Figures and data
Experimental protocol.
A) Study outline. This study examines how depression and anxiety influence mood fluctuations. The first experiment assesses the bifactor structure that disentangles shared and specific components of depression and anxiety in the psychometric dataset (N = 901). The second experiment tests associations between depression- and anxiety-specific traits and RPE-induced mood fluctuations using the questionnaire battery and a gambling task with momentary mood ratings in the laboratory dataset (N = 44). The third and fourth experiments replicate the second experiment in online samples (online dataset 1, N = 747; online dataset 2, N = 235). The fifth experiment tests whether these findings generalize to a clinical dataset of patients with affective disorders (N = 61). B) Mapping between the three factors and 128 items in the bifactor model. C) Factor loadings of items on the general factor, anxiety-specific factor, and depression-specific factor. D) Orthogonality among the general, anxiety-specific, and depression-specific factor scores across datasets with complete questionnaire data. E) Mean correlations between factor scores and questionnaire scores. Overall, the general factor showed high correlations with all questionnaires. The depression-specific factor correlated most strongly with TAIdep and MASQad, whereas the anxiety-specific factor correlated most strongly with the remaining questionnaires. These correlational results supported the bifactor structure of anxiety and depression. F) Gambling task design. On each trial, participants were asked to choose between a certain option and a gamble option. Once an option was selected, the corresponding outcome was displayed in the center of the screen. The cumulative score was always shown in the upper-right corner. Every 2 or 3 trials, participants were asked to complete a self-paced rating of “How happy are you at this moment?” on a slider scale ranging from 0 (very unhappy) to 100 (very happy). G) Temporal dynamics of happiness ratings for representative individuals with high (top 25%) and low (top 75%) mood variation, healthy datasets, and the clinical dataset. H) Momentary mood model. I) Results of momentary mood model for each dataset. Abbreviations: MASQaa, the subscale of anxious arousal in the Mood and Anxiety Symptoms Questionnaire; TAIanx, the subscale of anxiety in the Trait Anxiety Inventory; CESD, Center for Epidemiologic Studies Depression Scale; BDI, Beck Depression Inventory; BFIn, the subscale of neuroticism in the Big Five Inventory; PSWQ, Penn State Worry Questionnaire; MASQad, the subscale of anhedonic depression in the Mood and Anxiety Symptoms Questionnaire; TAIdep, the subscale of depression in the Trait Anxiety Inventory; CR, certain reward; EV, expected value; RPE, reward prediction error.
Basic demographic details.
Dissociable associations of depression and anxiety with mood fluctuations.
Correlations of depression- and anxiety-specific factor scores with mood variation and RPE-related mood sensitivity βRPE) for the laboratory dataset (A, E), online dataset 1 (B, F), online dataset 2 (C, G), and the combined dataset (N = 1,026; D, H). I) Reduced RPE-related mood sensitivity statistically mediated the association between depressionspecific scores and reduced mood fluctuations. J) Increased RPE-related mood sensitivity statistically mediated the association between anxiety-specific scores and increased mood fluctuations. K) Among the mood sensitivity parameters, the depression-specific factor was selectively associated with decreased RPE-related mood sensitivity. L) Among the mood sensitivity parameters, the anxiety-specific factor was selectively associated with increased RPE-related mood sensitivity. Regression coefficients are shown as bootstrapped mean ± SE. Abbreviations: CR, certain reward; EV, expected value; RPE, reward prediction error. *p < 0.05.
Clinical validation of reduced RPE-related mood sensitivity in depression.
AB) Correlations of depression and anxiety factor score with mood variation and mood parameter of RPE (βRPE) for the clinical dataset. C) The mediation model among depression, βRPE, and mood variation in the clinical population. The regression coefficients were represented by mean ± se, which were estimated by bootstrap. Abbreviations: RPE, reward prediction error; *p<0.05.
Consistent negative associations of the common factor with mood baseline and gain-domain risk attitude across datasets.
A) Negative association between the common factor and the baseline mood parameter. B) Negative association between the common factor and gain-domain risk attitude. Regression coefficients are shown as mean ± SE. *p < 0.05.
