Causality in Psychiatry: A Hybrid Symptom Network Construct Model

Mental health progress requires causal diagnostic nosology and scalable causal discovery

Nine hundred and seventy million individuals across the globe are estimated to carry the burden of a mental disorder. Limited progress has been achieved in alleviating this burden over decades of effort, compared to progress achieved for many other medical disorders. Progress on outcome improvement for all medical disorders, including mental disorders, requires research capable of discovering causality at sufficient scale and speed, and a diagnostic nosology capable of encoding the causal knowledge that is discovered. Accordingly, the field's guiding paradigm limits progress by maintaining: (a) a diagnostic nosology (DSM-5) with a profound lack of causality; (b) a misalignment between mental health etiologic research and nosology; (c) an over-reliance on clinical trials beyond their capabilities; and (d) a limited adoption of newer methods capable of discovering the complex etiology of mental disorders. We detail feasible directions forward, to achieve greater levels of progress on improving outcomes for mental disorders, by: (a) the discovery of knowledge on the complex etiology of mental disorders with application of Causal Data Science methods; and (b) the encoding of the etiological knowledge that is discovered within a causal diagnostic system for mental disorders.

Activation-Inhibition Coordination in Neuron, Brain, and Behavior Sequencing/Organization: Implications for Laterality and Lateralization

Activation-inhibition coordination is considered a dynamic process that functions as a common mechanism in the synchronization and functioning of neurons, brain, behavior, and their sequencing/organization, including over these different scales. The concept has broad applicability, for example, in applications to maladaptivity/atypicality. Young developed the hypothesis to help explain the efficacy of right-hand reaching to grasp in 1-month-olds, a study that implicated that the left hemisphere is specialized for activation-inhibition coordination. This underlying left-hemisphere function, noted to characterize the left hemisphere right from birth, can explain equally its language and fine motor skills, for example. The right hemisphere appears specialized for less complex inhibitory skills, such as outright damping/inhibition. The hypotheses related to inhibition and hemispheric specialization that appear in the literature typically refer to right hemisphere skills in these regards. The research to present also refers to excitation/inhibition balance/ratio in synaptic function, but not to coordination in the sense described here. Furthermore, it refers to the inhibitory function widely in neuronal networks. The paper presents a comprehensive literature review, framing the research in terms of the proposed concept. Further, the paper presents a broad model of activation-inhibition coordination that can help better understand neuron, brain, and behavior, generally, and left hemisphere specialization, specifically.

Psychotherapeutic Change Mechanisms and Causal Psychotherapy: Applications to Child Abuse and Trauma

The study of change mechanisms in psychotherapy needs to be integrated with the causality of behavior, which leads to the concept of causal psychotherapy. Causal psychotherapy is posited as a useful adjunct to standard, evidence based psychotherapies for child and youth victims of abuse and trauma. The article illustrates six processes that could be involved in causal psychotherapy in this context, from the distal to the proximal. They include the distal mechanism of activation-inhibition coordination. The most proximal one relates to executive function. The intermediate levels include ones related to co-regulation (e.g., self control), analysis-synthesis, objectivity-subjectivity, and psychological reserve, which is a new concept in the domain of psychological change mechanisms. Each of the variables can vary from high to low, with the low end being more problematic. Psychotherapy can aim to bring the patient toward adaptive levels. The literature review focuses on psychotherapeutic change mechanisms, and standard psychotherapies for child/youth abuse/trauma, especially trauma-focused cognitive behavior therapy (TF-CBT). Then, it considers causal aspects of child/youth abuse and trauma, including PTSD. The discussion relates causal therapy to the question of unifying psychology and psychotherapy under the rubric of causality as a core integrative mechanism.

A network analysis of social problem-solving and anxiety/depression in adolescents

Social problem-solving (SPS) involves the cognitive-behavioral processes through which an individual identifies and copes with everyday problems; it is considered to contribute to anxiety and depression. The Social Problem-Solving Inventory Revised is a popular tool measuring SPS problem orientations and problem-solving styles. Only a negative problem orientation (NPO) is considered strongly related to anxiety and depression. In the present study, we investigated the detailed connections among the five components of SPS and 14 anxiety-depression symptoms and specified the role of NPO and other components in the anxiety-depression network. We employed network analysis, constructed circular and multi-dimensional scaling (MDS) networks, and calculated the network centrality, bridge centrality, and stability of centrality indices. The results were as follows: (1) the MDS network showed a clustering of anxiety and depression symptoms, with NPO and avoidance style components from SPS being close to the anxiety-depression network (demonstrated by large bridge betweenness and bridge closeness); (2) the NPO and positive problem orientation from SPS were most influential on the whole network, though with an opposite effect; (3) strength was the most stable index [correlation stability (CS) coefficient = 0.516] among the centrality indices with case-dropping bootstraps. We also discussed this network from various perspectives and commented on the clinical implications and limitations of this study.

Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards

The Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition (DSM-IV) was revised based on a combination of a categorical and a dimensional approach such that in the DSM, Fifth Edition (DSM-5), depressive disorders have been separated as a distinctive disease entity from bipolar disorders, consistent with the deconstruction of Kraepelinian dualism. Additionally, the diagnostic thresholds of depressive disorders may be reduced due to the addition of "hopelessness" to the subjective descriptors of depressed mood and the removal of the "bereavement exclusion." Manic/hypomanic, psychotic, and anxious symptoms in major depressive disorder (MDD) and other depressive disorders are described using the transdiagnostic specifiers of "with mixed features," "with psychotic features," and "with anxious distress," respectively. Additionally, due to the polythetic and operational characteristics of the DSM-5 diagnostic criteria, the heterogeneity of MDD is inevitable. Thus, 227 different symptom combinations fulfill the DSM-5 diagnostic criteria for MDD. This heterogeneity of MDD is criticized in view of the Wittgensteinian analogy of language game. Depression subtypes determined by disturbances in monoamine levels and the severity of the disease have been identified in the literature. According to a review of the Gottesman and Gould criteria, neuroticism, morning cortisol, cortisol awakening response, asymmetry in frontal cortical activity on electroencephalography (EEG), and probabilistic reward learning, among other variables, are evidenced as endophenotypes for depressive disorders. Network analysis has been proposed as a potential method to compliment the limitations of current diagnostic criteria and to explore the pathways between depressive symptoms, as well as to identify novel and interesting relationships between depressive symptoms. Based on the literature on network analysis in this field, no differences in the centrality index of the DSM and non-DSM symptoms were repeatedly present among patients with MDD. Furthermore, MDD and other depressive syndromes include two of the Research Domain Criteria (RDoC), including the Loss construct within the Negative Valence Systems domains and various Reward constructs within the Positive Valence Systems domain.

Network Analysis of the Symptoms of Depressive Disorders Over the Course of Therapy: Changes in Centrality Measures

OBJECTIVE

Network analysis can be used in terms of a novel psychopathological approach for depressive syndrome. We aimed to estimate the successive network structures of depressive symptoms in patients with depressive disorder using data from the Clinical Research Center for Depression study.

METHODS

We enrolled 1,152 South Korean adult patients with depressive disorders who were beginning treatment for first-onset or recurrent depressive episodes. We examined the network structure of the severities of the items on the Hamilton Depression Rating Scale (HAMD) at baseline and at weeks 2, 12, 25, and 52. The node strength centrality of all the HAMD items at baseline and at week 2, 12, 25, and 52 in terms of network analysis.

RESULTS

In the severity networks, the anxiety (psychic) item was the most centrally situated in the initial period (baseline and week 2), while loss of weight was the most centrally situated item in the later period (weeks 25 and 52). In addition, the number of strong edges (i.e., edges representing strong correlations) increased in the late period compared to the initial period.

CONCLUSION

Our findings support a period-specific and symptom-focused therapeutic approach that can provide complementary information to the unidimensional total HAMD score.

The Centrality of Depression and Anxiety Symptoms in Major Depressive Disorder Determined Using a Network Analysis

BACKGROUND

Comorbid anxiety symptoms are highly prevalent and closely linked with poorer treatment outcomes, chronicity, and hospitalization in major depressive disorder (MDD). Our study aimed to estimate the network of depression and anxiety symptoms that was developed based on a sample of MDD patients.

METHODS

We constructed a network of the 21 Beck Depression Inventory (BDI) symptoms and 21 Beck Anxiety Inventory (BAI) symptoms in 223 patients with MDD who were beginning psychiatric treatment. In addition, each of the depression and anxiety symptoms was considered to be an ordered categorical variable ranging in value from 0 to 3.

RESULTS

The three depression symptoms including loss of energy, loss of interest, and worthlessness and the seven anxiety symptoms including faintness or lightheadedness, feeling of choking, feeling scared, fear of the worst happening, nervousness, inability to relax, and feeling shaky were identified as the ten most central nodes within a network of depression and anxiety symptoms. The inter-connection between irritability and nervousness was a strong trans-diagnostic edge within the network of depression and anxiety symptoms.

LIMITATIONS

Because our study was designed in a cross-sectional manner, the networks were estimated undirectionally.

CONCLUSIONS

Our findings show that depression symptoms are not more central than anxiety symptoms within an estimated network structure of symptoms in patients with MDD. Moreover, the inter-connection between irritability and nervousness may suggests a probable trans-diagnostic association in MDD symptomatology.

An exploration of the DSM-5 posttraumatic stress disorder symptom latent variable network

BACKGROUND

Both the latent variable model and the network model have been widely used to conceptualize mental disorders. However, it has been pointed out that there is no clear dichotomy between the two models, and a combination of these two model could enable a better understanding of psychopathology. The recently proposed latent network model (LNM) has provided a statistical framework to enable this combination. Evidence has shown that posttraumatic stress disorder (PTSD) could be a suitable candidate disorder to study the combined model. In the current study, we initiated the first investigation of the latent network of PTSD symptoms.

METHODS

The latent network of DSM-5 PTSD symptoms was estimated in 1196 adult survivors of China's 2008 Wenchuan earthquake. Validation testing of the latent network was conducted in a replication sample of children and adolescent who experienced various trauma types. PTSD symptoms were measured by the PTSD Checklist for DSM-5 (PCL-5). The latent network was estimated using the seven-factor hybrid model of DSM-5 PTSD symptoms, analysed using the R package lvnet.

RESULTS

The latent network model demonstrated good fit in both samples. A strong weighted edge between the intrusion and avoidance dimensions was identified (regularized partial correlation = 0.75). The externalizing behaviour dimension demonstrated the highest centrality in the latent network.

CONCLUSIONS

This study is the first to investigate the latent network of DSM-5 PTSD symptoms. Results suggest that both latent symptom dimension and associations between the dimensions should be considered in future PTSD studies and clinical practices.

Network analysis of the depressive symptom profiles in Asian patients with depressive disorders: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD)

AIM

We aimed to estimate the network structures of depressive symptoms using network analysis and evaluated the geographic regional differences in theses network structures among Asian patients with depressive disorders.

METHODS

Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD), the network of the ICD-10 diagnostic criteria for depressive episode was estimated from 1174 Asian patients with depressive disorders. The node strength centrality of all ICD-10 diagnostic criteria for a depressive episode was estimated using a community-detection algorithm. In addition, networks of depressive symptoms were estimated separately among East Asian patients and South or Southeast Asian patients. Moreover, networks were estimated separately among Asian patients from high-income countries and those from middle-income countries.

RESULTS

Persistent sadness, fatigue, and loss of interest were the most centrally situated within the network of depressive symptoms in Asian patients with depressive disorders overall. A community-detection algorithm estimated that when excluding psychomotor disturbance as an outlier, the other nine symptoms formed the largest clinically meaningful cluster. Geographic and economic variations in networks of depressive symptoms were evaluated.

CONCLUSION

Our findings demonstrated that the typical symptoms of the ICD-10 diagnostic criteria for depressive episode are the most centrally situated within the network of depressive symptoms. Furthermore, our findings suggested that cultural influences related to geographic and economic distributions of participants could influence the estimated depressive symptom network in Asian patients with depressive disorders.

Mediating role of cognitive biases, resilience and depressive symptoms in the relationship between childhood trauma and psychotic-like experiences in young adults

OBJECTIVES

The present study aimed to test a hypothetical model where causally linked and ordered cognitive biases, resilience and depressive symptoms serve as mediators of the relationship between early traumatic life events and psychotic-like experiences (PLEs) in the general population of young adults.

METHODS

Two thousand six hundred and fourteen people (1673 females) took part in the online survey. Participants completed self-report questionnaires measuring exposure to early traumatic life events, PLEs, cognitive biases, resilience and depressive symptoms. Correlation and multiple mediation analyses were performed.

RESULTS

All three mediators turned out to be significantly correlated with early trauma, PLEs and with each other. Mediational analysis demonstrated that hypothesized model of causally linked mediators was significant (P ≤ .001) and accounted for 33% (P < .001) of the explained variance in PLEs in comparison to 11% (P ≤ .001) without mediators.

CONCLUSIONS

First, our results provide evidence for significant associations between early traumatic life events, cognitive biases, depressive symptoms, psychological resilience and PLEs. Second, they indicate significant indirect effects of early trauma exposure on PLEs through a path consisted of cognitive biases, psychological resilience and depressive symptoms that suggest a possible importance of interventions bolstering resilience in young people in order to minimize the severity of depressive and psychotic psychopathology.

The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research

The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.

The interplay between childhood trauma, cognitive biases, psychotic-like experiences and depression and their additive impact on predicting lifetime suicidal behavior in young adults

BACKGROUND

Childhood trauma, psychosis risk, cognition, and depression have been identified as important risk markers for suicidal behaviors. However, little is known about the interplay between these distal and proximal markers in influencing the risk of suicide. We aim to investigate the interplay between childhood trauma, cognitive biases, psychotic-like experiences (PLEs) and depression in predicting suicidal behaviors in a non-clinical sample of young adults.

METHODS

In total, 3495 young adults were recruited to an online computer-assisted web interview. We used the Prodromal Questionnaire to assess PLEs. Childhood trauma was assessed with the Traumatic Experience Checklist (three items) and Childhood Experience of Care and Abuse Questionnaire (CECA.Q, three items). Cognitive biases were assessed with a short version of the Davos Assessment of Cognitive Biases Scale. Suicidality, psychiatric diagnoses, and substance use were screened with a self-report questionnaire.

RESULTS

Childhood trauma, as well as PLEs, was associated with an approximately five-fold increased risk of suicidal thoughts and plans as well as suicide attempts. Participants with depression were six times more likely to endorse suicidal behaviors. Path analysis revealed that PLEs, depression and cognitive biases are significant mediators of the relationship between trauma and suicidal behaviors. The model explained 44.6% of the variance in lifetime suicidality.

CONCLUSIONS

Cognitive biases, PLEs, and depression partially mediate the relationship between childhood trauma and suicidal behaviors. The interplay between distal and proximal markers should be recognized and become part of clinical screening and therapeutic strategies for preventing risk of suicidality.

Anxiety disorder symptoms at age 10 predict eating disorder symptoms and diagnoses in adolescence

BACKGROUND

Cross-sectional associations between anxiety disorders and eating disorders (EDs) have been well documented; however, limited research has examined whether symptoms of anxiety disorders are prospectively associated with EDs. Identifying these longitudinal associations can aid in discerning relationships among eating and anxiety disorders and point toward a mechanistic understanding of developmental psychopathology. This study investigated the prospective associations between parent-reported anxiety in mid-childhood (age 10) and child-reported ED behaviors and disorders in adolescence (at ages 14 and 16 years) in a population-based sample.

METHODS

Participants were individuals enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC), a population-based, prospective study of women and their children; 7,767 children whose parents provided data at age 10 were included in current analyses. An exploratory factor analysis identified latent anxiety factors at age 10, followed by a path analysis that evaluated associations between these factors and eating disorder symptoms and cognitions at age 14.

RESULTS

Parent-reported anxiety symptoms at age 10 yielded 5 factors: obsessive-compulsive disorder (OCD) symptoms related to symmetry and checking (Factor 1); OCD symptoms associated with aversion to dirt and germs (Factor 2); physical anxiety symptoms (Factor 3); worries (Factor 4); and social phobia symptoms (Factor 5). Factors 3 and 4 showed the most consistent, positive associations with a range of ED symptoms at age 14. Factor 3 predicted diagnosis of bulimia nervosa by age 16 (OR = 1.11, p = .007), whereas Factor 4 predicted diagnoses of anorexia nervosa (OR = 1.10, p = .01) and disordered eating by age 16 (OR = 1.08, p = .001).

CONCLUSIONS

Results indicate that symptoms of generalized anxiety in middle childhood may predict adolescent-onset ED symptoms and ED diagnoses.

Understanding the Multidimensional Nature of Student Engagement During the First Year of Higher Education

In the description of the complex relationship between individual students and their education context, as well as understanding of questions related to progression, retention or dropouts in higher education, student engagement is considered the primary construct. In particular, the significance of the first year of higher education in terms of engagement is decisive. We aim at developing a multidimensional conceptualization of engagement and utilized network analysis. Data were collected as part of the annual Student Barometer survey in Finland during the 2012-2013 academic year, and we gathered a nationally representative sample (n = 2422) of first-year students in different disciplines at 13 Finnish universities. Network analysis confirmed the multidimensional process model of engagement and its six dimensions. The central dimensions of engagement are identity and sense of belonging, which develop in the interplay between individual and collective dimensions as a long-term process. Additional network analyses with covariates identified positive and negative factors that affect engagement. The study adds new perspectives to existing knowledge of engagement. It is important to understand the process-like nature of engagement and make visible factors affecting the process. Based on these findings, we provide novel practical recommendations for interventions for university students who struggle with engagement during their first year.

Cognitive mechanisms of alexithymia in schizophrenia: Investigating the role of basic neurocognitive functioning and cognitive biases

Alexithymia is an important but poorly understood emotional deficit in schizophrenia. We aimed at investigating the role of basic cognitive functions, cognitive biases, and symptom severity in alexithymia among patients with schizophrenia. Sixty patients (31 females) with schizophrenia were assessed with standardized clinical interviews for symptom severity. Cognitive functioning was assessed with neuropsychological tests. A self-report scale (Davos Assessment of Cognitive Biases, DACOBS), as well as two experimental tasks assessing jumping to conclusions (the Fish task) and source monitoring (Action memory task), were used to investigate cognitive biases. Alexithymia was assessed with the Toronto Alexithymia Scale (TAS-20). Alexithymia was related to the severity of hallucinations but not delusions. Patients with a lifetime history of more psychotic symptoms had higher alexithymia. Alexithymia has broad relationships with different cognitive biases, especially in the self-reported measure. These relationships were not affected by neurocognition and symtpoms severity. In particular, difficulties in identification of feelings were related to various cognitive biases. Dysfunctional information processing can thus be considered as potential psychological correlates of alexithymia. The theoretical and clinical implications of our findings are discussed.

The mediating role of borderline personality features in the relationship between childhood trauma and psychotic-like experiences in a sample of help-seeking non-psychotic adolescents and young adults

Objective:

Psychotic-like experiences (PLEs) often occur across different non-psychotic disorders in adolescent and young adult population and are related to early trauma. However, the mechanisms of how exposure to early trauma shapes the risk of PLEs are unclear. In our study, we investigated whether borderline personality features and further non-psychotic symptoms, i.e. factors related to both PLEs and childhood trauma, may mediate the relationship between childhood trauma and PLEs.

Methods:

Two hundred inpatients aged 16–21 years who were treated due to non-psychotic disorders were included. PLEs were assessed with the Prodromal Questionnaire (PQ-16). Childhood Trauma was assessed with the Adverse Childhood Experience Questionnaire (ACE). Borderline personality features were assessed by using the Borderline-Symptom Checklist (BSL-23). Presence and frequency of depressive symptoms and anxiety were assessed by Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder Questionnaire (GAD-7).

Table 1

Results:

A significant relationship between childhood trauma (ACE total score) and PLEs was found (ß = 0.30, 95% CI 0.247--0.659). In particular, emotional neglect (r = 0.298, p < 0.001) and sexual abuse (r = 0.264, p < 0.001) were significantly associated with PLEs. Borderline personality features fully mediated the relationship of childhood trauma and PLEs (ß = 0.12, 95% CI: -0.019--0.370). Anxiety and Depression showed a significant, but partial mediation of the relationship.

Conclusion:

Borderline personality features seem to be an important mediator of the relationship between childhood trauma and PLEs in adolescent patients with different non-psychotic psychiatric disorders. Theoretical and clinical implications are discussed.

A Complex Network Perspective on Clinical Science

Contemporary classification systems for mental disorders assume that abnormal behaviors are expressions of latent disease entities. An alternative to the latent disease model is the complex network approach. Instead of assuming that symptoms arise from an underlying disease entity, the complex network approach holds that disorders exist as systems of interrelated elements of a network. This approach also provides a framework for the understanding of therapeutic change. Depending on the structure of the network, change can occur abruptly once the network reaches a critical threshold (the tipping point). Homogeneous and highly connected networks often recover more slowly from local perturbations when the network approaches the tipping point, potentially making it possible to predict treatment change, relapse, and recovery. In this article, we discuss the complex network approach as an alternative to the latent disease model and its implications for classification, therapy, relapse, and recovery.

Evidence that psychopathology symptom networks have limited replicability

Network analysis is quickly gaining popularity in psychopathology research as a method that aims to reveal causal relationships among individual symptoms. To date, 4 main types of psychopathology networks have been proposed: (a) association networks, (b) regularized concentration networks, (c) relative importance networks, and (d) directed acyclic graphs. The authors examined the replicability of these analyses based on symptoms of major depression and generalized anxiety between and within 2 highly similar epidemiological samples (i.e., the National Comorbidity Survey-Replication [n = 9282] and the National Survey of Mental Health and Wellbeing [n = 8841]). Although association networks were stable, the 3 other types of network analysis (i.e., the conditional independence networks) had poor replicability between and within methods and samples. The detailed aspects of the models-such as the estimation of specific edges and the centrality of individual nodes-were particularly unstable. For example, 44% of the symptoms were estimated as the "most influential" on at least 1 centrality index across the 6 conditional independence networks in the full samples, and only 13-21% of the edges were consistently estimated across these networks. One of the likely reasons for the instability of the networks is the predominance of measurement error in the assessment of individual symptoms. The authors discuss the implications of these findings for the growing field of psychopathology network research, and conclude that novel results originating from psychopathology networks should be held to higher standards of evidence before they are ready for dissemination or implementation in the field. (PsycINFO Database Record

PTSD in Court II: Risk factors, endophenotypes, and biological underpinnings in PTSD

The second article in the series of three for the journal on "PTSD in Court" especially concerns the biological bases that have been found to be associated with PTSD (posttraumatic stress disorder). The cohering concepts in this section relate to risk factors; candidate genes; polygenetics; "gene×environment" interactions; epigenetics; endophenotypes; biomarkers; and connective networks both structurally and functionally (in terms of intrinsic connectivity networks, ICNs, including the DMN, SN, and CEN; that is, default mode, salience, and central executive networks, respectively). Risk factors related to PTSD include pre-event, event- and post-event ones. Some of the genes related to PTSD include: FKBP5, 5-HTTLPR, and COMT (which are, respectively, FK506-binding protein 5 gene, serotonin-transporter linked polymorphic region, catechol-O-methyl-transferase). These genetic findings give an estimate of 30% for the genetic influence on PTSD. The typical brain regions involved in PTSD include the amygdala, hippocampus, and prefrontal cortex, along with the insula. Causal models of behavior are multifactorial and biopsychosocial, and these types of models apply to PTSD, as well. The paper presents a multilevel systems model of psychopathology, including PTSD, which involves three levels - a top-down psychological construct one, a bottom-up symptom connection one, and a middle one involving symptom appraisal. Legally, causality refers to the event at issue needing to meet the bar of being materially contributory to the outcome. Finally, this section of the article reviews empirically-supported therapies for PTSD and the dangers of not receiving treatment for it.

Forensic implications of changes in DSM-5 criteria for responses to trauma and stress

DSM-5 significantly changed the diagnostic criteria for Posttraumatic Stress Disorder (PTSD) relative to DSM-IV/DSM-IV-TR. These changes do not alter its basic approach to diagnosing mental disorders, which treats each disorder as a separate category. This article analyzes the strengths and weaknesses of the categorical approach, and reviews empirical evidence regarding the impact of changes within it on the ease or difficulty of receiving the PTSD diagnosis. It especially analyzes the impact of newly included symptoms that are meant to identify cases in which trauma exposure was associated with changes in more serious PTSD cases, known as Complex PTSD (C-PTSD). It proposes some effects that the changes could have on psychological injury claims. Many changes could support plaintiffs' claims while others could support defense claims. Some changes could support either. Overall, DSM-5 PTSD diagnosis is more responsive to individual differences in symptom presentations and appears able to diagnose some C-PTSD cases. The thesis throughout the article is that PTSD diagnostic accuracy could be improved further, especially for C-PTSD cases, by complementing its current exclusive reliance on behavioral symptoms that are characteristic of victims in general with assessment of the meaning that the symptoms have for individual victims. The article proposes some principles to guide interpretation of the individualized meaning of victims' symptoms, which help make the reasoning behind the interpretations explicit.