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.

Development of a Mobile Assessment Tool for Understanding Social Comparison Processes Among Individuals With Schizophrenia: Two-Phase Survey Study

Background

Digital tools may help to address social deficits in schizophrenia, particularly those that engage social comparison processes (ie, evaluating oneself relative to others). Yet, little is known about social comparison processes in schizophrenia or how best to capture between- versus within-person variability, which is critical to engaging comparisons in digital interventions.

Objective

The goals of this pilot study were to (1) better understand affective responses to social comparisons among individuals with schizophrenia, relative to healthy controls, using a validated global self-report measure; and (2) test a new brief, mobile assessment of affective responses to social comparison among individuals with schizophrenia, relative to the full measure. This study was conducted in 2 phases.

Methods

We first compared self-reported affective responses to social comparisons between individuals with schizophrenia (n=39) and healthy controls (n=38) using a traditional self-report measure, at 2 time points. We examined the temporal stability in responses and differences between groups. We then evaluated the performance of brief, mobile assessment of comparison responses among individuals with schizophrenia, completed over 12 weeks (n=31).

Results

Individuals with schizophrenia showed greater variability in affective responses to social comparison than controls on traditional measures and completed an average of 7.46 mobile assessments over 12 weeks. Mobile assessments captured within-person variability in affective responses in the natural environment (intraclass correlation coefficients of 0.40-0.60). Average scores for mobile assessments were positively correlated with responses to traditional measures.

Conclusions

Affective responses to social comparison vary both between and within individuals with schizophrenia and capturing this variability via smartphone surveys shows some evidence of feasibility. As affective variability is a potential indicator of poor outcomes among individuals with mental health conditions, in the future, a brief, mobile assessment of affective responses to social comparisons may be useful for screening among individuals with schizophrenia. Further research on this process is needed to identify when specific comparison messaging may be most effective in digital interventions and could suggest new therapeutic targets for illnesses such as schizophrenia.

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.

Smartphone apps for eating disorders: An overview of the marketplace and research trends

OBJECTIVE

Apps purporting to assist with the management of eating disorders are proliferating; although less is known about (a) the safety or efficacy of the apps on the marketplaces and (b) if the research evidence supports dissemination of these apps. In this research forum, we seek to synthesize the current data and provide practical considerations around the use and research of these apps.

METHODS

A search of the iOS and Google Play stores was conducted in June 2021 to identify publicly available apps targeting eating disorders. A PubMed search was also conducted in June 2021 to identify relevant publications around smartphone apps for eating disorders.

RESULTS

Sixty-five apps that support the treatment of eating disorders were identified and coded across 105 data points on the publicly available mindApps.org website. The literature search revealed 13 articles. Seven percent of marketplaces apps offered any research support and the 13 published studies focused on only four apps.

DISCUSSION

There is a need for more translational research on smartphone apps for eating disorders. Current marketplace offerings present risks that may not be balanced by their limited evidence. Research efforts should focus on offering evidenced-based apps for the marketplace. Clinicians should weigh known and emerging risks and benefits of these apps within the context of research gaps when making decisions around use.

Smartphone-Based Neuropsychological Assessment in Parkinson's Disease: Feasibility, Validity, and Contextually Driven Variability in Cognition

OBJECTIVES

The prevalence of neurodegenerative disorders demands methods of accessible assessment that reliably captures cognition in daily life contexts. We investigated the feasibility of smartphone cognitive assessment in people with Parkinson's disease (PD), who may have cognitive impairment in addition to motor-related problems that limit attending in-person clinics. We examined how daily-life factors predicted smartphone cognitive performance and examined the convergent validity of smartphone assessment with traditional neuropsychological tests.

METHODS

Twenty-seven nondemented individuals with mild-moderate PD attended one in-lab session and responded to smartphone notifications over 10 days. The smartphone app queried participants 5x/day about their location, mood, alertness, exercise, and medication state and administered mobile games of working memory and executive function.

RESULTS

Response rate to prompts was high, demonstrating feasibility of the approach. Between-subject reliability was high on both cognitive games. Within-subject variability was higher for working memory than executive function. Strong convergent validity was seen between traditional tests and smartphone working memory but not executive function, reflecting the latter's ceiling effects. Participants performed better on mobile working memory tasks when at home and after recent exercise. Less self-reported daytime sleepiness and lower PD symptom burden predicted a stronger association between later time of day and higher smartphone test performance.

CONCLUSIONS

These findings support feasibility and validity of repeat smartphone assessments of cognition and provide preliminary evidence of the effects of context on cognitive variability in PD. Further development of this accessible assessment method could increase sensitivity and specificity regarding daily cognitive dysfunction for PD and other clinical populations.

Financial Worry and Psychological Distress Among Immigrants in the United States, 2013-2018

The coronavirus disease 2019 (COVID-19) pandemic has highlighted links among economic stability, health outcomes, and migration. The facets of financial worry and their associated psychological burden have been understudied among the immigrant population. The goal of this study was to determine the specific facets of financial worry and associated psychological burden in immigrants. This cross-sectional study, which used data from the 2013 to 2018 National Health Interview Survey (NHIS), examined patient-reported measures of worry regarding financial strain. The NHIS is a household survey of noninstitutionalized, nonmilitary adults in the United States. Multivariable ordinal logistic regressions were used to define adjusted odds ratios (AORs) for financial worry and psychological distress, adjusting for various sociodemographic variables. Among 131,669 US-born and 26,155 non-US-born participants who responded to all 6 questions on the 6-item Kessler Psychological Distress Scale (K6), the overall prevalence of participants reporting any serious psychological distress (K6 score ≥13) was 3.0% and 2.25%, respectively. Despite these overall prevalence data, there were specific areas of financial worries that were higher in non-US-born participants than in US-born participants. Compared with US-born participants, non-US-born participants had higher rates of financial worries regarding retirement [75.78% vs. 69.08%, AOR=1.37, 95% confidence interval (CI) 1.29-1.45, P<0.001], medical costs due to illness (worry about not being able to pay medical costs of a serious illness or accident) (74.94% vs. 65.27%, AOR=1.37, 95% CI: 1.29-1.45, P<0.001), standard of living (74.25% vs. 65.29%, AOR=1.42, 95% CI: 1.34-1.51, P<0.001), and medical cost of health care (worry about not having enough to pay medical costs for normal health care) (66.52% vs. 52.67%, AOR=1.51, 95% CI: 1.43-1.60, P<0.001), among other costs. Notably, serious psychological distress in non-US-born individuals was associated with increased financial worry relative to US-born individuals with a similar level of psychological distress. Further research is needed to evaluate the role physicians can play in mitigating psychological distress in patients with increased financial worry.

Current directions in digital interventions for mood and anxiety disorders

PURPOSE OF REVIEW

The purpose of this review is to provide an overview of the current scope of digital interventions for anxiety and mood disorders, with a focus on smartphone apps, for clinicians and mental healthcare providers.

RECENT FINDINGS

Of the 11 randomized controlled trials analyzed, 7 showed evidence that guided digital interventions (those supported by humans) were effective in improving anxiety and mood symptoms, and 3 showed evidence that unguided (those not supported by humans) interventions were effective. Psychoeducation was the most popular feature of both guided and unguided interventions. Attrition was highest (50%) in the unguided app-based intervention and lowest in the guided interventions. Many studies lacked active control groups and comparison was often made to a nondigital or waitlist control condition.

SUMMARY

Guided digital interventions continue to show promising results and can be used to enhance clinical care with minimal resources although more direct comparisons to existing treatments are necessary to understand their actual efficacy. Unguided self-help apps and chatbots remain promising, but more work is necessary to understand the real-world engagement and efficacy of these interventions.

Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials

Mobile phone-based interventions have been proposed as a means for reducing the burden of disease associated with mental illness. While numerous randomized controlled trials and meta-analyses have investigated this possibility, evidence remains unclear. We conducted a systematic meta-review of meta-analyses examining mobile phone-based interventions tested in randomized controlled trials. We synthesized results from 14 meta-analyses representing 145 randomized controlled trials and 47,940 participants. We identified 34 effect sizes representing unique pairings of participants, intervention, comparisons, and outcome (PICO) and graded the strength of the evidence as using umbrella review methodology. We failed to find convincing evidence of efficacy (i.e., n > 1000, p < 10^-6, I ² < 50%, absence of publication bias); publication bias was rarely assessed for the representative effect sizes. Eight effect sizes provided highly suggestive evidence (i.e., n > 1000, p < 10^-6), including smartphone interventions outperforming inactive controls on measures of psychological symptoms and quality of life (ds = 0.32 to 0.47) and text message-based interventions outperforming non-specific controls and active controls for smoking cessation (ds = 0.31 and 0.19, respectively). The magnitude of effects and strength of evidence tended to diminish as comparison conditions became more rigorous (i.e., inactive to active, non-specific to specific). Four effect sizes provided suggestive evidence, 14 effect sizes provided weak evidence, and eight effect sizes were non-significant. Despite substantial heterogeneity, no moderators were identified. Adverse effects were not reported. Taken together, results support the potential of mobile phone-based interventions and highlight key directions to guide providers, policy makers, clinical trialists, and meta-analysts working in this area.

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

Background

Methods

Results

Discussion

Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review

Background

Poor diet, alcohol use, and tobacco smoking have been identified as strong determinants of chronic diseases, such as cardiovascular disease, diabetes, and cancer. Smartphones have the potential to provide a real-time, pervasive, unobtrusive, and cost-effective way to measure these health behaviors and deliver instant feedback to users. Despite this, the validity of using smartphones to measure these behaviors is largely unknown.

Objective

The aim of our review is to identify existing smartphone-based approaches to measure these health behaviors and critically appraise the quality of their measurement properties.

Methods

We conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsycINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Articles that were written in English; reported measuring diet, alcohol use, or tobacco use via a smartphone; and reported on at least one measurement property (eg, validity, reliability, and responsiveness) were eligible. The methodological quality of the included studies was assessed using the Consensus-Based Standards for the Selection of Health Measurement Instruments Risk of Bias checklist. Outcomes were summarized in a narrative synthesis. This systematic review was registered with PROSPERO, identifier CRD42019122242.

Results

Of 12,261 records, 72 studies describing the measurement properties of smartphone-based approaches to measure diet (48/72, 67%), alcohol use (16/72, 22%), and tobacco use (8/72, 11%) were identified and included in this review. Across the health behaviors, 18 different measurement techniques were used in smartphones. The measurement properties most commonly examined were construct validity, measurement error, and criterion validity. The results varied by behavior and measurement approach, and the methodological quality of the studies varied widely. Most studies investigating the measurement of diet and alcohol received very good or adequate methodological quality ratings, that is, 73% (35/48) and 69% (11/16), respectively, whereas only 13% (1/8) investigating the measurement of tobacco use received a very good or adequate rating.

Conclusions

This review is the first to provide evidence regarding the different types of smartphone-based approaches currently used to measure key behavioral risk factors for chronic diseases (diet, alcohol use, and tobacco use) and the quality of their measurement properties. A total of 19 measurement techniques were identified, most of which assessed dietary behaviors (48/72, 67%). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviors; however, the results varied by behavior and measurement approach. The methodological quality of the included studies also varied. Overall, more high-quality studies validating smartphone-based approaches against criterion measures are needed. Further research investigating the use of smartphones to assess alcohol and tobacco use and objective measurement approaches is also needed.

International Registered Report Identifier (IRRID)

RR2-https://doi.org/10.1186/s13643-020-01375-w

Information and communication technology-based interventions for suicide prevention implemented in clinical settings: a scoping review protocol

INTRODUCTION

There is a surplus of information and communication technology (ICT)-based interventions for suicide prevention. However, it is unclear which of these ICT-based interventions for suicide prevention have been implemented in clinical settings. Furthermore, evidence shows that implementation strategies have often been mismatched to existing barriers. In response, the authors recognise the critical need for prospectively assessing the barriers and facilitators and then strategically developing implementation strategies. This review is part of a multiphase project to develop and test tailored implementation strategies for mobile app-based suicide prevention in clinical settings. The overall objective of this scoping review is to identify and characterise ICT-based interventions for all levels of suicide prevention in clinical settings. Additionally, this review will identify and characterise the barriers and facilitators to implementing these ICT-based interventions as well as reported measures and outcomes. The findings will directly inform the subsequent phase to maximise implementation and inform future efforts for implementing other types of ICT-based interventions related to suicide prevention in clinical settings.

METHODS AND ANALYSIS

This review will adhere to the methods described by the Joanna Briggs Institute for conducting scoping reviews. The reporting will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review checklist. The following databases will be searched: Medline, PsycInfo, Embase, Cumulative Index to Nursing & Allied Health Literature (CINAHL), Web of Science and Library, Information Science & Technology Abstracts (LISTA). Two reviewers will independently screen the articles and extract data using a standardised data collection tool. Then, authors will characterise extracted data using frameworks, typology and taxonomies to address the proposed review questions.

ETHICS AND DISSEMINATION

Ethics approval is not required for this scoping review. Authors will share the results in a peer-reviewed, open access publication and conference presentations. Furthermore, the findings will be shared with relevant health organisations through lay language summaries and informal presentations.

Problematic Internet Use Before and During the COVID-19 Pandemic in Youth in Outpatient Mental Health Treatment: App-Based Ecological Momentary Assessment Study

BACKGROUND

Youth with existing psychiatric illness are more apt to use the internet as a coping skill. Because many "in-person" coping skills were not easily accessible during the COVID-19 pandemic, youth in outpatient mental health treatment may have been particularly vulnerable to the development of problematic internet use (PIU). The identification of a pandemic-associated worsening of PIU in this population is critical in order to guide clinical care; if these youth have become dependent upon the internet to regulate their negative emotions, PIU must be addressed as part of mental health treatment. However, many existing studies of youth digital media use in the pandemic do not include youth in psychiatric treatment or are reliant upon cross-sectional methodology and self-report measures of digital media use.

OBJECTIVE

This is a retrospective cohort study that used data collected from an app-based ecological momentary assessment protocol to examine potential pandemic-associated changes in digital media youth in outpatient mental health treatment. Secondary analyses assessed for differences in digital media use dependent upon personal and familial COVID-19 exposure and familial hospitalization, as well as factors associated with PIU in this population.

METHODS

The participants were aged 12-23 years and were receiving mental health treatment in an outpatient community hospital setting. All participants completed a 6-week daily ecological momentary assessment protocol on their personal smartphones. Questions were asked about depression (PHQ-8 [8-item Patient Health Questionnaire]), anxiety (GAD-7 [7-item General Anxiety Disorder]), PIU (PIU-SF-6 [Problematic Internet Use Short Form 6]), digital media use based on Apple's daily screen time reports, and personal and familial COVID-19 exposure. The analyses compared screen time, psychiatric symptoms, and PIU between cohorts, as well as between youth with personal or familial COVID-19 exposures and those without. The analyses also assessed for demographic and psychiatric factors associated with clinically significant PIU-SF-6 scores.

RESULTS

A total of 69 participants completed the study. The participants recruited during the pandemic were significantly more likely to meet the criteria for PIU based on their average PIU-SF-6 score (P=.02) and to spend more time using social media each day (P=.049). The overall amount of daily screen time did not differ between cohorts. Secondary analyses revealed a significant increase in average daily screen time among subjects who were exposed to COVID-19 (P=.01). Youth with clinically significant PIU-SF-6 scores were younger and more likely to have higher PHQ-8 (P=.003) and GAD-7 (P=.003) scores. No differences in scale scores or media use were found between subjects based on familial COVID-19 exposure or hospitalization.

CONCLUSIONS

Our findings support our hypothesis that PIU may have worsened for youth in mental health treatment during the pandemic, particularly the problematic use of social media. Mental health clinicians should incorporate screening for PIU into routine clinical care in order to prevent potential familial conflict and subsequent psychiatric crises that might stem from unrecognized PIU.

Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study

BACKGROUND

There is a growing need for the integration of patient-generated health data (PGHD) into research and clinical care to enable personalized, preventive, and interactive care, but technical and organizational challenges, such as the lack of standards and easy-to-use tools, preclude the effective use of PGHD generated from consumer devices, such as smartphones and wearables.

OBJECTIVE

This study outlines how we used mobile apps and semantic web standards such as HTTP 2.0, Representational State Transfer, JSON (JavaScript Object Notation), JSON Schema, Transport Layer Security (version 1.3), Advanced Encryption Standard-256, OpenAPI, HTML5, and Vega, in conjunction with patient and provider feedback to completely update a previous version of mindLAMP.

METHODS

The Learn, Assess, Manage, and Prevent (LAMP) platform addresses the abovementioned challenges in enhancing clinical insight by supporting research, data analysis, and implementation efforts around PGHD as an open-source solution with freely accessible and shared code.

RESULTS

With a simplified programming interface and novel data representation that captures additional metadata, the LAMP platform enables interoperability with existing Fast Healthcare Interoperability Resources-based health care systems as well as consumer wearables and services such as Apple HealthKit and Google Fit. The companion Cortex data analysis and machine learning toolkit offer robust support for artificial intelligence, behavioral feature extraction, interactive visualizations, and high-performance data processing through parallelization and vectorization techniques.

CONCLUSIONS

The LAMP platform incorporates feedback from patients and clinicians alongside a standards-based approach to address these needs and functions across a wide range of use cases through its customizable and flexible components. These range from simple survey-based research to international consortiums capturing multimodal data to simple delivery of mindfulness exercises through personalized, just-in-time adaptive interventions.

E-Mental Health for People with Personality Disorders: A Systematic Review

PURPOSE OF REVIEW

Provision of mental health services through digital technologies (e-mental health) can potentially expand access to treatments for personality disorders (PDs). We evaluated studies on e-mental health for PDs published over the last 3 years (2019-2022).

RECENT FINDINGS

Studies published in English that used e-mental health to treat people with PDs or PD-related symptoms were identified. We identified 19 studies, including four randomized controlled trials and one meta-analysis. Most interventions were based on Dialectical Behavior Therapy and delivered through smartphone applications for adults with Borderline Personality Disorder [BPD] or related symptoms. User experiences of the interventions were generally positive. Evidence for efficacy was limited. The current literature on e-mental health for PDs is limited in scope. Research in understudied populations and randomized controlled trials designed to establish efficacy are warranted. It is not yet clear whether e-mental health may be helpful for the treatment of PDs.

Smartphone digital phenotyping, surveys, and cognitive assessments for global mental health: Initial data and clinical correlations from an international first episode psychosis study

Objective

To examine feasibility and acceptability of smartphone mental health app use for symptom, cognitive, and digital phenotyping monitoring among people with schizophrenia in India and the United States.

Methods

Participants in Boston, USA and Bhopal and Bangalore, India used a smartphone app to monitor symptoms, play cognitive games, access relaxation and psychoeducation resources and for one month, with an initial clinical and cognitive assessment and a one-month follow-up clinical assessment. Engagement with the app was compared between study sites, by clinical symptom severity and by cognitive functioning. Digital phenotyping data collection was also compared between three sites.

Results

By Kruskal-Wallis rank-sum test, we found no difference between app activities completed or digital phenotyping data collected across the three study sites. App use also did not correlate to clinical or cognitive assessment scores. When using the app for symptom monitoring, preliminary findings suggest app-based assessment correlate with standard cognitive and clinical assessments.

Conclusions

Smartphone app for symptom monitoring and digital phenotyping for individuals with schizophrenia appears feasible and acceptable in a global context. Clinical utility of this app for real-time assessments is promising, but further research is necessary to determine the long-term efficacy and generalizability for serious mental illness.

Individualized Intervention to Support Mental Health Recovery Through Implementation of Digital Tools into Clinical Care: Feasibility Study

Myriad digital tools exist to support mental health but there are multiple barriers to using these tools in routine care. This study aimed to assess the feasibility of an intervention incorporating a support role to help the clinical team identify and use technology to promote recovery. The technology specialist intervention is 3 months in duration and comprises four stages: goal setting, researching and evaluating tools, demonstrating and selecting tools, and ongoing support. We implemented the intervention in a community mental health center and a dual diagnosis treatment program, working with eight clients and their case managers. Clients and case managers willingly engaged with the technology specialist and found the intervention beneficial. Integration and collaboration with the care team facilitated implementation of the technology specialist in these real-world settings. Clients reported that the intervention made it easy to try a digital tool. Six of the eight participants stated that they made substantial progress toward their goals. The technology specialist is a promising new role for mental health care delivery to augment traditional services and enhance individualized recovery.

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.

What gets resident physicians stressed and how would they prefer to be supported? A best-worst scaling study

INTRODUCTION

Physician burnout has severe consequences on clinician well-being. Residents face numerous work-stressors that can contribute to burnout; however, given specialty variation in work-stress, it is difficult to identify systemic stressors and implement effective burnout interventions on an institutional level. Assessing resident preferences by specialty for common wellness interventions could also contribute to improved efficacy.

METHODS

This cross-sectional study used best-worst scaling (BWS), a type of discrete choice modelling, to explore how 267 residents across nine specialties (anaesthesiology, emergency medicine, internal medicine, neurology, obstetrics and gynaecology, pathology, psychiatry, radiology and surgery) prioritised 16 work-stressors and 4 wellness interventions at a large academic medical centre during the COVID-19 pandemic (December 2020).

RESULTS

Top-ranked stressors were work-life integration and electronic health record documentation. Therapy (63%, selected as 'would realistically consider intervention') and coaching (58%) were the most preferred wellness supports in comparison to group-based peer support (20%) and individual peer support (22%). Pathology, psychiatry and OBGYN specialties were most willing to consider all intervention options, with emergency medicine and internal medicine specialties least willing to consider intervention options.

CONCLUSION

BWS can identify relative differences in surveyed stressors, allowing for the generation of specialty-specific stressor rankings and preferences for specific wellness interventions that can be used to drive institution-wide changes to improve clinician wellness. BWS surveys are a potential methodology for clinician wellness programmes to gather specific information on preferences to determine best practices for resident wellness.

The benefits and harms of open notes in mental health: A Delphi survey of international experts

IMPORTANCE

As of April 5, 2021, as part of the 21st Century Cures Act, new federal rules in the U.S. mandate that providers offer patients access to their online clinical records.

OBJECTIVE

To solicit the view of an international panel of experts on the effects on mental health patients, including possible benefits and harms, of accessing their clinical notes.

DESIGN

An online 3-round Delphi poll.

SETTING

Online.

PARTICIPANTS

International experts identified as clinicians, chief medical information officers, patient advocates, and informaticians with extensive experience and/or research knowledge about patient access to mental health notes.

MAIN OUTCOMES, AND MEASURES

An expert-generated consensus on the benefits and risks of sharing mental health notes with patients.

RESULTS

A total of 70 of 92 (76%) experts from 6 countries responded to Round 1. A qualitative review of responses yielded 88 distinct items: 42 potential benefits, and 48 potential harms. A total of 56 of 70 (80%) experts responded to Round 2, and 52 of 56 (93%) responded to Round 3. Consensus was reached on 65 of 88 (74%) of survey items. There was consensus that offering online access to mental health notes could enhance patients' understanding about their diagnosis, care plan, and rationale for treatments, and that access could enhance patient recall and sense of empowerment. Experts also agreed that blocking mental health notes could lead to greater harms including increased feelings of stigmatization. However, panelists predicted there could be an increase in patients demanding changes to their clinical notes, and that mental health clinicians would be less detailed/accurate in documentation.

CONCLUSIONS AND RELEVANCE

This iterative process of survey responses and ratings yielded consensus that there would be multiple benefits and few harms to patients from accessing their mental health notes. Questions remain about the impact of open notes on professional autonomy, and further empirical work into this practice innovation is warranted.

Self-Reported Preferences for Help-Seeking and Barriers to Using Mental Health Supports Among Internal Medicine Residents: Exploratory Use of an Econometric Best-Worst Scaling Framework for Gathering Physician Wellness Preferences

BACKGROUND

Burnout interventions are limited by low use. Understanding resident physician preferences for burnout interventions may increase utilization and improve the assessment of these interventions.

OBJECTIVE

This study aims to use an econometric best-worst scaling (BWS) framework to survey internal medicine resident physicians to establish help-seeking preferences for burnout and barriers to using wellness supports by quantifying selections for 7 wellness support options and 7 barriers.

METHODS

Internal medicine resident physicians at our institution completed an anonymous web-based BWS survey during the 2020-2021 academic year. This cross-sectional study was analyzed with multinomial logistic regression and latent class modeling to determine the relative rank ordering of factors for seeking support for burnout and barriers to using wellness supports. Analysis of variance with Tukey honest significant difference posthoc test was used to analyze differences in mean utility scores representing choice for barriers and support options.

RESULTS

Of the 163 invited residents, 77 (47.2% response rate) completed the survey. Top-ranking factors for seeking wellness supports included seeking informal peer support (best: 71%; worst: 0.6%) and support from friends and family (best: 70%; worst: 1.6%). Top-ranking barriers to seeking counseling included time (best: 75%; worst: 5%) and money (best: 35%; worst: 21%).

CONCLUSIONS

Overall, our findings suggest that low utilization of formal mental health support is reflective of resident preferences to seek help informally and that increasing utilization will require addressing pragmatic barriers of time and cost. Assessing physician preferences for wellness-related initiatives may contribute to understanding the low utilization of formal mental health services among physicians, which can be determined using a BWS framework.

Supporting the Mental Health Workforce During and After COVID-19

The COVID-19 pandemic has catalyzed structural changes in the public mental health sector, including a shift to telehealth and telesupervision, financial strain for community mental health organizations and clinicians, and risk of burnout among clinicians and staff. This Open Forum considers how technical assistance organizations have supported community mental health providers in adapting to these changes. Moving forward, knowledge gained through this work can help to build the body of practice-based evidence to inform future technical assistance activities in a postpandemic world.