How to use experience-sampling technology to understand daily functioning: A practical guide for mental health professionals.

Satisfying daily life functioning is essential in mental healthcare. Standard assessments focus on symptoms and are designed to detect underlying vulnerabilities. However, they offer insufficient insight into patterns of contextual variability and resilience. Consequently, interventions are planned using incomplete information. The experience-sampling method (ESM) is a structured moment-to-moment diary assessing the individual's affect, thoughts, perception and behaviour in the daily life context. ESM helps to understand variation in mental states (e.g., anxiety or sleeping problems) as adaptational processes in relation to contextual challenges (functional analysis). Although ESM has been extensively studied across psychological disorders, the adoption by mental health professionals and their patients remains limited because the 'how to' is unclear. This paper presents a practical guide for ESM application in routine clinical care. It integrates empirical knowledge with expert experiences and provides real-world examples and recommendations for successful implementation. The guide comprises how to engage and motivate patients and how to customize assessments to the patient's needs. It also includes instructions to interpret results and create an atmosphere of shared decision-making. Experience-sampling technology has merits for patients with various mental health complaints and across healthcare settings, although the exact use and implementation may vary depending on the individual case.

Aggression on the psychiatric ward: Prevalence and risk factors. A systematic review of the literature.

INTRODUCTION: On psychiatric wards, aggressive behaviour displayed by patients is common and problematic. Understanding factors associated with the development of aggression offers possibilities for prevention and targeted interventions. This review discusses factors that contribute to the development of aggression on psychiatric wards. METHOD: In Pubmed and Embase, a search was performed aimed at: prevalence data, ward characteristics, patient and staff factors that are associated with aggressive behaviour and from this search 146 studies were included. RESULTS: The prevalence of aggressive behaviour on psychiatric wards varied (8-76%). Explanatory factors of aggressive behaviour were subdivided into patient, staff and ward factors. Patient risk factors were diagnosis of psychotic disorder or bipolar disorder, substance abuse, a history of aggression, younger age. Staff risk factors included male gender, unqualified or temporary staff, job strain, dissatisfaction with the job or management, burn-out and quality of the interaction between patients and staff. Staff protective factors were a good functioning team, good leadership and being involved in treatment decisions. Significant ward risk factors were a higher bed occupancy, busy places on the ward, walking rounds, an unsafe environment, a restrictive environment, lack of structure in the day, smoking and lack of privacy. CONCLUSION: Despite a lack of prospective quantitative data, results did show that aggression arises from a combination of patient factors, staff factors and ward factors. Patient factors were studied most often, however, besides treatment, offering the least possibilities in prevention of aggression development. Future studies should focus more on the earlier stages of aggression such as agitation and on factors that are better suited for preventing aggression such as ward and staff factors. Management and clinicians could adapt staffing and ward in line with these results.

White matter microstructure and network-connectivity in emerging adults with subclinical psychotic experiences.

Group comparisons of individuals with psychotic disorder and controls have shown alterations in white matter microstructure. Whether white matter microstructure and network connectivity is altered in adolescents with subclinical psychotic experiences (PE) at the lowest end of the psychosis severity spectrum is less clear. DWI scan were acquired in 48 individuals with PE and 43 healthy controls (HC). Traditional tensor-derived indices: Fractional Anisotropy, Axial Diffusivity, Mean Diffusivity and Radial Diffusivity, as well as network connectivity measures (global/local efficiency and clustering coefficient) were compared between the groups. Subclinical psychopathology was assessed with the Community Assessment of Psychic Experiences (CAPE) and Montgomery-Åsberg Depression Rating Scale (MADRS) questionnaires and, in order to capture momentary subclinical expression of psychosis, the Experience Sampling Method (ESM) questionnaires. Within the PE-group, interactions between subclinical (momentary) symptoms and brain regions in the model of tensor-derived indices and network connectivity measures were investigated in a hypothesis-generating fashion. Whole brain analyses showed no group differences in tensor-derived indices and network connectivity measures. In the PE-group, a higher positive symptom distress score was associated with both higher local efficiency and clustering coefficient in the right middle temporal pole. The findings indicate absence of microstructural white matter differences between emerging adults with subclinical PE and controls. In the PE-group, attenuated symptoms were positively associated with network efficiency/cohesion, which requires replication and may indicate network alterations in emerging mild psychopathology.

Measuring within-day cognitive performance using the experience sampling method: A pilot study in a healthy population.

INTRODUCTION: People with depression, anxiety, or psychosis often complain of confusion, problems concentrating or difficulties cognitively appraising contextual cues. The same applies to people with neurodegenerative diseases or brain damage such as dementia or stroke. Assessments of those cognitive difficulties often occurs in cross-sectional and controlled clinical settings. Information on daily moment-to-moment cognitive fluctuations and its relation to affect and context is lacking. The development and evaluation of a digital cognition task is presented. It enables the fine-grained mapping of cognition and its relation to mood, intrapersonal factors and context. METHODS: The momentary Digit Symbol Substitution Task is a modified digital version of the original paper-and-pencil task, with a duration of 30 seconds and implemented in an experience sampling protocol (8 semi-random assessments a day on 6 consecutive days). It was tested in the healthy population (N = 40). Descriptive statistics and multilevel regression analyses were used to determine initial feasibility and assess cognitive patterns in everyday life. Cognition outcome measures were the number of trials within the 30-second sessions and the percentage of correct trials. RESULTS: Subjects reported the task to be easy, pleasant and do-able. On average, participants completed 11 trials with 97% accuracy per 30-second session. Cognitive variation was related to mood, with an interaction between positive and negative affect for accuracy (% correct) (p = .001) and an association between positive affect and speed (number of trials) (p = .01). Specifically, cheerful, irritated and anxious seem to covary with cognition. Distraction and location are relevant contextual factors. The number of trials showed a learning effect (p < .001) and was sensitive to age (p < .001). CONCLUSION: Implementing a digital cognition task within an experience-sampling paradigm shows promise. Fine-tuning in further research and in clinical samples is needed. Gaining insight into cognitive functioning could help patients navigate and adjust the demands of daily life.

Reward anticipation in individuals with subclinical psychotic experiences: A functional MRI approach.

Previous research in patients with psychotic disorder has shown widespread abnormalities in brain activation during reward anticipation. Research at the level of subclinical psychotic experiences in individuals unexposed to antipsychotic medication is limited with inconclusive results. Therefore, brain activation during reward anticipation was examined in a larger sample of individuals with subclinical psychotic experiences (PE). Participants in the PE-group were included based on CAPE scores. A sample of emerging adults aged 16-26 years (n = 47) with PE and healthy controls (HC) (n = 40) underwent fMRI scanning. The Monetary Incentive Delay task was conducted with cues related to win, loss or neutral conditions. fMRI nonparametric tests were used to examine the reward versus neutral cue contrast. A significant main effect of the large win (€3.00) > neutral contrast was found in both groups showing activation in many brain areas, including classic reward regions. Whole brain analysis on the group comparison regarding the large win > neutral contrast showed significantly decreased activation in the right insula, putamen and supramarginal gyrus in the PE-group compared to controls. There was no group difference in the hypothesized reward-related region. Decreased activation in the right insula, putamen and supramarginal gyrus during reward anticipation in individuals with PE may be consistent with altered processing of sensory information, related to decreased emotional valuing and motivational tendencies and/or altered motor-cognitive processes. The absence of group differences in striatal activation suggests that activation here is intact in the earliest stages of psychosis and may exhibit progressive deterioration in as the disease develops.

Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches.

The ubiquity of smartphones opened up the possibility of widespread use of the Experience Sampling Method (ESM). The method is used to collect longitudinal data of participants' daily life experiences and is ideal to capture fluctuations in emotions (momentary mental states) as an indicator for later mental ill-health. In this study, ESM data of patients with psychosis spectrum disorder and controls were used to examine daily life emotions and higher order patterns thereof. We attempted to determine whether aggregated ESM data, in which statistical measures represent the distribution and dynamics of the original data, were able to distinguish patients from controls in a predictive modeling framework. Variable importance, recursive feature elimination, and ReliefF methods were used for feature selection. Model training, tuning, and testing were performed in nested cross-validation, based on algorithms such as Random Forests, Support Vector Machines, Gaussian Processes, Logistic Regression, and Neural Networks. ROC analysis was used to post-process these models. Stability of model performance was studied using Monte Carlo simulations. The results provide evidence that patterns in emotion changes can be captured by applying a combination of these techniques. Acceleration in the variables anxious and insecure was particularly successful in adding further predictive power to the models. The best results were achieved by Support Vector Machines with radial kernel (accuracy = 82% and sensitivity = 82%). This proof-of-concept work demonstrates that synergistic machine learning and statistical modeling may be used to harness the power of ESM data in the future.

The Development and Psychometric Evaluation of the Group Schema Therapy Rating Scale - Revised.

BACKGROUND: Recent research has supported the efficacy of schema therapy as a treatment for personality disorders. A group format has been developed (group schema therapy; GST), which has been suggested to improve both the clinical and cost-effectiveness of the treatment. AIMS: Efficacy studies of GST need to assess treatment fidelity. The aims of the present study were to improve, describe and evaluate a fidelity measure for GST, the Group Schema Therapy Rating Scale - Revised (GSTRS-R). METHOD: Following a pilot study on an initial version of the scale (GSTRS), items were revised and guidelines were modified in order to improve the reliability of the scale. Students highly experienced with the scale rated recorded GST therapy sessions using the GSTRS-R in addition to a group cohesion measure, the Harvard Community Health Plan Group Cohesiveness Scale - II (GCS-II). The scores were used to assess internal consistency and inter-rater reliability. Discriminant validity was assessed by comparing the scores on the GSTRS-R with the GCS-II. RESULTS: The GSTRS-R displayed substantial internal consistency and inter-rater reliability, and adequate discriminate validity, evidenced by a weak positive correlation with the GCS-II. CONCLUSIONS: Overall, the GSTRS-R is a reliable tool that may be useful for evaluating therapist fidelity to GST model, and assisting GST training and supervision. Initial validity was supported by a weak association with GCS-II, indicating that although associated with cohesiveness, the instrument also assesses factors specific to GST. Limitations are discussed.

Constructing a Reward-Related Quality of Life Statistic in Daily Life-a Proof of Concept Study Using Positive Affect.

Background: Mental healthcare needs person-tailored interventions. Experience Sampling Method (ESM) can provide daily life monitoring of personal experiences. This study aims to operationalize and test a measure of momentary reward-related Quality of Life (rQoL). Intuitively, quality of life improves by spending more time on rewarding experiences. ESM clinical interventions can use this information to coach patients to find a realistic, optimal balance of positive experiences (maximize reward) in daily life. rQoL combines the frequency of engaging in a relevant context (a 'behavior setting') with concurrent (positive) affect. High rQoL occurs when the most frequent behavior settings are combined with positive affect or infrequent behavior settings co-occur with low positive affect. Methods: Resampling procedures (Monte Carlo experiments) were applied to assess the reliability of rQoL using various behavior setting definitions under different sampling circumstances, for real or virtual subjects with low-, average- and high contextual variability. Furthermore, resampling was used to assess whether rQoL is a distinct concept from positive affect. Virtual ESM beep datasets were extracted from 1,058 valid ESM observations for virtual and real subjects. Results: Behavior settings defined by Who-What contextual information were most informative. Simulations of at least 100 ESM observations are needed for reliable assessment. Virtual ESM beep datasets of a real subject can be defined by Who-What-Where behavior setting combinations. Large sample sizes are necessary for reliable rQoL assessments, except for subjects with low contextual variability. rQoL is distinct from positive affect. Conclusion: rQoL is a feasible concept. Monte Carlo experiments should be used to assess the reliable implementation of an ESM statistic. Future research in ESM should asses the behavior of summary statistics under different sampling situations. This exploration is especially relevant in clinical implementation, where often only small datasets are available.

Behavioral pattern separation and its link to the neural mechanisms of fear generalization.

Fear generalization is a prominent feature of anxiety disorders and post-traumatic stress disorder (PTSD). It is defined as enhanced fear responding to a stimulus that bears similarities, but is not identical to a threatening stimulus. Pattern separation, a hippocampal-dependent process, is critical for stimulus discrimination; it transforms similar experiences or events into non-overlapping representations. This study is the first in humans to investigate the extent to which fear generalization relies on behavioral pattern separation abilities. Participants (N = 46) completed a behavioral task taxing pattern separation, and a neuroimaging fear conditioning and generalization paradigm. Results show an association between lower behavioral pattern separation performance and increased generalization in shock expectancy scores, but not in fear ratings. Furthermore, lower behavioral pattern separation was associated with diminished recruitment of the subcallosal cortex during presentation of generalization stimuli. This region showed functional connectivity with the orbitofrontal cortex and ventromedial prefrontal cortex. Together, the data provide novel experimental evidence that pattern separation is related to generalization of threat expectancies, and reduced fear inhibition processes in frontal regions. Deficient pattern separation may be critical in overgeneralization and therefore may contribute to the pathophysiology of anxiety disorders and PTSD.

Demonstrating the reliability of transdiagnostic mHealth Routine Outcome Monitoring in mental health services using experience sampling technology.

BACKGROUND: Routine Outcome Monitoring (ROM) should provide a dynamic, within-treatment forward feedback loop to guide individual treatment decisions across diagnostic categories. It has been suggested that the Experience Sampling Method (ESM), capturing the film of daily life adaptive processes, offers a flexible, personalised and transdiagnostic feedback system for monitoring and adapting treatment strategies. This is the first study that uses an ESM application (the PsyMate™) as a routine mobile-ROM (mROM) tool in an ambulatory mental health setting. OBJECTIVE: To demonstrate adequate psychometric properties of the PsyMate™ app assessing both symptom severity levels as well as daily life functioning. METHOD: In a transdiagnostic sample of 64 outpatients, an mROM protocol (ESM for 6 days, at 10 semi-random moments a day) and a standard ROM instrument (HADS) were administered at baseline and at three-month follow-up. We measured positive affect (PA), negative affect (NA), quality of sleep, positive social interaction, activity-related stress, tiredness, and feeling unwell. RESULTS: Subjects completed 53% of the measurements at baseline (N = 64) and 48% at follow-up (N = 29). Factor analysis and subsequent reliability analysis of PA and NA confirmed the two constructs. Significant and meaningful correlations were found between PA, NA and HADS scores (ranging from r = .4 to r = .7). Multilevel analyses yielded significant change scores for all measures. CONCLUSION: The ESM-based, transdiagnostic mROM tool can be used reliably in clinical settings: it shows adequate psychometric properties, as well as concurrent validity and sensitivity to change over time with respect to relevant ROM constructs. Person-tailored items can be added. In addition, mROM offers added value over standard symptom-based ROM, as it provides information on adaptive functioning in the daily environment of patients.

The experience sampling method as an mHealth tool to support self-monitoring, self-insight, and personalized health care in clinical practice.

BACKGROUND: The experience sampling method (ESM) builds an intensive time series of experiences and contexts in the flow of daily life, typically consisting of around 70 reports, collected at 8-10 random time points per day over a period of up to 10 days. METHODS: With the advent of widespread smartphone use, ESM can be used in routine clinical practice. Multiple examples of ESM data collections across different patient groups and settings are shown and discussed, varying from an ESM evaluation of a 6-week randomized trial of mindfulness, to a twin study on emotion dynamics in daily life. RESULTS: Research shows that ESM-based self-monitoring and feedback can enhance resilience by strengthening the capacity to use natural rewards. Personalized trajectories of starting or stopping medication can be more easily initiated and predicted if sensitive feedback data are available in real time. In addition, personalized trajectories of symptoms, cognitive abilities, symptoms impacting on other symptoms, the capacity of the dynamic system of mental health to "bounce back" from disturbance, and patterns of environmental reactivity yield uniquely personal data to support shared decision making and prediction in clinical practice. Finally, ESM makes it possible to develop insight into previous implicit patterns of thought, experience, and behavior, particularly if rapid personalized feedback is available. CONCLUSIONS: ESM enhances clinical practice and research. It is empowering, providing co-ownership of the process of diagnosis, treatment evaluation, and routine outcome measurement. Blended care, based on a mix of face-to-face and ESM-based outside-the-office treatment, may reduce costs and improve outcomes.

Use of the experience sampling method in the context of clinical trials.

OBJECTIVE: The experience sampling method (ESM) is a structured diary technique to appraise subjective experiences in daily life. It is applied in psychiatric patients, as well as in patients with somatic illness. Despite the potential of ESM assessment, the improved logistics and its increased administration in research, its use in clinical trials remains limited. This paper introduces ESM for clinical trials in psychiatry and beyond. METHODS: ESM is an ecologically valid method that yields a comprehensive view of an individual's daily life. It allows the assessment of various constructs (eg, quality of life, psychopathology) and psychological mechanisms (eg, stress-sensitivity, coping). These constructs are difficult to assess using cross-sectional questionnaires. ESM can be applied in treatment monitoring, as an ecological momentary intervention, in clinical trials, or in single case clinical trials. Technological advances (eg, smartphone applications) make its implementation easier. RESULTS: Advantages of ESM are highlighted and disadvantages are discussed. Furthermore, the ecological nature of ESM data and its consequences are explored, including the potential pitfalls of ambiguously formulated research questions and the specificities of ESM in statistical analyses. The last section focuses on ESM in relation to clinical trials and discusses its future use in optimising clinical decision-making. CONCLUSIONS: ESM can be a valuable asset in clinical trial research and should be used more often to study the benefits of treatment in psychiatry and somatic health.