Productive explanation: A framework for evaluating explanations in psychological science.

The explanation of psychological phenomena is a central aim of psychological science. However, the nature of explanation and the processes by which we evaluate whether a theory explains a phenomenon are often unclear. Consequently, it is often unknown whether a given psychological theory indeed explains a phenomenon. We address this shortcoming by proposing a productive account of explanation: a theory explains a phenomenon to some degree if and only if a formal model of the theory produces the statistical pattern representing the phenomenon. Using this account, we outline a workable methodology of explanation: (a) explicating a verbal theory into a formal model, (b) representing phenomena as statistical patterns in data, and (c) assessing whether the formal model produces these statistical patterns. In addition, we provide three major criteria for evaluating the goodness of an explanation (precision, robustness, and empirical relevance), and examine some cases of explanatory breakdowns. Finally, we situate our framework within existing theories of explanation from philosophy of science and discuss how our approach contributes to constructing and developing better psychological theories. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

An examination of episodic future thinking in the emergency department among youth experiencing suicidal thoughts and behaviors.

Youth experiencing suicidal thoughts and/or behaviors (STBs) frequently present to emergency departments for acute psychiatric care. These settings offer a transitory yet pivotal opportunity to assess, intervene on, and plan continued care for STBs. This study examined a clinically relevant, understudied aspect of psychological functioning among youth experiencing STBs in the emergency department: episodic future thinking, or the ability to imagine discrete autobiographical future events. A sample of 167 youths (10-17 years) presenting to a pediatric psychiatric emergency department for STBs completed a performance-based measure of episodic future thinking assessing richness in detail and subjective characteristics of imagined future events. STB recurrence was assessed 6 months later. Immediately following a suicide-related crisis, youth demonstrated mixed abilities to imagine their future: they generated some concrete future event details but did not subjectively perceive these events as being very detailed or likely to occur. Older adolescents (i.e., 15-17) generated more episodic details than pre-/younger adolescents (i.e., 10-14), particularly those pertaining to actions or sensory perceptions. There was no evidence linking less detailed episodic future thinking and greater likelihood of STBs following the emergency department visit; instead, hopelessness was a more robust risk factor. Findings underscore the importance and clinical utility of better understanding the psychological state of youth during or immediately following a suicide-related crisis. In particular, assessing youths' future thinking abilities in the emergency department may directly inform approaches to acute care delivery.

Towards a general modeling framework of resource competition in cognitive development.

The current paper presents an integrated formal model of typical and atypical development based on the mechanisms of mutualism and resource competition. The mutualistic network model is extended with the dynamics of competition for limited resources, such as time and environmental factors. The proposed model generates patterns that resemble established phenomena in cognitive development: the positive manifold, developmental phases, developmental delays and lack of early indicators in atypical development, developmental regression, and "quasi-autism" caused by extreme environmental deprivation. The presented modeling framework fits a general movement towards formal theory construction in psychology. The model is easy to replicate and develop further, and we offer several avenues for future work.

Quantifying and addressing the impact of measurement error in network models.

Network psychometric models are often estimated using a single indicator for each node in the network, thus failing to consider potential measurement error. In this study, we investigate the impact of measurement error on cross-sectional network models. First, we conduct a simulation study to evaluate the performance of models based on single indicators as well as models that utilize information from multiple indicators per node, including average scores, factor scores, and latent variables. Our results demonstrate that measurement error impairs the reliability and performance of network models, especially when using single indicators. The reliability and performance of network models improves substantially with increasing sample size and when using methods that combine information from multiple indicators per node. Second, we use empirical data from the STAR*D trial (n = 3,731) to further evaluate the impact of measurement error. In the STAR*D trial, depression symptoms were assessed via three questionnaires, providing multiple indicators per symptom. Consistent with our simulation results, we find that when using sub-samples of this dataset, the discrepancy between the three single-indicator networks (one network per questionnaire) diminishes with increasing sample size. Together, our simulated and empirical findings provide evidence that measurement error can hinder network estimation when working with smaller samples and offers guidance on methods to mitigate measurement error.

The course of symptoms in the first 27 months following bereavement: A latent trajectory analysis of prolonged grief, posttraumatic stress, and depression.

BACKGROUND: Much remains unknown about the course of grief in the early months following bereavement, including the prevalence and timing of a recovery trajectory, whether specific symptoms mark a failure to recover, and the co-occurrence of chronic prolonged grief (PG), posttraumatic stress (PTS) and depression symptoms. METHODS: Two hundred fifty-nine participants completed PG, PTS and depression questionnaires up to eleven times every six weeks during the two years post-bereavement. We used Latent Class Growth Mixture Modeling (LCGMM) to identify subgroups of bereaved individuals sharing similar trajectories for each disorder. We used repeated measures ANOVA to evaluate differences in individual symptoms between trajectories. Finally, we investigated to what extent chronic trajectories of these three disorders co-occurred. RESULTS: Three trajectories of PG symptoms emerged: resilient (66.4%), chronic (25.1%) and acute recovery (8.4%). The overall severity and symptom profile of the acute recovery group were indistinguishable from that of the chronic group through 6 months post-bereavement, followed by reduction in PG from 6 to 18 months post-bereavement. Chronic PTS in the first-year post-bereavement tended to co-occur with chronic PG and/or chronic depression. CONCLUSIONS: Twenty five percent of those with initial elevations in grief recovered in the period of 6 to 12 months post-bereavement. These findings highlight the clinical importance of severe grief in the initial months following loss, but also suggests caution in diagnosing a grief disorder within the first-year post-bereavement.

Examining multiple features of episodic future thinking and episodic memory among suicidal adults.

BCKGROUND: Theories of suicide suggest that suicidal ideation (SI) results in part from difficulty imagining the future, which itself relies on the ability to remember the past. The present study examines multiple components of episodic future thinking and memory including event richness, which is commonly measured within the cognitive literature but has not previously been assessed with suicidal individuals. METHODS: Here, we tested the associations between SI and episodic future thinking and episodic memory across two studies (Study 1, n = 25; Study 2, n = 141): the first with a healthy comparison group and the second with a psychiatric comparison group. RESULTS: Future event richness yielded large but statistically non-significant deficits in the SI group relative to healthy controls in Study 1 after controling the false discovery rate. The most robust effects for future thinking emerged in the case of perceived duration of future events, such that the SI group (vs. psychiatric comparison) imagined future events as longer-lasting in Study 2. Across both studies, episodic memory was unrelated to SI, and neither episodic future thinking nor memory predicted future SI. CONCLUSION: Episodic future thinking may better distinguish individuals with SI history from psychiatric controls when compared with episodic memory, but that this effect is limited to select components of future thinking.

Estimating the symptom structure of bipolar disorder via network analysis: Energy dysregulation as a central symptom.

Using network analysis, we estimated the structure of relations among manic and depressive symptoms, respectively, in 486 patients (59% women; age: M = 37, SD = 12.1) with bipolar disorder prior to their entering a clinical trial. We computed three types of networks: (a) Gaussian graphical models (GGMs) depicting regularized partial correlations, (b) regression-based GGMs depicting nonregularized partial correlations, and (c) directed acyclic graphs (DAGs) via a Bayesian hill-climbing algorithm. Low energy and elevated energy were consistently identified as central nodes in the GGMs and as key parent nodes in the DAGs. Across analyses, pessimism about the future and depressed mood were the symptoms most strongly associated with suicidal thoughts and behavior. These exploratory analyses provide rich information about how bipolar disorder symptoms relate to one another, thereby furnishing a foundation for investigating how bipolar disorder symptoms may operate as a causal system. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The causal systems approach to prolonged grief: Recent developments and future directions.

The network theory of prolonged grief posits that causal interactions among symptoms of prolonged grief play a significant role in their coherence and persistence as a syndrome. Drawing on recent developments in the broader network approach to psychopathology, we argue that advancing our understanding of the causal system that gives rise to prolonged grief will require that we (a) strengthen our assessment of each component of the grief syndrome, (b) investigate intra-individual relationships among grief components as they evolve over time within individuals, (c) incorporate biological and social components into network studies of grief, and (d) generate formal theories that posit precisely how these biological, psychological, and social components interact with one another to give rise to prolonged grief disorder.

On the Control of Psychological Networks.

The combination of network theory and network psychometric methods has opened up a variety of new ways to conceptualize and study psychological disorders. The idea of psychological disorders as dynamic systems has sparked interest in developing interventions based on results of network analytic tools. However, simply estimating a network model is not sufficient for determining which symptoms might be most effective to intervene upon, nor is it sufficient for determining the potential efficacy of any given intervention. In this paper, we attempt to remedy this gap by introducing fundamental concepts of control theory to both psychometricians and applied psychologists. We introduce two controllability statistics to the psychometric literature, average and modal controllability, to facilitate selecting the best set of intervention targets. Following this introduction, we show how intervention scientists can probe the effects of both theoretical and empirical interventions on networks derived from real data and demonstrate how simulations can account for intervention cost and the desire to reduce specific symptoms. Every step is based on rich clinical EMA data from a sample of subjects undergoing treatment for complicated grief, with a focus on the outcome suicidal ideation. All methods are implemented in an open-source R package netcontrol, and complete code for replicating the analyses in this manuscript are available online.

Modeling psychopathology: From data models to formal theories.

Over the past decade, there has been a surge of empirical research investigating mental disorders as complex systems. In this article, we investigate how to best make use of this growing body of empirical research and move the field toward its fundamental aims of explaining, predicting, and controlling psychopathology. We first review the contemporary philosophy of science literature on scientific theories and argue that fully achieving the aims of explanation, prediction, and control requires that we construct formal theories of mental disorders: theories expressed in the language of mathematics or a computational programming language. We then investigate three routes by which one can use empirical findings (i.e., data models) to construct formal theories: (a) using data models themselves as formal theories, (b) using data models to infer formal theories, and (c) comparing empirical data models to theory-implied data models in order to evaluate and refine an existing formal theory. We argue that the third approach is the most promising path forward. We conclude by introducing the abductive formal theory construction (AFTC) framework, informed by both our review of philosophy of science and our methodological investigation. We argue that this approach provides a clear and promising way forward for using empirical research to inform the generation, development, and testing of formal theories both in the domain of psychopathology and in the broader field of psychological science. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Revisiting the theoretical and methodological foundations of depression measurement.

Depressive disorders are among the leading causes of global disease burden, but there has been limited progress in understanding the causes and treatments for these disorders. In this Perspective, we suggest that such progress crucially depends on our ability to measure depression. We review the many problems with depression measurement, including limited evidence of validity and reliability. These issues raise grave concerns about common uses of depression measures, such as diagnosis or tracking treatment progress. We argue that shortcomings arise because depression measurement rests on shaky methodological and theoretical foundations. Moving forward, we need to break with the field's tradition that has, for decades, divorced theories about depression from how we measure it. Instead, we suggest that epistemic iteration, an iterative exchange between theory and measurement, provides a crucial avenue for depression measurement to progress.

An Answer to "So What?" Implications of Network Theory for Research and Practice.

Research and practice in psychiatry and clinical psychology have been guided by differing schools of thought over the years. Recently, the network theory of psychopathology has arisen as a framework for thinking about mental health. Network theory challenges three common assumptions: psychological problems are caused by disease entities that exist independently of their signs and symptoms, classification and diagnosis of psychological problems should follow a medical model, and psychological problems are caused by diseases or aberrations in the brain. Conversely, network theory embraces other assumptions that are well accepted in clinical practice (e.g., the interaction of thoughts, behaviors, and emotions, as posited in cognitive-behavioral therapies) and integrates those assumptions into a coherent framework for research and practice. In this article, the authors review developments in network theory by focusing on anxiety-related conditions, discuss future areas for change, and outline implications of network theory for research and clinical practice.

Traumatic grief research and care in the aftermath of the COVID-19 pandemic.

BACKGROUND: A significant increase in the number of individuals suffering from prolonged grief disorder is expected in the aftermath of the COVID-19 pandemic for two main reasons. First, the number of excess deaths has contributed to an immense number of bereaved individuals. Second, recent literature has shown that circumstances associated with COVID-19 deaths may be contributing to increased risk for the development of prolonged grief disorder. OBJECTIVE: To best support those affected by loss during the COVID-19 pandemic, it is important to inform clinicians and researchers about the development, the nature and the treatment of prolonged grief disorder and employ sound research. METHOD: In this editorial, we discuss important themes regarding prolonged grief disorder in the aftermath of the COVID-19 pandemic, to gather and present useful information for clinicians and researchers. RESULTS: The following themes were addressed: 1. Harmonization in the diagnosis of prolonged grief disorder. 2. Screening tools and interventions. 3. Pharmacotherapy. 4. Special attention for the elderly. 5. Special attention for children and adolescents. 6. A causal system perspective for understanding grief and prolonged grief disorder. CONCLUSIONS: If those involved in bereavement research and care manage to collaborate, the tragic consequences of COVID-19 might catalyse improvement of care for those most impaired following the loss of a loved one.

Antecedentes: Se espera un aumento significativo en el número de personas que padecen de un trastorno de duelo prolongado como consecuencia de la pandemia de COVID-19 por dos razones principales. Primero, el número de muertes en exceso ha contribuido a un inmenso número de personas en duelo. En segundo lugar, la literatura reciente ha demostrado que las circunstancias asociadas con las muertes por COVID-19 pueden estar contribuyendo a un mayor riesgo de desarrollar un trastorno de duelo prolongado.Objetivo: Para apoyar mejor a los afectados por la pérdida durante la pandemia de COVID-19, es importante informar a los médicos e investigadores sobre el desarrollo, la naturaleza y el tratamiento del trastorno de duelo prolongado y emplear investigaciones sólidas.Método: En este editorial, discutimos temas importantes relacionados con el trastorno de duelo prolongado después de la pandemia de COVID-19, para recopilar y presentar información útil para médicos e investigadores.Resultados: Se abordaron los siguientes temas: 1. Armonización en el diagnóstico del trastorno de duelo prolongado. 2. Herramientas de tamizaje e intervenciones. 3. Farmacoterapia. 4. Atención especial para adultos mayores. 5. Atención especial para niños y adolescentes. 6. Una perspectiva del sistema causal para comprender el duelo y el trastorno de duelo prolongado.Conclusiones: Si los involucrados en la investigación y el cuidado del duelo logran colaborar, las trágicas consecuencias del COVID-19 podrían catalizar la mejora de la atención para los más afectados después de la pérdida de un ser querido.

Posttraumatic Distress Symptoms and Their Response to Treatment in Adults With Prolonged Grief Disorder.

OBJECTIVE: Posttraumatic stress disorder and prolonged grief disorder (PGD) arise following major life stressors and may share some overlapping symptomatology. This study aimed to examine the presence and response to treatment of posttraumatic stress symptoms (PTSS) in bereaved adults with a primary diagnosis of PGD. METHODS: A randomized controlled trial of 395 adults with PGD (defined as an Inventory of Complicated Grief score ≥ 30 plus confirmation on structured clinical interview) randomly assigned participants to either complicated grief treatment (CGT) with citalopram, CGT plus placebo, citalopram, or placebo between March 2010 and September 2014. This secondary analysis examined the presence of PTSS (per the Davidson Trauma Scale) at baseline and change in PTSS with treatment using longitudinal mixed-effects regression and examined the role of violent compared to nonviolent deaths (loss type). RESULTS: High levels of PTSS were present at baseline, regardless of loss type, and were associated with increased functional impairment (P < .001). CGT with placebo demonstrated efficacy for PTSS compared to placebo in both threshold (OR = 2.71; 95% CI, 1.13-6.52; P = .026) and continuous (P < .001; effect size d = 0.47) analyses, and analyses were suggestive of a greater effect for CGT plus citalopram compared to citalopram alone (threshold analysis: OR = 2.84; 95% CI, 1.20-6.70; P = .017; continuous analysis: P = .053; d = 0.25). In contrast, citalopram did not differ from placebo, and CGT plus citalopram did not differ from CGT plus placebo. CONCLUSIONS: Bereavement-related PTSS are common in bereaved adults with PGD in the context of both violent and nonviolent death and are associated with poorer functioning. CGT shows efficacy for PTSS, while the antidepressant citalopram does not. TRIAL REGISTRATION: : ClinicalTrials.gov identifier: NCT01179568.

Invisible Hands and Fine Calipers: A Call to Use Formal Theory as a Toolkit for Theory Construction.

In recent years, a growing chorus of researchers has argued that psychological theory is in a state of crisis: Theories are rarely developed in a way that indicates an accumulation of knowledge. Paul Meehl raised this very concern more than 40 years ago. Yet in the ensuing decades, little has improved. We aim to chart a better path forward for psychological theory by revisiting Meehl's criticisms, his proposed solution, and the reasons his solution failed to meaningfully change the status of psychological theory. We argue that Meehl identified serious shortcomings in our evaluation of psychological theories and that his proposed solution would substantially strengthen theory testing. However, we also argue that Meehl failed to provide researchers with the tools necessary to construct the kinds of rigorous theories his approach required. To advance psychological theory, we must equip researchers with tools that allow them to better generate, evaluate, and develop their theories. We argue that formal theories provide this much-needed set of tools, equipping researchers with tools for thinking, evaluating explanation, enhancing measurement, informing theory development, and promoting the collaborative construction of psychological theories.

Investigating the Utility of Fixed-margin Sampling in Network Psychometrics.

Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. We argue that fixed-margin sampling cannot be used for this purpose, as it generates data under a particular null-hypothesis: a unidimensional factor model with interchangeable indicators (i.e., the Rasch model). We show this by discussing relevant psychometric literature and by performing simulation studies. Results indicate that while eLasso correctly estimated network models and estimated almost no edges due to chance, fixed-margin sampling performed poorly in classifying true effects as "interesting" (Steinley et al. 2017, p. 1004). Further simulation studies indicate that fixed-margin sampling offers a powerful method for highlighting local misfit from the Rasch model, but performs only moderately in identifying global departures from the Rasch model. We conclude that fixed-margin sampling is not up to the task of assessing if results from estimated Ising models or other multivariate psychometric models are due to chance.

Sex differences in depressive symptoms and their networks in a treatment-seeking population - a cross-sectional study.

BACKGROUND: The higher prevalence of major depressive disorder (MDD) in females relative to males is well-established. Some authors have posited this difference arises to divergent symptom profiles in females vs. males. However, empirical tests of this hypothesis have yielded equivocal results. Here, we investigate sex differences in MDD of individual symptoms and symptom networks in a treatment-seeking sample. METHODS: We assessed depressive symptoms using Hamilton Depression Rating Scale (HDRS-17) in 590 treatment-seeking adults with MDD (300 females). We examined group differences in symptom endorsement. We investigated symptom networks and estimated Gaussian Graphical Models. Finally, we compared the female and male networks using the Network Comparison Test. RESULTS: Females scored significantly higher in psychological anxiety (p <0.001; rB = -0.155), somatic anxiety (p = .001; rB = -0.150) and feelings of guilt (p = .002; rB = -0.139). Male and female patients did not differ in depression sum scores. There were no sex differences in network structure or global strength. LIMITATIONS: Our study was sufficiently powered to detect only medium sized symptom differences. The generalizability of our study is limited to clinical samples and further studies are needed to investigate if findings also translate to outpatient samples. CONCLUSION: Females reported elevated anxiety symptoms and guilt. Clinicians should assess these symptom differences and tailor treatment to individual symptom profiles. No differences between sexes emerged in MDD network structures, indicating that features may be more similar than previously assumed. Sex differences in psychopathological features of MDD are important for future research and personalized treatment.

The pain of grief: Exploring the concept of psychological pain and its relation to complicated grief, depression, and risk for suicide in bereaved adults.

OBJECTIVE: Emotional or psychological pain is a core symptom of complicated grief (CG), yet its correlates are largely unexamined among bereaved individuals. METHOD: Bereaved adults (N = 135) completed self-reports regarding psychological pain, CG, depression, and suicidality. We assessed correlations among these variables and tested whether psychological pain was elevated among individuals with CG and individuals with current or past suicidal thoughts and behaviors. Using logistic regression, we also assessed psychological pain, depression, and CG symptom severity as predictors of suicide risk. RESULTS: Psychological pain was strongly associated with both CG and depression severity and was elevated among subjects reporting current or past suicidality. CG and depression were not statistically significant predictors of suicidal ideation after accounting for the effects of psychological pain. CONCLUSIONS: Psychological pain is strongly associated with bereavement-related psychopathology and warrants further investigation in studies examining the nature and treatment of CG.

Systems all the way down: embracing complexity in mental health research.

In this editorial for the collection on complexity in mental health research, we introduce and summarize the inaugural contributions to this collection: a series of theoretical, methodological, and empirical papers that aim to chart a path forward for investigating mental health in all its complexity. A central theme emerges from these contributions: if we are to make genuine progress in explaining, predicting, and treating mental illness, we must study the systems from which psychopathology emerges. As the articles in this collection make clear, the systems that give rise to psychopathology encompass a host of components across biological, psychological, and social levels of analysis, intertwined in a web of complex interactions. The task of advancing our understanding of these systems will be a challenging one. Yet, this challenge presents a unique opportunity. From physics to ecology, there is a rapidly evolving body of interdisciplinary research dedicated to investigating complex systems. This work provides clear guidance for psychiatric research, opportunities for collaboration, and a set of tools and concepts from which we can draw in our efforts to understand mental health, helping us move toward our ultimate aim of improving the prevention and treatment of psychopathology.