Validation of accelerometry as a digital phenotyping measure of negative symptoms in schizophrenia

Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data

BACKGROUND

Advancement in mental health care requires easily accessible, efficient diagnostic and treatment assessment tools. Viable biomarkers could enable objectification and automation of the diagnostic and treatment process, currently dependent on a psychiatric interview. Available wearable technology and computational methods make it possible to incorporate heart rate variability (HRV), an indicator of autonomic nervous system (ANS) activity, into potential diagnostic and treatment assessment frameworks as a biomarker of disease severity in mental disorders, including schizophrenia and bipolar disorder (BD).

METHOD

We used a commercially available electrocardiography (ECG) chest strap with a built-in accelerometer, i.e. Polar H10, to record R-R intervals and physical activity of 30 hospitalized schizophrenia or BD patients and 30 control participants through ca. 1.5-2 h time periods. We validated a novel approach to data acquisition based on a flexible, patient-friendly and cost-effective setting. We analyzed the relationship between HRV and the Positive and Negative Syndrome Scale (PANSS) test scores, as well as the HRV and mobility coefficient. We also proposed a method of rest period selection based on R-R intervals and mobility data. The source code for reproducing all experiments is available on GitHub, while the dataset is published on Zenodo.

RESULTS

Mean HRV values were lower in the patient compared to the control group and negatively correlated with the results of the PANSS general subcategory. For the control group, we also discovered the inversely proportional dependency between the mobility coefficient, based on accelerometer data, and HRV. This relationship was less pronounced for the treatment group.

CONCLUSIONS

HRV value itself, as well as the relationship between HRV and mobility, may be promising biomarkers in disease diagnostics. These findings can be used to develop a flexible monitoring system for symptom severity assessment.

Digital Phenotyping for Monitoring Mental Disorders: Systematic Review

BACKGROUND

The COVID-19 pandemic has increased the impact and spread of mental illness and made health services difficult to access; therefore, there is a need for remote, pervasive forms of mental health monitoring. Digital phenotyping is a new approach that uses measures extracted from spontaneous interactions with smartphones (eg, screen touches or movements) or other digital devices as markers of mental status.

OBJECTIVE

This review aimed to evaluate the feasibility of using digital phenotyping for predicting relapse or exacerbation of symptoms in patients with mental disorders through a systematic review of the scientific literature.

METHODS

Our research was carried out using 2 bibliographic databases (PubMed and Scopus) by searching articles published up to January 2023. By following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines, we started from an initial pool of 1150 scientific papers and screened and extracted a final sample of 29 papers, including studies concerning clinical populations in the field of mental health, which were aimed at predicting relapse or exacerbation of symptoms. The systematic review has been registered on the web registry Open Science Framework.

RESULTS

We divided the results into 4 groups according to mental disorder: schizophrenia (9/29, 31%), mood disorders (15/29, 52%), anxiety disorders (4/29, 14%), and substance use disorder (1/29, 3%). The results for the first 3 groups showed that several features (ie, mobility, location, phone use, call log, heart rate, sleep, head movements, facial and vocal characteristics, sociability, social rhythms, conversations, number of steps, screen on or screen off status, SMS text message logs, peripheral skin temperature, electrodermal activity, light exposure, and physical activity), extracted from data collected via the smartphone and wearable wristbands, can be used to create digital phenotypes that could support gold-standard assessment and could be used to predict relapse or symptom exacerbations.

CONCLUSIONS

Thus, as the data were consistent for almost all the mental disorders considered (mood disorders, anxiety disorders, and schizophrenia), the feasibility of this approach was confirmed. In the future, a new model of health care management using digital devices should be integrated with the digital phenotyping approach and tailored mobile interventions (managing crises during relapse or exacerbation).

Environmental resource reductions predict greater severity of negative symptoms in schizophrenia

No pharmacological or psychosocial interventions effectively treat negative symptoms in schizophrenia (SZ), despite the identification of biological and psychological mechanistic targets. Limited treatment progress may result from failure to account for non-person-level environmental factors that present barriers to performing recreational, social, and goal-directed activities. The bioecosystem model of negative symptoms proposes that four interactive ecosystems (i.e. microsystem, mesosystem, exosystem, and macrosystem) influence person-level factors (e.g., dysfunctional beliefs, glutamate, cortico-striatal functioning) to initiate and maintain negative symptoms. The current study tested this hypothesis by examining whether indirect environmental factors (e.g., access to resources for performing activities in the built environment) were associated with dysfunctional beliefs (defeatist performance, asocial, anhedonic) and negative symptoms (anhedonia, avolition, asociality). Self-reports of indirect environmental factors (i.e., the built environment), dysfunctional beliefs, and negative symptoms were collected from 31 individuals with SZ and 29 matched healthy controls. Mediation analyses were conducted with dysfunctional beliefs as the predictor, indirect environmental factors as mediator, and negative symptoms as the outcome. Individuals with SZ reported reduced access to environmental resources for performing recreational, goal-directed, and social activities; these reductions were associated with greater negative symptom severity. Mediation analyses indicated that the effect of dysfunctional beliefs on negative symptoms was mediated by participants' satisfaction with resources for performing activities in their environment. These findings suggest that psychosocial treatments could be augmented to not only target dysfunctional beliefs, but also environmental processes that lead these beliefs to emerge and contribute to 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 Phenotyping: Data-Driven Psychiatry to Redefine Mental Health

The term "digital phenotype" refers to the digital footprint left by patient-environment interactions. It has potential for both research and clinical applications but challenges our conception of health care by opposing 2 distinct approaches to medicine: one centered on illness with the aim of classifying and curing disease, and the other centered on patients, their personal distress, and their lived experiences. In the context of mental health and psychiatry, the potential benefits of digital phenotyping include creating new avenues for treatment and enabling patients to take control of their own well-being. However, this comes at the cost of sacrificing the fundamental human element of psychotherapy, which is crucial to addressing patients' distress. In this viewpoint paper, we discuss the advances rendered possible by digital phenotyping and highlight the risk that this technology may pose by partially excluding health care professionals from the diagnosis and therapeutic process, thereby foregoing an essential dimension of care. We conclude by setting out concrete recommendations on how to improve current digital phenotyping technology so that it can be harnessed to redefine mental health by empowering patients without alienating them.

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.

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.

Using Smartphones to Identify Momentary Characteristics of Persecutory Ideation Associated With Functional Disability

Objectives

Though often a feature of schizophrenia-spectrum disorders, persecutory ideation (PI) is also common in other psychiatric disorders as well as among individuals who are otherwise healthy. Emerging technologies allow for a more thorough understanding of the momentary phenomenological characteristics that determine whether PI leads to significant distress and dysfunction. This study aims to identify the momentary phenomenological features of PI associated with distress, dysfunction, and need for clinical care.

Methods

A total of 231 individuals with at least moderate PI from 43 US states participated in a study involving 30 days of data collection using a smartphone data collection system combining ecological momentary assessment and passive sensors, wherein they reported on occurrence of PI as well as related appraisals, responses, and cooccurring states. Most (N = 120, 51.9%) participants reported never having received treatment for their PI, while 50 participants had received inpatient treatment (21.6%), and 60 (26.4%) had received outpatient care only.

Results

Individuals with greater functional disability did not differ in PI frequency but were more likely at the moment to describe threats as important to them, to ruminate about those threats, to experience distress related to them, and to change their behavior in response. Groups based on treatment-seeking patterns largely did not differ in baseline measures or momentary phenomenology of PI as assessed by self-report or passive sensors.

Conclusions

Smartphone data collection allows for granular assessment of PI-related phenomena. Functional disability is associated with differences in appraisals of and responses to PI at the moment.

Digitale Phänotypisierung in der Psychologie – ein Quantensprung in der psychologischen Forschung?

Zusammenfassung. Digitale Phänotypisierung stellt einen neuen, leistungsstarken Ansatz zur Realisierung psychodiagnostischer Aufgaben in vielen Bereichen der Psychologie und Medizin dar. Die Grundidee besteht aus der Nutzung digitaler Spuren aus dem Alltag, um deren Vorhersagekraft für verschiedenste Anwendungsmöglichkeiten zu überprüfen und zu nutzen. Voraussetzungen für eine erfolgreiche Umsetzung sind elaborierte Smart Sensing Ansätze sowie Big Data-basierte Extraktions- (Data Mining) und Machine Learning-basierte Analyseverfahren. Erste empirische Studien verdeutlichen das hohe Potential, aber auch die forschungsmethodischen sowie ethischen und rechtlichen Herausforderungen, um über korrelative Zufallsbefunde hinaus belastbare Befunde zu gewinnen. Hierbei müssen rechtliche und ethische Richtlinien sicherstellen, dass die Erkenntnisse in einer für Einzelne und die Gesellschaft als Ganzes wünschenswerten Weise genutzt werden. Für die Psychologie als Lehr- und Forschungsdomäne bieten sich durch Digitale Phänotypisierung vielfältige Möglichkeiten, die zum einen eine gelebte Zusammenarbeit verschiedener Fachbereiche und zum anderen auch curriculare Erweiterungen erfordern. Die vorliegende narrative Übersicht bietet eine theoretische, nicht-technische Einführung in das Forschungsfeld der Digitalen Phänotypisierung, mit ersten empirischen Befunden sowie einer Diskussion der Möglichkeiten und Grenzen sowie notwendigen Handlungsfeldern.

Impaired Effort Allocation in Patients with Recent-Onset Schizophrenia and Its Relevance to Negative Symptoms Assessments and Persistent Negative Symptoms

(1) Background: Our aims in this study were (i) to compare effort allocation capacity measured between patients with recent-onset schizophrenia (SCZ) and healthy controls (HCs), (ii) within the SCZ, to investigate the association of effort allocation capacity with negative symptoms (NS), and (iii) to compare this association with the type of NS scale used. (2) Methods: Thirty-one patients with SCZ and 30 HCs participated in the study. The NS was examined using an older-generation (Scale for the Assessment of Negative Symptoms, SANS), a newer-generation (Brief Negative Symptoms Scale, BNSS), and a self-rated (Self-evaluation of Negative Symptoms Scale, SNS) negative symptom scale, as well as longitudinally by using persistent NS (PNS) distinction. (3) Results: The SCZ group was less willing to expend effort in high/moderate-probability and -magnitude conditions but more in low-probability and -magnitude conditions. A general reduction in effort allocation capacity was also present. Patients with PNS were less likely to choose hard tasks than non-PNS patients. Clinician-rated scales correlated with 50% probability and moderate-reward-magnitude conditions. Correlations with the SNS were minimal. (4) Conclusions: Our findings suggest that patients with SCZ may show a general reduction in effort allocation capacity and make inefficient choices, although they are not totally reward-insensitive. The effects of NS on effort expenditure can be more pronounced when the rewarding stimulus is vague.