GPS mobility as a digital biomarker of negative symptoms in schizophrenia: a case control study

Cognitive Impairments in Drug-Naive Patients With First-Episode Negative Symptom-Dominant Psychosis

Importance

Available antipsychotic medications are predominantly used to treat positive symptoms, such as hallucinations and delusions, in patients with first-episode psychosis (FEP). However, treating negative and cognitive symptoms, which are closely related to functional outcomes, remains a challenge.

Objective

To explore the cognitive characteristics of patients with negative symptom-dominant (NSD) psychosis.

Design, Setting, and Participants

This large-scale cross-sectional study of patients with FEP was led by the Shanghai Mental Health Center in China from 2016 to 2021, with participants recruited from 10 psychiatric tertiary hospitals. A comprehensive cognitive assessment was performed among 788 patients with FEP who were drug-naive. Symptom profiles were determined using the Positive and Negative Symptoms Scale (PANSS), and NSD was defined as a PANSS score for negative symptoms higher than that for positive and general symptoms. Positive symptom-dominant (PSD) and general symptom-dominant (GSD) psychosis were defined similarly. Data were analyzed in 2023.

Exposure

Psychotic symptoms were categorized into 3 groups: NSD, PSD, and GSD.

Main Outcomes and Measures

Neurocognitive performance, assessed using the Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery.

Results

This study included 788 individuals with FEP (median age, 22 [IQR, 17-28] years; 399 men [50.6%]). Patients with NSD exhibited more-pronounced cognitive impairment than did those with PSD or GSD. Specifically, cognitive differences between the NSD and PSD group, as well as between the NSD and GSD group, were most notable in the processing speed and attention domains (Trail Making [F = 4.410; P = .01], Symbol Coding [F = 4.957; P = .007], Verbal Learning [F = 3.198; P = .04], and Continuous Performance [F = 3.057; P = .05]). Patients with PSD and GSD showed no significant cognitive differences. Cognitive impairment was positively associated with the severity of negative symptoms. Most of the cognitive function tests used were able to differentiate patients with NSD from those with PSD and GSD, with significant differences observed across a range of tests, from Brief Visuospatial Memory Test-Revised (χ2 = 3.968; P = .05) to Brief Assessment of Cognition in Schizophrenia symbol coding (χ2 = 9.765; P = .002).

Conclusions and Relevance

The findings of this cross-sectional study of patients with FEP suggest the presence of a clinical subtype characterized by a predominance of negative symptoms and cognitive impairment.

Unique Challenges in Biomarkers for Psychotic Disorders

Biomarkers are observations that provide information about the risk of certain conditions (predictive) or their underlying mechanisms (explanatory) [...].

Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research

Background

Mental illness remains a major global health challenge largely due to the absence of definitive biomarkers applicable to diagnostics and care processes. Although remote sensing technologies, embedded in devices such as smartphones and wearables, offer a promising avenue for improved mental health assessments, their clinical integration has been slow.

Objective

This scoping review, following preferred reporting items for systematic reviews and meta-analyses guidelines, explores validation studies of remote sensing in clinical mental health populations, aiming to identify critical factors for clinical translation.

Methods

Comprehensive searches were conducted in six databases. The analysis, using narrative synthesis, examined clinical and socio-demographic characteristics of the populations studied, sensing purposes, temporal considerations and reference mental health assessments used for validation.

Results

The narrative synthesis of 50 included studies indicates that ten different sensor types have been studied for tracking and diagnosing mental illnesses, primarily focusing on physical activity and sleep patterns. There were many variations in the sensor methodologies used that may affect data quality and participant burden. Observation durations, and thus data resolution, varied by patient diagnosis. Currently, reference assessments predominantly rely on deficit focussed self-reports, and socio-demographic information is underreported, therefore representativeness of the general population is uncertain.

Conclusion

To fully harness the potential of remote sensing in mental health, issues such as reliance on self-reported assessments, and lack of socio-demographic context pertaining to generalizability need to be addressed. Striking a balance between resolution, data quality, and participant burden whilst clearly reporting limitations, will ensure effective technology use. The scant reporting on participants' socio-demographic data suggests a knowledge gap in understanding the effectiveness of passive sensing techniques in disadvantaged populations.

Evaluating a smartphone-based symptom self-monitoring app for psychosis in China (YouXin): A non-randomised validity and feasibility study with a mixed-methods design

Background

Psychosis causes a significant burden globally, including in China, where limited mental health resources hinder access to care. Smartphone-based remote monitoring offers a promising solution. This study aimed to assess the validity, feasibility, acceptability, and safety of a symptom self-monitoring smartphone app, YouXin, for people with psychosis in China.

Methods

A pre-registered non-randomised validity and feasibility study with a mixed-methods design. Participants with psychosis were recruited from a major tertiary psychiatric hospital in Beijing, China. Participants utilised the YouXin app to self-monitor psychosis and mood symptoms for four weeks. Feasibility outcomes were recruitment, retention and outcome measures completeness. Active symptom monitoring (ASM) validity was tested against corresponding clinical assessments (PANSS and CDS) using Spearman correlation. Ten participants completed qualitative interviews at study end to explore acceptability of the app and trial procedures.

Results

Feasibility parameters were met. The target recruitment sample of 40 participants was met, with 82.5% completing outcome measures, 60% achieving acceptable ASM engagement (completing >33% of all prompts), and 33% recording sufficient passive monitoring data to extract mobility indicators. Five ASM domains (hallucinations, suspiciousness, guilt feelings, delusions, grandiosity) achieved moderate correlation with clinical assessment. Both quantitative and qualitative evaluation showed high acceptability of YouXin. Clinical measurements indicated no symptom and functional deterioration. No adverse events were reported, suggesting YouXin is safe to use in this clinical population.

Conclusions

The trial feasibility, acceptability and safety parameters were met and a powered efficacy study is indicated. However, refinements are needed to improve ASM validity and increase passive monitoring data completeness.

Social Isolation and Serious Mental Illness: The Role of Context-Aware Mobile Interventions

Social isolation is a common problem faced by individuals with serious mental illness (SMI), and current intervention approaches have limited effectiveness. This paper presents a blended intervention approach, called mobile Social Interaction Therapy by Exposure (mSITE), to address social isolation in individuals with serious mental illness. The approach combines brief in-person cognitive-behavioral therapy (CBT) with context-triggered mobile CBT interventions that are personalized using mobile sensing data. Our approach targets social behavior and is the first context-aware intervention for improving social outcomes in serious mental illness.

Computational social science is growing up: why puberty consists of embracing measurement validation, theory development, and open science practices

Puberty is a phase in which individuals often test the boundaries of themselves and surrounding others and further define their identity - and thus their uniqueness compared to other individuals. Similarly, as Computational Social Science (CSS) grows up, it must strike a balance between its own practices and those of neighboring disciplines to achieve scientific rigor and refine its identity. However, there are certain areas within CSS that are reluctant to adopt rigorous scientific practices from other fields, which can be observed through an overreliance on passively collected data (e.g., through digital traces, wearables) without questioning the validity of such data. This paper argues that CSS should embrace the potential of combining both passive and active measurement practices to capitalize on the strengths of each approach, including objectivity and psychological quality. Additionally, the paper suggests that CSS would benefit from integrating practices and knowledge from other established disciplines, such as measurement validation, theoretical embedding, and open science practices. Based on this argument, the paper provides ten recommendations for CSS to mature as an interdisciplinary field of research.

Network analysis of discrete emotional states measured via ecological momentary assessment in schizophrenia

Prior studies demonstrate that schizophrenia (SZ) is associated with abnormalities in positive and negative emotional experience that predict clinical presentation. However, it is unclear whether specific discrete emotions within the broader positive/negative categories are driving those symptom associations. Further, it is also unclear whether specific emotions contribute to symptoms in isolation or via networks of emotional states that dynamically interact across time. The current study used network analysis to evaluate temporally dynamic interactions among discrete emotional states experienced in the real world as assessed via Ecological Momentary Assessment (EMA). Participants included 46 outpatients with chronic SZ and 52 demographically matched healthy controls (CN) who completed 6 days of EMA that captured reports of emotional experience and symptoms derived from monetary surveys and geolocation based symptom markers of mobility and home location. Results indicated that less dense emotion networks were associated with greater severity of negative symptoms, whereas more dense emotion networks were associated with more severe positive symptoms and mania. Additionally, SZ evidenced greater centrality for shame, which was associated with greater severity of positive symptoms. These findings suggest that positive and negative symptoms are associated with distinct profiles of temporally dynamic and interactive emotion networks in SZ. Findings have implications for adapting psychosocial therapies to target specific discrete emotional states in the treatment of positive versus negative symptoms.

Digital Phenotyping in Adults with Schizophrenia: A Narrative Review

PURPOSE OF REVIEW

As care for older adult patients with schizophrenia lacks innovation, technology can help advance the field. Specifically, digital phenotyping, the real-time monitoring of patients' behaviors through smartphone sensors and symptoms through surveys, holds promise as the method can capture the dynamicity and environmental correlates of disease.

RECENT FINDINGS

Few studies have used digital phenotyping to elucidate adult patients' experiences with schizophrenia. In this narrative review, we summarized the literature using digital phenotyping on adults with schizophrenia. No study focused solely on older adult patients. Studies including all adult patients were heterogeneous in measures used, duration, and outcomes. Despite limited research, digital phenotyping shows potential for monitoring outcomes such as negative, positive, and functional symptoms, as well as predicting relapse. Future research should work to target the symptomology persistent in chronic schizophrenia and ensure all patients have the digital literacy required to benefit from digital interventions and homogenize datasets to allow for more robust conclusions.

Digital health literacy and digital engagement for people with severe mental ill health across the course of the COVID-19 pandemic in England

BACKGROUND

An unprecedented acceleration in digital mental health services happened during the COVID-19 pandemic. However, people with severe mental ill health (SMI) might be at risk of digital exclusion, partly because of a lack of digital skills, such as digital health literacy. The study seeks to examine how the use of the Internet has changed during the pandemic for people with SMI, and explore digital exclusion, symptomatic/health related barriers to internet engagement, and digital health literacy.

METHODS

Over the period from July 2020 to February 2022, n = 177 people with an SMI diagnosis (psychosis-spectrum disorder or bipolar affective disorder) in England completed three surveys providing sociodemographic information and answering questions regarding their health, use of the Internet, and digital health literacy.

RESULTS

42.5% of participants reported experiences of digital exclusion. Cochrane-Q analysis showed that there was significantly more use of the Internet at the last two assessments (80.8%, and 82.2%) compared to that at the beginning of the pandemic (65.8%; ps < 0.001). Although 34.2% of participants reported that their digital skills had improved during the pandemic, 54.4% still rated their Internet knowledge as being fair or worse than fair. Concentration difficulties (62.6%) and depression (56.1%) were among the most frequently reported symptomatic barriers to use the Internet. The sample was found to have generally moderate levels of digital health literacy (M = 26.0, SD = 9.6). Multiple regression analysis showed that higher literacy was associated with having outstanding/good self-reported knowledge of the Internet (ES = 6.00; 95% CI: 3.18-8.82; p < .001), a diagnosis of bipolar disorder (compared to psychosis spectrum disorder - ES = 5.14; 95% CI: 2.47-7.81; p < .001), and being female (ES = 3.18; 95% CI: 0.59-5.76; p = .016).

CONCLUSIONS

These findings underline the need for training and support among people with SMI to increase digital skills, facilitate digital engagement, and reduce digital engagement, as well as offering non-digital engagement options to service users with SMI.

A Digital System (YouXin) to Facilitate Self-Management by People With Psychosis in China: Protocol for a Nonrandomized Validity and Feasibility Study With a Mixed Methods Design

BACKGROUND

Psychosis is one of the most disabling mental health conditions and causes significant personal, social, and economic burden. Accurate and timely symptom monitoring is critical to offering prompt and time-sensitive clinical services. Digital health is a promising solution for the barriers encountered by conventional symptom monitoring approaches, including accessibility, the ecological validity of assessments, and recall bias. However, to date, there has been no digital health technology developed to support self-management for people with psychosis in China.

OBJECTIVE

We report the study protocol to evaluate the validity, feasibility, acceptability, usability, and safety of a symptom self-monitoring smartphone app (YouXin; Chinese name ) for people with psychosis in China.

METHODS

This is a nonrandomized validity and feasibility study with a mixed methods design. The study was approved by the University of Manchester and Beijing Anding Hospital Research Ethics Committee. YouXin is a smartphone app designed to facilitate symptom self-monitoring for people with psychosis. YouXin has 2 core functions: active monitoring of symptoms (ie, smartphone survey) and passive monitoring of behavioral activity (ie, passive data collection via embedded smartphone sensors). The development process of YouXin utilized a systematic coproduction approach. A series of coproduction consultation meetings was conducted by the principal researcher with service users and clinicians to maximize the usability and acceptability of the app for end users. Participants with psychosis aged 16 years to 65 years were recruited from Beijing Anding Hospital, Beijing, China. All participants were invited to use the YouXin app to self-monitor symptoms for 4 weeks. At the end of the 4-week follow-up, we invited participants to take part in a qualitative interview to explore the acceptability of the app and trial procedures postintervention.

RESULTS

Recruitment to the study was initiated in August 2022. Of the 47 participants who were approached for the study from August 2022 to October 2022, 41 participants agreed to take part in the study. We excluded 1 of the 41 participants for not meeting the inclusion criteria, leaving a total of 40 participants who began the study. As of December 2022, 40 participants had completed the study, and the recruitment was complete.

CONCLUSIONS

This study is the first to develop and test a symptom self-monitoring app specifically designed for people with psychosis in China. If the study shows the feasibility of YouXin, a potential future direction is to integrate the app into clinical workflows to facilitate digital mental health care for people with psychosis in China. This study will inform improvements to the app, trial procedures, and implementation strategies with this population. Moreover, the findings of this trial could lead to optimization of digital health technologies designed for people with psychosis in China.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45170.

The Effects of Adopting Mobile Health and Fitness Apps on Hospital Visits: Quasi-Experimental Study

BACKGROUND

Overcrowding in public hospitals, a common issue in many countries, leads to a range of negative outcomes, such as insufficient access to medical services and patient dissatisfaction. Prior literature regarding solutions to reducing hospital overcrowding primarily focuses on organizational-level operational efficiency. However, few studies have investigated the strategies from the individual patient perspective. Specifically, we considered using mobile health and fitness apps to promote users' health behaviors and produce health benefits, thereby reducing hospital visits.

OBJECTIVE

This study estimated the causal effect of health and fitness app adoption on hospital visits by exploiting the staggered timing of adoption. We also investigated how the effect varied with users' socioeconomic status and digital literacy. This study provides causal evidence for the effects of health apps, extends the digital health literature, and sheds light on mobile health policies.

METHODS

This study used a data set containing health and fitness app use and hospital-related geolocation data of 267,651 Chinese mobile phone users from January to December 2019. We used the difference-in-differences and difference-in-difference-in-differences designs to estimate the causal effect. We performed a sensitivity analysis to establish the robustness of the findings. We also conducted heterogeneity analyses based on the interactions of postadoption indicators with users' consumption levels, city tiers, and digital literacy.

RESULTS

The preferred model (difference-in-difference-in-differences) showed a significant decrease in hospital visits after the adoption of health and fitness apps. App adoption led to a 5.8% (P<.001), 13.1% (P<.001), and 18.4% reduction (P<.001) in hospital visits 1, 2, and 3 months after adoption, respectively. In addition, the moderation analysis shows that the effect is greater for users with high consumption levels, in high-tier cities, or with high digital literacy.

CONCLUSIONS

This study estimated the causal effect of health and fitness app adoption on hospital visits. The results and sensitivity analysis showed that app adoption can reduce users' hospital visits. The effect varies with users' consumption levels, city tiers, and digital literacy. These findings provide useful insights for multiple stakeholders in the Chinese health care context.

Childhood trauma and real-world social experiences in psychosis

BACKGROUND

Childhood trauma is associated with a variety of negative outcomes in psychosis, but it is unclear clear if childhood trauma affects day-to-day social experiences. We aimed to examine the association between childhood trauma and functional and structural characteristics of real-world social relationships in psychosis.

METHODS

Participants with psychotic disorders or affective disorders with psychosis completed ecological momentary assessments (EMAs) over ten days (N = 209). Childhood trauma was assessed retrospectively using the Childhood Trauma Questionnaire. Associations between childhood trauma and EMA-assessed social behavior and perceptions were examined using linear mixed models. Analyses were adjusted for sociodemographic characteristics and psychotic and depressive symptom severity.

RESULTS

Higher levels of childhood trauma were associated with more perceived threat (B = -0.19, 95 % CI [-0.33, -0.04]) and negative self-perception (B = -0.18, 95 % CI [-0.34, -0.01]) during recent social interactions, as well as reduced social motivation (B = -0.29, 95 % CI [-0.47, -0.10]), higher desire for social avoidance (B = 0.34, 95 % CI [0.14, 0.55]), and lower sense of belongingness (B = -0.24, 95 % CI [-0.42, -0.06]). These negative social perceptions were mainly linked with emotional abuse and emotional neglect. In addition, paranoia was more strongly associated with negative social perceptions in individuals with high versus low levels of trauma. Childhood trauma was not associated with frequency (i.e., time spent alone) or type of social interactions.

CONCLUSION

Childhood trauma - particularly emotional abuse and neglect - is associated with negative social perceptions but not frequency of real-world social interactions. Our findings suggest that childhood trauma may affect day-to-day social experiences beyond its association with psychosis.

The positivity offset theory of anhedonia in schizophrenia: evidence for a deficit in daily life using digital phenotyping

BACKGROUND

Negative symptoms of schizophrenia have recently been proposed to result from a decoupling of (intact) hedonic experience and (diminished) approach behavior. The current study challenged this view by exploring the hypothesis that negative symptoms are driven by a specific type of emotional experience abnormality, a reduction in the positivity offset (i.e. the tendency to experience greater levels of positive relative to negative emotion in low-arousal contexts), which limits the production of approach behaviors in neutral environments.

METHODS

Participants included outpatients with SZ (n = 44) and healthy controls (CN: n = 48) who completed one week of active (ecological momentary assessment surveys of emotional experience and symptoms) and passive (geolocation, accelerometry) digital phenotyping. Mathematical modeling approaches from Cacioppo's Evaluative Space Model were used to quantify the positivity offset in daily life. Negative symptoms were assessed via standard clinical ratings, as well as active (EMA surveys) and passive (geolocation, accelerometry) digital phenotyping measures.

RESULTS

Results indicated that the positivity offset was reduced in SZ and associated with more severe anhedonia and avolition measured via clinical interviews and active and passive digital phenotyping.

CONCLUSIONS

These findings suggest that current conceptual models of negative symptoms, which assume hedonic normality, may need to be revised to account for reductions in the positivity offset and its connection to diminished motivated behavior. Findings identify key real-world contexts where negative symptoms could be targeted using psychosocial treatments.

New and emerging approaches to treat psychiatric disorders

Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact the lives of millions of people worldwide. Although their etiological and diagnostic heterogeneity has long challenged drug discovery, an emerging circuit-based understanding of psychiatric illness is offering an important alternative to the current reliance on trial and error, both in the development and in the clinical application of treatments. Here we review new and emerging treatment approaches, with a particular emphasis on the revolutionary potential of brain-circuit-based interventions for precision psychiatry. Limitations of circuit models, challenges of bringing precision therapeutics to market and the crucial advances needed to overcome these obstacles are presented.

Remote Assessment of Negative Symptoms of Schizophrenia

In contrast to the validated scales for face-to-face assessment of negative symptoms, no widely accepted tools currently exist for remote monitoring of negative symptoms. Remote assessment of negative symptoms can be broadly divided into 3 categories: (1) remote administration of an existing negative-symptom scale by a clinician, in real time, using videoconference technology to communicate with the patient; (2) direct inference of negative symptoms through detection and analysis of the patient's voice, appearance, or activity by way of the patient's smartphone or other device; and (3) ecological momentary assessment, in which the patient self-reports their condition upon receipt of periodic prompts from a smartphone or other device during their daily routine. These modalities vary in cost, technological complexity, and applicability to the different negative-symptom domains. Each modality has unique strengths, weaknesses, and issues with validation. As a result, an optimal solution may be more likely to employ several techniques than to use a single tool. For remote assessment of negative symptoms to be adopted as primary or secondary endpoints in regulated clinical trials, appropriate psychometric standards will need to be met. Standards for substituting 1 set of measures for another, as well as what constitutes a "gold" reference standard, will need to be precisely defined and a process for defining them developed. Despite over 4 decades of progress toward this goal, significant work remains to be done before clinical trials addressing negative symptoms can utilize remotely assessed secondary or primary outcome measures.

Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix

The fast expansion of ICT (information and communications technology) has provided rich sources of data for the analysis, modeling, and interpretation of human mobility patterns. Many researchers have already introduced behavior-aware protocols for a better understanding of architecture and realistic modeling of behavioral characteristics, similarities, and aggregation of mobile users. We are introducing the similarity analytical framework for the mobile encountering analysis to allow for more direct integration between the physical world and cyber-based systems. In this research, we propose a method for finding the similarity behavior of users' mobility patterns based on location and time. This research was conducted to develop a technique for producing co-occurrence matrices of users based on their similar behaviors to determine their encounters. Our approach, named SAA (similarity analysis approach), makes use of the device info i.e., IP (internet protocol) and MAC (media access control) address, providing an in-depth analysis of similarity behaviors on a daily basis. We analyzed the similarity distributions of users on different days of the week for different locations based on their real movements. The results show similar characteristics of users with common mobility behaviors based on location and time to showcase the efficacy. The results show that the proposed SAA approach is 33% more accurate in terms of recognizing the user's similarity as compared to the existing similarity approach.

Smartphone-based mobility metrics capture daily social motivation and behavior in schizophrenia

Impaired social functioning contributes to reduced quality of life and is associated with poor physical and psychological well-being in schizophrenia, and thus is a key psychosocial treatment target. Low social motivation contributes to impaired social functioning, but is typically examined using self-report or clinical ratings, which are prone to recall biases and do not adequately capture the dynamic nature of social motivation in daily life. In the current study, we examined the utility of global positioning system (GPS)-based mobility data for capturing social motivation and behavior in people with schizophrenia. Thirty-one participants with schizophrenia engaged in a 60-day mobile intervention designed to increase social motivation and functioning. We examined associations between twice daily self-reports of social motivation and behavior (e.g., number of social interactions) collected via Ecological Momentary Assessment (EMA) and passively collected daily GPS mobility metrics (e.g., number of hours spent at home) in 26 of these participants. Findings suggested that greater mobility on a given day was associated with more EMA-reported social interactions on that day for four out of five examined mobility metrics: number of hours spent at home, number of locations visited, probability of being stationary, and likelihood of following one's typical routine. In addition, greater baseline social functioning was associated with less daily time spent at home and lower probability of following a daily routine during the intervention. GPS-based mobility thus corresponds with social behavior in daily life, suggesting that more social interactions may occur at times of greater mobility in people with schizophrenia, while subjective reports of social interest and motivation are less associated with mobility for this population.

Technology and Mental Health: State of the Art for Assessment and Treatment

Technology is ubiquitous in society and is now being extensively used in mental health applications. Both assessment and treatment strategies are being developed and deployed at a rapid pace. The authors review the current domains of technology utilization, describe standards for quality evaluation, and forecast future developments. This review examines technology-based assessments of cognition, emotion, functional capacity and everyday functioning, virtual reality approaches to assessment and treatment, ecological momentary assessment, passive measurement strategies including geolocation, movement, and physiological parameters, and technology-based cognitive and functional skills training. There are many technology-based approaches that are evidence based and are supported through the results of systematic reviews and meta-analyses. Other strategies are less well supported by high-quality evidence at present, but there are evaluation standards that are well articulated at this time. There are some clear challenges in selection of applications for specific conditions, but in several areas, including cognitive training, randomized clinical trials are available to support these interventions. Some of these technology-based interventions have been approved by the U.S. Food and Drug administration, which has clear standards for which types of applications, and which claims about them, need to be reviewed by the agency and which are exempt.

Digital Phenotyping for Mental Health: Reviewing the Challenges of Using Data to Monitor and Predict Mental Health Problems

PURPOSE OF REVIEW

We review recent developments within digital phenotyping for mental health, a field dedicated to using digital data for diagnosing, predicting, and monitoring mental health problems. We especially focus on recent critiques and challenges to digital phenotyping from within the social sciences.

RECENT FINDINGS

Three significant strands of criticism against digital phenotyping for mental health have been developed within the social sciences. This literature problematizes the idea that digital data can be objective, that it can be unbiased, and argues that it has multiple ethical and practical challenges. Digital phenotyping for mental health is a rapidly growing and developing field, but with considerable challenges that are not easily solvable. This includes when, and if, data from digital phenotyping is actionable in practice; the involvement of user and patient perspectives in digital phenotyping research; the possibility of biased data; and challenges to the idea that digital phenotyping can be more objective than other forms of psychiatric assessment.

Measuring functional outcomes in schizophrenia in an increasingly digital world

With an unmet clinical need for effective interventions for cognitive and negative symptoms in patients with schizophrenia, measures of functional status (often a co-primary endpoint) remain key clinical trial outcomes. This review aims to give an overview of the different types of functional assessments commonly used in clinical trials and research involving patients with schizophrenia and highlight pertinent challenges surrounding the use of these as reliable, sensitive, and specific assessments in intervention trials. We provide examples of commonly used functional measures and highlight emerging real-time digital assessment tools. Informant- and clinician-rated functional outcome measures and functional capacity assessments are valid, commonly used measures of functional status that try to overcome the need for often overly ambitious and insensitive ‘real world’ milestones. The wide range of scientific and practical challenges associated with these different tools leave room for the development of improved functional outcome measures for use in clinical trials. In particular, many existing measures fail to capture small, but meaningful, functional changes that may occur over the course of typically short intervention trials. Adding passive digital data collection and short active real-time digital assessments whilst patients go about their day offers the opportunity to build a more fine-grained picture of functional improvements that, if thoughtfully developed and carefully applied, could provide the sensitivity needed to accurately evaluate functional status in intervention studies, aiding the development of desperately needed treatments.

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Functional outcome measures are important for evaluating the efficacy of treatments.

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A variety of these are available, each with their own strengths and limitations.

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However, consensus on the optimal functional outcome measure(s) is lacking.

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Digital measures may enhance the assessment of associated functional constructs.

Revisiting how People with Schizophrenia Spend Their Days: Associations of lifetime milestone Achievements with Daily Activities examined with Ecological Momentary Assessment

Milestone achievements are reduced in people with schizophrenia and are lower in comparison to people with bipolar disorder. However, it is not clear what the implications are for engagement in momentary activities based on milestone achievements. Further, some recent research has suggested that psychotic symptoms are associated with challenges in self-assessment of activities, but there is less information about the correlations of milestone achievements and ongoing psychotic symptoms. We examined momentary activities and symptoms as a function of lifetime milestone achievement in 102 individuals with schizophrenia and 71 with bipolar disorder. Ecological Momentary Assessment (EMA) was used to sample daily activities and concurrent symptoms 3 times per day for 30 days. Each survey asked the participant where they were, who they were with, and what they were doing, as well as sampling the concurrent presence of psychotic symptoms. Not being financially responsible for their residence was associated with engaging in fewer productive activities. Participants who never had a relationship were more commonly home and alone and engaged in fewer social interactions. A lifetime history of employment was correlated with engaging in more productive activities, including at home. More common momentary psychosis was seen in participants who failed to achieve each of the functional milestones. Lifetime milestone achievements were associated with greater frequencies of productive behaviors and with fewer momentary experiences of psychosis, suggesting that psychotic symptoms may have importance for sustaining disability that would be challenging to detect without momentary information.

Low goal-directed behavior in negative symptoms is explained by goal setting - Results of a diary study

BACKGROUND AND OBJECTIVES

Engaging in goal-directed activities is a core difficulty of people with negative symptoms in schizophrenia. A previously developed goal pursuit model of negative symptoms (Schlier et al. 2017) postulates that negative symptom severity correlates with a tendency to set more avoidance- than approach-oriented goals. This shift in goal orientation correlates with low levels of goal expectancy, goal importance, and goal commitment. We explored whether these alterations translate into reduced goal-directed behavior (i.e., reduced goal striving and goal attainment).

METHODS

We conducted a one-week diary-study in a population sample (N=91). Participants were assessed for subclinical negative symptoms at baseline. Next, they set a daily goal and completed an online survey measuring goal orientation, goal characteristics, goal pursuit, and goal attainment once per day for one week.

RESULTS

Multilevel regression analyses and structural equation models showed that negative symptoms correlated with a tendency to set less approach-oriented goals with reduced goal expectancy and goal commitment. Goal orientation, expectancy, and commitment mediated the association between negative symptoms and reduced goal pursuit and attainment.

LIMITATIONS

We used a community sample, thus our results need to be replicated in a clinical sample of people with motivational negative symptoms.

CONCLUSIONS

Our results support the hypothesis that dysfunctional goal pursuit processes explain why negative symptoms lead to reduced goal-directed behavior. Interventions focusing on goal setting and goal expectations could be promising in improving goal-directed behavior in people with negative symptoms.

Cognitive dysfunction in schizophrenia: An expert group paper on the current state of the art

Cognitive impairment in schizophrenia represents one of the main obstacles to clinical and functional recovery. This expert group paper brings together experts in schizophrenia treatment to discuss scientific progress in the domain of cognitive impairment to address cognitive impairments and their consequences in the most effective way. We report on the onset and course of cognitive deficits, linking them to the alterations in brain function and structure in schizophrenia and discussing their role in predicting the transition to psychosis in people at risk. We then address the assessment tools with reference to functioning and social cognition, examining the role of subjective measures and addressing new methods for measuring functional outcomes including technology based approaches. Finally, we briefly review treatment options for cognitive deficits, focusing on cognitive remediation programs, highlighting their effects on brain activity and conclude with the potential benefit of individualized integrated interventions combing cognitive remediation with other approaches.

Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: A cross-sectional study using GPS from 122 individuals in three European cities

Many aspects of our life are related to our mobility patterns and individuals can exhibit strong tendencies towards routine in their daily lives. Intrapersonal day-to-day variability in mobility patterns has been associated with mental health outcomes. The study aims were: (a) calculate intrapersonal day-to-day variability in mobility metrics for three cities; (b) explore interpersonal variability in mobility metrics by sex, season and city, and (c) describe intrapersonal variability in mobility and their association with perceived stress. Data came from the Physical Activity through Sustainable Transport Approaches (PASTA) project, 122 eligible adults wore location measurement devices over 7-consecutive days, on three occasions during 2015 (Antwerp: 41, Barcelona: 41, London: 40). Participants completed the Short Form Perceived Stress Scale (PSS-4). Day-to-day variability in mobility was explored via six mobility metrics using distance of GPS point from home (meters:m), distance travelled between consecutive GPS points (m) and energy expenditure (metabolic equivalents:METs) of each GPS point collected (n = 3,372,919). A Kruskal-Wallis H test determined whether the median daily mobility metrics differed by city, sex and season. Variance in correlation quantified day-to-day intrapersonal variability in mobility. Levene's tests or Kruskal-Wallis tests were applied to assess intrapersonal variability in mobility and perceived stress. There were differences in daily distance travelled, maximum distance from home and METS between individuals by sex, season and, for proportion of time at home also, by city. Intrapersonal variability across all mobility metrics were highly correlated; individuals had daily routines and largely stuck to them. We did not observe any association between stress and mobility. Individuals are habitual in their daily mobility patterns. This is useful for estimating environmental exposures and in fuelling simulation studies.

Similarity matrix-based anomaly detection for clinical intervention

The use of digital phenotyping methods in clinical care has allowed for improved investigation of spatiotemporal behaviors of patients. Moreover, detecting abnormalities in mobile sensor data patterns can be instrumental in identifying potential changes in symptomology. We propose a method that temporally aligns sensor data in order to achieve interpretable measures of similarity between time points. These computed measures can then be used for anomaly detection, baseline routine computation, and trajectory clustering. In addition, we apply this method on a study of 695 college participants, as well as on a patient with worsening anxiety and depression. With varying temporal constraints, we find mild correlations between changes in routine and clinical scores. Furthermore, in our experiment on an individual with elevated depression and anxiety, we are able to cluster GPS trajectories, allowing for improved understanding and visualization of routines with respect to symptomology. In the future, we aim to apply this method on individuals that undergo data collection for longer periods of time, thus allowing for a better understanding of long-term routines and signals for clinical intervention.

Expanding the positivity offset theory of anhedonia to the psychosis continuum

People with schizophrenia and negative symptoms show diminished net positive emotion in low-arousing contexts (diminished positivity offset) and co-activate positive and negative emotion more frequently (increased ambivalence). Here, we investigated whether diminished positivity offset and increased ambivalence covary with negative symptoms along the continuum of psychotic symptoms. We conducted an online-study in an ad-hoc community sample (N = 261). Participants self-reported on psychotic symptoms (negative symptoms, depression, positive symptoms, anhedonia) and rated positivity, negativity, and arousal elicited by pleasant, unpleasant, and neutral stimuli. The data were analyzed with multilevel linear models. Increasing levels of all assessed symptom areas showed significant associations with diminished positivity offset. Increased ambivalence was related only to positive symptoms. Our results show that the diminished positivity offset is associated with psychotic symptoms in a community sample, including, but not limited to, negative symptoms. Ecological validity and symptom specificity require further investigation.

Longitudinal symptom changes and association with home time in people with schizophrenia: An observational digital phenotyping study

BACKGROUND

Smartphone assessments and sensors offer the ability to easily assess symptoms across environments in a naturalistic and longitudinal manner. However, the value of this new data to make inferences about personal vs population health and the role of environment in moderating symptoms in schizophrenia has not been fully explored in a scalable and reproducible manner.

METHODS

Eighty-six adults with a diagnosis of schizophrenia were recruited from the Greater Boston Area between August 2019 and May 2021. Using the open-source mindLAMP app in an observational manner, smartphone surveys and sensors (GPS, accelerometer, screen on/off and call and text logs) were collected for up to six months.

RESULTS

Sixty-three participants were analyzed, who had at least completed one survey in the app. App-based self-reported symptom surveys were highly correlated with scores on gold standard clinical assessments (r = 0.80, p = 10^-11 for mood and r = 0.78, p = 10^-12 for anxiety). For these app-based assessments, inter-individual differences account for a larger proportion of the correlations in longitudinal symptoms as compared to intra-individual differences. Mood, sleep, and psychosis symptoms reported on app surveys were more severe when taken at home as determined by the smartphone's GPS sensor.

DISCUSSION

The intra-individual symptom correlations and the stratification of symptoms by home-time highlight the utility of digital phenotyping methods as a diagnostic tool, as well as the potential for personalized psychiatric treatment building on this data.

Stress and emotional arousal in urban environments: A biosocial study with persons having experienced a first-episode of psychosis and persons at risk

This article examines the entanglement between feelings of stress and discomfort, physiological arousal and urban experiences of persons living with early psychosis. It adopts a biosocial approach, using mixed methods combining ambulatory skin conductance monitoring, mobile interviews and contextual data, collected through GPS and video recordings. The study draws on and strives to cross-fertilize two recent strands of research. The first relates to the use of digital phenotyping in mental health research. The second explores stress and emotional arousal in cities using ambulatory physiological measures. Empirically, the paper is based on fieldwork in Basel, Switzerland, with nine participants recruited within the Basel Early Treatment Service (BEATS), and four controls. We focus on three salient elements in our results: visual perception of moving bodies, spatial transitions and openness and enclosure of the built environment. The analysis shows how these elements elicit physiological responses of arousal and expressed feelings of discomfort. In the concluding section we discuss the methodological implications of these results and suggest the notion of regime of attention as a focus for future biosocial research on urban mental health.

Momentary severity of psychotic symptoms predicts overestimation of competence in domains of everyday activities and work in schizophrenia: An ecological momentary assessment study

OBJECTIVES

Schizophrenia participants generate self-reports of their competencies that differ from objective information. They may base their reports on momentary moods or experiences rather than objective data. Theories of delusion formation implicate overconfidence during self-assessment as a cause.

METHODS

Ecological momentary assessment (EMA) was used to sample activities and experiences in 101 participants with schizophrenia up to 3 times a day for 30 days. Each survey asked where and with whom they were, what they were doing, and moods and psychotic symptoms they were experiencing. Self-reports and observer ratings of competence in work and everyday activities were collected.

RESULTS

Being home was associated with self-reports of better functioning in activities and work skills (p<.001) and being alone correlated with better self-reported functioning in activities (p<.001). Participants who reported more occurrences of hearing voices, paranoid ideation, and other psychotic symptoms reported their functioning as better (p<.001).

IMPLICATIONS

Schizophrenia was marked by a disconnect between momentary activities and self-assessments. Being home more was associated with better self-reported functioning on tasks that are only performed away from home. Psychotic  symptoms were associated with overestimation, consistent with previous theories positing that overconfidence and suspension of plausibility assessment may be associated with psychotic experiences.

Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study

BACKGROUND

The mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored.

OBJECTIVE

We aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time.

METHODS

Data used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse-Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants' location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility.

RESULTS

This study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=-0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=-0.07, P<.001) the subsequent periodicity of mobility.

CONCLUSIONS

Several phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.

The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones

BACKGROUND

Most smartphones and wearables are currently equipped with location sensing (using GPS and mobile network information), which enables continuous location tracking of their users. Several studies have reported that various mobility metrics, as well as home stay, that is, the amount of time an individual spends at home in a day, are associated with symptom severity in people with major depressive disorder (MDD). Owing to the use of small and homogeneous cohorts of participants, it is uncertain whether the findings reported in those studies generalize to a broader population of individuals with MDD symptoms.

OBJECTIVE

The objective of this study is to examine the relationship between the overall severity of depressive symptoms, as assessed by the 8-item Patient Health Questionnaire, and median daily home stay over the 2 weeks preceding the completion of a questionnaire in individuals with MDD.

METHODS

We used questionnaire and geolocation data of 164 participants with MDD collected in the observational Remote Assessment of Disease and Relapse-Major Depressive Disorder study. The participants were recruited from three study sites: King's College London in the United Kingdom (109/164, 66.5%); Vrije Universiteit Medisch Centrum in Amsterdam, the Netherlands (17/164, 10.4%); and Centro de Investigación Biomédica en Red in Barcelona, Spain (38/164, 23.2%). We used a linear regression model and a resampling technique (n=100 draws) to investigate the relationship between home stay and the overall severity of MDD symptoms. Participant age at enrollment, gender, occupational status, and geolocation data quality metrics were included in the model as additional explanatory variables. The 95% 2-sided CIs were used to evaluate the significance of model variables.

RESULTS

Participant age and severity of MDD symptoms were found to be significantly related to home stay, with older (95% CI 0.161-0.325) and more severely affected individuals (95% CI 0.015-0.184) spending more time at home. The association between home stay and symptoms severity appeared to be stronger on weekdays (95% CI 0.023-0.178, median 0.098; home stay: 25th-75th percentiles 17.8-22.8, median 20.9 hours a day) than on weekends (95% CI -0.079 to 0.149, median 0.052; home stay: 25th-75th percentiles 19.7-23.5, median 22.3 hours a day). Furthermore, we found a significant modulation of home stay by occupational status, with employment reducing home stay (employed participants: 25th-75th percentiles 16.1-22.1, median 19.7 hours a day; unemployed participants: 25th-75th percentiles 20.4-23.5, median 22.6 hours a day).

CONCLUSIONS

Our findings suggest that home stay is associated with symptom severity in MDD and demonstrate the importance of accounting for confounding factors in future studies. In addition, they illustrate that passive sensing of individuals with depression is feasible and could provide clinically relevant information to monitor the course of illness in patients with MDD.

Anhedonia in Schizophrenia

Anhedonia has long been considered a cardinal symptom of schizophrenia. This symptom is strongly associated with poor functional outcome, and limited treatment options are available. While originally conceptualized as an inability to experience pleasure, recent work has consistently shown that individuals with schizophrenia have an intact capacity to experience pleasure in-the-moment. Adjacent work in basic affective neuroscience has broadened the conceptualization of anhedonia to include not only the capacity to experience pleasure but highlights important temporal affective dynamics and decision-making processes that go awry in schizophrenia. Here we detail these mechanisms for emotional and motivational impairment in people with schizophrenia including: (1) initial response to reward; (2) reward anticipation; (3) reward learning; (4) effort-cost decision-making; (5) working memory and cognitive control. We will review studies that utilized various types of rewards (e.g., monetary, social), in order to draw conclusions regarding whether findings vary by reward type. We will then discuss how modern assessment methods may best incorporate each of the mechanisms, to provide a more fine-grained understanding of anhedonia in individuals with schizophrenia. We will close by providing a discussion of relevant future directions.

Mapping Personal Geographies in Psychosis: From Space to Place

Recently, there has been a growing interest in the interaction between the urban milieu and the development of psychosis. While growing up in an urban environment constitutes a risk factor for developing psychosis, patients who develop a first episode of psychosis tend to avoid city centers and suffer from isolation. These observations have fostered emerging interest in ways of developing contexts in cities that are favorable to mental health and that may help service users in their paths to recovery. Building on work on place attachment as well as systemic therapy, we present a new approach to map the urban spaces experienced by service users. We propose two tools, the "place attachment diagram" and "life space network," to situate emotional bond and spatial dimension respectively at their center and help service users to map meaningful places in the city. We also suggest that different facets of the illness such as epidemiological risk factors (residential mobility, migration, urban living, trauma), early place attachment and abnormal space experience, may shape individual space and place experience in psychosis. Psychotherapeutic process with patients should aim at turning urban "spaces" into "places" characterized by a sense of familiarity, security and opportunity. Finally, we argue that the "spatial" is a forgotten dimension in psychotherapy and should be taken into account when treating individuals with psychosis.

Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study

With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with these behavioral changes, we collected smartphone sensing data using the Beiwe platform from two groups of undergraduate students at a major North American university, one from January to March of 2020 (74 participants), the other from May to August (52 participants), to observe the differences in students' daily life patterns before and after the start of the pandemic. In this paper, we focus on the mobility patterns evidenced by GPS signal tracking from the students' smartphones and report findings using several analytical methods including principal component analysis, circadian rhythm analysis, and predictive modeling of perceived sadness levels using mobility-based digital metrics. Our findings suggest that compared to the pre-COVID group, students in the mid-COVID group generally 1) registered a greater amount of midday movement than movement in the morning (8-10 a.m.) and in the evening (7-9 p.m.), as opposed to the other way around; 2) exhibited significantly less intradaily variability in their daily movement; 3) visited less places and stayed at home more everyday, and; 4) had a significant lower correlation between their mobility patterns and negative mood.

Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring

Collecting and analyzing data from sensors embedded in the context of daily life has been widely employed for the monitoring of mental health. Variations in parameters such as movement, sleep duration, heart rate, electrocardiogram, skin temperature, etc., are often associated with psychiatric disorders. Namely, accelerometer data, microphone, and call logs can be utilized to identify voice features and social activities indicative of depressive symptoms, and physiological factors such as heart rate and skin conductance can be used to detect stress and anxiety disorders. Therefore, a wide range of devices comprising a variety of sensors have been developed to capture these physiological and behavioral data and translate them into phenotypes and states related to mental health. Such systems aim to identify behaviors that are the consequence of an underlying physiological alteration, and hence, the raw sensor data are captured and converted into features that are used to define behavioral markers, often through machine learning. However, due to the complexity of passive data, these relationships are not simple and need to be well-established. Furthermore, parameters such as intrapersonal and interpersonal differences need to be considered when interpreting the data. Altogether, combining practical mobile and wearable systems with the right data analysis algorithms can provide a useful tool for the monitoring and management of mental disorders. The current review aims to comprehensively present and critically discuss all available smartphone-based, wearable, and environmental sensors for detecting such parameters in relation to the treatment and/or management of the most common mental health conditions.

Geolocation, ethics, and HIV research

The HIV epidemic continues to disproportionally affect marginalized populations. Digital tools, including global positioning system and ecologic momentary assessment, have been studied as methods for improving data collection and interventions among HIV-affected communities. Although people living with HIV and populations at high risk have found it acceptable to use digital technologies for HIV research, concerns over privacy and trust have also been expressed. This paper explores and describes the use of geolocation technology data (e.g., location-based social media) in HIV research as well as the ethical and implementation considerations that warrant examination prior to use. Transparent and clear language in consent forms might improve participant trust in the project and investigators' ability to keep participant data secure and private. With respect to institutional review boards, a committee member who is knowledgeable about digital technologies and consumer protections may offer guidance in assessing adequate protections in study protocols. As technology used in research continues to evolve, investigators and the research community must continue to examine the ethical challenges that emerge to address participant concerns.

Evaluating the utility of digital phenotyping to predict health outcomes in schizophrenia: protocol for the HOPE-S observational study

INTRODUCTION

The course of schizophrenia illness is characterised by recurrent relapses which are associated with adverse clinical outcomes such as treatment-resistance, functional and cognitive decline. Early identification is essential and relapse prevention remains a primary treatment goal for long-term management of schizophrenia. With the ubiquity of devices such as smartphones, objective digital biomarkers can be harnessed and may offer alternative means for symptom monitoring and relapse prediction. The acceptability of digital sensors (smartphone and wrist-wearable device) and the association between the captured digital data with clinical and health outcomes in individuals with schizophrenia will be examined.

METHODS AND ANALYSIS

In this study, we aim to recruit 100 individuals with schizophrenia spectrum disorders who are recently discharged from the Institute of Mental Health (IMH), Singapore. Participants are followed up for 6 months, where digital, clinical, cognitive and functioning data are collected while health utilisation data are obtained at the 6 month and 1 year timepoint from study enrolment. Associations between digital, clinical and health outcomes data will be examined. A data-driven machine learning approach will be used to develop prediction algorithms to detect clinically significant outcomes. Study findings will inform the design, data collection procedures and protocol of future interventional randomised controlled trial, testing the effectiveness of digital phenotyping in clinical management of individuals with schizophrenia spectrum disorders.

ETHICS AND DISSEMINATION

Ethics approval has been granted by the National Healthcare Group (NHG) Domain Specific Review Board (DSRB Reference no.: 2019/00720). The results will be published in peer-reviewed journals and presented at conferences.

TRIAL REGISTRATION NUMBER

NCT04230590.

On Blurry Boundaries When Defining Digital Biomarkers: How Much Biology Needs to Be in a Digital Biomarker?

Recent years have seen a rise in research where so called "digital biomarkers" represent the focal study interest. Many researchers understand that digital biomarkers describe digital footprints providing insights into healthy and pathological human (neuro-)biology. Beyond that the term digital biomarker is also used at times to describe more general concepts such as linking digital footprints to human behavior (which itself can be described as the result of a biological system). Given the lack of consensus on how to define a digital biomarker, the present short mini-review provides i) an overview on various definitions and ii) distinguishes between direct (narrow) or indirect (broad) concepts of digital biomarkers. From our perspective, digital biomarkers meant as a more direct (or narrow) concept describe digital footprints being directly linked to biological variables, such as stemming from molecular genetics, epigenetics, endocrinology, immunology or brain imaging, to name a few. More indirect concepts of digital biomarkers encompass digital footprints being linked to human behavior that may act as latent variables indirectly linked to biological variables.

Increased Social Interactions Reduce the Association Between Constricted Life-Space and Lower Daily Happiness in Older Adults With and Without HIV: A GPS and Ecological Momentary Assessment Study

OBJECTIVE

Older persons with human immunodeficiency virus (HIV) (PWH) are particularly susceptible to life-space restrictions. The aims of this study included: 1) using global positioning system (GPS) derived indicators as an assessment of time spent at home among older adults with and without HIV; 2) using ecological momentary assessment (EMA) to examine real-time relationships between life-space, mood (happiness, sadness, anxious), fatigue, and pain; and 3) determining if number of daily social interactions moderated the effect of life-space on mood.

METHODS

Eighty-eight older adults (PWH n = 54, HIV-negative n = 34) completed smartphone-based EMA surveys assessing mood, fatigue, pain, and social interactions four times per day for two weeks. Participants' smartphones were GPS enabled throughout the study. Mixed-effects regression models analyzed concurrent and lagged associations among life-space and behavioral indicators of health.

RESULTS

PWH spent more of their time at home (79% versus 70%, z = -2.08; p = 0.04) and reported lower mean happiness (3.2 versus 3.7; z = 2.63; p = 0.007) compared to HIV-negative participants. Controlling for covariates, more daily social interactions were associated with higher ratings of real-time happiness (b = 0.12; t = 5.61; df = 1087.9; p< 0.001). Similar findings were seen in lagged analyses: prior day social interactions (b = 0.15; t = 7.3; df = 1024.9; p < 0.0001) and HIV status (b = -0.48; t = -2.56; df = 1026.8; p = 0.01) attenuated the effect of prior day time spent at home on happiness.

CONCLUSION

Accounting for engagement in social interactions reduced the significant effect of time spent at home and lower happiness. Interventions targeting social isolation within the context of constricted life-space may be beneficial for increasing positive mood in older adults, and especially relevant to older PWH.

The relationship between conventional clinical assessments and momentary assessments of symptoms and functioning in schizophrenia spectrum disorders: A systematic review

BACKGROUND

Symptoms and functioning are critical dimensions in those with schizophrenia and are typically measured using validated conventional clinical assessments. Researchers and clinicians have begun to use real-time digital methods, such as ecological momentary assessment (EMA), to assess symptoms and functioning in the moment and outside of traditional hospital and laboratory settings, which may yield more naturalistic data. Although digital methods have advantages, it is unclear whether these momentary assessments capture core aspects of symptoms and functioning.

OBJECTIVE

This systematic literature review aimed to evaluate the association between conventional clinical and momentary-based assessments of functioning and symptoms in individuals with schizophrenia.

METHODS

Studies were included if they met the following criteria: (1) written or translated into English; (2) peer-reviewed; (3) included primary quantitative data; (4) 60% of the clinical sample included persons with schizophrenia spectrum disorders; (5) included a clinical assessment of functioning and/or symptoms; (6) included active momentary assessment and/or passive data; and (7) assessed the relationship between the momentary and conventional clinical assessments.

RESULTS

A total of 49 studies (87 analyses) were included. Conventional clinical assessments of functioning and positive, negative, and depressive symptoms were related to momentary assessments of these symptom domains. Passive data was beneficial for assessing negative symptoms, but research is warranted for other domains.

CONCLUSIONS

The reviewed studies highlight the utility of EMA methodologies to collect detailed data on symptoms and functioning. Such data is being used to develop more sophisticated models of schizophrenia to enhance our understanding of important mechanisms and develop targeted interventions.

Digital phenotyping adherence, feasibility, and tolerability in outpatients with schizophrenia

Digital phenotyping has potential for use as an objective and ecologically valid form of symptom assessment in clinical trials for schizophrenia. However, there are critical methodological factors that must be addressed before digital phenotyping can be used for this purpose. The current study evaluated levels of adherence, feasibility, and tolerability for active (i.e., signal and event contingent ecological momentary assessment surveys) and passive (i.e., geolocation, accelerometry, and ambulatory psychophysiology) digital phenotyping methods recorded from smartphone and smartband devices. Participants included outpatients diagnosed with schizophrenia (SZ: n = 54) and demographically matched healthy controls (CN: n = 55), who completed 6 days of digital phenotyping. Adherence was significantly lower in SZ than CN for active recordings, but not markedly different for passive recordings. Some forms of passive recordings had lower adherence (ambulatory psychophysiology) than others (accelerometry and geolocation). Active digital phenotyping adherence was predicted by higher psychosocial functioning, whereas passive digital phenotyping adherence was predicted by education, positive symptoms, negative symptoms, and psychosocial functioning in people with SZ. Both groups found digital phenotyping methods tolerable and feasibility was supported by low frequency of invalid responding, brief survey completion times, and similar impediments to study completion. Digital phenotyping methods can be completed by individuals with SZ with good adherence, feasibility, and tolerability. Recommendations are provided for using digital phenotyping methods in clinical trials for SZ.

Evidence for avolition in bipolar disorder? A 30-day ecological momentary assessment comparison of daily activities in bipolar disorder and schizophrenia

OBJECTIVES

Disability is common in bipolar disorder (BD) and predicted by persistent sadness. We used ecological momentary assessment (EMA) to examine daily activities in people with BD and schizophrenia. We classified activities as productive, unproductive, or passive recreation, relating them to momentary sadness, location, and social context.

METHODS

71 people with BD and 102 people with schizophrenia were sampled 3 times/day for 30 days with an EMA survey. Each survey asked where they were, with whom, what they were doing, and if they were sad.

RESULTS

People with BD were home more than 50% of the time. There were no differences in prevalence of activity types across diagnoses. People with BD were less likely to report only one activity since the prior survey, but the most surveys still reported only one. For both groups, sadness and being home and alone since the last survey was associated with less productive activity and more passive recreation.

CONCLUSIONS

Participants with BD and schizophrenia manifested high levels of unproductive and passive activities, predicted by momentary sadness. These activity patterns are consistent with descriptions of avolition and they minimally differentiated people with BD and schizophrenia. Previous reports of negative symptoms in BD may have been identifying these behaviors.

Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma

Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promising avenues for research and development. The present study examined the ability to utilize Global Positioning System (GPS) data, derived passively from a smartphone across seven days, to detect PTSD diagnostic status among a cohort (N = 185) of high-risk, previously traumatized women. Using daily time spent away and maximum distance traveled from home as a basis for model feature engineering, the results suggested that diagnostic group status can be predicted out-of-fold with high performance (AUC = 0.816, balanced sensitivity = 0.743, balanced specificity = 0.8, balanced accuracy = 0.771). Results further implicate the potential utility of GPS information as a digital biomarker of the PTSD behavioral repertoire. Future PTSD research will benefit from application of GPS data within larger, more diverse populations.

Smartphone sensing of social interactions in people with and without schizophrenia

Social impairment is a cardinal feature of schizophrenia spectrum disorders (SZ). Smaller social network size, diminished social skills, and loneliness are highly prevalent. Existing, gold-standard assessments of social impairment in SZ often rely on self-reported information that depends on retrospective recall and detailed accounts of complex social behaviors. This is particularly problematic in people with SZ given characteristic cognitive impairments and reduced insight. Ecological Momentary Assessment (EMA; repeated self-reports completed in the context of daily life) allows for the measurement of social behavior as it occurs in vivo, yet still relies on participant input. Momentary characterization of behavior using smartphone sensors (e.g., GPS, microphone) may also provide ecologically valid indicators of social functioning. In the current study we tested associations between both active (e.g., EMA-reported number of interactions) and passive (GPS-based mobility, conversations captured by microphone) smartphone-based measures of social activity and measures of social functioning and loneliness to examine the promise of such measures for understanding social impairment in SZ. Our results indicate that passive markers of mobility were more consistently associated with EMA measures of social behavior in controls than in people with SZ. Furthermore, dispositional loneliness showed associations with mobility metrics in both groups, while general social functioning was less related to these metrics. Finally, interactions detected in the ambient audio were more tied to social functioning in SZ than in controls. Findings speak to the promise of smartphone-based digital phenotyping as an approach to understanding objective markers of social activity in people with and without schizophrenia.

Self-reported social functioning and social cognition in schizophrenia and bipolar disorder: Using ecological momentary assessment to identify the origin of bias

OBJECTIVES

People with schizophrenia (SCZ) and bipolar illness (BPI) generate self-reports of their functioning that diverge from objective information. It has been suggested that these participants do not base such reports on daily experiences, relying on other information. We used ecological momentary assessment (EMA) to sample socially relevant daily activities in SCZ and BPI and related them to self-reported and observer-rated social functioning and social cognitive ability.

METHODS

71 people with (BPI) were compared to 102 people with SCZ. Participants were sampled 3 times per day for 30 days with a smartphone-based survey. Each survey asked where they were, with whom they were, what they were doing, and if they were sad. Participants and observers were asked to provide ratings on social functioning and social cognitive abilities at the end of the EMA period.

RESULTS

There was no association between being home or alone and self-reports of everyday social functioning. In contrast observer ratings were highly correlated with the momentary survey results. Reports of very low levels of sadness were associated with overestimated functioning and participants who were commonly home and alone rated their social functioning as better than participants who were commonly away in the presence of others.

IMPLICATIONS

Both SCZ and BPI were marked by a disconnect between momentary experiences and self-reports. The largest effect was overestimation of functioning by participants who reported no sadness. Experience appears important, as participants who were routinely home and alone reported better social functioning than participants who spent more time others.

Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint

To support the successful adoption of digital measures into internal decision making and evidence generation for medical product development, we present a unified lexicon to aid communication throughout this process, and highlight key concepts including the critical role of participant engagement in development of digital measures. We detail the steps of bringing a successful proof of concept to scale, focusing on key decisions in the development of a new digital measure: asking the right question, optimized approaches to evaluating new measures, and whether and how to pursue qualification or acceptance. Building on the V3 framework for establishing verification and analytical and clinical validation, we discuss strategic and practical considerations for collecting this evidence, illustrated with concrete examples of trailblazing digital measures in the field.

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

BACKGROUND

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

METHODS

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

RESULTS

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

DISCUSSION

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

Avolition as the core negative symptom in schizophrenia: relevance to pharmacological treatment development

Negative symptoms have long been considered a core component of schizophrenia. Modern conceptualizations of the structure of negative symptoms posit that there are at least two broad dimensions (motivation and pleasure and diminished expression) or perhaps five separable domains (avolition, anhedonia, asociality, blunted affect, alogia). The current review synthesizes a body of emerging research indicating that avolition may have a special place among these dimensions, as it is generally associated with poorer outcomes and may have distinct neurobiological mechanisms. Network analytic findings also indicate that avolition is highly central and interconnected with the other negative symptom domains in schizophrenia, and successfully remediating avolition results in global improvement in the entire constellation of negative symptoms. Avolition may therefore reflect the most critical treatment target within the negative symptom construct. Implications for targeted treatment development and clinical trial design are discussed.

Development of Novel, Value-Based, Digital Endpoints for Clinical Trials: A Structured Approach Toward Fit-for-Purpose Validation

Novel digital endpoints gathered via wearables, small devices, or algorithms hold great promise for clinical trials. However, implementation has been slow because of a lack of guidelines regarding the validation process of these new measurements. In this paper, we propose a pragmatic approach toward selection and fit-for-purpose validation of digital endpoints. Measurements should be value-based, meaning the measurements should directly measure or be associated with meaningful outcomes for patients. Devices should be assessed regarding technological validity. Most importantly, a rigorous clinical validation process should appraise the tolerability, difference between patients and controls, repeatability, detection of clinical events, and correlation with traditional endpoints. When technically and clinically fit-for-purpose, case building in interventional clinical trials starts to generate evidence regarding the response to new or existing health-care interventions. This process may lead to the digital endpoint replacing traditional endpoints, such as clinical rating scales or questionnaires in clinical trials. We recommend initiating more data-sharing collaborations to prevent unnecessary duplication of research and integration of value-based measurements in clinical care to enhance acceptance by health-care professionals. Finally, we invite researchers and regulators to adopt this approach to ensure a timely implementation of digital measurements and value-based thinking in clinical trial design and health care. SIGNIFICANCE STATEMENT: Novel digital endpoints are often cited as promising for the clinical trial of the future. However, clear validation guidelines are lacking in the literature. This paper contains pragmatic criteria for the selection, technical validation, and clinical validation of novel digital endpoints and provides recommendations for future work and collaboration.