Changes in positive and negative affect in psychotherapy for depression and anxiety.

OBJECTIVE: Positive and negative affect play critical roles in depression and anxiety treatment, but the dynamic processes of how affect changes over treatment in relation to changes in symptoms is unclear. The study goal was to examine relationships among changes in positive and negative affect with changes in depression and anxiety symptoms. METHOD: This secondary analysis used a combined sample (N = 196) of two trials (Craske et al., 2019, 2023) comparing positive affect treatment (PAT) to negative affect treatment. Longitudinal cross-lag panel models explored whether changes in positive and negative affect (Positive and Negative Affect Schedule; Watson et al., 1988) predicted subsequent changes in depression and anxiety symptoms (Depression Anxiety Stress Scales; Lovibond & Lovibond, 1995), whether symptoms predicted subsequent changes in affect, and whether treatment condition moderated these relationships. RESULTS: Increases in positive affect predicted subsequent decreases in depression and anxiety symptoms, regardless of treatment condition. Symptoms did not reciprocally predict changes in positive affect. For individuals in PAT, decreases in negative affect predicted subsequent decreases in symptoms. Moreover, decreases in symptoms predicted subsequent decreases in negative affect, regardless of treatment condition. CONCLUSIONS: Results did not support a reciprocal relationship between positive affect and symptoms of depression and anxiety since positive affect predicted depression and anxiety symptoms but not vice versa. Results supported a reciprocal relationship between negative affect and symptoms of depression and anxiety since negative affect predicted depression and anxiety symptoms in PAT, and depression and anxiety symptoms predicted negative affect in both treatment conditions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effects of positive and negative affect inductions on interpretive and response bias.

Affective states and interpretations of ambiguous stimuli are inherently related constructs, although effects of induced affective states on interpretive and response biases have not been comprehensively explored. The present study examined the relationship between induced affective states and interpretive and response bias in a sample of 189 undergraduates. Participants completed an online study in which they were randomized into one of two mood induction conditions and subsequently completed an interpretive bias task. Results demonstrated significant condition differences in affect after the mood induction; the positive induction condition demonstrated significantly more positive mood and the negative condition demonstrated more negative mood. A significant difference between conditions emerged with respect to positive interpretive bias for non-social scenarios, with the positive mood induction condition demonstrating more positive interpretive bias to non-social situations than the negative induction condition (p = .04). The negative induction condition demonstrated significantly greater negative response bias for social scenarios (p = .03) and, unexpectedly, a significantly higher positive response bias for non-social scenarios (p = .05). Findings offer some support for the notion that inducing positive affect may promote more positive interpretations of ambiguous scenarios.

The Role of Positive and Negative Aspects of Life Events in Depressive and Anxiety Symptoms.

Negative or stressful life events are robust risk factors for depression and anxiety. Less attention has been paid to positive aspects of events and whether positivity buffers the impact of negative aspects of events. The present study examined positivity and negativity of interpersonal and non-interpersonal episodic life events in predicting anxiety and depressive symptoms in a sample of 373 young adults. Regressions tested main and interactive effects of positivity and negativity ratings of events in predicting symptom factors (Fears, Anhedonia-Apprehension (AA), General Distress (GD)) relevant to anxiety and depression. A significant interaction demonstrated that positivity protected against high levels of negativity of non-interpersonal events in predicting GD. A main effect of interpersonal negativity predicting higher AA was observed. Results for Fears were non-significant. Findings suggest that positivity of life events may buffer against negativity in predicting symptoms shared between anxiety and depression.

Evaluating training needs in clinical psychology doctoral programs.

OBJECTIVE: Advances in clinical psychology must be accompanied by advances in training. This study assessed training content, quality, and needs during clinical psychology doctoral programs among current or past doctoral students. METHODS: Current or past clinical psychology doctoral students (N = 343) completed an anonymous survey assessing training experiences and needs. A descriptive-focused exploratory factor analysis (EFA) also examined whether common subgroups of academic interests emerged. RESULTS: Most participants reported that they sought training beyond required coursework, primarily in clinical training, cultural competency, and professional development, and reported having taken one or more unhelpful course, including discipline-specific knowledge requirements. Descriptive results from the EFA demonstrated common training areas of interest: diversity topics, biological sciences, clinical practice, and research methods. DISCUSSION: This study demonstrates that trainees and early career psychologists are aware of their nuanced and in some cases, unmet training needs. CONCLUSION: This work foregrounds the need to adapt extant training opportunities to support the next generation of clinical psychologists.

Longitudinal associations among dimensional symptoms of depression and anxiety and first onset suicidal ideation in adolescents.

INTRODUCTION: Depression and anxiety are implicated in suicide risk, but the contributionof specific symptom dimensions within these disorders is not well understood. The present study examined longitudinal associations of transdiagnostic symptoms (General Distress[GD]) and unique symptom dimensions (Anhedonia-Apprehension [AA], Fears, and Narrow Depression [ND]) of depression and anxiety and suicidal ideation (SI). METHODS: Data from 551 adolescents oversampled on high neuroticism were examined in a series of discrete-time survival analyses to predict first SI onset over an 8-year period. RESULTS: Results indicate that GD, AA, and ND were independent predictors of increased likelihood of SI onset and remained significant when controlling for effects of fears. Furthermore, AA and GD remained significant when controlling for one another. ND effects reduced by 24% when adjusting for AA and 74% when adjusting for GD. Fears did not significantly predict SI onset. CONCLUSION: Results suggest that broad levels of distress across depression and anxiety, deficits in positive affect, and elevated negative affect specific to depression increase the likelihood of suicidal thoughts. As such, attention to broader distress and a lack of pleasure, interest, and motivation-potentially more so than negative affect characterizing depression-are particularly important for addressing suicide risk in adolescents.

Early-life adversity and risk for depression and anxiety: The role of interpersonal support.

Early-life adversity is a major risk factor for psychopathology, but not all who experience adversity develop psychopathology. The current study evaluated whether the links between child and adolescent adversity and depression and anxiety were described by general benefits and/or buffering effects of interpersonal support. Data from 456 adolescents oversampled on neuroticism over a 5-year period were examined in a series of discrete-time survival analyses to predict subsequent disorder onsets. Models examined linear, quadratic, and interactive effects of interpersonal support over time, as measured by chronic interpersonal stress interview ratings. Results did not support buffering effects of interpersonal support against either child or adolescent adversity in predicting depression or anxiety. However, there was support for the general benefits model of interpersonal support as evidenced by follow-up analyses of significant quadratic effects of interpersonal support, demonstrating that higher interpersonal support led to decreased likelihood of depression and anxiety onsets. Secondary analyses demonstrated that effects of interpersonal support remained after accounting for baseline depression and anxiety diagnoses. Further, quadratic effects were driven by social domains as opposed to familial domains when considering child adversity. Implications for interventions and randomized controlled prevention trials regarding interpersonal relationships are discussed.

Examining the dimensionality of anxiety and depression: A latent profile approach to modeling transdiagnostic features.

Depression and anxiety are highly prevalent psychological disorders; our understanding of these conditions remains limited. Efforts to explain anxiety and depression have been constrained in part by binary classification systems. Dimensional approaches to understanding psychopathology may be more effective. The present study used latent profile analysis (LPA) to assess whether unique subgroups exist within a tri-level model of anxiety and depression. Participants (N=627) completed self-report questionnaires from which tri-level model factors were derived. LPA was conducted on those factors. A 4-profile model offered optimal fit to the data at baseline. This model was replicated at a second time point. Models derived included profiles labelled 'Mixed Fears,' 'Anxious Arousal,' 'Low Mood/Anhedonia,' and 'Sub-Clinical.' Profiles were validated at Time 1 using diagnostic status and clinical severity ratings associated with mood and anxiety presentations. Profiles demonstrated flexibility in accommodating breadth in clinical presentations and common comorbidities. Latent variable models may offer more ecologically valid approaches to understanding psychopathology.

Fear-potentiated startle predicts longitudinal change in transdiagnostic symptom dimensions of anxiety and depression.

BACKGROUND: Elevated defensive responding, through startle reflex (SR) and skin conductance response (SCR), may contribute to onset and maintenance of depression and anxiety. Most work examining SR and SCR has predicted psychiatric diagnoses. There is a paucity of research examining links between SR or SCR and dimensional measures of psychopathology. METHODS: We used latent growth curve modeling to predict longitudinal change in three symptom factors (i.e., General Distress, Fears, Anhedonia-Apprehension) from SR and SCR measured during a fear-potentiated startle paradigm among adolescents oversampled for neuroticism (N = 129). RESULTS: Elevated SCR in danger phases before and after an unpleasant muscle contraction predicted increasing Fears over time. Elevated SR in safe phases post-contraction also predicted increasing Fears over time. Attenuated SR in safe phases post-contraction predicted elevated General Distress longitudinally. Attenuated SCR pre-contraction in danger phases predicted elevated Anhedonia-Apprehension over time. LIMITATIONS: Our non-clinical sample may limit generalizability of results. Additionally, we did not assess change in SR and SCR over time. CONCLUSIONS: The present study demonstrates that SR and SCR during a fear-potentiated startle paradigm predict longitudinal change in dimensional anxiety and depression symptom factors and relatedly, that SR and SCR may represent risk factors for the exacerbation of symptomatology.

Impact of the COVID-19 Pandemic on Mental Health among 157,213 Americans.

BACKGROUND: The coronavirus (COVID-19) pandemic presents an unprecedented crisis with potential negative mental health impacts. METHODS: This study used data collected via Youper, a mental health app, from February through July 2020. Youper users (N = 157,213) in the United States self-reported positive and negative emotions and anxiety and depression symptoms during the pandemic. We examined emotions and symptoms before (pre), during (acute), and after (sustained) COVID-related stay-at-home orders. RESULTS: For changes in frequency of reported acute emotions, from the pre to acute periods, anxiety increased while tiredness, calmness, happiness, and optimism decreased. From the acute to sustained periods, sadness, depression, and gratitude increased. Anxiety, stress, and tiredness decreased. Between the pre and sustained periods, sadness and depression increased, as did happiness and calmness. Anxiety and stress decreased. Among symptom measures, anxiety increased initially, from the pre to the acute periods, but later returned to baseline. LIMITATIONS: The study sample was primarily comprised of young people and women. The app does not collect racial or ethnicity data. These factors may limit generalizability. Sample size was also not consistent for all data collected. CONCLUSIONS: The present study suggests that although there were initial negative impacts on emotions and mental health symptoms in the first few weeks, many Americans demonstrated resilience over the following months. The impact of the pandemic on mental health may not be as severe as predicted, although future work is necessary to understand longitudinal effects as the pandemic continues.

Neurobiological research with suicidal participants: A framework for investigators.

OBJECTIVE: Suicide is a public health threat. Nevertheless, the research literature on actively suicidal participants is relatively sparse, in part because they are often excluded from medical, psychiatric, and psychological research for a host of logistical, ethical, and safety concerns. These obstacles to research participation and enrollment may contribute to our lack of understanding regarding the neurobiology of the suicidal crisis as well as to the dearth of evidence concerning both risk prediction and treatment. METHOD: In order to directly investigate neurobiological markers of acute suicide risk, the National Institute of Mental Health Intramural Research Program (NIMH-IRP) implemented the Neurobiology of Suicide protocol. In this protocol, actively suicidal individuals consent to research for both neurobiological assessment and potential rapid-acting interventions. RESULTS AND CONCLUSIONS: This article reviews lessons learned from implementing this protocol in the hopes of assisting future research on the neurobiology of suicide. Areas of specific discussion include the Failure Modes and Effects Analysis (FMEA), recruitment and informed consent, participant monitoring, and the safety of the physical environment.

Functional Imaging of the Implicit Association of the Self With Life and Death.

OBJECTIVE: A critical need exists to identify objective markers of suicide ideation. One potential suicide risk marker is the Suicide Implicit Association Task (S-IAT), a behavioral task that uses differential reaction times to compare the implicit association between the self and death to the implicit association between the self and life. Individuals with a stronger association between the self and death on the S-IAT are more likely to attempt suicide in the future. To better understand the neural underpinnings of the implicit association between self and either life or death, a functional magnetic resonance imaging (fMRI) version of the S-IAT was adapted and piloted in healthy volunteers. METHOD: An fMRI version of the S-IAT was administered to 28 healthy volunteers (ages 18-65, 14F/14M). RESULTS: Behavioral results were comparable to those seen in non-scanner versions of the task. The task was associated with patterns of neural activation in areas relevant to emotional processing, specifically the insula and right ventrolateral prefrontal cortex. CONCLUSIONS: Performance on the S-IAT fMRI task may reflect scores obtained outside of the scanner. In future evaluations, this task could help assess whether individuals at increased risk of suicide display a different pattern of neural activation in response to self/death and self/life stimuli.

Characterizing the course of suicidal ideation response to ketamine.

BACKGROUND: No pharmacological treatments exist for active suicidal ideation (SI), but the glutamatergic modulator ketamine elicits rapid changes in SI. We developed data-driven subgroups of SI trajectories after ketamine administration, then evaluated clinical, demographic, and neurobiological factors that might predict SI response to ketamine. METHODS: Data were pooled from five clinical ketamine trials. Treatment-resistant inpatients (n = 128) with DSM-IV-TR-diagnosed major depressive disorder (MDD) or bipolar depression received one subanesthetic (0.5 mg/kg) ketamine infusion over 40 min. Composite SI variable scores were analyzed using growth mixture modeling to generate SI response classes, and class membership predictors were evaluated using multinomial logistic regressions. Putative predictors included demographic variables and various peripheral plasma markers. RESULTS: The best-fitting growth mixture model comprised three classes: Non-Responders (29%), Responders (44%), and Remitters (27%). For Responders and Remitters, maximal improvements were achieved by Day 1. Improvements in SI occurred independently of improvements in a composite Depressed Mood variable for Responders, and partially independently for Remitters. Indicators of chronic SI and self-injury were associated with belonging to the Non-Responder group. Higher levels of baseline plasma interleukin-5 (IL-5) were linked to Remitters rather than Responders. LIMITATIONS: Subjects were not selected for active suicidal thoughts; findings only extend to Day 3; and plasma, rather than CSF, markers were used. CONCLUSION: The results underscore the heterogeneity of SI response to ketamine and its potential independence from changes in Depressed Mood. Individuals reporting symptoms suggesting a longstanding history of chronic SI were less likely to respond or remit post-ketamine.

Glutamatergic Signaling Drives Ketamine-Mediated Response in Depression: Evidence from Dynamic Causal Modeling.

BACKGROUND: The glutamatergic modulator ketamine has rapid antidepressant effects in individuals with major depressive disorder and bipolar depression. Thus, modulating glutamatergic transmission may be critical to effectively treating depression, though the mechanisms by which this occurs are not fully understood. METHODS: This double-blind, crossover, placebo-controlled study analyzed data from 18 drug-free major depressive disorder subjects and 18 heathy controls who received a single i.v. infusion of ketamine hydrochloride (0.5 mg/kg) as well as an i.v. saline placebo. Magnetoencephalographic recordings were collected prior to the first infusion and 6 to 9 hours after both ketamine and placebo infusions. During scanning, participants passively received tactile stimulation to the right index finger. Antidepressant response was assessed across timepoints using the Montgomery-Asberg Depression Rating Scale. Dynamic causal modeling was used to measure changes in α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA)- and N-methyl-D-aspartate (NMDA)-mediated connectivity estimates in major depressive disorder subjects and controls using a simple model of somatosensory evoked responses. RESULTS: Both major depressive disorder and healthy subjects showed ketamine-mediated NMDA-blockade sensitization, with major depressive disorder subjects showing enhanced NMDA connectivity estimates in backward connections and controls showing enhanced NMDA connectivity estimates in forward connections in our model. Within our major depressive disorder subject group, ketamine efficacy, as measured by improved mood ratings, correlated with reduced NMDA and AMPA connectivity estimates in discrete extrinsic connections within the somatosensory cortical network. CONCLUSIONS: These findings suggest that AMPA- and NMDA-mediated glutamatergic signaling play a key role in antidepressant response to ketamine and, further, that dynamic causal modeling is a powerful tool for modeling AMPA- and NMDA-mediated connectivity in vivo. CLINICALTRIALS.GOV: NCT#00088699.

Parsing the heterogeneity of depression: An exploratory factor analysis across commonly used depression rating scales.

BACKGROUND: Due to the heterogeneity of depressive symptoms-which can include depressed mood, anhedonia, negative cognitive biases, and altered activity levels-researchers often use a combination of depression rating scales to assess symptoms. This study sought to identify unidimensional constructs measured across rating scales for depression and to evaluate these constructs across clinical trials of a rapid-acting antidepressant (ketamine). METHODS: Exploratory factor analysis (EFA) was conducted on baseline ratings from the Beck Depression Inventory (BDI), the Hamilton Depression Rating Scale (HAM-D), the Montgomery-Asberg Depression Rating Scale (MADRS), and the Snaith-Hamilton Pleasure Rating Scale (SHAPS). Inpatients with major depressive disorder (n = 76) or bipolar depression (n = 43) were participating in clinical ketamine trials. The trajectories of the resulting unidimensional scores were evaluated in 41 subjects with bipolar depression who participated in clinical ketamine trials. RESULTS: The best solution, which exhibited excellent fit to the data, comprised eight factors: Depressed Mood, Tension, Negative Cognition, Impaired Sleep, Suicidal Thoughts, Reduced Appetite, Anhedonia, and Amotivation. Various response patterns were observed across the clinical trial data, both in treatment effect (ketamine versus placebo) and in degree of placebo response, suggesting that use of these unidimensional constructs may reveal patterns not observed with traditional scoring of individual instruments. LIMITATIONS: Limitations include: 1) small sample (and related inability to confirm measurement invariance); 2) absence of an independent sample for confirmation of factor structure; and 3) the treatment-resistant nature of the population, which may limit generalizability. CONCLUSIONS: The empirical identification of unidimensional constructs creates more refined scores that may elucidate the connection between specific symptoms and underlying pathophysiology.