Assessing Cognition Outside of the Clinic: Smartphones and Sensors for Cognitive Assessment Across Diverse Psychiatric Disorders

Measuring Cognitive Impairments Associated With Schizophrenia in Clinical Practice: Overview of Current Challenges and Future Opportunities

BACKGROUND

Cognitive impairment associated with schizophrenia (CIAS) negatively impacts daily functioning, quality of life, and recovery, yet effective pharmacotherapies and practical assessments for clinical practice are lacking. Despite the pivotal progress made with establishment of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) for clinical research, implementation of the full MCCB is too time-consuming and cost-ineffective for most clinicians in clinical practice.

STUDY DESIGN

Here we discuss current assessments in relation to delivery format (interview-based and performance-based), validity, ease of use for clinicians and patients, reliability/reproducibility, cost-effectiveness, and suitability for clinical implementation. Key challenges and future opportunities for improving cognitive assessments are also presented.

STUDY RESULTS

Current assessments that require 30 min to complete would have value in clinical settings, but the associated staff training and time required might preclude their application in most clinical settings. Initial profiling of cognitive deficits may require about 30 min to assist in the selection of evidence-based treatments; follow-up monitoring with brief assessments (10-15 min in duration) to detect treatment-related effects on global cognition may complement this approach. Guidance on validated brief cognitive tests for the strategic monitoring of treatment effects on CIAS is necessary.

CONCLUSIONS

With increased advancements in technology-based and remote assessments, development of validated formats of remote and in-person assessment, and the necessary training models and infrastructure required for implementation, are likely to be of increasing clinical relevance for future clinical practice.

CLINICAL AND COGNITIVE PHENOTYPING OF COPY NUMBER VARIANTS PATHOGENIC FOR NEURODEVELOPMENTAL DISORDERS FROM A MULTI-ANCESTRY BIOBANK

Background

Rare copy number variants (CNVs) are pathogenic for neurodevelopmental disorders (NDDs) and effect neurocognitive impairment. In aggregate, NDD CNVs may present in up to 2% of population cohorts with implications for neuropsychiatric disease risk and cognitive health. However, analyses of NDD CNVs in biobanks or population cohorts have been hindered by limited clinical or cognitive phenotypes, and a lack of ancestral diversity. In the current proof-of-concept study, NDD CNV carriers were recontacted from BioMe, a multi-ancestry biobank derived from the Mount Sinai healthcare system, to enable 'deep phenotyping' beyond electronic health record outcomes.

Methods

From BioMe biobank, 892 adult participants were recontacted, including 335 harboring NDD CNVs, 217 with schizophrenia and 340 neurotypical controls as comparators. Clinical and cognitive assessments were administered to each recruited participant.

Results

Seventy-three participants completed study assessments (mean age=48.8 years; 66% female; 36% African, 26% European, 34% Hispanic), or 8% of the recontacted subset, including 30 NDD CNV carriers across 15 loci. Among NDD CNV carriers, assessments indicated 40% with mood and anxiety disorders, 30% with learning disorders, and 13% with a history of special education. NDD CNV carriers were significantly cognitively impaired compared to controls on digit span backwards (Beta=-1.76, FDR=0.04) and digit span sequencing (Beta=-2.01, FDR=0.04).

Conclusions

Feasibility of "recall-by-genotype" from a multi-ancestry biobank was established for NDD CNV carriers, along with comparator groups. The current study corroborated past reports of NDD CNVs effects of cognitive impairment, while elucidating clinical phenotypes for recalled individuals. Future "recall-by-genotype" studies may further facilitate clinical characterization of disease-relevant genomic variants.

Emerging wearable technologies for multisystem monitoring and treatment of Parkinson's disease: a narrative review

Parkinson's disease (PD) is a chronic movement disorder characterized by a variety of motor and nonmotor comorbidities, including cognitive impairment, gastrointestinal (GI) dysfunction, and autonomic/sleep disturbances. Symptoms typically fluctuate with different settings and environmental factors and thus need to be consistently monitored. Current methods, however, rely on infrequent rating scales performed in clinic. The advent of wearable technologies presents a new avenue to track objective measures of PD comorbidities longitudinally and more frequently. This narrative review discusses and proposes emerging wearable technologies that can monitor manifestations of motor, cognitive, GI, and autonomic/sleep comorbidities throughout the daily lives of PD individuals. This can provide more wholistic insight into real-time physiological versus pathological function with the potential to better assess treatments during clinical trials and allow physicians to optimize treatment regimens. Additionally, this narrative review briefly examines novel applications of wearables as therapy for PD patients.

Engagement of individuals with serious mental illness in outpatient mental health services and telehealth use during the COVID-19 pandemic

Questions remain regarding whether the transition and continued use of telehealth was associated with changes in treatment engagement among patients with serious mental illness (SMI). Using NYS Medicaid claims, we identified 116,497 individuals with SMI receiving outpatient mental health services from September 1, 2019-February 28, 2021 and a comparison cohort of 101,995 from September 1, 2017-February 28, 2019 to account for unmeasured and seasonal variation. We characterized engagement in three 6-month increments (T0-T1-T2) using clinically meaningful measures of high, partial, low, and none. Subgroup differences were compared, and telehealth users were compared to those with only in-person visits. Engagement, as characterized, was largely maintained during COVID. The 19.0 % with only in-person visits during COVID had different characteristics than telehealth users. Telehealth use was greater among younger people by T2 (33.1 %), women (57.7 %), non-Hispanic White people (38.9 %), and those with MDD (18.0 %), but lower among non-Hispanic Black people, in NYC, and those with schizophrenia or SUD. Most telehealth users were highly engaged (77.1 %); most using only in-person services had low engagement (47.5 %). The shift to telehealth preserved access to many outpatient services for this SMI population. Exploring reasons for not using telehealth may identify opportunities to increase care access.

A Technology-Enriched Approach to Studying Microlongitudinal Aging Among Adults Aged 18 to 85 Years: Protocol for the Labs Without Walls Study

BACKGROUND

Traditional longitudinal aging research involves studying the same individuals over a long period, with measurement intervals typically several years apart. App-based studies have the potential to provide new insights into life-course aging by improving the accessibility, temporal specificity, and real-world integration of data collection. We developed a new research app for iOS named Labs Without Walls to facilitate the study of life-course aging. Combined with data collected using paired smartwatches, the app collects complex data including data from one-time surveys, daily diary surveys, repeated game-like cognitive and sensory tasks, and passive health and environmental data.

OBJECTIVE

The aim of this protocol is to describe the research design and methods of the Labs Without Walls study conducted between 2021 and 2023 in Australia.

METHODS

Overall, 240 Australian adults will be recruited, stratified by age group (18-25, 26-35, 36-45, 46-55, 56-65, 66-75, and 76-85 years) and sex at birth (male and female). Recruitment procedures include emails to university and community networks, as well as paid and unpaid social media advertisements. Participants will be invited to complete the study onboarding either in person or remotely. Participants who select face-to-face onboarding (n=approximately 40) will be invited to complete traditional in-person cognitive and sensory assessments to be cross-validated against their app-based counterparts. Participants will be sent an Apple Watch and headphones for use during the study period. Participants will provide informed consent within the app and then begin an 8-week study protocol, which includes scheduled surveys, cognitive and sensory tasks, and passive data collection using the app and a paired watch. At the conclusion of the study period, participants will be invited to rate the acceptability and usability of the study app and watch. We hypothesize that participants will be able to successfully provide e-consent, input survey data through the Labs Without Walls app, and have passive data collected over 8 weeks; participants will rate the app and watch as user-friendly and acceptable; the app will allow for the study of daily variability in self-perceptions of age and gender; and data will allow for the cross-validation of app- and laboratory-based cognitive and sensory tasks.

RESULTS

Recruitment began in May 2021, and data collection was completed in February 2023. The publication of preliminary results is anticipated in 2023.

CONCLUSIONS

This study will provide evidence regarding the acceptability and usability of the research app and paired watch for studying life-course aging processes on multiple timescales. The feedback obtained will be used to improve future iterations of the app, explore preliminary evidence for intraindividual variability in self-perceptions of aging and gender expression across the life span, and explore the associations between performance on app-based cognitive and sensory tests and that on similar traditional cognitive and sensory tests.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47053.

The current state of artificial intelligence-augmented digitized neurocognitive screening test

The cognitive screening test is a brief cognitive examination that could be easily performed in a clinical setting. However, one of the main drawbacks of this test was that only a paper-based version was available, which restricts the test to be manually administered and graded by medical personnel at the health centers. The main solution to these problems was to develop a potential remote assessment for screening individuals with cognitive impairment. Currently, multiple studies have been adopting artificial intelligence (AI) technology into these tests, evolving the conventional paper-based neurocognitive test into a digitized AI-assisted neurocognitive test. These studies provided credible evidence of the potential of AI-augmented cognitive screening tests to be better and provided the framework for future studies to further improve the implementation of AI technology in the cognitive screening test. The objective of this review article is to discuss different types of AI used in digitized cognitive screening tests and their advantages and disadvantages.

Remote cognitive assessment in severe mental illness: a scoping review

Many individuals living with severe mental illness, such as schizophrenia, present cognitive deficits and reasoning biases negatively impacting clinical and functional trajectories. Remote cognitive assessment presents many opportunities for advancing research and treatment but has yet to be widely used in psychiatric populations. We conducted a scoping review of remote cognitive assessment in severe mental illness to provide an overview of available measures and guide best practices. Overall, 34 studies (n = 20,813 clinical participants) were reviewed and remote measures, psychometrics, facilitators, barriers, and future directions were synthesized using a logic model. We identified 82 measures assessing cognition in severe mental illness across 11 cognitive domains and four device platforms. Remote measures were generally comparable to traditional versions, though psychometric properties were infrequently reported. Facilitators included standardized procedures and wider recruitment, whereas barriers included imprecise measure adaptations, technology inaccessibility, low patient engagement, and poor digital literacy. Our review identified several remote cognitive measures in psychiatry across all cognitive domains. However, there is a need for more rigorous validation of these measures and consideration of potentially influential factors, such as sex and gender. We provide recommendations for conducting remote cognitive assessment in psychiatry and fostering high-quality research using digital technologies.

Digital cognitive testing using a tablet-based app in patients with brain tumors: a single-center feasibility study comparing the app to the gold standard

OBJECTIVE

Healthcare digitization has led to increasing tablet-based apps to improve diagnostics, self-discipline, and well-being in patients. Moreover, patient-reported outcome measures are crucial for optimized treatment, with superior applicability if independent from patient visits. Whereas most uses cover health maintenance, only a few studies have focused on cognitive testing in neurosurgical patients despite its nature as one of the most integrative outcome measures in neurooncology.

METHODS

The authors performed a prospective single-center feasibility study including neurosurgical patients affected by intraaxial tumors and healthy subjects, testing cognitive function by using a digitized app-based approach and conventional paper-and-pencil (PP) tests. Healthy subjects underwent follow-up testing for retest reliability.

RESULTS

The authors included 24 patients with brain tumor and 10 healthy subjects, all of whom completed both tests. Equivalent mean performance results were found in the tablet-based digital app and PP counterparts; whereas the digital approach had shorter test duration in patients (29.9 minutes for PP vs 21.9 minutes for app, p = 0.019) and in the healthy cohort (23.2 minutes for PP vs 16.4 minutes for app, p = 0.003), patients with brain tumor scored lower when both test strategies were applied. Results were consistent in healthy subjects after a median of 3 months.

CONCLUSIONS

Cognitive function assessment is feasible using a digitized tablet-based app, with equivalent results to those of PP tests in healthy subjects and patients with brain tumor. Thus, this approach allows much closer follow-up independent of patient visits and might provide a viable option to improve patient follow-ups.

Wearables in Schizophrenia: Update on Current and Future Clinical Applications

Schizophrenia affects 1% of the world population and is associated with a reduction in life expectancy of 20 years. The increasing prevalence of both consumer technology and clinical-grade wearable technology offers new metrics to guide clinical decision-making remotely and in real time. Herein, recent literature is reviewed to determine the potential utility of wearables in schizophrenia, including their utility in diagnosis, first-episode psychosis, and relapse prevention and their acceptability to patients. Several studies have further confirmed the validity of various devices in their ability to track sleep—an especially useful metric in schizophrenia, as sleep disturbances may be predictive of disease onset or the acute worsening of psychotic symptoms. Through machine learning, wearable-obtained heart rate and motor activity were used to differentiate between controls and patients with schizophrenia. Wearables can capture the autonomic dysregulation that has been detected when patients are actively experiencing paranoia, hallucinations, or delusions. Multiple platforms are currently being researched, such as Health Outcomes Through Positive Engagement and Self-Empowerment, Mobile Therapeutic Attention for Treatment-Resistant Schizophrenia, and Sleepsight, that may ultimately link patient data to clinicians. The future is bright for wearables in schizophrenia, as the recent literature exemplifies their potential to offer real-time insights to guide diagnosis and management.

Applying machine learning to smartphone based cognitive and sleep assessments in schizophrenia

Background

Methods

Results

Discussion

Validation of an ecological momentary assessment to measure processing speed and executive function in schizophrenia

Cognitive impairments are a core feature of schizophrenia that have negative impacts on functional outcomes. However, it remains challenging to assess these impairments in clinical settings. Smartphone apps provide the opportunity to measure cognitive impairments in an accessible way; however, more research is needed to validate these cognitive assessments in schizophrenia. We assessed the initial accessibility, validity, and reliability of a smartphone-based cognitive test to measure cognition in schizophrenia. A total of 29 individuals with schizophrenia and 34 controls were included in the analyses. Participants completed the standard pen-and-paper Trail Making Tests (TMT) A and B, and smartphone-based versions, Jewels Trail Tests (JTT) A and B, at the single in-lab visit. Participants were asked to complete the JTT remotely once per week for three months. We also investigated how subjective sleep quality and mood may affect cognitive performance longitudinally. In-lab and remote JTT scores moderately and positively correlated with in-lab TMT scores. Moderate test-retest reliability was observed across the in-lab, first remote, and last remote completion times of the JTT. Additionally, individuals with schizophrenia had significantly lower performance compared to controls on both the in-lab JTT and TMT. Self-reported mood had a significant effect on JTT A performance over time but no other significant relationships were found remotely. Our results support the initial accessibility, validity and reliability of using the JTT to measure cognition in schizophrenia. Future research to develop additional smartphone-based cognitive tests as well as with larger samples and in other psychiatric populations are warranted.

The Utility of Cognitive Screeners in the Detection of Dementia Spectrum Disorders in Spanish-Speaking Populations

Increasing rates of dementia spectrum disorders among Spanish-speaking geriatric populations necessitate the development of culturally appropriate cognitive screening tests that can identify neurodegenerative disorders in their earliest stages when emerging disease-modifying treatments are most likely to be effective. This scoping review identified 26 brief Spanish language cognitive screening tools (<20 minutes) by searching academic databases using a combination of search terms. Results suggest that the Mini-Mental Status Examination and Montreal Cognitive Assessment appear to be less valid than other screeners. Instruments such as the 7-Minute Screen and Mini-Cog evidence higher classification rates of dementia, while Phototest detected mild cognitive impairment at higher rates more consistently than other screeners. Different sensitivity and specificity outcomes and cutoffs were observed when the same cognitive screener was evaluated in different countries. Results indicate that it is imperative to increase nation-specific validation and normative data for these instruments to best serve diverse populations.

Citrus Polyphenols in Brain Health and Disease: Current Perspectives

In addition to essential micronutrients such as vitamin C, citrus fruits represent a considerably rich source of non-essential bioactive compounds, in particular flavanones which form a sub-set of the flavonoid group. Preclinical studies have demonstrated the neuroprotective potential of citrus flavonoids and have highlighted both the well-established (anti-inflammatory and anti-oxidative properties), and newly emerging (influence upon blood-brain barrier function/integrity) mechanistic actions by which these neurological effects are mediated. Encouragingly, results from human studies, although limited in number, appear to support this preclinical basis, with improvements in cognitive performance and disease risk observed across healthy and disease states. Therefore, citrus fruits - both as whole fruit and 100% juices - should be encouraged within the diet for their potential neurological benefit. In addition, there should be further exploration of citrus polyphenols to establish therapeutic efficacy, particularly in the context of well-designed human interventions.

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

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

Deriving symptom networks from digital phenotyping data in serious mental illness

BACKGROUND

Symptoms of serious mental illness are multidimensional and often interact in complex ways. Generative models offer value in elucidating the underlying relationships that characterise these networks of symptoms.

AIMS

In this paper we use generative models to find unique interactions of schizophrenia symptoms as experienced on a moment-by-moment basis.

METHOD

Self-reported mood, anxiety and psychosis symptoms, self-reported measurements of sleep quality and social function, cognitive assessment, and smartphone touch screen data from two assessments modelled after the Trail Making A and B tests were collected with a digital phenotyping app for 47 patients in active treatment for schizophrenia over a 90-day period. Patients were retrospectively divided up into various non-exclusive subgroups based on measurements of depression, anxiety, sleep duration, cognition and psychosis symptoms taken in the clinic. Associated transition probabilities for the patient cohort and for the clinical subgroups were calculated using state transitions between adjacent 3-day timesteps of pairwise survey domains.

RESULTS

The three highest probabilities for associated transitions across all patients were anxiety-inducing mood (0.357, P < 0.001), psychosis-inducing mood (0.276, P < 0.001), and anxiety-inducing poor sleep (0.268, P < 0.001). These transition probabilities were compared against a validation set of 17 patients from a pilot study, and no significant differences were found. Unique symptom networks were found for clinical subgroups.

CONCLUSIONS

Using a generative model using digital phenotyping data, we show that certain symptoms of schizophrenia may play a role in elevating other schizophrenia symptoms in future timesteps. Symptom networks show that it is feasible to create clinically interpretable models that reflect the unique symptom interactions of psychosis-spectrum illness. These results offer a framework for researchers capturing temporal dynamics, for clinicians seeking to move towards preventative care, and for patients to better understand their lived experience.

Use of a Mobile App to Augment Psychotherapy in a Community Psychiatric Clinic: Feasibility and Fidelity Trial

BACKGROUND

Even though 1 in 5 Americans experience some form of mental illness each year, 80% have been shown to discontinue psychotherapy prematurely. The traditional psychotherapy service delivery model, consisting of isolated clinical sessions, lacks the ability to keep patients engaged outside clinical sessions. Newer digital mental health platforms can address the clinical need for a robust tool that tracks mental well-being and improves engagement in patients with depressive symptoms.

OBJECTIVE

The primary goals of this feasibility study were to (1) assess compliance among providers and their patients with a digital mental health platform protocol, and (2) examine the usability and fidelity of a mobile app through structured participant feedback.

METHODS

A sample of 30 participants was recruited for a 5-week study from a community-based mental health clinic in Baltimore, Maryland, USA. Inclusion criteria were: aged 18 years or older, having access to a smartphone, and having at least mild-to-moderate depression and/or anxiety as measured by the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) scales, respectively. Eligible participants were randomized into one of two study arms: (1) the intervention arm or (2) the waitlist control arm. Participants in the intervention arm were asked to download the Rose app and were prompted to complete clinical assessments (PHQ-9 and GAD-7) every other week, daily mood and anxiety Likert scales, and daily journal entries. The participants in the waitlist arm served as controls for the study and completed the clinical assessments only. Both arms engaged in weekly psychotherapy sessions, with participant in-app input informing the psychotherapy process of the intervention arm, while those in the waitlist control arm continued their standard care. Outcomes of interest included adherence to completion of in-app assessments and usability of the Rose mobile app assessed through the modified Mobile Application Rating Scale.

RESULTS

Over the study period, a sample of 30 participants used the Rose app 2834 times to complete clinical assessments. On average, 70% (21; 95% CI 61.14%-77.41%) of participants completed mood and anxiety daily check-ins and journal entries 5 days per week. Nearly all participants (29/30, 97%) completed all PHQ-9 and GAD-7 in-app scales during the study. Subjective impressions showed that 73% (22/30) of participants found the mobile app to be engaging and in line with their needs, and approximately 70% (21/30) of participants reported the app functionality and quality of information to be excellent. Additionally, more than two-thirds of the participants felt that their knowledge and awareness of depression and anxiety management improved through using the app.

CONCLUSIONS

Steady compliance and high app ratings showcase the utility of the Rose mobile mental health app in augmenting the psychotherapy process for patients with mood disorders and improving mental health knowledge. Future studies are needed to further examine the impact of Rose on treatment outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04200170; https://clinicaltrials.gov/ct2/show/NCT04200170.