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Experience sampling methodology and daily diary (ESM/DD) research elicits repeated reports of immediate or very recent experiences from the same sample of people for several days or weeks. Experience sampling and diary methods were almost unheard of in organizational research 15 years ago, but the past decade has seen a rapid rise in their use. These methods are helpful in studying dynamic within-person processes involving affect, behavior, interpersonal interactions, work events, and other transient workplace phenomena over time. Assessing cross-level effects of traits or other stable features on within-person processes and reactivity is also possible with ESM/DD data. We provide an introduction to issues in designing and carrying out an ESM/DD study, including data collection choices and schedules, measures, technology, training and motivation of participants, and analysis of multilevel data. We offer best practice recommendations and refer readers to further resources for additional detail on conducting and analyzing ESM/DD research.

Abstract Background Ecological momentary assessment (EMA) involves completing multiple surveys over time in daily life, capturing in-the-moment experiences in real-world contexts. EMA use in psychosis studies has surged over several decades. To critically examine EMA use in psychosis research and assist future researchers in designing new EMA studies, this systematic review aimed to summarize the methodological approaches used for positive symptoms in psychosis populations and evaluate feasibility with a focus on completion rates. Methods A systematic review of PubMed, PsycINFO, MEDLINE, Web of Science, EBSCOhost, and Embase databases using search terms related to EMA and psychosis was conducted. Excluding duplicate samples, a meta-analysis was conducted of EMA survey completion rates and meta-regression to examine predictors of completion. Results Sixty-eight studies were included in the review. Characteristics and reporting of EMA methodologies were variable across studies. The meta-mean EMA survey completion computed from the 39 unique studies that reported a mean completion rate was 67.15% (95% CI = 62.3, 71.9), with an average of 86.25% of the sample meeting a one-third EMA completion criterion. No significant predictors of completion were found in the meta-regression. A variety of EMA items were used to measure psychotic experiences, of which few were validated. Conclusions EMA methods have been widely applied in psychosis studies using a range of protocols. Completion rates are high, providing clear evidence of feasibility in psychosis populations. Recommendations for reporting in future studies are provided.

The examination of moment-to-moment, ‘micro-level’ patterns of experience and behaviour using experience sampling methodology has contributed to our understanding of the ‘macro-level’ development of full-blown symptoms and disorders. This paper argues that the micro-level perspective can be used to identify the smallest building blocks underlying the onset and course of mental ill-health. Psychopathology may be the result of the continuous dynamic interplay between micro-level moment-to-moment experiences and behavioural patterns over time. Reinforcing loops between momentary states may alter the course of mental health towards either a more or less healthy state. An example with observed data, from a population of individuals with depressive symptoms, supports the validity of a dynamic network model of psychopathology and shows that together and over time, this continuous interplay between momentary states may result in the cluster of symptoms we call major depressive disorder. This approach may help conceptualize the nature of mental disorders, and generate individualized insights useful for diagnosis and treatment in psychiatry.

This position paper by the international IMMERSE consortium reviews the evidence of a digital mental health solution based on Experience Sampling Methodology (ESM) for advancing person-centered mental health care and outlines a research agenda for implementing innovative digital mental health tools into routine clinical practice. ESM is a structured diary technique recording real-time self-report data about the current mental state using a mobile application. We will review how ESM may contribute to (1) service user engagement and empowerment, (2) self-management and recovery, (3) goal direction in clinical assessment and management of care, and (4) shared decision-making. However, despite the evidence demonstrating the value of ESM-based approaches in enhancing person-centered mental health care, it is hardly integrated into clinical practice. Therefore, we propose a global research agenda for implementing ESM in routine mental health care addressing six key challenges: (1) the motivation and ability of service users to adhere to the ESM monitoring, reporting and feedback, (2) the motivation and competence of clinicians in routine healthcare delivery settings to integrate ESM in the workflow, (3) the technical requirements and (4) governance requirements for integrating these data in the clinical workflow, (5) the financial and competence related resources related to IT-infrastructure and clinician time, and (6) implementation studies that build the evidence-base. While focused on ESM, the research agenda holds broader implications for implementing digital innovations in mental health. This paper calls for a shift in focus from developing new digital interventions to overcoming implementation barriers, essential for achieving a true transformation toward person-centered care in mental health.

PurposeIntensive longitudinal studies, in which participants complete questionnaires multiple times a day over an extended period, are increasingly popular in the social sciences in general and quality-of-life research in particular. The intensive longitudinal methods allow for studying the dynamics of constructs (e.g., how much patient-reported outcomes vary across time). These methods promise higher ecological validity and lower recall bias than traditional methods that question participants only once, since the high frequency means that participants complete questionnaires in their everyday lives and do not have to retrospectively report about a large time interval. However, to ensure the validity of the results obtained from analyzing the intensive longitudinal data (ILD), greater awareness and understanding of appropriate measurement practices are needed.MethodWe surveyed 42 researchers experienced with ILD regarding their measurement practices and reasons for suboptimal practices.ResultsResults showed that researchers typically do not use measures validated specifically for ILD. Participants assessing the psychometric properties and invariance of measures in their current studies was even less common, as was accounting for these properties when analyzing dynamics. This was mainly because participants did not have the necessary knowledge to conduct these assessments or were unaware of their importance for drawing valid inferences. Open science practices, in contrast, appear reasonably well ingrained in ILD studies.ConclusionMeasurement practices in ILD still need improvement in some key areas; we provide recommendations in order to create a solid foundation for measuring and analyzing psychological constructs.

Pre-diagnostic stages of psychotic illnesses, including 'clinical high risk' (CHR), are marked by sleep disturbances. These sleep disturbances appear to represent a key aspect in the etiology and maintenance of psychotic disorders. We aimed to examine the relationship between self-reported sleep dysfunction and attenuated psychotic symptoms (APS) on a day-to-day basis. Seventy-six CHR young people completed the Experience Sampling Methodology (ESM) component of the European Union Gene-Environment Interaction Study, collected through PsyMate® devices, prompting sleep and symptom questionnaires 10 times daily for 6 days. Bayesian multilevel mixed linear regression analyses were performed on time-variant ESM data using the package in R. We investigated the day-to-day associations between sleep and psychotic experiences bidirectionally on an item level. Sleep items included sleep onset latency, fragmentation, and quality. Psychosis items assessed a range of perceptual, cognitive, and bizarre thought content common in the CHR population. Two of the seven psychosis variables were unidirectionally predicted by previous night's number of awakenings: every unit increase in number of nightly awakenings predicted a 0.27 and 0.28 unit increase in feeling unreal or paranoid the next day, respectively. No other sleep variables credibly predicted next-day psychotic symptoms or vice-versa. In this study, the relationship between sleep disturbance and APS appears specific to the item in question. However, some APS, including perceptual disturbances, had low levels of endorsement amongst this sample. Nonetheless, these results provide evidence for a unidirectional relationship between sleep and some APS in this population.

Psychotic experiences (PEs) and social isolation (SI) seem related during early stages of psychosis, but the temporal dynamics between the two are not clear. Literature so far suggests a self-perpetuating cycle wherein momentary increases in PEs lead to social withdrawal, which, subsequently, triggers PEs at a next point in time, especially when SI is associated with increased distress. The current study investigated the daily-life temporal associations between SI and PEs, as well as the role of SI-related and general affective distress in individuals at clinical high risk (CHR) for psychosis. We used experience sampling methodology in a sample of 137 CHR participants. We analyzed the association between SI, PEs, and distress using time-lagged linear mixed-effects models. SI did not predict next-moment fluctuations in PEs, or . Furthermore, although SI-related distress was not predictive of subsequent PEs, general affective distress during SI was a robust predictor of next-moment PEs. Our results suggest that SI and PEs are not directly related on a moment-to-moment level, but a negative emotional state when alone does contribute to the risk of PEs. These findings highlight the role of affective wellbeing during early-stage psychosis development.

Theoretical and anecdotal work suggests that Prolonged Grief Disorder (PGD) reactions go up and down during the day. However, empirical evidence supporting this claim is lacking. It is also unknown in which context PGD reactions go up and down. Using Experience Sampling Methodology (ESM), we examined whether PGD reactions (ESM-PGD) relate to contextual factors in daily life. For 14 days, five times per day, bereaved adults ( N  = 53; 74% women) rated the intensity of 11 ESM-PGD reactions representing DSM-5-TR PGD symptoms. Using mixed-effect regression analyses, we examined whether contextual factors (i.e., physical and social environments, and time of day) were associated with each ESM-PGD reaction separately. Being away from home compared to being at home was associated with more avoidance. Being alone compared to being in a pleasant social contact was associated with more preoccupation with the loss, intensified feelings that part of oneself died, and increased perception of the loss as unreal. Lastly, a later time of day was related to stronger feelings of loneliness and difficulties moving on. Our findings suggest that ESM-PGD reactions may be context-dependent. This calls for a context-sensitive treatment approach, such as ecological momentary interventions.

Network analysis of ESM data has become popular in clinical psychology. In this approach, discrete-time (DT) vector auto-regressive (VAR) models define the network structure with centrality measures used to identify intervention targets. However, VAR models suffer from time-interval dependency. Continuous-time (CT) models have been suggested as an alternative but require a conceptual shift, implying that DT-VAR parameters reflect total rather than direct effects. In this paper, we propose and illustrate a CT network approach using CT-VAR models. We define a new network representation and develop centrality measures which inform intervention targeting. This methodology is illustrated with an ESM dataset.

Increasing research effort is being dedicated to investigating the links between emotional processes and psychosis, despite the traditional demarcation between the two. Particular focus has alighted upon two specific anxious and depressive processes, worry and rumination, given the potential for links with aspects of delusions and auditory hallucinations. This study rigorously explored the nature of these links in the context of the daily life of people currently experiencing psychosis. Experience sampling methodology (ESM) was used to assess the momentary links between worry and rumination on the one hand, and persecutory delusional ideation and auditory hallucinations on the other. Twenty-seven participants completed the 6-day experience sampling period, which required repeated self-reports on thought processes and experiences. Multilevel modelling was used to examine the links within the clustered data. We found that antecedent worry and rumination predicted delusional and hallucinatory experience, and the distress they elicited. Using interaction terms, we have shown that the links with momentary symptom severity were moderated by participants' trait beliefs about worry/rumination, such that they were reduced when negative beliefs about worry/rumination (meta-cognitions) were high. The current findings offer an ecologically valid insight into the influence of worry and rumination on the experience of psychotic symptoms, and highlight possible avenues for future intervention strategies.