Integrating theory-based and data-driven methods to case conceptualization: A functional analysis approach with ecological momentary assessment

What time-varying network models based on functional analysis tell us about the course of a patient's problem

Background: Relations among psychological variables are assumed to be complex and to vary over time. Personalized networks can model multivariate complex interactions. The development of time-varying networks allows to model the variation of parameters over time. Objectives: We aimed to determine the value of time-varying networks for clinical practice. Methods: We applied time-varying mixed graphical models (TV-MGM) and time-varying vector autoregressive models (TV-VAR) to intensive longitudinal data of nine participants with depressive symptoms (n = 6) or anxiety (n = 3). Results: Most of the participants showed temporal changes in network topology within the assessment period of 30 days. Time-varying networks of participants with small, medium, and large time variability in edge parameters clearly show the different temporal evolvements of dynamic interactions between variables. The case example indicates clinical utility but also limitations to the application of time-varying networks in clinical practice. Conclusion: Time-varying network models provide a data-driven and exploratory approach that could complement current diagnostic standards by reflecting interacting, often mutually reinforcing processes of mental health problems and by accounting for variation over time. They can be used to generate hypotheses for further confirmatory and clinical testing.

Methodological Characteristics and Feasibility of Ecological Momentary Assessment Studies in Psychosis: a Systematic Review and Meta-Analysis

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.

To Use or Not to Use: Exploring Therapists' Experiences with Pre-Treatment EMA-Based Personalized Feedback in the TheraNet Project

BACKGROUND

Using idiographic network models in psychotherapy has been a growing area of interest. However, little is known about the perceived clinical utility of network models. The present study aims to explore therapists' experiences with network model-based feedback within the context of the TheraNet Project.

METHODS

In total, 18 therapists who had received network-based feedback for at least 1 patient at least 2 months prior were invited to retrospective focus groups. The focus group questions related to how participation in the study influenced the therapeutic relationship, how the networks were used, and what might improve their clinical utility. The transcribed focus groups were analyzed descriptively using qualitative content analysis.

RESULTS

Most therapists mentioned using the feedback to support their existingtheir case concept, while fewer therapists discussed the feedback directly with the patients. Several barriers to using the feedback were discussed, as well as various suggestions for how to make it more clinically useful. Many therapists reported skepticism with regards to research in the outpatient training center in general, though they were also all pleasantly surprised by being involved, having their opinions heard, and showing a readiness to adapt research to their needs/abilities.

CONCLUSIONS

This study highlights the gap between researchers' and therapists' perceptions about what useful feedback should look like. The TheraNet therapists' interest in adapting the feedback and building more informative feedback systems signals a general openness to the implementation of clinically relevant research. We provide suggestions for future implementations of network-based feedback systems in the outpatient clinical training center setting.

Translating the Transdiagnostic: Aligning Assessment Practices With Research Advances

Researchers and clinicians working within the Diagnostic and Statistical Manual of Mental Disorders: Fifth Edition, Text Rev (DSM-5-TR) framework face a difficult question: what does it mean to have an evidence-based assessment of a nonevidence-based diagnostic construct? Alternative nosological approaches conceptualize psychopathology as (a) hierarchical, allowing researchers to move between levels of description and (b) dimensional, eliminating artificial dichotomies between disorders and the dichotomy between mental illness and mental well-being. In this article, we provide an overview of ongoing efforts to develop validated measures of transdiagnostic nosologies (i.e., the Hierarchical Taxonomy of Psychopathology; HiTOP) with applications for measurement-based care. However, descriptive models like HiTOP, which summarize patterns of covariation among psychopathology symptoms, do not address dynamic processes underlying the problems associated with psychopathology. Ambulatory assessment, well-suited to examine such dynamic processes, has also developed rapidly in recent decades. Thus, the goal of the current article is twofold. First, we provide a brief overview of developments in constructing valid measures of the HiTOP model as well as developments in ambulatory assessment practices. Second, we outline how these parallel developments can be integrated to advance measurement-based treatment. We end with a discussion of some major challenges for future research to address to integrate advances more fully in transdiagnostic and ambulatory assessment practices.

The added value of daily diary data in 1- and 3-year prediction of psychopathology and psychotic experiences in individuals at risk for psychosis

This study aimed to assess whether adding information on psychological experiences derived from a daily diary to baseline cross-sectional data could improve short- (1-year) and long-term (3-years) prediction of psychopathology and positive psychotic experiences (PEs). We used 90-day daily diary data from 96 individuals in early subclinical risk stages for psychosis. Stepwise linear regression models were built for psychopathology and PEs at 1- and 3-years follow-up, adding: (1) baseline questionnaires, (2) the mean and variance of daily psychological experiences, and (3) individual symptom network density. We assessed whether similar results could be achieved with a subset of the data (7-14- and 30-days). The mean and variance of the diary improved model prediction of short- and long-term psychopathology and PEs, compared to prediction based on baseline questionnaires solely. Similar results were achieved with 7-14- and 30-day subsets. Symptom network density did not improve model prediction except for short-term prediction of PEs. Simple metrics, i.e., the mean and variance from 7 to 14 days of daily psychological experiences assessments, can improve short- and long-term prediction of both psychopathology and PEs in individuals in early subclinical stages for psychosis. Diary data could be a valuable addition to clinical risk prediction models for psychopathology development.

Personalized pain management: Is it time for process-based therapy for particular people with chronic pain?

BACKGROUND AND OBJECTIVE

Psychological treatments for chronic pain have helped many people around the world. They are among the most researched and best evidenced treatments a person can receive when they have persistent, disabling and distressing pain. At the same time, improvements in the effectiveness of these treatments appear to be at a standstill. This may be due to an inherent lack of generalizability from aggregated group data to the individual, limited utility of our current schemes for categorizing people with pain conditions, faced with their inherent heterogeneity, our relatively coarse categories of treatment types and focus on treatment packages rather than individual methods, and our current failures to find adequate predictors of outcome, or to assign people their best-suited treatment methods, based on group data. In this review, it is argued that the development and examination of truly personalized treatment is a next logical step to create progress and improve the results people achieve.

METHODS

Key research studies pertaining to psychological treatments, treatment outcome, heterogeneity in chronic pain, prediction of treatment outcome, subtyping and treatment tailoring are reviewed.

RESULTS AND CONCLUSION

It is suggested that development of future treatments for chronic pain ought to incorporate an idiographic, process-based approach, focused on evidence-based mechanisms of change, individually and dynamically addressed, based on contextually sensitive ongoing assessment. Knowledge and practical solutions needed to make process-based therapy for chronic pain happen are discussed.

SIGNIFICANCE

Psychological approaches to chronic pain have been highly successful in the past but improvement in the effectiveness of these over time is slow to nonexistent. It is argued here that this has happened due to a failure to adequately consider the individual. Future psychological treatments for chronic pain ought to incorporate an idiographic, process-based approach, focused on evidence-based mechanisms of change, individually and dynamically addressed, grounded in ongoing contextually sensitive assessment.

Showing True Colours: EMA Case Descriptions of Narcissistic States

Traditionally, narcissistic characteristics are considered relatively stable, although clinical accounts and recent research show that additional narcissistic states are variable and fluctuate in actuality. Narcissism research tends to focus on cross-sectional, group-based, trait approaches. Momentary ecological assessments allow one to discover individuals' true colors by observing narcissistic experiences while they unfold in real-time and real-world settings. Within momentary ecological assessments, inspecting single cases enables insight into individual dynamics and presentations. Consequently, this research collected grandiose and vulnerable narcissistic trait and state data 10 times a day for 6 days. Based on the highest trait scores, two individual cases are presented per category: predominantly grandiose narcissistic, predominantly vulnerable narcissistic, and combined narcissistic. Overall, the descriptions provide evidence for the dynamics within and between grandiose and vulnerable narcissistic states. Further, broad patterns for each narcissistic dimension were uncovered, in which the grandiose subdimension experienced mainly grandiosity, and the vulnerable and combined subdimensions experienced both grandiosity and vulnerability. Out of the three, the combined subdimension experienced the highest instability and levels of daily vulnerability. However, each individual case showed unique fluctuation patterns that highlight the importance of personalized, real-life assessments in research and clinical care.

Perceived causal symptom network of adolescent mental health issues

Adolescent mental health is difficult to capture in categories such as depression or specific anxiety disorders. An alternative is to approach psychiatric symptoms as causal networks, potentially revealing feedback loops that maintain a pathological state. One approach to creating such networks, implemented in the PECAN methodology, is to ask adolescents about their perceptions of the causes to their symptoms. For this purpose, a transdiagnostic item list was created, and adolescents who screened positive for depression (N = 55) completed twice in two weeks a survey quantifying perceptions of causality between their mental health problems. A network that was averaged across all participants was reliable and revealed three strong feedback loops: a first loop running through stress, insomnia, fatigue, procrastination, and back to stress; a second loop between stress and overthinking; and a third loop between stress and procrastination. Although all adolescents in the study screened positive for depression, symptoms of depression were not particularly central to the network. Instead, the most central symptoms were procrastination and overthinking. The average test-retest reliability for individual networks was low, limiting clinical application. In conclusion, PECAN was found to be reliable and useful when creating a group-level network of adolescent mental health problems. While informative at a group level, the method should be improved before it can be used to inform treatment at the individual level.