Insights of Patients and Clinicians on the Promise of the Experience Sampling Method for Psychiatric Care

OBJECTIVE: This qualitative study aimed to map the relevance of the experience sampling method (ESM) for psychiatric practice and identify barriers and facilitators for implementation, as perceived by patients and clinicians. METHODS: Participants were 22 patients with various diagnoses and 21 clinicians (e.g., psychiatrists, psychologists) who participated in interviews or focus groups. Using Atlas.TI, the authors conducted qualitative thematic analysis to analyze the transcripts, resulting in four themes: applications, advantages, undesirable effects, and requirements for implementation of ESM in care. RESULTS: Clinicians and patients believed ESM could be relevant in every phase of care to increase patients' awareness, insight, and self-management; personalize interventions; and alert patients to rising symptoms. Further, ESM was expected to improve the patient-clinician relationship; lead to objective, personalized, reliable and visual data; and increase efficiency of care. However, participants warned against high assessment burden and potential symptom worsening. CONCLUSIONS: This study provides first evidence that the potential of ESM is recognized by both patients and clinicians. Key recommendations for optimal implementation of ESM in psychiatric care include flexible application of ESM, collaboration between patient and clinician, regular evaluation, awareness of negative reactivity, availability to patients with different psychiatric syndromes, and implementation by an interdisciplinary team of patients, clinicians, researchers, and information technology specialists

Leefplezier: Personalized well-being

Each person is different and should be treated assuch. Comparing personal data to group averages can give basicideas about personal conditions, but does not suffice for providing‘true’ personalized feedback. In health psychology, a paradigmshift is taking place from a general population approach towardsa more person-centered one. Instead of comparing a person withpopulation averages, the focus shifts towards comparing peoplewith themselves over time. The ‘Leefplezier’ project elaborateson this focus shift, by helping to sustain or improve the wellbeingof elderly people. The participating elderly people are askedto keep track of various psychological factors for a period oftime, by means of repetitive questionnaires via a mobile phoneapplication. At the end of this period, feedback is automaticallygenerated, based on the resulting time series dataset and by meansof automated vector autoregression

Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals

Background In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. The present study investigated whether EWS can anticipate manic and depressive transitions in individual patients with bipolar disorder. Methods Twenty bipolar type I/II patients (with >= 2 episodes in the previous year) participated in ecological momentary assessment (EMA), completing five questionnaires a day for four months (Mean = 491 observations per person). Transitions were determined by weekly completed questionnaires on depressive (Quick Inventory for Depressive Symptomatology Self-Report) and manic (Altman Self-Rating Mania Scale) symptoms. EWS (rises in autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective and symptomatic EMA states. Positive and negative predictive values were calculated to determine clinical utility. Results Eleven patients reported 1-2 transitions. The presence of EWS increased the probability of impending depressive and manic transitions from 32-36% to 46-48% (autocorrelation) and 29-41% (standard deviation). However, the absence of EWS could not be taken as a sign that no transition would occur in the near future. The momentary states that indicated nearby transitions most accurately (predictive values: 65-100%) were full of ideas, worry, and agitation. Large individual differences in the utility of EWS were found. Conclusions EWS show theoretical promise in anticipating manic and depressive transitions in bipolar disorder, but the level of false positives and negatives, as well as the heterogeneity within and between individuals and preprocessing methods currently limit clinical utility

Ecological Momentary Assessments and Automated Time Series Analysis to Promote Tailored Health Care:A Proof-of-Principle Study

BACKGROUND: Health promotion can be tailored by combining ecological momentary assessments (EMA) with time series analysis. This combined method allows for studying the temporal order of dynamic relationships among variables, which may provide concrete indications for intervention. However, application of this method in health care practice is hampered because analyses are conducted manually and advanced statistical expertise is required. OBJECTIVE: This study aims to show how this limitation can be overcome by introducing automated vector autoregressive modeling (VAR) of EMA data and to evaluate its feasibility through comparisons with results of previously published manual analyses. METHODS: We developed a Web-based open source application, called AutoVAR, which automates time series analyses of EMA data and provides output that is intended to be interpretable by nonexperts. The statistical technique we used was VAR. AutoVAR tests and evaluates all possible VAR models within a given combinatorial search space and summarizes their results, thereby replacing the researcher's tasks of conducting the analysis, making an informed selection of models, and choosing the best model. We compared the output of AutoVAR to the output of a previously published manual analysis (n=4). RESULTS: An illustrative example consisting of 4 analyses was provided. Compared to the manual output, the AutoVAR output presents similar model characteristics and statistical results in terms of the Akaike information criterion, the Bayesian information criterion, and the test statistic of the Granger causality test. CONCLUSIONS: Results suggest that automated analysis and interpretation of times series is feasible. Compared to a manual procedure, the automated procedure is more robust and can save days of time. These findings may pave the way for using time series analysis for health promotion on a larger scale. AutoVAR was evaluated using the results of a previously conducted manual analysis. Analysis of additional datasets is needed in order to validate and refine the application for general use

Impact of receiving recorded mental health recovery narratives on quality of life in people experiencing psychosis, people experiencing other mental health problems and for informal carers: Narrative Experiences Online (NEON) study protocol for three randomised controlled trials.

BACKGROUND: Mental health recovery narratives have been defined as first-person lived experience accounts of recovery from mental health problems which refer to events or actions over a period of time and which include elements of adversity or struggle, and also self-defined strengths, successes or survival. They are readily available in invariant recorded form, including text, audio or video. Previous studies have provided evidence that receiving recorded recovery narratives can provide benefits to recipients. This protocol describes three pragmatic trials that will be conducted by the Narrative Experiences Online (NEON) study using the NEON Intervention, a web application that delivers recorded recovery narratives to its users. The aim of the NEON Trial is to understand whether receiving online recorded recovery narratives through the NEON Intervention benefits people with experience of psychosis. The aim of the NEON-O and NEON-C trials is to evaluate the feasibility of conducting a definitive trial on the use of the NEON Intervention with people experiencing non-psychosis mental health problems and those who care for others experiencing mental health problems respectively. METHODS: The NEON Trial will recruit 683 participants with experience of psychosis. The NEON-O Trial will recruit at least 100 participants with experience of non-psychosis mental health problems. The NEON-C Trial will recruit at least 100 participants with experience of caring for others who have experienced mental health problems. In all three trials, participants will be randomly allocated into one of two arms. Intervention arm participants will receive treatment as usual plus immediate access to the NEON Intervention for 1 year. Control arm participants will receive treatment as usual plus access to the NEON Intervention after 1 year. All participants will complete demographics and outcome measures at baseline, 1 week, 12 weeks and 52 weeks. For the NEON Trial, the primary outcome measure is the Manchester Short Assessment of Quality of Life at 52 weeks, and secondary outcome measures are the CORE-10, Herth Hope Index, Mental Health Confidence Scale and Meaning in Life Questionnaire. A cost-effectiveness analysis will be conducted using data collected through the EQ-5D-5 L and the Client Service Receipt Inventory. DISCUSSION: NEON Trial analyses will establish both effectiveness and cost-effectiveness of the NEON Intervention for people with experience of psychosis, and hence inform future clinical recommendations for this population. TRIAL REGISTRATION: All trials were prospectively registered with ISRCTN. NEON Trial: ISRCTN11152837 . Registered on 13 August 2018. NEON-C Trial: ISRCTN76355273 . Registered on 9 January 2020. NEON-O Trial: ISRCTN63197153 . Registered on 9 January 2020

The mechanisms and processes of connection: developing a causal chain model capturing impacts of receiving recorded mental health recovery narratives.

BACKGROUND: Mental health recovery narratives are a core component of recovery-oriented interventions such as peer support and anti-stigma campaigns. A substantial number of recorded recovery narratives are now publicly available online in different modalities and in published books. Whilst the benefits of telling one's story have been investigated, much less is known about how recorded narratives of differing modalities impact on recipients. A previous qualitative study identified connection to the narrator and/or to events in the narrative to be a core mechanism of change. The factors that influence how individuals connect with a recorded narrative are unknown. The aim of the current study was to characterise the immediate effects of receiving recovery narratives presented in a range of modalities (text, video and audio), by establishing the mechanisms of connection and the processes by which connection leads to outcomes. METHOD: A study involving 40 mental health service users in England was conducted. Participants were presented with up to 10 randomly-selected recovery narratives and were interviewed on the immediate impact of each narrative. Thematic analysis was used to identify the mechanisms of connection and how connection leads to outcome. RESULTS: Receiving a recovery narrative led participants to reflect upon their own experiences or those of others, which then led to connection through three mechanisms: comparing oneself with the narrative and narrator; learning about other's experiences; and experiencing empathy. These mechanisms led to outcomes through three processes: the identification of change (through attending to narrative structure); the interpretation of change (through attending to narrative content); and the internalisation of interpretations. CONCLUSIONS: This is the first study to identify mechanisms and processes of connection with recorded recovery narratives. The empirically-based causal chain model developed in this study describes the immediate effects on recipients. This model can inform selection of narratives for use in interventions, and be used to support peer support workers in recounting their own recovery narratives in ways which are maximally beneficial to others