Remote Digital Psychiatry for Mobile Mental Health Assessment and Therapy: MindLogger Platform Development Study

Association Between Electronic Diary-Rated Sleep, Mood, Energy, and Stress With Incident Headache in a Community-Based Sample

BACKGROUND AND OBJECTIVES

The aim of this study was to examine the diurnal links between average and changes in average levels of prospectively rated mood, sleep, energy, and stress as predictors of incident headache in a community-based sample.

METHODS

This observational study included structured clinical diagnostic assessment of both headache syndromes and mental disorders and electronic diaries that were administered 4 times per day for 2 weeks yielding a total of 4,974 assessments. The chief outcomes were incident morning (am) and later-day (pm) headaches. Generalized linear mixed-effects models were used to evaluate the average and lagged values of predictors including subjectively rated mood, anxiety, energy, stress, and sleep quality and objectively measured sleep duration and efficiency on incident am and pm headaches.

RESULTS

The sample included 477 participants (61% female), aged 7 through 84 years. After adjusting for demographic and clinical covariates and emotional states, incident am headache was associated with lower average (ß = -0.206*; confidence intervals: -0.397 to -0.017) and a decrease in average sleep quality on the prior day (ß = -0.172*; confidence interval: -0.305, -0.039). Average stress and changes in subjective energy levels on the prior day were associated with incident headaches but with different valence for am (decrease) (ß = -0.145* confidence interval: -0.286, -0.005) and pm (increase) (ß = 0.157*; confidence interval: 0.032, 0.281) headache. Mood and anxiety disorders were not significantly associated with incident headache after controlling for history of a diagnosis of migraine.

DISCUSSION

Both persistent and acute changes in arousal states manifest by subjective sleep quality and energy are salient precursors of incident headaches. Whereas poorer sleep quality and decreased energy on the prior day were associated with incident morning headache, an increase in energy and greater average stress were associated with headache onsets later in the day. Different patterns of predictors of morning and later-day incident headache highlight the role of circadian rhythms in the manifestations of headache. These findings may provide insight into the pathophysiologic processes underlying migraine and inform clinical intervention and prevention. Tracking these systems in real time with mobile technology provides a valuable ancillary tool to traditional clinical assessments.

Test-retest reliability and agreement of remote home-based functional capacity self-administered assessments in community-dwelling, socially isolated older adults

Objectives

To determine the test-retest reliability and agreement of home-based functional capacity self-administered assessments in socially isolated older adults.

Methods

Fourteen community-dwelling older adults (eight females, 67.9 ± 7.7 years) volunteered for this study. Before testing, participants were screened online for eligibility and received instructional videos explaining test set-up and execution. Participants underwent the 30-second sit-to-standing test, gait speed tests at the usual pace, and timed-up-and-go tests administered 4 weeks apart. For the 30-second sit-to-standing protocol, participants were instructed to repeatedly sit and stand from a chair (with a height of ∼ 43 cm and without armrests) for 30 s, with the number of repetitions recorded. In the gait speed test protocol, participants were instructed to walk at their usual and comfortable pace, with the time taken recorded (seconds). In the timed-up-and-go, participants stood up from a chair, walked as fast as possible for 3 m, circled a marked point, and returned to the chair to sit down, completing the test, with the score recorded (seconds). A trained researcher conducted the scoring virtually via synchronous video.

Results

30-second sit-to-standing, gait speed test, and timed-up-and-go showed excellent mean coefficient of variation values (2.0-4.9), small standard error of measurement (0.08-1.27), excellent intraclass coefficient (0.97-0.99), very strong correlations (0.97-0.99) and good agreement between the two days of testing.

Conclusion

Self-administered functional capacity tests performed by older adults at home were reliable with good agreement. Healthcare professionals and older adults should take advantage of simple remote self-administered assessments performed at home to evaluate older adults' health status.

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.

Illuminating the daily life experiences of adolescents with and without ADHD: protocol for an ecological momentary assessment study

INTRODUCTION

Adolescents with attention-deficit/hyperactivity disorder (ADHD) are at elevated risk of a range of difficulties, among which emotion regulation, peer and co-occurring mental health problems are prominent challenges. To better support adolescents with ADHD, ecologically valid interventions that can be embedded in daily life to target the most proximal antecedents of these challenges are needed. Ecological momentary assessment (EMA) designs are ideally suited to meeting this need.

METHODS AND ANALYSES

In the mental health in the moment ADHD study, we will use an EMA design to capture the daily life experiences of approximately 120 adolescents aged 11-14 years with a clinical diagnosis of ADHD and the same number of age-matched and gender-matched peers without a diagnosis of ADHD. We will combine this with comprehensive information gathered from online surveys. Analysing the data using techniques such as dynamic structural equation modelling, we will examine, among other research questions, the role of emotion regulation and peer problems in mediating the links between characteristics of ADHD and commonly co-occurring outcomes such as anxiety, depression and conduct problems. The results can help inform interventions to support improved peer functioning and emotion regulation for adolescents with ADHD.

ETHICS AND DISSEMINATION

This study received a favourable ethical opinion through the National Health Service ethical review board and the University of Edinburgh PPLS Research Ethics panel. The results will be disseminated through journal publications, conferences and seminar presentations and to relevant stakeholders, such as those with ADHD, their families and clinicians.

Patterns of ongoing thought in the real world

Health and well-being are impacted by our thoughts and the things we do. In the laboratory, studies suggest specific task contexts impact thought processes. More broadly, this suggests the people we are with, the places we are in, and the activities we perform may influence our thought patterns. In our study, participants completed experience sampling surveys for five days in daily life. Principal component analysis decomposed this data to identify common "patterns of thought," and linear mixed modelling related these patterns to the participants' activities. Our study replicated the influence of socializing on patterns of thought and established that this is part of a broader set of relationships linking activities to how thoughts are organized in daily life. Our study suggests sampling thinking in the real world may help map thoughts to activities, and these "thought-activity" mappings could be useful to researchers and health care professionals interested in health and well-being.

NIDM-Terms: community-based terminology management for improved neuroimaging dataset descriptions and query

The biomedical research community is motivated to share and reuse data from studies and projects by funding agencies and publishers. Effectively combining and reusing neuroimaging data from publicly available datasets, requires the capability to query across datasets in order to identify cohorts that match both neuroimaging and clinical/behavioral data criteria. Critical barriers to operationalizing such queries include, in part, the broad use of undefined study variables with limited or no annotations that make it difficult to understand the data available without significant interaction with the original authors. Using the Brain Imaging Data Structure (BIDS) to organize neuroimaging data has made querying across studies for specific image types possible at scale. However, in BIDS, beyond file naming and tightly controlled imaging directory structures, there are very few constraints on ancillary variable naming/meaning or experiment-specific metadata. In this work, we present NIDM-Terms, a set of user-friendly terminology management tools and associated software to better manage individual lab terminologies and help with annotating BIDS datasets. Using these tools to annotate BIDS data with a Neuroimaging Data Model (NIDM) semantic web representation, enables queries across datasets to identify cohorts with specific neuroimaging and clinical/behavioral measurements. This manuscript describes the overall informatics structures and demonstrates the use of tools to annotate BIDS datasets to perform integrated cross-cohort queries.

Evaluating the Use of Online Self-Report Questionnaires as Clinically Valid Mental Health Monitoring Tools in the Clinical Whitespace

Although digital health solutions are increasingly popular in clinical psychiatry, one application that has not been fully explored is the utilization of survey technology to monitor patients outside of the clinic. Supplementing routine care with digital information collected in the "clinical whitespace" between visits could improve care for patients with severe mental illness. This study evaluated the feasibility and validity of using online self-report questionnaires to supplement in-person clinical evaluations in persons with and without psychiatric diagnoses. We performed a rigorous in-person clinical diagnostic and assessment battery in 54 participants with schizophrenia (N = 23), depressive disorder (N = 14), and healthy controls (N = 17) using standard assessments for depressive and psychotic symptomatology. Participants were then asked to complete brief online assessments of depressive (Quick Inventory of Depressive Symptomatology) and psychotic (Community Assessment of Psychic Experiences) symptoms outside of the clinic for comparison with the ground-truth in-person assessments. We found that online self-report ratings of severity were significantly correlated with the clinical assessments for depression (two assessments used: R = 0.63, p < 0.001; R = 0.73, p < 0.001) and psychosis (R = 0.62, p < 0.001). Our results demonstrate the feasibility and validity of collecting psychiatric symptom ratings through online surveys. Surveillance of this kind may be especially useful in detecting acute mental health crises between patient visits and can generally contribute to more comprehensive psychiatric treatment.

A Web-Based Application for Personalized Ecological Momentary Assessment in Psychiatric Care: User-Centered Development of the PETRA Application

BACKGROUND

Smartphone self-monitoring of mood, symptoms, and contextual factors through ecological momentary assessment (EMA) provides insights into the daily lives of people undergoing psychiatric treatment. Therefore, EMA has the potential to improve their care. To integrate EMA into treatment, a clinical tool that helps clients and clinicians create personalized EMA diaries and interpret the gathered data is needed.

OBJECTIVE

This study aimed to develop a web-based application for personalized EMA in specialized psychiatric care in close collaboration with all stakeholders (ie, clients, clinicians, researchers, and software developers).

METHODS

The participants were 52 clients with mood, anxiety, and psychotic disorders and 45 clinicians (psychiatrists, psychologists, and psychiatric nurses). We engaged them in interviews, focus groups, and usability sessions to determine the requirements for an EMA web application and repeatedly obtained feedback on iteratively improved high-fidelity EMA web application prototypes. We used human-centered design principles to determine important requirements for the web application and designed high-fidelity prototypes that were continuously re-evaluated and adapted.

RESULTS

The iterative development process resulted in Personalized Treatment by Real-time Assessment (PETRA), which is a scientifically grounded web application for the integration of personalized EMA in Dutch clinical care. PETRA includes a decision aid to support clients and clinicians with constructing personalized EMA diaries, an EMA diary item repository, an SMS text message-based diary delivery system, and a feedback module for visualizing the gathered EMA data. PETRA is integrated into electronic health record systems to ensure ease of use and sustainable integration in clinical care and adheres to privacy regulations.

CONCLUSIONS

PETRA was built to fulfill the needs of clients and clinicians for a user-friendly and personalized EMA tool embedded in routine psychiatric care. PETRA is unique in this codevelopment process, its extensive but user-friendly personalization options, its integration into electronic health record systems, its transdiagnostic focus, and its strong scientific foundation in the design of EMA diaries and feedback. The clinical effectiveness of integrating personalized diaries via PETRA into care requires further research. As such, PETRA paves the way for a systematic investigation of the utility of personalized EMA for routine mental health care.

Envisioning Post-pandemic Digital Neurological, Psychiatric and Mental Health Care

The SARS-Cov-2 pandemic placed a dramatic burden on managed healthcare and perhaps nowhere as evident as in neurological and psychiatric disease care. This said, the duration of the pandemic mandated adaptability of the entire care system and the oft-vaunted benefits of telehealth and telemedicine were subjected to deep scrutiny at scale. Positive experiences were reported by both patients and providers from routine check-ups, to use of cognitive behavioral therapy associated with mental disorders, and management of complex diseases such as multiple sclerosis and other neurological and psychiatric conditions. Integration into standard care looks likely in the post pandemic era with many healthcare systems moving to expand reimbursement categories and develop equitable incentive models for developers and providers. In this commentary we share perspective on how the future of care may evolve through hybrid delivery models, and the advent of new therapeutic approaches which can address pain points identified during the pandemic.