Ecological momentary assessment as a measurement tool in depression trials

Affect dimensions and variability during major depressive episodes: Ecological momentary assessment of unipolar, bipolar, and borderline patients and healthy controls

Differentiating major depressive episodes (MDEs) of major depressive disorder (MDD), bipolar disorder (MDE/BD) and the MDEs comorbid with borderline personality disorder (MDE/BPD) is crucial for appropriate treatment, and knowledge of phenomenological differences may aid this. However, studies comparing affect experiences of these three patient groups and healthy subjects are scarce. In our study, participants (N = 114), including patients with MDD (n = 34), MDE/BD (n = 27), and MDE/BPD (n = 24), and healthy controls (HC, n = 29) responded to ecological momentary assessment (EMA) with ten circumplex model affect items ten times daily for seven days (7709 recordings). Explorative factor analysis resulted in two affect dimensions. The positive dimension included active, excited, cheerful (high arousal), and content (low arousal) affects, and the negative dimension irritated, angry, and nervous (high arousal) affects. Relative to HC, patients reported 3.5-fold negative affects (mean MDD 1.36 (SD 0.92), MDE/BD 1.43 (0.76), MDE/BPD 1.81 (0.95) vs. HC 0.44 (0.49) (p < 0.01)) but 0.5-fold positive affects (2.01 (0.90), 1.95 (0.89), 2.24 (1.03), vs. 3.2 (0.95), respectively (p < 0.01)). We used multilevel modelling. Negative-affect within-individual stability was lowest in MDE/BPD and highest in MDD. Negative affect predicted concurrent positive affect more in MDE/BPD than in MDD. Moderate size of subcohorts and no inpatients were limitations. Despite apparently similar MDEs, affective experiences may differ between BPD, BD, and MDD patients. Clinical subgroups of patients with depression may vary in affective instability and concurrent presence of negative and positive affects during depression.

Predicting Completion of Ecological Momentary Assessments Among Substance-Using Women Experiencing Intimate Partner Violence

Noncompletion of ecological momentary assessment (EMA) surveys is a common issue and may yield bias in results if not properly handled. Using data observed at scheduled times as well as data retrieved later to fill missing responses, this study aims to investigate predictors of EMA completion, including demographic characteristics, time-related factors, and momentary experiences/behaviors. Data were from a 30-day EMA study including 145 women currently experiencing intimate partner violence (IPV) and using substances. The average rate of EMA completion was initially 51.4% at the scheduled times and increased to 72.6% after incorporating data from later-retrieved surveys. Participants who were younger, had more children, or had lower mean levels of negative affect dysregulation showed lower completion rates. At the momentary survey level, more days into the study and afternoon/evening reports (vs. morning reports) were associated with lower completion; lower levels of negative affect dysregulation, less smoking or alcohol use, and experiencing IPV were linked to lower momentary completion. Implications of the results for handling missing data in EMA are discussed and have important ramifications for future research, practice, and theory.

Improving older adults' autobiographical memory through video-conferencing intervention during COVID-19

BACKGROUND

Autobiographical memory (AM) is valuable not only as an indicator of mental health and cognitive function, but also as a target of therapeutic intervention for older adults. In the context of the COVID-19 pandemic, the demand for online psychosocial interventions and assessment services has sharply increased. Thus, the present study examined the effectiveness of videoconferencing AM (vAM) intervention using the Ecological Momentary Assessment (EMA) method in addition to the traditional paper-and-pencil assessment among samples of community dwelling older adults.

METHODS

Twenty-seven older adults (aged 66-86 years) participated in a vAM intervention composed of 4 weekly 90-min sessions. The primary outcome was AM specificity, with secondary outcomes as depressive symptom and cognitive function, measured before and after the intervention. In addition, daily emotions were measured through EMA over 4 weeks of intervention. The EMA data were analyzed using a multilevel analysis.

RESULTS

The results showed low dropout rates (7%) and high EMA response rates (85%). Autobiographical memory specificity increased (Cohen's d = 0.678), and the level of depression declined significantly (Cohen's d = 0.375) after the program. Additionally, measures assessing cognitive function, such as Seoul Verbal Learning Test and DSC (Digit Symbol Coding), showed significant improvements. The EMA results indicated a decrease in the intensity and proportion of negative emotions experienced during the program.

CONCLUSIONS

This study is the first to utilize videoconferencing and EMA to deliver an AM intervention targeting older adults. The intervention was effective in improving mental health and cognitive function, including AM in older adults. Additionally, EMA was found to be a feasible tool for use in older adults.

Recommendations for selection and adaptation of rating scales for clinical studies of rapid-acting antidepressants

The novel mechanisms of action (MOA) derived from some recently introduced molecular targets have led to regulatory approvals for rapid acting antidepressants (RAADs) that can generate responses within hours or days, rather than weeks or months. These novel targets include the N-methyl-D-glutamate receptor antagonist ketamine, along with its enantiomers and various derivatives, and the allosteric modulators of gamma-aminobutyric acid (GABA) receptors. There has also been a strong resurgence in interest in psychedelic compounds that impact a range of receptor sites including D1, 5-HT7, KOR, 5-HT5A, Sigma-1, NMDA, and BDNF. The RAADs developed from these novel targets have enabled successful treatment for difficult to treat depressed individuals and has generated a new wave of innovation in research and treatment. Despite the advances in the neurobiology and clinical treatment of mood disorders, we are still using rating instruments that were created decades ago for drugs from a different era (e.g., The Hamilton and Montgomery-Åsberg depression rating scales, HDRS, and MADRS) continue to be used. These rating instruments were designed to assess mood symptoms over a 7-day time frame. Consequently, the use of these rating instruments often requires modifications to address items that cannot be assessed in short time frames, such as the sleep and appetite items. This review describes the adaptative approaches that have been made with the existing scales to meet this need and examines additional domains such as daily activities, side effects, suicidal ideation and behavior, and role functioning. Recommendations for future studies are described, including the challenges related to implementation of these adapted measures and approaches to mitigation.

Integrating personalized experience sampling in psychotherapy: A case illustration of the Therap-i module

Background

The experience sampling methodology (ESM) is increasingly being suggested as a clinical tool in mental health care, as it offers ecologically valid, microlevel information on psychopathological processes. Patients and clinicians have recommended that applications of ESM should be personalized and integrated into the existing clinical process, but there is still much uncertainty about how implementation may look like.

Objective

To provide an example of personalized ESM assessment and feedback being integrated into psychotherapy for depression, specifically looking at the collaborative use of ESM in case conceptualization.

Methods

George, a 27-year-old man diagnosed with depression, and his therapist participated in the Therap-i randomized controlled trial, which investigates the efficacy of a personalized ESM module added to psychotherapy. Together, they created a personalized ESM questionnaire, aiming to capture their hypotheses and questions regarding George's case conceptualization. George then filled out his ESM questionnaire five times per day, for 8 weeks. During this period, ESM data were discussed and interpreted by George, his therapist, and a researcher, in three feedback sessions. In these sessions, data were visualized in a flexible feedback interface that allowed for collaborative exploration of George's data. Both patient and therapist evaluated the module through questionnaires and George also participated in a semi-structured evaluation interview.

Results

George's ESM questionnaire included personalized items on the topics of self-esteem and open versus withdrawn behavior. He completed 241 (89.3%) assessments. Discussions during the feedback sessions focused on two core themes: First, George's low energy level, which was further explored with regard to his sleep, medication, and activity patterns. Second, his low sense of self-esteem, which led to an in-depth exploration of his thinking patterns and social interactions. The ESM module was seen as useful and insightful by both George and therapist.

Conclusions

This case shows how ESM and ESM-based feedback can stimulate the collaborative exploration of the patient's complaints, and how it can provide useful insights for treatment. We discuss how our personalized ESM module relates to current clinical principles and practices, and make suggestions for further implementation.

Pilot study of a smartphone-based tinnitus therapy using structured counseling and sound therapy: A multiple-baseline design with ecological momentary assessment

Tinnitus affects a considerable part of the population and develops into a severe disorder in some sufferers. App-based interventions are able to provide low-threshold, cost-effective, and location-independent care for tinnitus patients. Therefore, we developed a smartphone app combining structured counseling with sound therapy and conducted a pilot study to evaluate treatment compliance and symptom improvement (trial registration: DRKS00030007). Outcome variables were Ecological Momentary Assessment (EMA) measured tinnitus distress and loudness and Tinnitus Handicap Inventory (THI) at baseline and final visit. A multiple-baseline design with a baseline phase (only EMA) followed by an intervention phase (EMA and intervention) was applied. 21 patients with chronic tinnitus (≥ 6 months) were included. Overall compliance differed between modules (EMA usage: 79% of days, structured counseling: 72%, sound therapy: 32%). The THI score improved from baseline to final visit indicating a large effect (Cohens d = 1.1). Tinnitus distress and loudness did not improve significantly from baseline phase to the end of intervention phase. However, 5 of 14 (36%) improved clinically meaningful in tinnitus distress (ΔDistress ≥ 10) and 13 of 18 (72%) in THI score (ΔTHI ≥ 7). The positive relationship between tinnitus distress and loudness weakened over the course of the study. A trend but no level effect for tinnitus distress could be demonstrated by a mixed effect model. The improvement in THI was strongly associated with the improvement scores in EMA of tinnitus distress (r = -0.75; 0.86). These results indicate that app-based structured counseling combined with sound therapy is feasible, has an impact on tinnitus symptoms and reduces distress for several patients. In addition, our data suggest that EMA could be used as a measurement tool to detect changes in tinnitus symptoms in clinical trials as has already been shown in other areas of mental health research.

Impact of smartphone overuse on 1-year severe depressive symptoms and momentary negative affect: Longitudinal and experience sampling findings from a representative epidemiological youth sample in Hong Kong

Smartphone overuse can have detrimental impacts on youth mental health. How it may be longitudinally associated with depressive symptoms and functioning, and with daily momentary affect, remains to be investigated. A total of 3,033 young people were consecutively recruited from a large-scale epidemiological youth mental health study in Hong Kong. A subsample (n = 936) was followed-up after 1 year, with experience sampling data collected from 177 participants. Separate multivariable logistic regression models were applied to examine the prospective associations between smartphone overuse and depressive symptoms, with multilevel models fitted to examine its associations with momentary affect. The prevalence of smartphone overuse in the Hong Kong youth population was 29.3%. Smartphone overuse was significantly associated with more depressive symptoms and functional impairments both cross-sectionally and longitudinally. The associations between smartphone overuse and 1-year depressive symptoms were significant, even when accounting for baseline symptoms, social media use, and other risk and protective factors. Baseline depressive symptoms, in contrast, were not associated with 1-year smartphone overuse after adjusting for baseline smartphone overuse. Smartphone overuse was also significantly associated with higher levels of momentary negative affect, even when accounting for depressive symptoms. Strategies to mitigate the impact of smartphone overuse can have important long-term implications.

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

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

Mental health services use and depressive symptom scores among gay and bisexual men in Canada

PURPOSE

To evaluate the association between mental health services (MHS) use and depressive symptom scores among gay and bisexual men (GBM) and compare with heterosexual men in Canada.

METHODS

We used data from the 2015-2016 cycles of the Canadian Community Health Survey. Depressive symptoms were assessed using the PHQ-9 questionnaire (prior two weeks). MHS consultations with any licensed mental health professional (prior year) were categorized as 0, 1, 2-11, ≥ 12. We fit linear regression models to quantify the associations between MHS use and PHQ-9 scores, with an interaction term for sexual identity (GBM and heterosexual men). Models were adjusted for socioeconomic and health-related indicators.

RESULTS

Among 21,383 men, 97.3% self-identified as heterosexual and 2.7% as GBM. Compared to heterosexual men, GBM used any MHS (21% vs. 10%, p < 0.05) and consulted ≥ 2 health professionals for their mental health (6% vs. 2%, p < 0.05) in the preceding year more frequently. Overall, mean PHQ-9 scores were higher among GBM compared to heterosexual men (3.9 vs. 2.3, p < 0.05). Relative to no consultations, higher MHS use (2-11, ≥ 12 consultations) was associated with higher PHQ-9 scores (1.4-4.9 points higher). Associations between MHS use and PHQ-9 scores did not differ statistically between GBM and heterosexual men.

CONCLUSION

Our findings were inconclusive in demonstrating a difference between heterosexual men and GBM for the association between MHS use and PHQ-9 scores. However, GBM consistently had higher average PHQ-9 scores for every category of consultations. Considering the higher use of MHS and higher burden of depressive symptoms among GBM, more research is needed.

Psychiatric diagnosis and treatment in the 21st century: paradigm shifts versus incremental integration

Psychiatry has always been characterized by a range of different models of and approaches to mental disorder, which have sometimes brought progress in clinical practice, but have often also been accompanied by critique from within and without the field. Psychiatric nosology has been a particular focus of debate in recent decades; successive editions of the DSM and ICD have strongly influenced both psychiatric practice and research, but have also led to assertions that psychiatry is in crisis, and to advocacy for entirely new paradigms for diagnosis and assessment. When thinking about etiology, many researchers currently refer to a biopsychosocial model, but this approach has received significant critique, being considered by some observers overly eclectic and vague. Despite the development of a range of evidence-based pharmacotherapies and psychotherapies, current evidence points to both a treatment gap and a research-practice gap in mental health. In this paper, after considering current clinical practice, we discuss some proposed novel perspectives that have recently achieved particular prominence and may significantly impact psychiatric practice and research in the future: clinical neuroscience and personalized pharmacotherapy; novel statistical approaches to psychiatric nosology, assessment and research; deinstitutionalization and community mental health care; the scale-up of evidence-based psychotherapy; digital phenotyping and digital therapies; and global mental health and task-sharing approaches. We consider the extent to which proposed transitions from current practices to novel approaches reflect hype or hope. Our review indicates that each of the novel perspectives contributes important insights that allow hope for the future, but also that each provides only a partial view, and that any promise of a paradigm shift for the field is not well grounded. We conclude that there have been crucial advances in psychiatric diagnosis and treatment in recent decades; that, despite this important progress, there is considerable need for further improvements in assessment and intervention; and that such improvements will likely not be achieved by any specific paradigm shifts in psychiatric practice and research, but rather by incremental progress and iterative integration.

Utilizing daily mood diaries and wearable sensor data to predict depression and suicidal ideation among medical interns

BACKGROUND

Intensive longitudinal methods (ILMs) for collecting self-report (e.g., daily diaries, ecological momentary assessment) and passive data from smartphones and wearable sensors provide promising avenues for improved prediction of depression and suicidal ideation (SI). However, few studies have utilized ILMs to predict outcomes for at-risk, non-clinical populations in real-world settings.

METHODS

Medical interns (N = 2881; 57 % female; 58 % White) were recruited from over 300 US residency programs. Interns completed a pre-internship assessment of depression, were given Fitbit wearable devices, and provided daily mood ratings (scale: 1-10) via mobile application during the study period. Three-step hierarchical logistic regressions were used to predict depression and SI at the end of the first quarter utilizing pre-internship predictors in step 1, Fitbit sleep/step features in step 2, and daily diary mood features in step 3.

RESULTS

Passively collected Fitbit features related to sleep and steps had negligible predictive validity for depression, and no incremental predictive validity for SI. However, mean-level and variability in mood scores derived from daily diaries were significant independent predictors of depression and SI, and significantly improved model accuracy.

LIMITATIONS

Work schedules for interns may result in sleep and activity patterns that differ from typical associations with depression or SI. The SI measure did not capture intent or severity.

CONCLUSIONS

Mobile self-reporting of daily mood improved the prediction of depression and SI during a meaningful at-risk period under naturalistic conditions. Additional research is needed to guide the development of adaptive interventions among vulnerable populations.

A novel peripheral biomarker for depression and antidepressant response

In contrast to healthy controls, the heterotrimeric G protein, Gsalpha (Gsα) is ensconced predominantly in lipid rafts in subjects with major depressive disorder (MDD) resulting in impaired stimulation of adenylyl cyclase. In this small proof-of-concept study, we examined the hypothesis that translocation of Gsα from lipid rafts toward a more facile activation of adenylyl cyclase is a biomarker for clinical response to antidepressants. There were 49 subjects with MDD (HamD₁₇ score ≥15) and 59 healthy controls at the screen visit. The AlphaScreen (PerkinElmer) assay measured both basal activity and prostaglandin E1 (PGE1) stimulation of Gsα-adenylyl cyclase to assess the extent of coupling of Gsα with adenylyl cyclase. At screen, platelet samples obtained from MDD subjects revealed significantly lower PGE1 activation of adenylyl cyclase activity than controls (p = 0.02). Subsequently, 19 consenting MDD subjects completed a 6-week open label antidepressant treatment trial. The 11 antidepressant responders (HamD₁₇ improvement ≥50% from screen) revealed significant increase in PGE1-stimulated adenylyl cyclase compared to non-responders (p = 0.05) with an effect size of 0.83 for the PGE1/Gsα lipid-raft biomarker. PGE1 stimulation increased by ≥30% from screen assessment in eight responders (72.7%) and two non-responders (25.0%) [Fisher exact = 0.07] with a positive predictive value for response of 80.0%. In this small, pilot study, increased PGE1 stimulated adenylyl cyclase was associated with antidepressant response in MDD subjects. These data suggest that a simple, high-throughput-capable assay for depression and antidepressant response can be developed. Future studies are needed to evaluate the utility of this biomarker for the treatment of MDD.

A Data-Driven Clustering Method for Discovering Profiles in the Dynamics of Major Depressive Disorder Using a Smartphone-Based Ecological Momentary Assessment of Mood

BACKGROUND

Although major depressive disorder (MDD) is characterized by a pervasive negative mood, research indicates that the mood of depressed patients is rarely entirely stagnant. It is often dynamic, distinguished by highs and lows, and it is highly responsive to external and internal regulatory processes. Mood dynamics can be defined as a combination of mood variability (the magnitude of the mood changes) and emotional inertia (the speed of mood shifts). The purpose of this study is to explore various distinctive profiles in real-time monitored mood dynamics among MDD patients in routine mental healthcare.

METHODS

Ecological momentary assessment (EMA) data were collected as part of the cross-European E-COMPARED trial, in which approximately half of the patients were randomly assigned to receive the blended Cognitive Behavioral Therapy (bCBT). In this study a subsample of the bCBT group was included (n = 287). As part of bCBT, patients were prompted to rate their current mood (on a 1-10 scale) using a smartphone-based EMA application. During the first week of treatment, the patients were prompted to rate their mood on three separate occasions during the day. Latent profile analyses were subsequently applied to identify distinct profiles based on average mood, mood variability, and emotional inertia across the monitoring period.

RESULTS

Overall, four profiles were identified, which we labeled as: (1) "very negative and least variable mood" (n = 14) (2) "negative and moderate variable mood" (n = 204), (3) "positive and moderate variable mood" (n = 41), and (4) "negative and highest variable mood" (n = 28). The degree of emotional inertia was virtually identical across the profiles.

CONCLUSIONS

The real-time monitoring conducted in the present study provides some preliminary indications of different patterns of both average mood and mood variability among MDD patients in treatment in mental health settings. Such varying patterns were not found for emotional inertia.

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 growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality

As the COVID-19 pandemic has largely increased the utilization of telehealth, mobile mental health technologies - such as smartphone apps, vir-tual reality, chatbots, and social media - have also gained attention. These digital health technologies offer the potential of accessible and scalable interventions that can augment traditional care. In this paper, we provide a comprehensive update on the overall field of digital psychiatry, covering three areas. First, we outline the relevance of recent technological advances to mental health research and care, by detailing how smartphones, social media, artificial intelligence and virtual reality present new opportunities for "digital phenotyping" and remote intervention. Second, we review the current evidence for the use of these new technological approaches across different mental health contexts, covering their emerging efficacy in self-management of psychological well-being and early intervention, along with more nascent research supporting their use in clinical management of long-term psychiatric conditions - including major depression; anxiety, bipolar and psychotic disorders; and eating and substance use disorders - as well as in child and adolescent mental health care. Third, we discuss the most pressing challenges and opportunities towards real-world implementation, using the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework to explain how the innovations themselves, the recipients of these innovations, and the context surrounding innovations all must be considered to facilitate their adoption and use in mental health care systems. We conclude that the new technological capabilities of smartphones, artificial intelligence, social media and virtual reality are already changing mental health care in unforeseen and exciting ways, each accompanied by an early but promising evidence base. We point out that further efforts towards strengthening implementation are needed, and detail the key issues at the patient, provider and policy levels which must now be addressed for digital health technologies to truly improve mental health research and treatment in the future.

Digital Clinics and Mobile Technology Implementation for Mental Health Care

PURPOSE OF REVIEW

Interest in digital mental health, especially smartphone apps, has expanded in light of limited access to mental health services and the need for remote care during COVID-19. Digital clinics, in which apps are blended into routine care, offer a potential solution to common implementation challenges including low user engagement and lack of clinical integration of apps.

RECENT FINDINGS

While the number of mental health apps available in commercial marketplaces continues to rise, there are few examples of successful implementation of these apps into care settings. We review one example of a digital clinic created within an academic medical center and another within the Department of Veterans Affairs. We then discuss how implementation science can inform new efforts to effectively integrate mental health technologies across diverse use cases. Integrating mental health apps into care settings is feasible but requires careful attention to multiple domains that will influence implementation success, including characteristics of the innovation (e.g., utility and complexity of the app), the recipients of the technology (e.g., patients and clinicians), and context (e.g., healthcare system buy-in, reimbursement, and regulatory policies). Examples of effective facilitation strategies that can be utilized to improve implementation efforts include co-production of technology involving all end users, specialized trainings for staff and patients, creation of new team members to aid in app usage (e.g., digital navigators), and re-design of clinical workflows.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

IMPLICATIONS

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