Methodological and Statistical Practices of Using Symptom Networks to Evaluate Mental Health Interventions: A Review and Reflections.

The network approach to psychopathology, which assesses associations between individual symptoms, has recently been applied to evaluate treatments for mental disorders. While various options for conducting network analyses in intervention research exist, an overview and an evaluation of the various approaches are currently missing. Therefore, we conducted a review on network analyses in intervention research. Studies were included if they constructed a symptom network, analyzed data that were collected before, during or after treatment of a mental disorder, and yielded information about the treatment effect. The 56 included studies were reviewed regarding their methodological and analytic strategies. About half of the studies based on data from randomized trials conducted a network intervention analysis, while the other half compared networks between treatment groups. The majority of studies estimated cross-sectional networks, even when repeated measures were available. All but five studies investigated networks on the group level. This review highlights that current methodological practices limit the information that can be gained through network analyses in intervention research. We discuss the strength and limitations of certain methodological and analytic strategies and propose that further work is needed to use the full potential of the network approach in intervention research.

A novel approach for constructing personalized networks from longitudinal perceived causal relations.

Personalized networks of psychological symptoms aim to advance therapy by identifying treatment targets for specific patients. Statistical relations in such networks can be estimated from intensive longitudinal data, but their causal interpretation is limited by strong statistical assumptions. An alternative is to create networks from patient perceptions, which comes with other limitations such as retrospective bias. We introduce the Longitudinal Perceived Causal Problem Networks (L-PECAN) approach to address both these concerns. 20 participants screening positive for depression completed 4 weeks day of brief daily assessments of perceived symptom interactions. Quality criteria of this new method are introduced, answering questions such as "Which symptoms should be included in networks?", "How many datapoints need to be collected to achieve stable networks?", and "Does the network change over time?". Accordingly, about 40% of respondents achieved stable networks and only few respondents exhibited network structure that changed during the assessment period. The method was time-efficient (on average 7.4 min per day), and well received. Overall, L-PECAN addresses several of the prevailing issues found in statistical networks and therefore provides a clinically meaningful method for personalization.

Reporting standards for psychological network analyses in cross-sectional data.

Statistical network models describing multivariate dependency structures in psychological data have gained increasing popularity. Such comparably novel statistical techniques require specific guidelines to make them accessible to the research community. So far, researchers have provided tutorials guiding the estimation of networks and their accuracy. However, there is currently little guidance in determining what parts of the analyses and results should be documented in a scientific report. A lack of such reporting standards may foster researcher degrees of freedom and could provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific work. We conclude by discussing how the network literature specifically can benefit from such guidelines for reporting and transparency. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Daily dynamics and mechanisms of anxious symptomatology in the general population: A network study during the COVID-19 pandemic.

To understand the interplay between anxiety symptoms and their maintaining psychological processes in the population, an analysis of longitudinal within-person relationships is required. A sample of 1706 individuals completed daily measures during a 40-day period with strict mitigation protocols. Data of 1368 individuals who completed at least 30 assessments were analyzed with the multilevel vector autoregressive (mlVAR) model. This model estimates a temporal, a contemporaneous, and a between-person network. Uncontrollability of worry, generalized worry, fear of being infected, fear of significant others being infected, and threat monitoring had the highest outstrength within the temporal network, indicating that daily fluctuations in these components were the most predictive of next-day fluctuations in other components. Of specific connections, both fear of self and fear of close others being infected predicted generalized worry and threat monitoring. In turn, generalized worry and threat monitoring engaged in several positive feedback loops with other anxiety symptoms and processes. Also, intolerance of uncertainty was predictive of other components. The findings align with the mechanisms both in the metacognitive therapy (MCT) model and in the intolerance of uncertainty model of generalized anxiety disorder (GAD).

A clinical PREMISE for personalized models: Toward a formal integration of case formulations and statistical networks.

Over the past decade, the idiographic approach has received significant attention in clinical psychology, incentivizing the development of novel approaches to estimate statistical models, such as personalized networks. Although the notion of such networks aligns well with the way clinicians think and reason, there are currently several barriers to implementation that limit their clinical utility. To address these issues, we introduce the Prior Elicitation Module for Idiographic System Estimation (PREMISE), a novel approach that formally integrates case formulations with personalized network estimation via prior elicitation and Bayesian inference. PREMISE tackles current implementation barriers of personalized networks; incorporating clinical information into personalized network estimation systematically allows theoretical and data-driven integration, supporting clinician and patient collaboration when building a dynamic understanding of the patient's psychopathology. To illustrate its potential, we estimate clinically informed networks for a patient suffering from obsessive-compulsive disorder. We discuss open challenges in selecting statistical models for PREMISE, as well as specific future directions for clinical implementation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Integrating clinician and patient case conceptualization with momentary assessment data to construct idiographic networks: Moving toward personalized treatment for eating disorders.

Eating disorders are serious psychiatric illnesses with treatments ineffective for about 50% of individuals due to high heterogeneity of symptom presentation even within the same diagnoses, a lack of personalized treatments to address this heterogeneity, and the fact that clinicians are left to rely upon their own judgment to decide how to personalize treatment. Idiographic (personalized) networks can be estimated from ecological momentary assessment data, and have been used to investigate central symptoms, which are theorized to be fruitful treatment targets. However, both efficacy of treatment target selection and implementation with 'real world' clinicians could be maximized if clinician input is integrated into such networks. An emerging line of research is therefore proposing to integrate case conceptualizations and statistical routines, tying together the benefits from clinical expertise as well as patient experience and idiographic networks. The current pilot compares personalized treatment implications from different approaches to constructing idiographic networks. For two patients with a diagnosis of anorexia nervosa, we compared idiographic networks 1) based on the case conceptualization from clinician and patient, 2) estimated from patient EMA data (the current default in the literature), and 3) based on a combination of case conceptualization and patient EMA data networks, drawing on informative priors in Bayesian inference. Centrality-based treatment recommendations differed to varying extent between these approaches for patients. We discuss implications from these findings, as well as how these models may inform clinical practice by pairing evidence-based treatments with identified treatment targets.

Back to life, back to reality: A multi-level dynamic network analysis of student mental health upon return to campus during the COVID-19 pandemic.

Lockdown measures during the COVID-19 pandemic resulted in drastic disruptions of university students' everyday life and study mode, such as marked reductions in face-to-face teaching activities. Previous research on student mental health during the pandemic found that prolonged campus relocation had negative effects on students' mental well-being. However, these studies focussed on the initial lockdown period, or periods of active lockdown measures. This longitudinal study collected 456 observations of 23 undergraduate students in the Netherlands using ecological momentary assessment data on mental health related items (anxiety, stress, social context) during the first two weeks of on-campus teaching after prolonged lockdown measures. Using multi-level dynamic network modelling, we analysed the temporal and contemporaneous interplay of students' mental health factors following the return to campus in September 2021. On average, students reported low to medium scores on stress and anxiety both before and after the assessment period. Results of network analyses showed that students experienced social unease in relation to accumulating difficulties at university and vice versa. Furthermore, there were clusters of different states of social unease next to clusters of stress, anger, loss of control, and feeling upset. Lastly, we found beneficial effects of self-efficacy on experiencing social comfort in university. We discuss implications and concrete examples of interventions in universities, such as the promotion of self-efficacy, providing guidance in structuring study load, as well as help with stress management. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-03196-7.

Evaluation of the cognitive behavioural theory of eating disorders: A network analysis investigation.

OBJECTIVE: One of the prevailing theories of eating disorders (ED) is the transdiagnostic cognitive behavioural theory of eating disorders, which suggests that certain ED symptoms, such as over-valuation of eating, shape, and weight, may be more central than others. In the present study, network analyses were used to evaluate these assumptions in a patient sample. METHODS: Participants were 336 individuals receiving treatment at an expert center for ED in the Netherlands. Eating disorder symptoms were used to create transdiagnostic and diagnosis-specific networks and assess symptom centrality and density of the networks. RESULTS: Networks for patients with bulimia nervosa and binge eating disorder confirmed that over-valuation of shape, weight, and eating is the most central symptom in the network. A transdiagnostic network of ED symptoms and separate networks for patients with anorexia nervosa and bulimia nervosa showed that strict dieting was an additional central ED symptom. An exploratory analysis revealed that, although eating disorder symptoms decreased, there were no differences in density of the eating disorder networks before and after treatment with cognitive behavioural therapy. DISCUSSION: In conclusion, the current study confirmed that over-valuation of shape, weight, and eating is a central symptom across eating disorders, in agreement with the transdiagnostic cognitive behavioural model of eating disorders. Specifically targeting this symptom in treatment could lead to other symptoms improving as a result.

Within- and across-day patterns of interplay between depressive symptoms and related psychopathological processes: a dynamic network approach during the COVID-19 pandemic.

BACKGROUND: In order to understand the intricate patterns of interplay connected to the formation and maintenance of depressive symptomatology, repeated measures investigations focusing on within-person relationships between psychopathological mechanisms and depressive components are required. METHODS: This large-scale preregistered intensive longitudinal study conducted 68,240 observations of 1706 individuals in the general adult population across a 40-day period during the COVID-19 pandemic to identify the detrimental processes involved in depressive states. Daily responses were modeled using multi-level dynamic network analysis to investigate the temporal associations across days, in addition to contemporaneous relationships between depressive components within a daily window. RESULTS: Among the investigated psychopathological mechanisms, helplessness predicted the strongest across-day influence on depressive symptoms, while emotion regulation difficulties displayed more proximal interactions with symptomatology. Helplessness was further involved in the amplification of other theorized psychopathological mechanisms including rumination, the latter of which to a greater extent was susceptible toward being influenced rather than temporally influencing other components of depressive states. Distinctive symptoms of depression behaved differently, with depressed mood and anhedonia most prone to being impacted, while lethargy and worthlessness were more strongly associated with outgoing activity in the network. CONCLUSIONS: The main mechanism predicting the amplifications of detrimental symptomatology was helplessness. Lethargy and worthlessness revealed greater within-person carry-over effects across days, providing preliminary indications that these symptoms may be more strongly associated with pushing individuals toward prolonged depressive state experiences. The psychopathological processes of rumination, helplessness, and emotion regulation only exhibited interactions with the depressed mood and worthlessness component of depression, being unrelated to lethargy and anhedonia. The findings have implications for the impediment of depressive symptomatology during and beyond the pandemic period. They further outline the gaps in the literature concerning the identification of psychopathological processes intertwined with lethargy and anhedonia on the within-person level.

Using clinical expertise and empirical data in constructing networks of trauma symptoms in refugee youth.

Background: In recent years, many adolescents have fled their home countries due to war and human rights violations, consequently experiencing various traumatic events and putting them at risk of developing mental health problems. The symptomatology of refugee youth was shown to be multifaceted and often falling outside of traditional diagnoses. Objective: The present study aimed to investigate the symptomatology of this patient group by assessing the network structure of a wide range of symptoms. Further, we assessed clinicians' perceptions of symptoms relations in order to evaluate the clinical validity of the empirical network. Methods: Empirical data on Post-Traumatic Stress Disorder (PTSD), depression and other trauma symptoms from N = 366 refugee youth were collected during the routine diagnostic process of an outpatient centre for refugee youth in Germany. Additionally, four clinicians of this outpatient centre were asked how they perceive symptom relations in their patients using a newly developed tool. Separate networks were constructed based on 1) empirical symptom data and 2) clinicians' perceived symptom relations (PSR). Results: Both the network based on empirical data and the network based on clinicians' PSR showed that symptoms of PTSD and depression related most strongly within each respective cluster (connected mainly via sleeping problems), externalizing symptoms were somewhat related to PTSD symptoms and intrusions were central. Some differences were found within the clinicians' PSR as well as between the PSR and the empirical network. Still, the general PSR-network structure showed a moderate to good fit to the empirical data. Conclusion: Our results suggest that sleeping problems and intrusions play a central role in the symptomatology of refugee children, which has tentative implications for diagnostics and treatment. Further, externalizing symptoms might be an indicator for PTSD-symptoms. Finally, using clinicians' PSR for network construction offered a promising possibility to gain information on symptom networks and their clinical validity.

Antecedentes: En los últimos años, muchos adolescentes han huido de sus países de origen debido a la guerra y a violaciones contra los derechos humanos experimentando, como consecuencia, diversos eventos traumáticos y situándose en riesgo de desarrollar problemas de salud mental. La sintomatología de los refugiados jóvenes mostró ser multifacética y, por lo general, quedando fuera de los diagnósticos tradicionales.Objetivos: Este estudio tiene por objetivo investigar la sintomatología de este grupo de pacientes evaluando la estructura de redes de un amplio rango de síntomas. Además, evaluamos la percepción de los clínicos respecto a la relación de los síntomas para evaluar la validez clínica del trabajo de redes empírico.Métodos: Se recolectaron datos empíricos sobre el trastorno de estrés postraumático (TEPT), la depresión y otros síntomas de trauma de N = 366 jóvenes refugiados durante los procesos diagnósticos de rutina de un centro ambulatorio para refugiados jóvenes en Alemania. Además, a cuatro clínicos de este centro ambulatorio se les preguntó sobre cómo percibían las relaciones de los síntomas de sus pacientes empleando una herramienta recientemente desarrollada. Se construyeron redes separadas sobre la base de 1) datos empíricos de síntomas y 2) la percepción de la relación de los síntomas (PRS) de los clínicos.Resultados: Tanto las redes basadas en datos empíricos como las redes basadas en la PRS de los clínicos mostraron que los síntomas del TEPT y de la depresión se relacionaban con más fuerza con cada racimo respectivo de síntomas (conectados principalmente a través de los problemas de sueño). Los síntomas externalizantes estaban algo relacionados con los síntomas asociados al TEPT mientras que las intrusiones se constituyeron en algo central. Se encontraron algunas diferencias entre las propias PRS's de los clínicos, así como entre la PRS y las redes empíricas. Aun así, la restructura general de redes basadas en la PRS mostró una correspondencia moderada a buena con los datos empíricos.Conclusión: Nuestros resultados sugieren que los problemas de sueño y las intrusiones tienen un papel central en la sintomatología de los niños refugiados, lo que tiene implicancias tentativas para el diagnóstico y el tratamiento. Además, los síntomas externalizantes podrían ser un indicador de síntomas asociados al TEPT. Finalmente, empleando la PRS de los clínicos para la construcción de redes brindó una posibilidad prometedora para obtener información sobre las redes de síntomas y su validez clínica.

Bridging the gap between complexity science and clinical practice by formalizing idiographic theories: a computational model of functional analysis.

BACKGROUND: The past decades of research have seen an increase in statistical tools to explore the complex dynamics of mental health from patient data, yet the application of these tools in clinical practice remains uncommon. This is surprising, given that clinical reasoning, e.g., case conceptualizations, largely coincides with the dynamical system approach. We argue that the gap between statistical tools and clinical practice can partly be explained by the fact that current estimation techniques disregard theoretical and practical considerations relevant to psychotherapy. To address this issue, we propose that case conceptualizations should be formalized. We illustrate this approach by introducing a computational model of functional analysis, a framework commonly used by practitioners to formulate case conceptualizations and design patient-tailored treatment. METHODS: We outline the general approach of formalizing idiographic theories, drawing on the example of a functional analysis for a patient suffering from panic disorder. We specified the system using a series of differential equations and simulated different scenarios; first, we simulated data without intervening in the system to examine the effects of avoidant coping on the development of panic symptomatic. Second, we formalized two interventions commonly used in cognitive behavioral therapy (CBT; exposure and cognitive reappraisal) and subsequently simulated their effects on the system. RESULTS: The first simulation showed that the specified system could recover several aspects of the phenomenon (panic disorder), however, also showed some incongruency with the nature of panic attacks (e.g., rapid decreases were not observed). The second simulation study illustrated differential effects of CBT interventions for this patient. All tested interventions could decrease panic levels in the system. CONCLUSIONS: Formalizing idiographic theories is promising in bridging the gap between complexity science and clinical practice and can help foster more rigorous scientific practices in psychotherapy, through enhancing theory development. More precise case conceptualizations could potentially improve intervention planning and treatment outcomes. We discuss applications in psychotherapy and future directions, amongst others barriers for systematic theory evaluation and extending the framework to incorporate interactions between individual systems, relevant for modeling social learning processes. With this report, we hope to stimulate future efforts in formalizing clinical frameworks.

Bereavement or breakup: Differences in networks of depression.

BACKGROUND: Prior network analyses demonstrated that the death of a loved one potentially precedes specific depression symptoms, primarily loneliness, which in turn links to other depressive symptoms. In this study, we extend prior research by comparing depression symptom network structures following two types of marital disruption: bereavement versus separation. METHODS: We fitted two Gaussian Graphical Models to cross-sectional data from a Swiss survey of older persons (145 bereaved, 217 separated, and 362 married controls), and compared symptom levels across bereaved and separated individuals. RESULTS: Separated compared to widowed individuals were more likely to perceive an unfriendly environment and oneself as a failure. Both types of marital disruption were strongly linked to loneliness, from where different relations emerged to other depressive symptoms. Amongst others, loneliness had a stronger connection to perceiving oneself as a failure in separated compared to widowed individuals. Conversely, loneliness had a stronger connection to getting going in widowed individuals. LIMITATIONS: Analyses are based on cross-sectional between-subjects data, and conclusions regarding dynamic processes on the within-subjects level remain putative. Further, some of the estimated parameters in the network exhibited overlapping confidence intervals and their order needs to be interpreted with care. Replications should thus aim for studies with multiple time points and larger samples. CONCLUSIONS: The findings of this study add to a growing body of literature indicating that depressive symptom patterns depend on contextual factors. If replicated on the within-subjects level, such findings have implications for setting up patient-tailored treatment approaches in dependence of contextual factors.

Drug Policy and Indigenous Peoples.

This paper identifies the principal concerns of indigenous peoples with regard to current international treaties on certain psychoactive substances and policies to control and eradicate their production, trafficking, and sale. Indigenous peoples have a specific interest in the issue since their traditional lands have become integrated over time into the large-scale production of coca, opium poppy, and cannabis crops, in response to high demand from the American and European markets, among others. As a consequence, indigenous peoples are persecuted because of their traditional use of these and other plant-based narcotics and hallucinogens. They are also victims of the drug producers who remove them from their lands or forcibly recruit them into the production process. As indigenous peoples are caught in the violent world of illicit drug production, law enforcement often targets them first, resulting in disproportionate rates of criminalization and incarceration.

Adaptive emotion regulation mediates the relationship between self-compassion and depression in individuals with unipolar depression.

OBJECTIVES: To identify the mechanisms involved in the association between self-compassion and depression, we examined whether adaptive emotion regulation would mediate the relationship between self-compassion and depression in individuals with unipolar depression. Furthermore, we explored which specific emotion regulation skills would be most important in this relationship. DESIGN AND METHOD: Sixty-nine individuals with unipolar depression were assessed with the Self-Compassion Scale and the Emotion Regulation Skills Questionnaire at baseline and with the Beck Depression Inventory-II 1 week later. RESULTS: The results showed that successful application of emotion regulation skills mediates the association between self-compassion and depression. Among eight specific emotion regulation skills, only the ability to tolerate negative emotions was identified as a significant mediator in the self-compassion-depression relationship. CONCLUSIONS: These findings provide preliminary evidence that systematically fostering self-compassion might help depressed individuals cope with their symptoms by enhancing their abilities to tolerate undesired emotions. PRACTITIONER POINTS: Systematically fostering self-compassion through specific compassion-focused interventions might facilitate a reduction in depressive symptoms by improving the person's emotion regulation abilities, especially by improving his or her ability to tolerate negative emotions. Hence, compassion-focused interventions might be particularly promising in depressed patients with a tendency to avoid negative emotions and deficits in tolerating them.