Enhancing early psychosis treatment using smartphone technology: A longitudinal feasibility and validity study

Perspective of patients with first-episode psychosis, their relatives, and mental health professionals on the design and usability of an app in clinical practice

AIM

Therapeutic non-compliance remains the main difficulty for people with psychotic disorders, standing around 50% in people with schizophrenia. Lack of treatment adherence, either partial or total, to medication has economic and clinical consequences. E-health technologies may be a promising therapeutic tool to improve adherence, with the subsequent reduction in clinical and economic burden. Our aims were to know the preferences on how technologies in mental health treatment should be for use in clinical practice, and to learn about the opinion and preferences on the use of technologies in mental health treatment from the perspectives of patients with FEP, their relatives, and mental health professionals.

METHODS

Forty-one patients with a diagnosis of first-episode psychosis (FEP), 18 relatives and 49 mental health professionals were included in the study. They completed an online survey related to the use, availability and user-skill of online platforms and apps created by a group of experts in psychosis and in the use of technologies. Data were summarized in frequencies, percentages, and means, and Chi-square tests were used to calculate differences between-groups.

RESULTS

An app directed to people with psychosis would be well received by users if it contains psychoeducational material, offers reminders for scheduled visits and treatment and allows online consultations.

CONCLUSIONS

Co-creating an app with users, their families and mental health professionals allows incorporating their preferences to increase its use, improve outpatient care and creating an app that is viable in clinical practice.

Efficacy of a Smartphone App in Enhancing Medication Adherence and Accuracy in Individuals With Schizophrenia During the COVID-19 Pandemic: Randomized Controlled Trial

BACKGROUND

Poor medication adherence or inaccuracy in taking prescribed medications plays an important role in the recurrence or worsening of psychiatric symptoms in patients with schizophrenia, and the COVID-19 pandemic impacted their medication adherence with exacerbated symptoms or relapse. The use of mobile health services increased during the COVID-19 pandemic, and their role in improving mental health is becoming clearer.

OBJECTIVE

This study aimed to explore the effectiveness of a smartphone app (MedAdhere) on medication adherence and accuracy among patients with schizophrenia and to measure their psychiatric symptoms and cognitive functions.

METHODS

In this 12-week experimental study, participants were provided interventions with the MedAdhere app, and data were collected between June 2021 and September 2022. A total of 105 participants were randomly assigned to either the experimental or control groups. We used the Positive and Negative Syndrome Scale and Mini-Mental State Examination to measure the participants' psychiatric symptoms and cognitive functions. Generalized estimating equations were used for data analysis.

RESULTS

A total of 94 participants met the inclusion criteria and completed the protocol, and the medication adherence rate of the experimental group was 94.72% (2785/2940) during the intervention. Psychotic symptoms (positive, negative, and general psychopathology symptoms) and cognitive functions (memory, language, and executive function) were significantly improved in the experimental group compared to the control group after the intervention.

CONCLUSIONS

The MedAdhere app effectively and significantly improved medication adherence and, thereby, the psychiatric symptoms of patients with schizophrenia. This artificial intelligence assisted app could be extended to all patients who need to be reminded to take medication on schedule.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05892120; https://clinicaltrials.gov/study/NCT05892120.

Incorporating Community Partner Perspectives on eHealth Technology Data Sharing Practices for the California Early Psychosis Intervention Network: Qualitative Focus Group Study With a User-Centered Design Approach

BACKGROUND

Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of ethical data use practices to increase user acceptability and trust.

OBJECTIVE

First, the study explored EP community partner perspectives on data sharing best practices, including beliefs, attitudes, and preferences for ethical data sharing and how best to present end-user license agreements (EULAs). Second, we present a test case of adopting a user-centered design approach to develop a EULA protocol consistent with community partner perspectives and priorities.

METHODS

We conducted an exploratory, qualitative, and focus group-based study exploring mental health data sharing and privacy preferences among individuals involved in delivering or receiving EP care within the California Early Psychosis Intervention Network. Key themes were identified through a content analysis of focus group transcripts. Additionally, we conducted workshops using a user-centered design approach to develop a EULA that addresses participant priorities.

RESULTS

In total, 24 participants took part in the study (14 EP providers, 6 clients, and 4 family members). Participants reported being receptive to data sharing despite being acutely aware of widespread third-party sharing across digital domains, the risk of breaches, and motives hidden in the legal language of EULAs. Consequently, they reported feeling a loss of control and a lack of protection over their data. Participants indicated these concerns could be mitigated through user-level control for data sharing with third parties and an understandable, transparent EULA, including multiple presentation modalities, text at no more than an eighth-grade reading level, and a clear definition of key terms. These findings were successfully integrated into the development of a EULA and data opt-in process that resulted in 88.1% (421/478) of clients who reviewed the video agreeing to share data.

CONCLUSIONS

Many of the factors considered pertinent to informing data sharing practices in a mental health setting are consistent among clients, family members, and providers delivering or receiving EP care. These community partners' priorities can be successfully incorporated into developing EULA practices that can lead to high voluntary data sharing rates.

Exploring engagement with the CBT-informed Actissist smartphone application for early psychosis

BACKGROUND

Individuals with psychosis report favourable attitudes towards psychological interventions delivered via smartphone apps. Evidence for acceptability, safety, feasibility and efficacy is promising but in-depth reporting of app engagement in trials is sparse.

AIMS

To examine how people with psychosis engaged with the cognitive behaviour therapy (CBT)-informed Actissist app over a 12-week intervention period, and to examine factors associated with app engagement.

METHODS

Secondary data from participants in the intervention arm (n = 24) of a proof-of-concept randomised controlled trial of the Actissist app were analysed. The app prompted participants to engage with app-based CBT-informed material in five domains (voices, socialization, cannabis use, paranoia, perceived criticism) at pseudo-random intervals (three notifications per day, six days per week). Participants could self-initiate use any time. App use was financially incentivised.

RESULTS

Participants responded to 47% of app notifications. Most app engagements (87%) were app-initiated rather than self-initiated. Participants engaged most with the voices domain, then paranoia. Age and employment status were significantly associated with overall app engagement.

CONCLUSION

Individuals with psychosis engaged well with Actissist, particularly with areas focussing on voice-hearing and paranoia. App-generated reminders successfully prompted app engagement. As financial incentives may have increased app engagement, future studies of non-incentivized engagement in larger samples are needed.

A Mobile Health App (ChillTime) Promoting Emotion Regulation in Dual Disorders: Acceptability and Feasibility Pilot Study

BACKGROUND

A growing number of studies highlight the importance of emotion regulation in the treatment and recovery of individuals with psychosis and concomitant disorders such as substance use disorder (SUD), for whom access to integrated dual-disorder treatments is particularly difficult. In this context, dedicated smartphone apps may be useful tools to provide immediate support to individuals in need. However, few studies to date have focused on the development and assessment of apps aimed at promoting emotional regulation for people with psychosis.

OBJECTIVE

The aim of this study was to evaluate the feasibility, acceptability, and potential clinical impact of a dedicated app (ChillTime) for individuals with psychotic disorders and concurrent SUD. The app design process followed recommendations for reducing cognitive effort on a mobile app. A total of 20 coping strategies regrouped in four categories (behavioral, emotional, cognitive, spiritual) were included in the app.

METHODS

This open pilot study followed a pre-post design. After the initial assessment, researchers asked participants to use the app as part of their treatment over a 30-day period. Feasibility was determined by the frequency of use of the app and measured using the number of completed strategies. Acceptability was determined by measuring ease of use, ease of learning, satisfaction, and perceived utility at the end of the 30-day study period based on responses to satisfaction questionnaires. Clinical scales measuring emotion regulation, substance use (ie, type of substance, amount taken, and frequency of use), and various psychiatric symptoms were administered at the beginning and end of the 30-day period.

RESULTS

A total of 13 participants were recruited from two first-episode psychosis clinics in Montreal, Quebec, Canada. All participants were symptomatically stable, were between 18 and 35 years of age (mostly men; 70% of the sample), and had a schizophrenia spectrum disorder with a comorbid substance use diagnosis. A total of 11 participants completed the study (attrition<20%). Approximately half of the participants used the tool at least 33% of the days (11-21 days). Cognitive and emotion-focused techniques were rated the highest in terms of usefulness and were the most frequently used. The majority of participants gave positive answers about the ease of use and the ease of learning the tool. A nonsignificant association of ChillTime use with negative symptoms and drug use was observed. No other statistically significant changes were observed.

CONCLUSIONS

The ChillTime app showed good feasibility (approximately half of the participants used the tool at least 33% of the days) and acceptability among people with schizophrenia spectrum disorder and SUD. Trends suggesting a potential impact on certain clinical outcomes will need to be replicated in larger-sample studies before any conclusion can be drawn.

The Feasibility of Implementing Remote Measurement Technologies in Psychological Treatment for Depression: Mixed Methods Study on Engagement

BACKGROUND

Remote measurement technologies (RMTs) such as smartphones and wearables can help improve treatment for depression by providing objective, continuous, and ecologically valid insights into mood and behavior. Engagement with RMTs is varied and highly context dependent; however, few studies have investigated their feasibility in the context of treatment.

OBJECTIVE

A mixed methods design was used to evaluate engagement with active and passive data collection via RMT in people with depression undergoing psychotherapy. We evaluated the effects of treatment on 2 different types of engagement: study attrition (engagement with study protocol) and patterns of missing data (engagement with digital devices), which we termed data availability. Qualitative interviews were conducted to help interpret the differences in engagement.

METHODS

A total of 66 people undergoing psychological therapy for depression were followed up for 7 months. Active data were gathered from weekly questionnaires and speech and cognitive tasks, and passive data were gathered from smartphone sensors and a Fitbit (Fitbit Inc) wearable device.

RESULTS

The overall retention rate was 60%. Higher-intensity treatment (χ21=4.6; P=.03) and higher baseline anxiety (t56.28=-2.80, 2-tailed; P=.007) were associated with attrition, but depression severity was not (t50.4=-0.18; P=.86). A trend toward significance was found for the association between longer treatments and increased attrition (U=339.5; P=.05). Data availability was higher for active data than for passive data initially but declined at a sharper rate (90%-30% drop in 7 months). As for passive data, wearable data availability fell from a maximum of 80% to 45% at 7 months but showed higher overall data availability than smartphone-based data, which remained stable at the range of 20%-40% throughout. Missing data were more prevalent among GPS location data, followed by among Bluetooth data, then among accelerometry data. As for active data, speech and cognitive tasks had lower completion rates than clinical questionnaires. The participants in treatment provided less Fitbit data but more active data than those on the waiting list.

CONCLUSIONS

Different data streams showed varied patterns of missing data, despite being gathered from the same device. Longer and more complex treatments and clinical characteristics such as higher baseline anxiety may reduce long-term engagement with RMTs, and different devices may show opposite patterns of missingness during treatment. This has implications for the scalability and uptake of RMTs in health care settings, the generalizability and accuracy of the data collected by these methods, feature construction, and the appropriateness of RMT use in the long term.

User engagement in mobile apps for people with schizophrenia: A scoping review

Over the past decade, there has been an increase in the number of mobile apps designed for mental health proposes and mHealth has been perceived as a promising approach to help people with schizophrenia to manage their condition. However, adoption rates are relatively low and long-term user engagement is a major issue. The aim of this study is to identify and better understand what strategies and factors may influence user engagement and facilitate prolonged use of apps for people with schizophrenia to better manage their illness. A scoping review was conducted in accordance with the Arksey and O'Malley scoping review framework and following PRISMA ScR guidelines. The sources consisted of searching four electronic databases. Rayyan software was used for this study selection process and a narrative approach was used to synthesize the extracted data. A total of 28 studies which met the inclusion criteria were identified. The engagement strategies included push notifications, message prompts, personalization, application customization, goal setting, game-like features, use of different multimedia formats, social connectedness, support (peers and professionals), reliability of content and quality of feedback received. Some demographic factors may influence adherence such as age, gender, education level and socioeconomic status. Other factors also may play a role impacting engagement: health status, data privacy and security, involvement in design process, incentives for participation, app usage fitting in the user routines, initial training, and constant technical support. Included studies present high heterogeneity in outcome measures and thresholds criteria to assess engagement. Understanding what influences engagement and how to measure it is essential to enhance the design of mobile apps and deliver scalable solutions to help people with schizophrenia better manage their illness in their real-world uptake.

Accessibility and availability of smartphone apps for schizophrenia

App-based interventions have the potential to enhance access to and quality of care for patients with schizophrenia. However, less is known about the current state of schizophrenia apps in research and how those translate to publicly available apps. This study, therefore, aimed to review schizophrenia apps offered on marketplaces and research literature with a focus on accessibility and availability. A search of recent reviews, gray literature, PubMed, and Google Scholar was conducted in August 2022. A search of the U.S. Apple App Store and Google Play App Store was conducted in July 2022. All eligible studies and apps were systematically screened/reviewed. The academic research search produced 264 results; 60 eligible studies were identified. 51.7% of research apps were built on psychosis-specific platforms and 48.3% of research apps were built on non-specific platforms. 83.3% of research apps offered monitoring functionalities. Only nine apps, two designed on psychosis-specific platforms and seven on non-specific platforms were easily accessible. The search of app marketplaces uncovered 537 apps; only six eligible marketplace apps were identified. 83.3% of marketplace apps only offered psychoeducation. All marketplace apps lacked frequent updates with the average time since last update 1121 days. There are few clinically relevant apps accessible to patients on the commercial marketplaces. While research efforts are expanding, many research apps are unavailable today. Better translation of apps from research to the marketplace and a focus on sustainable interventions are important targets for the field.

Technology-enabled collaborative care for youth with early psychosis: Results of a feasibility study to improve physical health behaviours

AIM

Psychotic disorders are associated with excess morbidity and premature mortality. Contributing factors include tobacco smoking, low physical activity, and poor nutrition. This study tested a Technology-Enabled Collaborative Care model to improve health behaviours among youth with early psychosis.

METHODS

A feasibility study among youth (ages 16-29) with early psychosis in Ontario, Canada. Participants were randomized to either a health coach supervised by a virtual care team (high intensity, n = 29), or self-directed learning (low intensity, n = 23) for 12 weeks. The primary outcome was participant engagement, defined as self-perceived benefit of changing health behaviours. Secondary outcomes were measures of health behaviours and programme-use metrics.

RESULTS

Engagement was higher for high intensity participants for physical activity (adjusted group difference in change at 24 weeks = 3.4, CI95% = 1.9-4.9, p < .001) and nutrition (adjusted difference = 2.9, CI95% = 1.2-4.6, p = .001). No change was observed in health behaviours. Sixty two percent of participants completed 6 or more of the 12 weekly remote individualized health coaching sessions. Nine (39%) low intensity and 12 (41%) high intensity participants completed the final follow-up.

CONCLUSIONS

Personalized health coaching for youth with psychosis is feasible and may have sustained benefits. However, retention with this population for 12 weeks is challenging.

Elevated emotion reactivity and emotion regulation in individuals at clinical high risk for developing psychosis and those diagnosed with a psychotic disorder

AIMS

Disrupted affective processes are core features of psychosis; yet emotion reactivity and emotion regulation impairments have not been fully characterized in individuals at clinical high-risk for developing psychosis (CHR) or adolescents diagnosed with a psychotic disorder (AOP). Characterizing these impairments may provide a fuller understanding of factors contributing to psychosis risk and psychosis onset. Using cross-sectional and longitudinal data, we evaluated (1) group-level effects of emotion reactivity and regulation, (2) stability of group-level effects over time and age, (3) relationships between emotion reactivity and regulation, and (4) associations between these measures and psychosocial functioning and clinical symptomatology.

METHODS

Eighty-seven participants (CHR = 32, TD = 42, AOP = 13; 12-25 years, 1-5 visits) completed the Emotion Reactivity Scale, Difficulties in Emotion Regulation Scale, and Emotion Regulation Questionnaire. We assessed psychotic symptoms with the Structured Interview for Prodromal Syndromes and measured real-world functioning with the Global Functioning: Social and Role Scales. We used analysis of variance to assess Aim 1 and linear mixed models to address Aims 2-4.

RESULTS

CHR and AOP endorsed experiencing heightened levels of emotion reactivity and greater difficulty utilizing emotion regulation strategies compared to TD. These impairments were stable across time and adolescent development. Greater levels of emotion reactivity were associated with greater emotion regulation impairments. Greater impairments in emotion regulation were associated with lower social functioning and greater negative symptom severity.

CONCLUSION

Therapeutic interventions designed to reduce emotion reactivity and improve one's ability to utilize emotion regulation strategies may be effective in reducing clinical symptomatology and improving real-world functioning in CHR and AOP.

A systematic review of engagement reporting in remote measurement studies for health symptom tracking

Remote Measurement Technologies (RMTs) could revolutionise management of chronic health conditions by providing real-time symptom tracking. However, the promise of RMTs relies on user engagement, which at present is variably reported in the field. This review aimed to synthesise the RMT literature to identify how and to what extent engagement is defined, measured, and reported, and to present recommendations for the standardisation of future work. Seven databases (Embase, MEDLINE and PsycINFO (via Ovid), PubMed, IEEE Xplore, Web of Science, and Cochrane Central Register of Controlled Trials) were searched in July 2020 for papers using RMT apps for symptom monitoring in adults with a health condition, prompting users to track at least three times during the study period. Data were synthesised using critical interpretive synthesis. A total of 76 papers met the inclusion criteria. Sixty five percent of papers did not include a definition of engagement. Thirty five percent included both a definition and measurement of engagement. Four synthetic constructs were developed for measuring engagement: (i) engagement with the research protocol, (ii) objective RMT engagement, (iii) subjective RMT engagement, and (iv) interactions between objective and subjective RMT engagement. The field is currently impeded by incoherent measures and a lack of consideration for engagement definitions. A process for implementing the reporting of engagement in study design is presented, alongside a framework for definition and measurement options available. Future work should consider engagement with RMTs as distinct from the wider eHealth literature, and measure objective versus subjective RMT engagement.Registration: This review has been registered on PROSPERO [CRD42020192652].

An examination of neurocognition and theory of mind as predictors of engagement with a tailored digital therapeutic in persons with serious mental illness

There is an increasing interest in the development and implementation of digital therapeutics (apps) in individuals with serious mental illness (SMI). However, there is limited understanding of the role of neurocognition and social cognition on engagement with apps. The present study is a secondary analysis of a pilot randomized controlled trial (N = 62) comparing a tailored digital intervention to treat tobacco use disorder in individuals with SMI to a standard of care digital intervention for the general population. The purpose of this study was to examine the impact of neurocognition, social cognition, and clinical characteristics on indices of app engagement in users of the tailored app compared to users of the standard of care app. Correlational analyses demonstrated that individuals with low levels of neurocognition and social cognition engaged more often and for longer duration with the tailored app compared to the standard of care app. In a series of multilevel zero-inflated negative binomial models, assignment to the tailored app remained the most robust predictor of app interactions (Risk Ratio [RR] = 1.72; p < .01), duration of app use (RR = 6.47; p < .01), and average length of interaction (RR = 2.70; p < .01), after adjusting for key demographic and clinical characteristics, and two measures of cognition. This is one of the first studies to demonstrate that digital therapeutics can be designed to mitigate the impact of neurocognition and social cognition on device engagement in SMI populations. Recommendations are made to advance the use of new analytic models to uncover patterns of engagement with digital therapeutics.

Multipurpose Mobile Apps for Mental Health in Chinese App Stores: Content Analysis and Quality Evaluation

Background

Mental disorders impose varying degrees of burden on patients and their surroundings. However, people are reluctant to take the initiative to seek mental health services because of the uneven distribution of resources and stigmatization. Thus, mobile apps are considered an effective way to eliminate these obstacles and improve mental health awareness.

Objective

This study aims to evaluate the quality, function, privacy measures, and evidence-based and professional background of multipurpose mental health apps in Chinese commercial app stores.

Methods

A systematic search was conducted on iOS and Android platforms in China to identify multipurpose mental health apps. Two independent reviewers evaluated the identified mobile apps using the Mobile App Rating Scale (MARS). Each app was downloaded, and the general characteristics, privacy and security measures, development background, and functional characteristics of each app were evaluated.

Results

A total of 40 apps were analyzed, of which 35 (87.5%) were developed by companies and 33 (82.5%) provided links to access the privacy policy; 21 (52.5%) apps did not mention the involvement of relevant professionals or the guidance of a scientific basis in the app development process. The main built-in functions of these apps include psychological education (38/40, 95%), self-assessment (34/40, 85%), and counseling (33/40, 82.5%). The overall quality average MARS score of the 40 apps was 3.54 (SD 0.39), and the total score was between 2.96 and 4.30. The total MARS score was significantly positively correlated with the scores of each subscale (r=0.62-0.88, P<.001). However, the user score of the app market was not significantly correlated with the total MARS score (r=0.17, P=.33).

Conclusions

The quality of multipurpose mental health apps in China’s main app market is generally good. However, health professionals are less involved in the development of these apps, and the privacy protection policy of the apps also needs to be described in more detail. This study provides a reference for the development of multipurpose mental health apps.

The Extent of User Involvement in the Design of Self-tracking Technology for Bipolar Disorder: Literature Review

BACKGROUND

The number of self-monitoring apps for bipolar disorder (BD) is increasing. The involvement of users in human-computer interaction (HCI) research has a long history and is becoming a core concern for designers working in this space. The application of models of involvement, such as user-centered design, is becoming standardized to optimize the reach, adoption, and sustained use of this type of technology.

OBJECTIVE

This paper aims to examine the current ways in which users are involved in the design and evaluation of self-monitoring apps for BD by investigating 3 specific questions: are users involved in the design and evaluation of technology? If so, how does this happen? And what are the best practice ingredients regarding the design of mental health technology?

METHODS

We reviewed the available literature on self-tracking technology for BD and make an overall assessment of the level of user involvement in design. The findings were reviewed by an expert panel, including an individual with lived experience of BD, to form best practice ingredients for the design of mental health technology. This combines the existing practices of patient and public involvement and HCI to evolve from the generic guidelines of user-centered design and to those that are tailored toward mental health technology.

RESULTS

For the first question, it was found that out of the 11 novel smartphone apps included in this review, 4 (36%) self-monitoring apps were classified as having no mention of user involvement in design, 1 (9%) self-monitoring app was classified as having low user involvement, 4 (36%) self-monitoring apps were classified as having medium user involvement, and 2 (18%) self-monitoring apps were classified as having high user involvement. For the second question, it was found that despite the presence of extant approaches for the involvement of the user in the process of design and evaluation, there is large variability in whether the user is involved, how they are involved, and to what extent there is a reported emphasis on the voice of the user, which is the ultimate aim of such design approaches. For the third question, it is recommended that users are involved in all stages of design with the ultimate goal of empowering and creating empathy for the user.

CONCLUSIONS

Users should be involved early in the design process, and this should not just be limited to the design itself, but also to associated research ensuring end-to-end involvement. Communities in health care-based design and HCI design need to work together to increase awareness of the different methods available and to encourage the use and mixing of the methods as well as establish better mechanisms to reach the target user group. Future research using systematic literature search methods should explore this further.

Portable technologies for digital phenotyping of bipolar disorder: A systematic review

BACKGROUND

Bias-prone psychiatric interviews remain the mainstay of bipolar disorder (BD) assessment. The development of digital phenotyping promises to improve BD management. We present a systematic review of the evidence about the use of portable digital devices for the identification of BD, BD types and BD mood states and for symptom assessment.

METHODS

We searched Web of Knowledge^SM, Scopus ®, IEEE Xplore, and ACM Digital Library databases (until 5/1/2021) for articles evaluating the use of portable/wearable digital devices, such as smartphone apps, wearable sensors, audio and/or visual recordings, and multimodal tools. The protocol is registered in PROSPERO (CRD42020200086).

RESULTS

We included 62 studies (2325 BD; 724 healthy controls, HC): 27 using smartphone apps, either for recording self-assessments (n = 10) or for passively gathering metadata (n = 7) or both (n = 10); 15 using wearable sensors for physiological parameters; 17 analysing audio and/or video recordings; 3 using multiple technologies. Two thirds of the included studies applied artificial intelligence (AI)-based approaches. They achieved fair to excellent classification performances.

LIMITATIONS

The included studies had small sample sizes and marked heterogeneity. Evidence of overfitting emerged, limiting generalizability. The absence of clear guidelines about reporting classification performances, with no shared standard metrics, makes results hardly interpretable and comparable.

CONCLUSIONS

New technologies offer a noteworthy opportunity to BD digital phenotyping with objectivity and high granularity. AI-based models could deliver important support in clinical decision-making. Further research and cooperation between different stakeholders are needed for addressing methodological, ethical and socio-economic considerations.

Systematic Review of Digital Phenotyping and Machine Learning in Psychosis Spectrum Illnesses

BACKGROUND

Digital phenotyping is the use of data from smartphones and wearables collected in situ for capturing a digital expression of human behaviors. Digital phenotyping techniques can be used to analyze both passively (e.g., sensor) and actively (e.g., survey) collected data. Machine learning offers a possible predictive bridge between digital phenotyping and future clinical state. This review examines passive digital phenotyping across the schizophrenia spectrum and bipolar disorders, with a focus on machine-learning studies.

METHODS

A systematic review of passive digital phenotyping literature was conducted using keywords related to severe mental illnesses, data-collection devices (e.g., smartphones, wearables, actigraphy devices), and streams of data collected. Searches of five databases initially yielded 3312 unique publications. Fifty-one studies were selected for inclusion, with 16 using machine-learning techniques.

RESULTS

All studies differed in features used, data pre-processing, analytical techniques, algorithms tested, and performance metrics reported. Across all studies, the data streams and other study factors reported also varied widely. Machine-learning studies focused on random forest, support vector, and neural net approaches, and almost exclusively on bipolar disorder.

DISCUSSION

Many machine-learning techniques have been applied to passively collected digital phenotyping data in schizophrenia and bipolar disorder. Larger studies, and with improved data quality, are needed, as is further research on the application of machine learning to passive digital phenotyping data in early diagnosis and treatment of psychosis. In order to achieve greater comparability of studies, common data elements are identified for inclusion in future studies.

An Integrated Account of Expert Perspectives on Functioning in Schizophrenia

An integrated and interdisciplinary care system for individuals with schizophrenia is essential, which implies the need for a tool that assesses the difficulties and contextual factors of relevance to their functioning, and facilitates coordinated working across the different professions involved in their care. The International Classification of Functioning, Disability and Health Core Sets (ICF-CS) cover these requirements. This study aimed to evaluate the content validity of the ICF-CSs for schizophrenia from the perspective of experts. Six three-round Delphi studies were conducted with expert panels from different professional backgrounds which have played a significant role in the treatment of individuals with schizophrenia (psychiatry, psychology, nursing, occupational therapy, social work and physiotherapy). In total, 790 experts from 85 different countries participated in the first round. In total, 90 ICF categories and 28 Personal factors reached expert consensus (reached consensus from four or more professional perspectives). All the categories in the brief version of the ICF-CS for schizophrenia reached consensus from all the professional perspectives considered. As for the comprehensive version, 89.7% of its categories reached expert consensus. The results support the worldwide content validity of the ICF-CSs for schizophrenia from an expert perspective and underline the importance of assessing functioning by considering all the components implied.

PLAN-e-PSY, a mobile application to improve case management and patient's functioning in first episode psychosis: protocol for an open-label, multicentre, superiority, randomised controlled trial

INTRODUCTION

The prognosis of first episode psychosis (FEP), which is a severe disorder, can be notably impaired by patients' disengagement from healthcare providers. Coordinated specialty care with case management is now considered as the gold standard in this population, but there are still challenges for engagement with subsequent functional impairments. Youth-friendly and patient-centred clinical approaches are sought to improve engagement in patients with FEP. Mobile applications are widely used by young people, including patients with FEP, and can increase the youth friendliness of clinical tools. We hypothesise that a co-designed mobile application used during case management can improve functioning in patients with FEP as compared with usual case management practices.

METHODS AND ANALYSIS

A mobile case management application for planning and monitoring individualised care objectives will be co-designed with patients, caregivers and health professionals in a recovery-oriented approach. The application will be compared with usual case management practices in a multicentre, two-arm and parallel groups clinical trial. Patients will be recruited by specialised FEP teams. Impact on functioning will be assessed using the Personal and Social Performance Scale; the variation between baseline and 12 months in each group (control and active) will be the primary outcome.

ETHICS AND DISSEMINATION

This study has been approved by the Inserm Institutional Review Board IRB00003888 (Comité d'évaluation éthique de l'INSERM, reference number 20-647). The results of the study will be published in a peer-reviewed journal and presented at national and international conferences. We will also communicate the results to patients and family representatives' associations. An optimised version of the application will be then disseminated through the French FEP network (Transition Network).

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov: NCT04657380.

Improving social functioning in people with schizophrenia-spectrum disorders via mobile experimental interventions: Results from the CLIMB pilot trial

Background

Patients with Schizophrenia Spectrum Disorders (SSD) demonstrate poor social functioning. While group-based approaches show long-term improvements, access to treatments is limited. Digital platforms hold promise to overcome barriers to treatment delivery and improve outcomes.

Objective

In a parallel arm, double-blind RCT, we tested CLIMB, a clinician-assisted, adjunct to treatment that includes computerized social cognition training (SCT), ecological momentary assessments (EMAs), group tele-therapy, and moderated messaging. CLIMB was compared to an active control that includes computerized general cognitive training (GCT), unstructured support groups, and unmoderated messaging.

Methods

The primary outcome was social functioning. Secondary outcomes were negative symptoms and quality of life (QoL). Given the sample size, Propensity Score Models were used to ensure balanced baseline covariates. Mixed-effects models examined change over time.

Results

24 participants completed the study (12 per arm). No significant between-group differences emerged in engagement. CLIMB participants engaged in a median of 8 sessions (IQR = 2), 2.8 h of SCT (IQR = 7.5), and 2710 EMAs; control participants engaged in a median of 9 sessions (IQR = 3) and 2.2 h of GCT (IQR = 7.9). As a group, participants showed significant improvements in social functioning (p = .046), with no between-group differences. Intent-to-treat analyses indicated greater improvements in QoL (p = .025) for the active control.

Conclusions

Delivering group-based mobile interventions to individuals with SSD is feasible. EMAs allow clinicians to maintain inter-session engagement, build participant self-awareness, and tailor treatment delivery. In this treatment model, whether SCT or GCT is more effective remains unclear. Further research will evaluate group-based mobile interventions to improve outcomes in SSD.

Use of Ecological Momentary Assessment Through a Passive Smartphone-Based App (eB2) by Patients With Schizophrenia: Acceptability Study

Background

Ecological momentary assessment (EMA) tools appear to be useful interventions for collecting real-time data on patients’ behavior and functioning. However, concerns have been voiced regarding the acceptability of EMA among patients with schizophrenia and the factors influencing EMA acceptability.

Objective

The aim of this study was to investigate the acceptability of a passive smartphone-based EMA app, evidence-based behavior (eB2), among patients with schizophrenia spectrum disorders and the putative variables underlying their acceptance.

Methods

The participants in this study were from an ongoing randomized controlled trial (RCT) of metacognitive training, consisting of outpatients with schizophrenia spectrum disorders (F20-29 of 10th revision of the International Statistical Classification of Diseases and Related Health Problems), aged 18-64 years, none of whom received any financial compensation. Those who consented to installation of the eB2 app (users) were compared with those who did not (nonusers) in sociodemographic, clinical, premorbid adjustment, neurocognitive, psychopathological, insight, and metacognitive variables. A multivariable binary logistic regression tested the influence of the above (independent) variables on “being user versus nonuser” (acceptability), which was the main outcome measure.

Results

Out of the 77 RCT participants, 24 (31%) consented to installing eB2, which remained installed till the end of the study (median follow-up 14.50 weeks) in 14 participants (70%). Users were younger and had a higher education level, better premorbid adjustment, better executive function (according to the Trail Making Test), and higher cognitive insight levels (measured with the Beck Cognitive Insight Scale) than nonusers (univariate analyses) although only age (OR 0.93, 95% CI 0.86-0.99; P=.048) and early adolescence premorbid adjustment (OR 0.75, 95% CI 0.61-0.93; P=.01) survived the multivariable regression model, thus predicting eB2 acceptability.

Conclusions

Acceptability of a passive smartphone-based EMA app among participants with schizophrenia spectrum disorders in this RCT where no participant received financial compensation was, as expected, relatively low, and linked with being young and good premorbid adjustment. Further research should examine how to increase EMA acceptability in patients with schizophrenia spectrum disorders, in particular, older participants and those with poor premorbid adjustment.

Trial Registration

ClinicalTrials.gov NCT04104347; https://clinicaltrials.gov/ct2/show/NCT04104347

Mapping brain-behavior space relationships along the psychosis spectrum

Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 PSD patients spanning several diagnoses, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results with current sample sizes. However, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and neural gene expression maps derived from the Allen Human Brain Atlas. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.

Creative Technology-Based Strategies for Engaging Young People with Serious Mental Health Conditions in Longitudinal Mental Health Services Research

A better understanding of the transition from child to adult community mental health services is important given the high rates of service drop-out. Conducting longitudinal research is challenging during a major service provider change. Developmentally-typical transition-to-adulthood instability can deter study engagement. This study examines the efficacy of creative technology-based strategies to recruit and engage adolescents and young adults (AYA) with serious mental health diagnoses in a qualitative study during their transition from child to adult services. Participants were recruited from one agency to complete three in-depth qualitative interviews and monthly surveys exploring mental health service experiences over 12-months. Participants received a smartphone and data plan for 6-months at initial interview, $50 at 6-month interview and $55 at 12-month interview. Four research assistants used a shared Google Voice account to text monthly online surveys and to communicate with participants. 19 participants enrolled; 74% remained enrolled across the 12-months. Smartphones and data plans were not effective in recruiting nor sustaining study engagement for most participants. Participants preferred a mix of texting and phone calls to prompt study engagement; 60% of online surveys were completed. Unanticipated participant-researcher communication outside of research scope suggests that the formation of strong relationships and additional support during this transitional time is critical for sustained study engagement. Study findings have practical implications for social work longitudinal research design and effective study implementation. Future social work research is warranted on innovative strategies to boost study and service engagement among AYA with serious co-occurring mental health and developmental instability.

Engagement with online psychosocial interventions for psychosis: A review and synthesis of relevant factors

BACKGROUND

Little is known about factors associated with engagement with online interventions for psychosis. This review aimed to synthesise existing data from relevant literature to develop a working model of potential variables that may impact on engagement with online interventions for psychosis.

METHODS

Online databases were searched for studies relevant to predictors of engagement with online interventions for psychosis; predictors of Internet use amongst individuals with psychosis; and predictors of engagement with traditional psychosocial treatments for psychosis. Data were synthesised into a conceptual model highlighting factors relevant to engagement with online interventions for psychosis.

RESULTS

Sixty-one studies were identified. Factors relevant to engagement related directly to the impact of psychosis, response to psychosis, integration of technology into daily lives and intervention aspects.

CONCLUSION

While several candidate predictors were identified, there is minimal research specifically investigated predictors of engagement with online interventions for psychosis. Further investigation examining both individual- and intervention-related factors is required to inform effective design and dissemination of online interventions for psychosis.

Expanding the Reach of Research: Quantitative Evaluation of a Web-Based Approach for Remote Recruitment of People Who Hear Voices

Background

Similar to other populations with highly stigmatized medical or psychiatric conditions, people who hear voices (ie, experience auditory verbal hallucinations [AVH]) are often difficult to identify and reach for research. Technology-assisted remote research strategies reduce barriers to research recruitment; however, few studies have reported on the efficiency and effectiveness of these approaches.

Objective

This study introduces and evaluates the efficacy of technology-assisted remote research designed for people who experience AVH.

Methods

Our group developed an integrated, automated and human complementary web-based recruitment and enrollment apparatus that incorporated Google Ads, web-based screening, identification verification, hybrid automation, and interaction with live staff. We examined the efficacy of that apparatus by examining the number of web-based advertisement impressions (ie, number of times the web-based advertisement was viewed); clicks on that advertisement; engagement with web-based research materials; and the extent to which it succeeded in representing a broad sample of individuals with AVH, assessed through the self-reported AVH symptom severity and demographic representativeness (relative to the US population) of the sample recruited.

Results

Over an 18-month period, our Google Ads advertisement was viewed 872,496 times and clicked on 11,183 times. A total amount of US $4429.25 was spent on Google Ads, resulting in 772 individuals who experience AVH providing consent to participate in an entirely remote research study (US $0.40 per click on the advertisement and US $5.73 per consented participant) after verifying their phone number, passing a competency screening questionnaire, and providing consent. These participants reported high levels of AVH frequency (666/756, 88.1% daily or more), distress (689/755, 91.3%), and functional interference (697/755, 92.4%). They also represented a broad sample of diversity that mirrored the US population demographics. Approximately one-third (264/756, 34.9%) of the participants had never received treatment for their AVH and, therefore, were unlikely to be identified via traditional clinic-based research recruitment strategies.

Conclusions

Web-based procedures allow for time saving, cost-efficient, and representative recruitment of individuals with AVH and can serve as a model for future studies focusing on hard-to-reach populations.

Patient electronic communication data in clinical care: what is known and what is needed

The novel coronavirus (COVID-19) and physical distancing guidelines around the world have resulted in unprecedented changes to normal routine and increased smartphone use to maintain social relationships and support. Reports of depressive and anxiety symptom are on the rise, contributing to suffering among people-especially adolescents and young adults-with pre-existing mental health conditions. Psychiatric care has shifted primarily to telehealth limiting the important patient nonverbal communication that has been part of in-person clinical sessions. Supplementing clinical care with patient electronic communication (EC) data may provide valuable information and influence treatment decision making. Research in the impact of patient EC data on managing psychiatric symptoms is in its infancy. This review aims to identify how patient EC has been used in clinical care and its benefits in psychiatry and research. We discuss smartphone applications used to gather different types of EC data, how data have been integrated into clinical care, and implications for clinical care and research.

Can Smartphone Apps Assist People with Serious Mental Illness in Taking Medications as Prescribed?

Adherence research commonly happens in a silo, focused on a particular disease state or type of therapy. Learning from outside disciplines can bring new insights and ideas. This article presents adherence research as related to people with a diagnosis of a serious mental illness (SMI) and medication adherence through smartphone applications (apps). Individuals with SMI have high rates of not taking medication, increasing risks of relapse and hospitalization. Advances in technology may be advantageous in promoting taking medication. Smartphones apps have been designed for people with SMI. Further research is needed to evaluate their efficacy on improving rates of taking medication.

Integration of a smartwatch within an internet-delivered intervention for depression: Protocol for a feasibility randomized controlled trial on acceptance

BACKGROUND

Mood tracking is commonly employed within a range of mental health interventions. Physical activity and sleep are also important for contextualizing mood data but can be difficult to track manually and rely on retrospective recall. Smartwatches could enhance self-monitoring by addressing difficulties in recall of sleep and physical activity and reducing the burden on patients in terms of remembering to track and the effort of tracking. This feasibility study will explore the acceptance of a smartwatch app for self-monitoring of mood, sleep, and physical activity, in an internet-based cognitive-behavioral therapy (iCBT) for depression offered in a routine care setting.

METHODS

Seventy participants will be randomly allocated to (i) iCBT intervention plus smartwatch app or (ii) iCBT intervention alone. Patient acceptance will be measured longitudinally using a theory-based acceptance questionnaire to understand and compare the evolution of acceptance of the technology-delivered self-report in the two groups. A post-treatment interview will explore participants subjective experience of using the smartwatch. Engagement with the intervention, including self-report, and clinical outcomes, will be measured across both groups to assess for any differences.

IMPLICATIONS

This is the first study investigating the evolution of patient acceptance of smartwatch self-report in an iCBT delivered intervention in a clinical sample. Through an engaging and convenient means of capturing ecologically valid mood data, the study has the potential to show that smartwatches are an acceptable means for patient self-monitoring within iCBT interventions for depression and support potential use-cases for smartwatches in the context of mental health interventions in general. Prospectively registered at ClinicalTrials.gov (NCT04568317).

Digital biomarkers from geolocation data in bipolar disorder and schizophrenia: a systematic review

OBJECTIVE

The study sought to explore to what extent geolocation data has been used to study serious mental illness (SMI). SMIs such as bipolar disorder and schizophrenia are characterized by fluctuating symptoms and sudden relapse. Currently, monitoring of people with an SMI is largely done through face-to-face visits. Smartphone-based geolocation sensors create opportunities for continuous monitoring and early intervention.

MATERIALS AND METHODS

We searched MEDLINE, PsycINFO, and Scopus by combining terms related to geolocation and smartphones with SMI concepts. Study selection and data extraction were done in duplicate.

RESULTS

Eighteen publications describing 16 studies were included in our review. Eleven studies focused on bipolar disorder. Common geolocation-derived digital biomarkers were number of locations visited (n = 8), distance traveled (n = 8), time spent at prespecified locations (n = 7), and number of changes in GSM (Global System for Mobile communications) cell (n = 4). Twelve of 14 publications evaluating clinical aspects found an association between geolocation-derived digital biomarker and SMI concepts, especially mood. Geolocation-derived digital biomarkers were more strongly associated with SMI concepts than other information (eg, accelerometer data, smartphone activity, self-reported symptoms). However, small sample sizes and short follow-up warrant cautious interpretation of these findings: of all included studies, 7 had a sample of fewer than 10 patients and 11 had a duration shorter than 12 weeks.

CONCLUSIONS

The growing body of evidence for the association between SMI concepts and geolocation-derived digital biomarkers shows potential for this instrument to be used for continuous monitoring of patients in their everyday lives, but there is a need for larger studies with longer follow-up times.

mHealth-Assisted Detection of Precursors to Relapse in Schizophrenia

Theoretical views and a growing body of empirical evidence suggest that psychiatric relapses in schizophrenia-spectrum disorders (SSDs) have measurable warning signs. However, because they are time- and resource-intensive, existing assessment approaches are not well-suited to detect these warning signs in a timely, scalable fashion. Mobile technologies deploying frequent measurements-i.e., ecological momentary assessment-could be leveraged to detect increases in symptoms that may precede relapses. The present study examined EMA measurements with growth curve models in the 100 days preceding and following 27 relapses (among n = 20 individuals with SSDs) to identify (1) what symptoms changed in the periods gradually preceding, following, and right as relapses occur, (2) how large were these changes, and (3) on what time scale did they occur. Results demonstrated that, on average, participants reported elevations in negative mood (d = 0.34), anxiety (d =0.49), persecutory ideation (d =0.35), and hallucinations (d =0.34) on relapse days relative to their average during the study. These increases emerged gradually on average from significant and steady increases (d = 0.05 per week) in persecutory ideation and hallucinations over the 100-day period preceding relapse. This suggests that brief (i.e., 1-2 item) assessments of psychotic symptoms may detect meaningful signals that precede psychiatric relapses long before they occur. These assessments could increase opportunities for relapse prevention as remote measurement-based care management platforms develop.

A systematic review of smartphone apps for gastro-oesophageal reflux disease: the need for regulation and medical professional involvement

BACKGROUND

Expansion in smartphone use and mobile health (mHealth) apps has generated a large and unregulated sector. Gastro-oesophageal Reflux Disease (GORD) is a widely prevalent disease in the UK. The aim of this study is to evaluate the smartphone apps focused on GORD, available on major digital platforms, with particular emphasis on their recorded evidence base (EB) and the extent of medical professional involvement (MPI) in their constitution.

METHODS

Relevant apps were extracted using defined search terms and inclusion (using a wide array of search terms) and exclusion criteria (non-English language, duplicates) were applied. Data was collected from the overview provided by the developer in the app store and from the developer website for each app, and classified according to various variables. EB and professional involvement data was obtained from the application details provided in the app stores as well as information section of individual apps.

RESULTS

A vast majority of the apps (97.3%) were developed targeting the general public. Of the 73 apps, 11 (15.1%) had a documented EB. Two apps stated if healthcare professionals were involved in the development, screening or assessment of the app content, meaning only 2.73% of the apps (2/73) stated their content had been contributed by medical professionals (individual, group or organisation of health providers). Thirty-four apps had recent updates in 2019 (47%, 34/73).

CONCLUSIONS

Regulation and accreditation of mHealth apps related to GORD are needed.

Automatically Generated Smartphone Data in Young Patients With Newly Diagnosed Bipolar Disorder and Healthy Controls

Background: Smartphones may facilitate continuous and fine-grained monitoring of behavioral activities via automatically generated data and could prove to be especially valuable in monitoring illness activity in young patients with bipolar disorder (BD), who often present with rapid changes in mood and related symptoms. The present pilot study in young patients with newly diagnosed BD and healthy controls (HC) aimed to (1) validate automatically generated smartphone data reflecting physical and social activity and phone usage against validated clinical rating scales and questionnaires; (2) investigate differences in automatically generated smartphone data between young patients with newly diagnosed BD and HC; and (3) investigate associations between automatically generated smartphone data and smartphone-based self-monitored mood and activity in young patients with newly diagnosed BD. Methods: A total of 40 young patients with newly diagnosed BD and 21 HC aged 15-25 years provided daily automatically generated smartphone data for 3-779 days [median (IQR) = 140 (11.5-268.5)], in addition to daily smartphone-based self-monitoring of activity and mood. All participants were assessed with clinical rating scales. Results: (1) The number of outgoing phone calls was positively associated with scores on the Young Mania Rating Scale and subitems concerning activity and speech. The number of missed calls (p = 0.015) and the number of outgoing text messages (p = 0.017) were positively associated with the level of psychomotor agitation according to the Hamilton Depression Rating scale subitem 9. (2) Young patients with newly diagnosed BD had a higher number of incoming calls compared with HC (BD: mean = 1.419, 95% CI: 1.162, 1.677; HC: mean = 0.972, 95% CI: 0.637, 1.308; p = 0.043) and lower self-monitored mood and activity (p's < 0.001). (3) Smartphone-based self-monitored mood and activity were positively associated with step counts and the number of outgoing calls, respectively (p's < 0.001). Conclusion: Automatically generated data on physical and social activity and phone usage seem to reflect symptoms. These data differ between young patients with newly diagnosed BD and HC and reflect changes in illness activity in young patients with BD. Automatically generated smartphone-based data could be a useful clinical tool in diagnosing and monitoring illness activity in young patients with BD.

Assessing the relationship between routine and schizophrenia symptoms with passively sensed measures of behavioral stability

Increased stability in one's daily routine is associated with well-being in the general population and often a goal of behavioral interventions for people with serious mental illnesses like schizophrenia. Assessing behavioral stability has been limited in clinical research by the use of retrospective scales, which are susceptible to reporting biases and memory inaccuracies. Mobile passive sensors, which are less susceptible to these sources of error, have emerged as tools to assess behavioral patterns in a range of populations. The present study developed and examined a metric of behavioral stability from data generated by a passive sensing system carried by 61 individuals with schizophrenia for one year. This metric-the Stability Index-appeared orthogonal from existing measures drawn from passive sensors and matched the predictive performance of state-of-the-art features. Specifically, greater stability in social activity (e.g., calls and messages) were associated with lower symptoms, and greater stability in physical activity (e.g., being still) appeared associated with elevated symptoms. This study provides additional support for the predictive value of individualized over population-level data in psychiatric populations. The Stability Index offers also a promising tool for generating insights about the impact of behavioral stability in schizophrenia-spectrum disorders.

Single-Subject Research in Psychiatry: Facts and Fictions

Scientific evidence in the field of psychiatry is mainly derived from group-based ("nomothetic") studies that yield group-aggregated results, while often the need is to answer questions that apply to individuals. Particularly in the presence of great inter-individual differences and temporal complexities, information at the individual-person level may be valuable for personalized treatment decisions, individual predictions and diagnostics. The single-subject study design can be used to make inferences about individual persons. Yet, the single-subject study is not often used in the field of psychiatry. We believe that this is because of a lack of awareness of its value rather than a lack of usefulness or feasibility. In the present paper, we aimed to resolve some common misconceptions and beliefs about single-subject studies by discussing some commonly heard "facts and fictions." We also discuss some situations in which the single-subject study is more or less appropriate, and the potential of combining single-subject and group-based study designs into one study. While not intending to plea for single-subject studies at the expense of group-based studies, we hope to increase awareness of the value of single-subject research by informing the reader about several aspects of this design, resolving misunderstanding, and providing references for further reading.

Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review

BACKGROUND

Psychiatric disorders often have an onset at an early age, and early identification and intervention help improve prognosis. A fine-grained, unobtrusive, and effective way to monitor symptoms and level of function could help distinguish severe psychiatric health problems from normal behavior and potentially lead to a more efficient use of clinical resources in the current health care system. The use of smartphones to monitor and treat children, adolescents, and young adults with psychiatric disorders has been widely investigated. However, no systematic review concerning smartphone-based monitoring and treatment in this population has been published.

OBJECTIVE

This systematic review aims at describing the following 4 features of the eligible studies: (1) monitoring features such as self-assessment and automatically generated data, (2) treatment delivered by the app, (3) adherence to self-monitoring, and (4) results of the individual studies.

METHODS

We conducted a systematic literature search of the PubMed, Embase, and PsycInfo databases. We searched for studies that (1) included a smartphone app to collect self-monitoring data, a smartphone app to collect automatically generated smartphone-based data, or a smartphone-based system for treatment; (2) had participants who were diagnosed with psychiatric disorders or received treatment for a psychiatric disorder, which was verified by an external clinician; (3) had participants who were younger than 25 years; and (4) were published in a peer-reviewed journal. This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The risk of bias in each individual study was systematically assessed.

RESULTS

A total of 2546 unique studies were identified through literature search; 15 of these fulfilled the criteria for inclusion. These studies covered 8 different diagnostic groups: psychosis, eating disorders, depression, autism, self-harm, anxiety, substance abuse, and suicidal behavior. Smartphone-based self-monitoring was used in all but 1 study, and 11 of them reported on the participants' adherence to self-monitoring. Most studies were feasibility/pilot studies, and all studies on feasibility reported positive attitudes toward the use of smartphones for self-monitoring. In 2 studies, automatically generated data were collected. Three studies were randomized controlled trials investigating the effectiveness of smartphone-based monitoring and treatment, with 2 of these showing a positive treatment effect. In 2 randomized controlled trials, the researchers were blinded for randomization, but the participants were not blinded in any of the studies. All studies were determined to be at high risk of bias in several areas.

CONCLUSIONS

Smartphones hold great potential as a modern, widely available technology platform to help diagnose, monitor, and treat psychiatric disorders in children and adolescents. However, a higher level of homogeneity and rigor among studies regarding their methodology and reporting of adherence would facilitate future reviews and meta-analyses.

Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

BACKGROUND

Designing technologies that users will be interested in, start using, and keep using has long been a challenge. In the health domain, the question of technology acceptance is even more important, as the possible intrusiveness of technologies could lead to patients refusing to even try them. Developers and researchers must address this question not only in the design and evaluation of new health care technologies but also across the different stages of the user's journey. Although a range of definitions for these stages exists, many researchers conflate related terms, and the field would benefit from a coherent set of definitions and associated measurement approaches.

OBJECTIVE

This review aims to explore how technology acceptance is interpreted and measured in mobile health (mHealth) literature. We seek to compare the treatment of acceptance in mHealth research with existing definitions and models, identify potential gaps, and contribute to the clarification of the process of technology acceptance.

METHODS

We searched the PubMed database for publications indexed under the Medical Subject Headings terms "Patient Acceptance of Health Care" and "Mobile Applications." We included publications that (1) contained at least one of the terms "acceptability," "acceptance," "adoption," "accept," or "adopt"; and (2) defined the term. The final corpus included 68 relevant studies.

RESULTS

Several interpretations are associated with technology acceptance, few consistent with existing definitions. Although the literature has influenced the interpretation of the concept, usage is not homogeneous, and models are not adapted to populations with particular needs. The prevalence of measurement by custom surveys suggests a lack of standardized measurement tools.

CONCLUSIONS

Definitions from the literature were published separately, which may contribute to inconsistent usage. A definition framework would bring coherence to the reporting of results, facilitating the replication and comparison of studies. We propose the Technology Acceptance Lifecycle, consolidating existing definitions, articulating the different stages of technology acceptance, and providing an explicit terminology. Our findings illustrate the need for a common definition and measurement framework and the importance of viewing technology acceptance as a staged process, with adapted measurement methods for each stage.

A pilot digital intervention targeting loneliness in young people with psychosis

PURPOSE

Loneliness has been identified as a significant challenge for people with psychosis. Interventions targeting loneliness are lacking but adopting a positive psychology approach may reduce loneliness, promote well-being, and support meaningful social interactions. Together with youth mental health consumers, we developed a digital smartphone application (app) called +Connect, which delivers positive psychology content daily for 6 weeks.

MATERIALS AND METHODS

Twelve participants diagnosed with a psychotic disorder were recruited from early psychosis services. Loneliness was assessed pre-intervention, post-intervention, and 3-month post-intervention. Acceptability, feasibility, and usability were measured post-intervention, including a semi-structured interview on the user's experience of +Connect.

RESULTS

We found evidence for the feasibility of +Connect. All but two participants completed the +Connect program, completing 95% (40.10 out of 42 days) of the program. Furthermore, 66.67% (8 out of the 12 participants) remained engaged with the program 3-months post-intervention. Our data indicates preliminary evidence that +Connect may reduce loneliness, with scores from pre-intervention (M = 50.00, SD = 8.47) to post-intervention (M = 48.10, SD = 10.38) and 3-months post-intervention (M = 42.89, SD = 7.04). We found that positive reinforcement of in-game rewards and evidence of positive mood changes added to the feasibility of the app. Regarding acceptability, while 10% (1/10 participants) reported not finding +Connect useful or enjoyable, 90% of participants agreed that +Connect helped them to increase their social confidence, enjoy life, look forward to being with other people, and feel more connected with others. Participant interviews supported these results, with participants highlighting the app's strengths in providing useful information, stimulating self-reflection, fostering positive affect, and encouraging transfer of skills into their social interactions.

DISCUSSION

While preliminary findings indicated that +Connect yielded high levels of acceptability and feasibility, it is important to consider that we recruited a small and selected sample of lonely young people. Further iterations of this proof of concept app, which can incorporate participant feedback such preferences for increased personalisation, in-app feedback, and gamification, may allow an opportunity to test an improved version in the future.

How Are Information and Communication Technologies Supporting Routine Outcome Monitoring and Measurement-Based Care in Psychotherapy? A Systematic Review

Psychotherapy has proven to be effective for a wide range of mental health problems. However, not all patients respond to the treatment as expected (not-on-track patients). Routine outcome monitoring (ROM) and measurement-based care (MBC), which consist of monitoring patients between appointments and using this data to guide the intervention, have been shown to be particularly useful for these not-on-track patients. Traditionally, though, ROM and MBC have been challenging, due to the difficulties associated with repeated monitoring of patients and providing real-time feedback to therapists. The use of information and communication technologies (ICTs) might help reduce these challenges. Therefore, we systematically reviewed evidence regarding the use of ICTs for ROM and MBC in face-to-face psychological interventions for mental health problems. The search included published and unpublished studies indexed in the electronic databases PubMed, PsycINFO, and SCOPUS. Main search terms were variations of the terms “psychological treatment”, “progress monitoring or measurement-based care”, and “technology”. Eighteen studies met eligibility criteria. In these, ICTs were frequently handheld technologies, such as smartphone apps, tablets, or laptops, which were involved in the whole process (assessment and feedback). Overall, the use of technology for ROM and MBC during psychological interventions was feasible and acceptable. In addition, the use of ICTs was found to be effective, particularly for not-on-track patients, which is consistent with similar non-ICT research. Given the heterogeneity of reviewed studies, more research and replication is needed to obtain robust findings with different technological solutions and to facilitate the generalization of findings to different mental health populations.

Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-Being, Engagement, and Recovery: Protocol for a Feasibility Cluster Randomized Controlled Trial Harnessing Mobile Phone Technology Blended With Peer Support

Background

Relapse in schizophrenia is a major cause of distress and disability and is predicted by changes in symptoms such as anxiety, depression, and suspiciousness (early warning signs [EWSs]). These can be used as the basis for timely interventions to prevent relapse. However, there is considerable uncertainty regarding the implementation of EWS interventions.

Objective

This study was designed to establish the feasibility of conducting a definitive cluster randomized controlled trial comparing Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) against treatment as usual (TAU). Our primary outcomes are establishing parameters of feasibility, acceptability, usability, safety, and outcome signals of a digital health intervention as an adjunct to usual care that is deliverable in the UK National Health Service and Australian community mental health service (CMHS) settings. We will assess the feasibility of candidate primary outcomes, candidate secondary outcomes, and candidate mechanisms for a definitive trial.

Methods

We will randomize CMHSs to EMPOWER or TAU. We aim to recruit up to 120 service user participants from 8 CMHSs and follow them for 12 months. Eligible service users will (1) be aged 16 years and above, (2) be in contact with local CMHSs, (3) have either been admitted to a psychiatric inpatient service or received crisis intervention at least once in the previous 2 years for a relapse, and (4) have an International Classification of Diseases-10 diagnosis of a schizophrenia-related disorder. Service users will also be invited to nominate a carer to participate. We will identify the feasibility of the main trial in terms of recruitment and retention to the study and the acceptability, usability, safety, and outcome signals of the EMPOWER intervention. EMPOWER is a mobile phone app that enables the monitoring of well-being and possible EWSs of relapse on a daily basis. An algorithm calculates changes in well-being based on participants’ own baseline to enable tailoring of well-being messaging and clinical triage of possible EWSs. Use of the app is blended with ongoing peer support.

Results

Recruitment to the trial began September 2018, and follow-up of participants was completed in July 2019. Data collection is continuing. The database was locked in July 2019, followed by analysis and disclosing of group allocation.

Conclusions

The knowledge gained from the study will inform the design of a definitive trial including finalizing the delivery of our digital health intervention, sample size estimation, methods to ensure successful identification, consent, randomization, and follow-up of participants, and the primary and secondary outcomes. The trial will also inform the final health economic model to be applied in the main trial.

Trial Registration

International Standard Randomized Controlled Trial Number (ISRCTN): 99559262; http://isrctn.com/ISRCTN99559262

International Registered Report Identifier (IRRID)

DERR1-10.2196/15058

Are we there yet?!-a literature review of recent digital technology advances for the treatment of early psychosis

Access to psychological interventions during early stages of psychosis is essential for ameliorating outcomes and improving prognosis. However, reaching and engaging individuals at these stages of the illness can be very challenging for early intervention teams. Recent digital technological advances have emerged to overcome some of these challenges and to improve access to psychological interventions. The aim of the present literature review is to summarise main findings of relevant studies published during the last 10 years on the utilization of digital technologies (i.e., virtual reality, smartphone technology and web-based interventions) to enhance psychological treatment outcomes in early psychosis. A literature search from January 2009 to June 2019 was performed to identify relevant papers. Of 1,502 studies identified, nine met inclusion criteria for the review and only five presented results from finalised trials. Overall, these studies showed positive feasibility and acceptability results, along with preliminary evidence of improved therapy outcomes. The present review offers a state-of-the-art summary of the main features of these user-centered digital interventions for early stages of psychosis and a critical discussion about their future implementation in mental health services.

An Examination of the Community Participation Interests of Young Adults with Serious Mental Illnesses

Participation in various aspects of community life (e.g., education, employment) plays a critical role in fostering young adult development and health. To support behavioral health services in addressing a broader array of meaningful community participation areas, the current study examined the participation interests of young adults with serious mental illnesses via a literature review and focus groups interviews. Literature review results revealed a range of community participation areas of interest to these individuals, including employment, education, religion and spirituality, social networking (e.g., using social media), volunteering activities, socializing, and civic and artistic participation (e.g., attending a political event, playing music). Focus group participants named many of these same areas, but also mentioned unique areas of participation that have not been the focus of previous research (i.e., playing games, sports, exploration of other communities (e.g., traveling), hanging out, and nature-based participation). Implications for future research and behavioral health practice are discussed.

The importance of loneliness in psychotic-like symptoms: Data from three studies

Poor social connection or loneliness is a prominent feature of schizotypy and may exacerbate psychosis risk. Previous studies have examined the inter-relationships between loneliness and psychosis risk, but critically, they have largely been conducted in non-clinical samples or exclusively used laboratory questionnaires with limited consideration of the heterogeneity within schizotypy (i.e., positive, negative, disorganized factors). The present study examined links between loneliness and psychotic-like symptoms across the dimensions of schizotypy through cross-sectional, laboratory-based questionnaires (Study 1; N = 160), ambulatory assessment (Study 2; N = 118) in undergraduates, and ambulatory assessment in inpatients in a substance abuse treatment program (Study 3; N = 48). Trait positive schizotypy consistently predicted cross-sectional and state psychotic-like symptoms. Loneliness, assessed via cross-sectional and ambulatory means, was largely linked with psychotic-like symptoms. Importantly, psychotic-like symptoms were dynamic: psychotic-like symptoms largely increased with loneliness in individuals with elevated positive and disorganized schizotypal traits, though there were some inconsistency related to disorganized schizotypy and state psychotic-like symptoms. Negative schizotypy and loneliness did not significantly interact to predict psychotic-like symptoms, suggesting specificity to positive schizotypy. Ambulatory approaches provide the opportunity for ecologically valid identification of risk states across psychopathology, thus informing early intervention.

Advances in clinical staging, early intervention, and the prevention of psychosis

The development of effective intervention and prevention strategies among individuals with psychosis risk syndromes may help to reduce symptomatology and conversion to a psychotic disorder. Although strides have been made in this area, more work is needed, particularly given the setbacks that remain (such as heterogeneity among this group). There has been a shift with the introduction of clinical staging models toward expanding current intervention and prevention efforts to a more developmental and transdiagnostic approach. With this, this article seeks to review treatments both recently and currently discussed in the staging literature, introduce advances in psychosis risk syndrome treatments that may be beneficial to consider in clinical staging heuristics, and pinpoint other promising options.

Mobile Health Apps for Self-Management of Rheumatic and Musculoskeletal Diseases: Systematic Literature Review

BACKGROUND

Although the increasing availability of mobile health (mHealth) apps may enable people with rheumatic and musculoskeletal diseases (RMDs) to better self-manage their health, there is a general lack of evidence on ways to ensure appropriate development and evaluation of apps.

OBJECTIVE

This study aimed to obtain an overview on existing mHealth apps for self-management in patients with RMDs, focusing on content and development methods.

METHODS

A search was performed up to December 2017 across 5 databases. For each publication relevant to an app for RMDs, information on the disease, purpose, content, and development strategies was extracted and qualitatively assessed.

RESULTS

Of 562 abstracts, 32 were included in the analysis. Of these 32 abstracts, 11 (34%) referred to an app linked to a connected device. Most of the apps targeted rheumatoid arthritis (11/32, 34%). The top three aspects addressed by the apps were pain (23/32, 71%), fatigue (15/32, 47%), and physical activity (15/32, 47%). The development process of the apps was described in 84% (27/32) of the articles and was of low to moderate quality in most of the cases. Despite most of the articles having been published within the past two years, only 5 apps were still commercially available at the time of our search. Moreover, only very few studies showed improvement of RMD outcome measures.

CONCLUSIONS

The development process of most apps was of low or moderate quality in many studies. Owing to the increasing RMD patients' willingness to use mHealth apps for self-management, optimal standards and quality assurance of new apps are mandatory.

Smartphone Apps to Support Coordinated Specialty Care for Prodromal and Early Course Schizophrenia Disorders: Systematic Review

Background

Demand for mental health services, especially for clinical high-risk and early psychosis, has increased, creating a need for new solutions to increase access to and quality of care. Smartphones and mobile technology are potential tools to support coordinated specialty care for early psychosis, given their potential to augment the six core roles of care: case management and team leadership, recovery-oriented psychotherapy, medication management, support for employment and education, coordination with primary care services, and family education and support. However, the services smartphones are actually offering specifically for coordinated specialty care and the level of evidence are unknown.

Objective

This study aimed to review the published literature on smartphone technology to enhance care for patients with prodromal and early course psychosis and schizophrenia and to analyze studies by type, aligned with coordinated specialty care domains.

Methods

A systematic literature search was conducted on August 16 and 17, 2019, using the PubMed, EMBASE, Web of Sciences, and PsycINFO electronic databases. The eligible studies were reviewed and screened based on inclusion and exclusion criteria.

Results

The search uncovered 388 unique results, of which 32 articles met the initial inclusion criteria; 21 eligible studies on 16 unique app platforms were identified. Feasibility studies showed a high user engagement and interest among patients, monitoring studies demonstrated a correlation between app assessments and clinical outcomes, and intervention studies indicated that these apps have the potential to advance care. Eighteen studies reported on app use for the case management roles of coordinated specialty care. No app studies focused on employment and education, coordination with primary care services, and family education and support.

Conclusions

Although the published literature on smartphone apps for prodromal and first-episode psychosis is small, it is growing exponentially and holds promise to augment both monitoring and interventions. Although the research results and protocols for app studies are not well aligned with all coordinated specialty care roles today, high rates of adoption and feasibility suggest the potential for future efforts. These results will be used to develop coordinated specialty care–specific app evaluation scales and toolkits.

Designing for engagement with self-monitoring: A user-centered approach with low-income, Latino adults with Type 2 Diabetes

BACKGROUND AND SIGNIFICANCE

Data-driven interventions for health can help to personalize self-management of Type 2 Diabetes (T2D), but lack of sustained engagement with self-monitoring among disadvantaged populations may widen existing health disparities. Prior work developing approaches to increase motivation and engagement with self-monitoring holds promise, but little is known about applicability of these approaches to underserved populations.

OBJECTIVE

To explore how low-income, Latino adults with T2D respond to different design concepts for data-driven solutions in health that require self-monitoring, and what features resonate with them the most.

MATERIAL AND METHODS

We developed a set of mockups that incorporated different design features for promoting engagement with self-monitoring in T2D. We conducted focus groups to examine individuals' perceptions and attitudes towards mockups. Multiple interdisciplinary researchers analyzed data using directed content analysis.

RESULTS

We conducted 14 focus groups with 25 English- and Spanish-speaking adults with T2D. All participants reacted positively to external incentives. Social connectedness and healthcare expert feedback were also well liked because they enhanced current social practices and presented opportunities for learning. However, attitudes were more mixed towards goal setting, and very few participants responded positively to self-discovery and personalized decision support features. Instead, participants wished for personalized recommendations for meals and other health behaviors based on their personal health data.

CONCLUSION

This study suggests connections between individuals' degree of internal motivation and motivation for self-monitoring in health and their attitude towards designs of self-monitoring apps. We relate our findings to the self-determination continuum in self-determination theory (SDT) and propose it as a blueprint for aligning incentives for self-monitoring to different levels of motivation.

A technology-assisted life of recovery from psychosis

Developments in digital health technologies have the potential to expedite and strengthen the path towards recovery for people with psychosis. This perspective piece provides a snapshot of how a range of digital technologies can be deployed to support a young adult’s efforts to cope with schizophrenia-spectrum illness. In conjunction with a day in the life of this individual, we provide examples of innovations in digital health research designed for this clinical population, as well as brief summaries of the evidence supporting the usability, feasibility, or effectiveness of each approach. From early detection to ongoing symptom management and vocational rehabilitation, this day-in-the-life vignette provides an overview of the ways in which digital health innovations could be used in concert to augment, scaffold, and enhance schizophrenia-spectrum illness management and recovery.

Evaluation of Mobile Applications Intended to Aid in Conception Using a Systematic Review Framework

Objective: This review identified and evaluated apps intended to aid women in conception that were available across major mobile platforms; secondary objectives were to highlight additional criteria and considerations when evaluating conception-related apps. Data Sources: Apple iTunes and Google Play stores were searched using the keywords conception, fertility, and pregnant. Data Selection: Included apps were as follows: contained in the first 50 search results; presented in English; intended for layperson use; updated July 1, 2018, or after; marketed as a conception aid; and used a defined fertility tracking method. Excluded apps were intended for men only, marketed for contraception only, promoted a single fertility service or branded product, or not found in both app stores. Data Extraction: Apps were evaluated using the adapted APPLICATIONS Scoring System. Two additional criteria were assessed: inclusion of a privacy policy and inclusion of a search function, medical terminology glossary, or Frequently Asked Questions section. Data Synthesis: A total of 300 apps were screened; 7 app pairs were analyzed. Scores ranged from 9 to 13 of a possible 15 points (mean = 11; median = 11). No app reported advisement from a health professional during development. Relevance to Patient Care in Clinical Practice: Widely available apps that score highly per the adapted APPLICATIONS Scoring System may be considered for use by and recommended to women seeking apps useful for conception. Conclusion: Evaluation tools should evolve as app features change. Criteria related to privacy and search functions that promote health literacy should be considered for future app evaluation tools.

Feasibility and outcomes of a multi-function mobile health approach for the schizophrenia spectrum: App4Independence (A4i)

Relative to the large investments in mobile health (mHealth) strategies for mental illnesses such as anxiety and depression, the development of technology to facilitate illness self-management for people with schizophrenia spectrum illnesses is limited. This situation falls out of step with the opportunity mHealth represents for providing inexpensive and accessible self-care resources and the routine use of mobile technologies by people with schizophrenia. Accordingly, the focus of this study was upon the feasibility of a schizophrenia-focused mobile application: App4Independence (A4i). A4i is a multi-feature app that uses feed, scheduling, and text-based functions co-designed with service users to enhance illness self-management. This study was completed in a large urban Canadian centre and employed pre-post assessments over a 1-month period that examined medication adherence, personal recovery, and psychiatric symptomatology. App use metrics were assessed as was qualitative feedback through semi-structured interview. Findings are reported in line with the World Health Organization mHealth Evidence and Assessment (mERA) checklist. Among the 38 individuals with a primary psychosis who participated, there was no research attrition and classic retention on the app was 52.5%. Significant improvement was observed in some psychiatric symptom domains with small-medium effects. Significant change in recovery engagement and medication adherence were not observed after controlling for multiple comparisons. Those who interacted with the app more frequently were more depressed and had higher hostility and interpersonal sensitivity at baseline. Satisfaction with the app was high and qualitative feedback provided insights regarding feature enhancements. This research suggested that A4i is feasible in terms of outcome and process indicators and is a technology that is ready to move on to clinical trial and validation testing. This study contributes to the small but emergent body of work investigating digital health approaches in severe mental illness populations.