How etiological beliefs contribute to the structure of depression symptom networks.

OBJECTIVES: Each person possesses a unique view surrounding depressive symptomology and etiology that is shaped by idiosyncratic experiences. However, the influence that subjective etiological beliefs regarding a person's depressive symptoms have on actual symptom presentation and organization is seldom considered. METHODS: The current study employed network analytic techniques to examine how subjective views surrounding the cause of depressive symptoms altered actual symptom presentation networks. Additionally, the interaction between depressive symptoms and various etiological beliefs was examined. RESULTS: The results revealed that characterological beliefs, representing the idea that depression is caused by an internal sense of self, are strongly connected to a negative view of self, as well as a saddened mood. Additionally, the characterological beliefs node exhibited the greatest node predictability in its respective network, as well as in an omnibus network consisting of all depression symptoms and potential etiological beliefs. Whereas an achievement-based view of depression has a strong connection with concentration difficulties, a physical view of depression tends to form strong connections with physically based depressive symptoms. CONCLUSION: Subjective views regarding the cause of depression have the potential to influence symptom presentation and organization within a network, which may influence a person's willingness to engage in treatment or specific treatment preferences.

Detecting major depressive disorder presence using passively-collected wearable movement data in a nationally-representative sample.

Major Depressive Disorder (MDD) is a heterogeneous disorder, resulting in challenges with early detection. However, changes in sleep and movement patterns may help improve detection. Thus, this study aimed to explore the utility of wrist-worn actigraphy data in combination with machine learning (ML) and deep learning techniques to detect MDD using a commonly used screening method: Patient Health Questionnaire-9 (PHQ-9). Participants (N = 8,378; MDD Screening = 766 participants) completed the and wore Actigraph GT3X+ for one week as part of the National Health and Nutrition Examination Survey (NHANES). Leveraging minute-level, actigraphy data, we evaluated the efficacy of two commonly used ML approaches and identified actigraphy-derived biomarkers indicative of MDD. We employed two ML modeling strategies: (1) a traditional ML approach with theory-driven feature derivation, and (2) a deep learning Convolutional Neural Network (CNN) approach, coupled with gramian angular field transformation. Findings revealed movement-related features to be the most influential in the traditional ML approach and nighttime movement to be the most influential in the CNN approach for detecting MDD. Using a large, nationally-representative sample, this study highlights the potential of using passively-collected, actigraphy data for understanding MDD to better improve diagnosing and treating MDD.

Depressive symptoms as a heterogeneous and constantly evolving dynamical system: Idiographic depressive symptom networks of rapid symptom changes among persons with major depressive disorder.

Major depressive disorder (MDD) is conceptualized by individual symptoms occurring most of the day for at least two weeks. Despite this operationalization, MDD is highly variable with persons showing greater variation within and across days. Moreover, MDD is highly heterogeneous, varying considerably across people in both function and form. Recent efforts have examined MDD heterogeneity byinvestigating how symptoms influence one another over time across individuals in a system; however, these efforts have assumed that symptom dynamics are static and do not dynamically change over time. Nevertheless, it is possible that individual MDD system dynamics change continuously across time. Participants (N = 105) completed ratings of MDD symptoms three times a day for 90 days, and we conducted time varying vector autoregressive models to investigate the idiographic symptom networks. We then illustrated this finding with a case series of five persons with MDD. Supporting prior research, results indicate there is high heterogeneity across persons as individual network composition is unique from person to person. In addition, for most persons, individual symptom networks change dramatically across the 90 days, as evidenced by 86% of individuals experiencing at least one change in their most influential symptom and the median number of shifts being 3 over the 90 days. Additionally, most individuals had at least one symptom that acted as both the most and least influential symptom at any given point over the 90-day period. Our findings offer further insight into short-term symptom dynamics, suggesting that MDD is heterogeneous both across and within persons over time. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Does grit protect against the adverse effects of depression on academic achievement?

Depressive symptoms have been shown to be negatively related to academic achievement, as measured by grade point average (GPA). Grit, or the passion for and the ability to persevere toward a goal despite adversity, has been linked to GPA. Thus, grit may potentially buffer against the negative effects of depressive symptoms in relation to academic achievement. However, social desirability may might impact the validity of grit when assessed by self-report measures, so how these constructs are all related is unknown. The current study explored the relationship between depressive symptoms, grit, social desirability, and GPA among University students (N = 520) in the United States using a cross-sectional design. We conducted a moderated-moderation model to examine how social desirability moderated the relationship between depressive symptoms, grit, and GPA. Findings replicated prior work and indicated negative relationships between depressive symptoms and social desirability with GPA and a positive relationship, albeit non-significant, between grit and GPA. However, results suggest that grit did not moderate the relationship between depressive symptoms and GPA when including social desirability in the model. Future research should investigate this relationship in a longitudinal setting to further examine how grit and depressive symptoms influence one another in academic domains.

Longitudinal and experimental investigations of implicit happiness and explicit fear of happiness.

ABSTRACTSome individuals devalue positivity previously associated with negativity (Winer & Salem, 2016). Positive emotions (e.g. happiness) may be seen as threatening and result in active avoidance of future situations involving positivity. Although some self-report measures can capture emotions of happiness-averse individuals, they are not always capable of capturing automatic processing. Thus, we examined the association between implicitly-assessed happiness and explicit (i.e. self-reported) fear of happiness in three studies. In Study 1, participants completed the Fear of Happiness Scale (FHS) and an implicit measure of emotions at four-time points over approximately one year. The implicit measure required participants to choose which emotion (i.e. anger, fear, happiness, sadness, or none) best corresponded to 20 individual Chinese characters. In Studies 2 and 3, we utilized an experimental design, implementing a mood induction to emphasise the relationship between explicit fear of happiness and implicitly-assessed happiness. Participants completed the FHS and chose which emotion they believed the artist tried to convey in 20 abstract images. Results indicated that greater self-reported fear of happiness was related to reduced implicit happiness. Findings from these studies provide compound evidence that individuals who hold negative views of positivity may process implicit happiness in a devaluative manner.

A network analytic investigation of avoidance, dampening, and devaluation of positivity.

BACKGROUND AND OBJECTIVES: Reward Devaluation Theory suggests that devaluation of positivity may be integral in understanding depression (Winer & Salem, 2016). Specifically, the anticipatory (e.g., fear of happiness) and responsive (e.g., dampening) behaviors related to the processing of positivity may play a role in the development and maintenance of depression. METHODS: The goal of this study was to examine the potential overlap between measures that operationalize positivity avoidance, two Fear of Happiness Scales (Gilbert et al., 2012; Joshanloo, 2013), as well as positivity dampening, measured via the dampening subscale of the Responses to Positive Affect Questionnaire (Feldman et al., 2008). Network and community analyses were employed to examine the extent to which the items of these measures clustered into their parent measures and investigate the dynamic interactions between items. RESULTS: The results of the community analysis revealed that the three self-report measures overall clustered into their parent measures, except for the Gilbert et al. (2012) Fear of Happiness Scale, which clustered into two separate communities. The most influential nodes represented the concept that good feelings are often followed by negative outcomes. Additionally, nodes related to the theme of fear of letting oneself become happy emerged as the strongest bridge nodes. LIMITATIONS: One limitation of this study is the use of a cross-sectional design; thus, causality cannot be inferred, but the results can guide future longitudinal network designs. CONCLUSIONS: These findings demonstrate how anticipatory avoidance and responsive dampening may influence depression, thus providing evidence for unique targets for treatment.

Individuals fearing positivity do not perceive positive affect treatments as strong fits: A novel experimental finding and replication.

BACKGROUND AND OBJECTIVES: Positive affect treatments, which hold great promise to connect with those who are otherwise resistant to depression treatments, attempt to upregulate positive emotions. These treatments have potential advantages over standard therapies because they target cross-diagnostic core symptoms (e.g., anhedonia) that may respond better to interventions aimed at increased positivity. However, the extent to which these treatments are a perceived fit by individuals for whom they were developed (i.e., individuals who are afraid of, avoid, or experience less positivity) is unclear. METHODS: We conducted two independent studies utilizing a cross-sectional, experimental design to examine perceived treatment fit. Participants (Study 1: N = 416; Study 2: N = 321) read counterbalanced treatment descriptions of (1) positive affect treatment and (2) psychodynamic psychotherapy and answered questions regarding perceived treatment fit, effectiveness, and preference of the two treatments. RESULTS: Our findings suggest that individuals fearful of happiness perceived a prospective depression treatment specifically targeting positivity as a poorer fit, demonstrating an opposite pattern to the overall samples' treatment preference in both studies. Thus, as predicted by Reward Devaluation Theory, those fearing positivity exhibited avoidance behaviors for treatments that are to an extent designed, and might otherwise be most effective, for them. LIMITATIONS: The current study utilized a college student sample. CONCLUSION: These empirical findings may ultimately inform psychoeducation of why positive affect treatments, which are in direct contrast with clients' preferences, may be the very treatments they need the most.

Examining rumination, devaluation of positivity, and depressive symptoms via community-based network analysis.

OBJECTIVE: Components of rumination, including brooding and reflection, as well as devaluating prospective positivity, may help maintain depressive symptoms. We examined these components together for the first time using network analysis. METHODS: We examined the robustness of rumination communities of closely related items in one network and then examined the interrelationships between rumination communities, devaluation of positivity, and depression, in a second network. RESULTS: Three rumination communities emerged, replicating findings of Bernstein et al. (2019). Within a dense network, nodes representing brooding, reflective pondering, and difficulty trusting positive feelings were most influential. In addition, the node representing the depressive symptom negative self-views shared strong edges with nodes representing devaluation of positivity and brooding. CONCLUSION: Brooding, reflective pondering, and elements of devaluing positivity are influential to depressive symptoms and may be important future experimental and therapeutic targets. Depressed individuals with negative self-views may engage in brooding and devalue their experience of positivity.

Negative affect interference and fear of happiness are independently associated with depressive symptoms.

OBJECTIVES: Reward devaluation theory (RDT) posits that some depressed individuals avoid positivity due to its previous association with negative outcomes. Behavioral indicators of avoidance of reward support RDT, but self-report indicators have yet to be examined discriminantly. Two candidate self-report measures were examined in relation to depression: negative affect interference (NAI), or the experience of negative affect in response to positivity, and fear of happiness, a fear of prospective happiness. METHOD: Participants completed measures assessing NAI, fear of happiness scale, and depression online via Amazon's Mechanical Turk at three time points (N = 375). Multilevel modeling examined the relationship between NAI, fear of happiness, and depressive symptoms longitudinally. RESULTS: NAI and fear of happiness were both positively associated with depressive symptoms. They both uniquely predicted depressive symptoms when included within the same model. CONCLUSIONS: These findings suggest that different conceptualizations of positivity avoidance are uniquely associated with depressive symptoms.

Conceptualizing anhedonias and implications for depression treatments.

Anhedonia has been implicated as a core symptom of depression and schizophrenia, and studying anhedonia has yielded a wide array of important findings aiding the understanding and identification of psychological disorders. However, anhedonia is a complex and multifaceted construct; indeed, the term anhedonia has been defined in psychological and psychiatric research as many different concepts, a number of which are theoretically and methodologically independent of one another. In this review alone, we discuss research that separates social aspects of anhedonia from the physical contexts of anhedonia, with the former emphasizing interpersonal relationships as important to anhedonic symptoms, and the latter emphasizing biological and brain-related impairment as potential causes of chronic anhedonia states. We highlight research that distinguishes between interest in (wanting) or experience of (liking) potential pleasure as definitions of anhedonia and also disambiguate methodologically and theoretically distinct ways of assessing 1) trait-level dispositional tendencies, 2) state-level cross-sectional assessments, and 3) symptom-based recent changes from baseline, all of which have been used to indicate anhedonia. Lastly, we describe cutting-edge translations of basic anhedonia research into treatment and discuss how different conceptualizations of anhedonia, guided by recent theoretical and methodological advances, have begun to usher in a science of anhedonia that is consistent with increasingly personalized assessment and treatment. We conclude with a note for future research, emphasizing that continued application of theoretically based operationalizations of anhedonia and sound design are paramount to continue the recent progress toward meaningful and specific use of the anhedonia construct in clinical research.