who experience the mental/cognitive disabilities resulting from mental health problems to identify assistive technology solutions.

Digital Technology for Caregivers of People With Psychosis: Systematic Review

BACKGROUND

Psychotic disorders are severe mental health conditions that adversely affect the quality of life and life expectancy. Schizophrenia, the most common and severe form of psychosis affects 21 million people globally. Informal caregivers (families) are known to play an important role in facilitating patient recovery outcomes, although their own health and well-being could be adversely affected by the illness. The application of novel digital interventions in mental health care for patient groups is rapidly expanding; interestingly, however, far less is known about their role with family caregivers.

OBJECTIVE

This study aimed to systematically identify the application of digital interventions that focus on informal caregivers of people with psychosis and describe their outcomes.

METHODS

We completed a search for relevant papers in four electronic databases (EMBASE, MEDLINE, PsycINFO, and Web of Science). The search also included the Cochrane database and manual search of reference lists of relevant papers. The search was undertaken in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines.

RESULTS

The search identified 9 studies derived from 8 unique datasets. Most studies were assessments of feasibility and were undertaken in the United States. Interventions were predominately Web-based, with a focus on improving the caregivers' knowledge and understanding about psychosis.

CONCLUSIONS

This study offers preliminary support for the feasibility and acceptability of digital interventions for psychosis in informal caregiver populations. However, the findings underpin a clear need for greater development in the range of caregiver-focused digital approaches on offer and robust evaluation of their outcomes. The use of digital approaches with caregiver populations seemingly lags someway behind the significant developments observed in patient groups.

Pre-post, mixed-methods feasibility study of the WorkingWell mobile support tool for individuals with serious mental illness in the USA: a pilot study protocol

INTRODUCTION

Successful competitive employment has been found to be related to enhanced self-esteem, higher quality of life and reduced mental health service use for individuals living with serious mental illnesses (SMIs) including schizophrenia, bipolar disorder and major depression. The effectiveness of the individual placement and support model has been demonstrated in multiple randomised controlled trials in many countries. The management of stress, depression and anxiety in the workplace may be effectively enhanced through digital mental health interventions. The WorkingWell mobile support tool ('app') is specifically designed to meet the need for illness management support for individuals with SMI in the workplace, as an adjunct to professional treatment.

METHODS AND ANALYSIS

The WorkingWell app, grounded in evidence-based supported employment, is informed by user experience design. It will be tested in a pre-post design, mixed-methods pilot study to explore issues of feasibility, acceptability and usefulness, and to provide preliminary data on the impact of use. Putative mediators of improved job tenure and psychological well-being, including postintervention changes in social support, self-efficacy and work-related motivation, will be investigated. Forty individuals at least 18 years of age, meeting the eligibility requirements for supported employment services (ie, diagnosed with a mental illness meeting the criteria for severity, duration and treatment), working a minimum of 10 hours per week at study enrolment, and speaking, reading and writing in English will be recruited for the pilot study. Research staff will recruit individuals at community-based mental health agencies; provide orientation to the study, the study smartphones and the WorkingWell app; conduct research interviews including standardised measures as well as semistructured items; and provide technical assistance in telephone calls and inperson meetings. A sample of 10 agency staff will be recruited to obtain further information on the feasibility, acceptability and usefulness of WorkingWell.

ETHICS AND DISSEMINATION

The study design and procedures are approved by the Dartmouth-Hitchcock Medical Center Committee for the Protection of Human Subjects, the Massachusetts Department of Mental Health Central Office Research Review Committee and the Vermont Agency of Human Services Institutional Review Board. Study findings will be disseminated to agency partners, state agencies and funders, and to the research and technology development communities. Findings from the study will inform the design, data collection procedures and protocol for future full-scale randomised controlled trial testing of the effectiveness of the WorkingWell app, as well as investigations of work-related variables as mediators of psychological well-being and quality of life for individuals with SMI.

Patterns of Fitbit Use and Activity Levels Throughout a Physical Activity Intervention: Exploratory Analysis from a Randomized Controlled Trial

BACKGROUND

There has been a rapid increase in the use of technology-based activity trackers to promote behavior change. However, little is known about how individuals use these trackers on a day-to-day basis or how tracker use relates to increasing physical activity.

OBJECTIVE

The aims were to use minute level data collected from a Fitbit tracker throughout a physical activity intervention to examine patterns of Fitbit use and activity and their relationships with success in the intervention based on ActiGraph-measured moderate to vigorous physical activity (MVPA).

METHODS

Participants included 42 female breast cancer survivors randomized to the physical activity intervention arm of a 12-week randomized controlled trial. The Fitbit One was worn daily throughout the 12-week intervention. ActiGraph GT3X+ accelerometer was worn for 7 days at baseline (prerandomization) and end of intervention (week 12). Self-reported frequency of looking at activity data on the Fitbit tracker and app or website was collected at week 12.

RESULTS

Adherence to wearing the Fitbit was high and stable, with a mean of 88.13% of valid days over 12 weeks (SD 14.49%). Greater adherence to wearing the Fitbit was associated with greater increases in ActiGraph-measured MVPA (b_interaction=0.35, P<.001). Participants averaged 182.6 minutes/week (SD 143.9) of MVPA on the Fitbit, with significant variation in MVPA over the 12 weeks (F=1.91, P=.04). The majority (68%, 27/40) of participants reported looking at their tracker or looking at the Fitbit app or website once a day or more. Changes in Actigraph-measured MVPA were associated with frequency of looking at one's data on the tracker (b=-1.36, P=.07) but not significantly associated with frequency of looking at one's data on the app or website (P=.36).

CONCLUSIONS

This is one of the first studies to explore the relationship between use of a commercially available activity tracker and success in a physical activity intervention. A deeper understanding of how individuals engage with technology-based trackers may enable us to more effectively use these types of trackers to promote behavior change.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02332876; https://clinicaltrials.gov/ct2/show/NCT02332876?term=NCT02332876 &rank=1 (Archived by WebCite at http://www.webcitation.org/6wplEeg8i).

Tomorrow's world: current developments in the therapeutic use of technology for psychosis

There is now an established evidence base for the use of information and communication technology (ICT) to support mental healthcare (‘e-mental health’) for common mental health problems. Recently, there have been significant developments in the therapeutic use of computers, mobile phones, gaming and virtual reality technologies for the assessment and treatment of psychosis. We provide an overview of the therapeutic use of ICT for psychosis, drawing on searches of the scientific literature and the internet and using interviews with experts in the field. We outline interventions that are already relevant to clinical practice, some that may become available in the foreseeable future and emerging challenges for their implementation.

Toward research-tested mobile health interventions to prevent diabetes and cardiovascular disease among persons with pre-diabetes

Background

About 35% of US adults have pre-diabetes and an increased risk of diabetes. Consumer-facing devices such as the Fitbit help users become more physically active and manage their weight which reduces risk of diabetes and cardiovascular disease.

Methods

In this commentary we provide a summary of healthy lifestyle intervention studies involving persons with pre-diabetes including those conducted in routine clinical practice. We also provide an account of how such interventions might be enhanced through the use of wearable devices linked to smartphone applications.

Results

In initial trials focusing on overweight and obesity, consumer wearable devices have been shown to increase physical activity and reduce weight. However, the acceptability and effectiveness of these mHealth interventions among persons with impaired glucose tolerance or impaired fasting glucose is unknown; studies involving persons with pre-diabetes have not yet been reported.

Conclusions

Research is needed to determine the feasibility and efficacy of wearable devices in improving physical activity and weight management in persons with pre-diabetes who are at-risk of diabetes and cardiovascular disease.

Predictors of rapid high weight gain in schizophrenia: Longitudinal analysis of the French FACE-SZ cohort

Metabolic syndrome (MetS) is highly prevalent in schizophrenia. However very little is known about the time course of MetS and its components. The few longitudinal studies that have been carried out had small sample sizes and a short follow-up. The aim of our study was to evaluate the prevalence of MetS and its components, at baseline and one year later, and to investigate predictors of weight gain (WG) in a cohort of individuals with schizophrenia. We followed 167 schizophrenia patients from the FACE-SZ cohort for one year. The Structured Clinical Interview for DSM-IV (SCID) was used to confirm the diagnosis of schizophrenia. Data on socio-demographic and clinical characteristics, antipsychotic treatment, and comorbidities were collected, and a blood sample was drawn. We found that the prevalence of MetS increased from 21.0% to 26.6% after one year. Patients with baseline depressive symptoms had a 4.5-fold higher risk of WG at the one-year follow-up (p = 0.02) than those without depressive symptoms, after adjusting for confounding variables. WG also correlated with high levels of metabolic parameters and peripheral inflammation. These findings highlight the need to systematically diagnose depression in Schizophrenia. Future studies should determine whether specific pharmacological and non-pharmacological interventions for depression in SZ subjects are effective in preventing rapid high weight gain.

Developing digital interventions for people living with serious mental illness: perspectives from three mHealth studies

The rapidly expanding field of mobile health (mHealth) seeks to harness increasingly affordable and ubiquitous mobile digital technologies including smartphones, tablets, apps and wearable devices to enhance clinical care. Accumulating evidence suggests that mHealth interventions are increasingly being adopted and valued by people living with serious mental illnesses such as schizophrenia and bipolar disorder, as a means of better understanding and managing their condition. We draw on experiences from three geographically and methodologically distinct mHealth studies to provide a pragmatic overview of the key challenges and considerations relating to the process of developing digital interventions for this population.

Health behavior models for informing digital technology interventions for individuals with mental illness

OBJECTIVE

Theoretical models offer valuable insights for designing effective and sustainable behavioral health interventions, yet the application of theory for informing digital technology interventions for people with mental illness has received limited attention. We offer a perspective on the importance of applying behavior theories and models to developing digital technology interventions for addressing mental and physical health concerns among people with mental illness.

METHOD

In this commentary, we summarize prominent theories of human behavior, highlight key theoretical constructs, and identify opportunities to inform digital health interventions for people with mental illness. We consider limitations with existing theories and models, and examine recent theoretical advances that can specifically guide development of digital technology interventions.

RESULTS

Established behavioral frameworks including health belief model, theory of planned behavior, transtheoretical model, and social cognitive theory consist of important and overlapping constructs that can inform digital health interventions for people with mental illness. As digital technologies continue to evolve and enable longitudinal data collection, real-time behavior monitoring, and adaptive features tailored to users' changing needs over time, there are new opportunities to broaden our understanding of health behaviors and mechanisms of behavior change. Recent advances include dynamic models of behavior, persuasive system design, the behavioral intervention technology model, and behavioral models for just-in-time adaptive interventions.

CONCLUSION AND IMPLICATIONS FOR PRACTICE

Behavior theories offer advantages for guiding use of digital technologies. Future researchers must explore how theoretical models can effectively advance efforts to develop, evaluate, and disseminate digital health interventions targeting individuals with mental illness. (PsycINFO Database Record

Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review

Background

Electronic mental health interventions for mood disorders have increased rapidly over the past decade, most recently in the form of various systems and apps that are delivered via smartphones.

Objective

We aim to provide an overview of studies on smartphone-based systems that combine subjective ratings with objectively measured data for longitudinal monitoring of patients with affective disorders. Specifically, we aim to examine current knowledge on: (1) the feasibility of, and adherence to, such systems; (2) the association of monitored data with mood status; and (3) the effects of monitoring on clinical outcomes.

Methods

We systematically searched PubMed, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials for relevant articles published in the last ten years (2007-2017) by applying Boolean search operators with an iterative combination of search terms, which was conducted in February 2017. Additional articles were identified via pearling, author correspondence, selected reference lists, and trial protocols.

Results

A total of 3463 unique records were identified. Twenty-nine studies met the inclusion criteria and were included in the review. The majority of articles represented feasibility studies (n=27); two articles reported results from one randomized controlled trial (RCT). In total, six different self-monitoring systems for affective disorders that used subjective mood ratings and objective measurements were included. These objective parameters included physiological data (heart rate variability), behavioral data (phone usage, physical activity, voice features), and context/environmental information (light exposure and location). The included articles contained results regarding feasibility of such systems in affective disorders, showed reasonable accuracy in predicting mood status and mood fluctuations based on the objectively monitored data, and reported observations about the impact of monitoring on clinical state and adherence of patients to the system usage.

Conclusions

The included observational studies and RCT substantiate the value of smartphone-based approaches for gathering long-term objective data (aside from self-ratings to monitor clinical symptoms) to predict changes in clinical states, and to investigate causal inferences about state changes in patients with affective disorders. Although promising, a much larger evidence-base is necessary to fully assess the potential and the risks of these approaches. Methodological limitations of the available studies (eg, small sample sizes, variations in the number of observations or monitoring duration, lack of RCT, and heterogeneity of methods) restrict the interpretability of the results. However, a number of study protocols stated ambitions to expand and intensify research in this emerging and promising field.

Methodology and Reporting of Mobile Heath and Smartphone Application Studies for Schizophrenia

The increasing prevalence of mobile devices among patients of all demographic groups has the potential to transform the ways we diagnose, monitor, treat, and study mental illness. As new tools and technologies emerge, clinicians and researchers are confronted with an increasing array of options both for clinical assessment, through digital capture of the essential behavioral elements of a condition, and for intervention, through formalized treatments, coaching, and other technology-assisted means of patient communication. And yet, as with any new set of tools for the assessment or treatment of a medical condition, establishing and adhering to reporting guidelines-that is, what works and under what conditions-is an essential component of the translational research process. Here, using the recently published World Health Organization mHealth Evaluation, Reporting and Assessment guidelines for evaluating mobile health applications, we review the methodological strengths and weaknesses of existing studies on smartphones and wearables for schizophrenia. While growing evidence supports the feasibility of using mobile tools in severe mental illness, most studies to date failed to adequately report accessibility, interoperability, costs, scalability, replicability, data security, usability testing, or compliance with national guidelines or regulatory statutes. Future research efforts addressing these specific gaps in the literature will help to advance our understanding and to realize the clinical potential of these new tools of psychiatry.

How people with serious mental illness use smartphones, mobile apps, and social media

OBJECTIVE

Research shows that people with serious mental illness are increasingly using mobile devices. Less is known about how these individuals use their mobile devices or whether they access social media. We surveyed individuals with serious mental illness to explore their use of these technologies.

METHOD

Individuals with serious mental illness engaged in lifestyle interventions through community mental health centers completed a survey about their use of mobile and online technologies. Responses were compared with data from the general population.

RESULTS

Among respondents (n = 70), 93% owned cellphones, 78% used text messaging, 50% owned smartphones, and 71% used social media such as Facebook. Most respondents reported daily use of text messaging, mobile apps, and social media. Technology use was comparable to the general population, though smartphone ownership was lower.

CONCLUSIONS AND IMPLICATIONS FOR PRACTICE

These findings can inform future interventions that fully leverage this group's use of popular digital technologies. (PsycINFO Database Record

Use of Consumer Wearable Devices to Promote Physical Activity: A Review of Health Intervention Studies

BACKGROUND

Although many wearable devices for monitoring and tracking physical activity are available to consumers, relatively few research studies have been conducted to determine their efficacy in promoting health.

METHODS

In this article, data on the use of consumer wearable devices in promoting healthy behaviors are summarized based upon bibliographic searches in PubMed and Psychology and Behavioral Sciences Collection with relevant search terms through September 2016.

RESULTS

A total of 274 articles were identified in the bibliographic searches. By screening abstracts or full-text articles, six pre/post test trials and seven randomized controlled trials were identified. In initial trials, consumer wearable devices have been shown to increase physical activity and help users lose weight. However, the number of studies completed to date is small and limited by small sample sizes, short study durations, and uncertain generalizability of the findings.

CONCLUSIONS

Future studies should utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better establish the efficacy of wearable devices in promoting physical activity. Additional research is needed to determine the feasibility and effectiveness of wearable devices in promoting physical activity and weight loss in community settings including communities affected by health disparities. Studies focusing on children and adolescents are also needed.

Wearable devices and mobile technologies for supporting behavioral weight loss among people with serious mental illness

Promoting physical activity is essential for addressing elevated cardiovascular risk and high obesity rates affecting people with serious mental illness. Numerous challenges interfere with exercise participation in this high-risk group including mental health symptoms, low motivation, and limited access to safe and affordable options for physical activity. Wearable devices and mobile health technologies may afford new opportunities for promoting physical activity and supporting behavioral weight loss efforts. This exploratory study examined whether daily step count measured using Fitbit wearable devices was associated with weight loss and improved fitness among individuals with serious mental illness enrolled in a 6-month lifestyle program. Participants (n=34) had a schizophrenia spectrum disorder (23.5%), major depression (50.0%), or bipolar disorder (26.5%), and wore Fitbits most of the days (M=86.2%; SD=18.4%) they were enrolled in the study. At 6-months, higher average daily step count was associated with greater weight loss (F=5.07; df=1,32; p=0.0314), but not improved fitness (F=1.92; df=1,31; p=0.176). These findings demonstrate that encouraging participants with serious mental illness enrolled in lifestyle interventions to collect more steps may contribute to greater weight loss. This suggests that wearable devices may offer a feasible and potentially effective strategy for supporting behavioral weight loss in community mental health settings.