Objective: Despite the importance for understanding mechanisms of change, little is known about the order of change in daily life emotions, cognitions, and behaviors during treatment of depression. This study examined the within-person temporal order of emotional, cognitive, and behavioral improvements using ecological momentary assessment data.
Method: Thirty-two individuals with diagnosed depression completed ecological momentary assessment questions on emotions (sad mood, happy mood), behaviors (social interaction, number of activities), and cognitive variables (worrying, negative self-thoughts) 5 times a day during a 4-month period in which they underwent psychotherapy for depression. Nonparametric change-point analyses were used to determine the timing of gains (i.e., improvements in the mean of each variable) for each individual. We then established whether the first (i.e., earliest) gains in emotions preceded, followed, or occurred in the same week as cognitive and behavioral gains for each individual.
Results: Contrary to our hypotheses, first gains in behaviors did not precede first emotional gains (3 times, 8%) more often than they followed them (26 times, 70%). Cognitive gains often occurred in the same week as first emotional gains (43 times, 58%) and less often preceded (13 times, 18%) or followed emotional gains (18 times, 24%).
Conclusion: The first improvements in behaviors did not tend to precede the first improvements in emotions likely because fewer behavioral gains were found. The finding that cognitive variables tend to improve around the same time as sad mood may explain why many studies failed to find that cognitive change predicts later change in depressive symptoms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Objective: Negative affect and affect variability figure prominently in models of addictive behaviors but are not without controversy. Negative affect variability may better capture a mechanism of behavior change in alcohol use disorder (AUD) treatment because it contains information about affect regulation, a common clinical target. The aims of this study are to examine the change in: (a) trajectory of negative affect variability, (b) association of negative affect variability and abstinence, and (c) association of negative affect variability and heavy drinking during AUD treatment.
Method: This article is a secondary analysis of data drawn from a randomized clinical trial. N = 181 participants diagnosed with Diagnostic and Statistical Manual of Mental Disorders, fifth edition AUD (Mage = 50.8, SDage = 10.6; 51.4% female) received 12 sessions of Cognitive Behavioral Coping Skills Therapy for AUD. Participants completed one daily diary prompt per day for 84 consecutive days. Each day, participants reported on negative affect and number of alcoholic drinks consumed the previous day. Time-varying effect models examined changes in negative affect variability and its associations with abstinence and heavy drinking.
Results: Negative affect variability decreased throughout treatment. The positive association between negative affect variability and heavy drinking became nonsignificant (decoupled) midway through treatment. The inverse association between negative affect variability and daily abstinence became nonsignificant (decoupled) at approximately day 75 of 84. When mean levels of NA were added as a covariate, the effects were in the same direction but no longer statistically significant.
Conclusion: Reductions in negative affect variability may capture an important change mechanism of behavioral treatments for AUD because it contains information about affect regulation as compared with mean levels of negative affect. Negative affect variability warrants further consideration as a mechanism of behavior change. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Objective: Recurrent depressive episodes are preceded by changing mean levels of repeatedly assessed emotions (e.g., feeling restless), which can be detected in real time using statistical process control (SPC). This study investigated whether monitoring changes in the standard deviation (SD) of emotions and negative thinking improves the early detection of recurrent depression.
Method: Formerly depressed adults (N = 41) monitored their emotions five times a day for 4 consecutive months. During the study, 22 individuals experienced recurrent depression. We used SPC to detect warning signs (i.e., changing means and SDs) of four emotions (positive and negative affect with high or low arousal) and negative thinking.
Results: SD-based warning signs only preceded 23%-36% of recurrences, but almost never reflected a false alarm (0%-16%). Correspondingly, SD-based warnings had a high specificity (at the cost of sensitivity), while mean-based warnings had a higher sensitivity (but lower specificity). There was little overlap in mean- and SD-based warning signs. For the majority of emotions, monitoring for high SDs alongside monitoring changes in mean levels improved the detection of depression (p < .015) compared to when only monitoring for changing mean levels.
Conclusions: Warning signs for depression manifest not only in changing mean levels of emotions and cognitions but also in increasing SDs. These warnings could eventually be used to detect not just who is at increased risk for depression but also when risk is rising. Further research is needed to evaluate the clinical utility of depression SPC. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Objective: Behavioral activation (BA) is a brief intervention for depression encouraging gradual and systematic re-engagement with rewarding activities and behaviors. Given this treatment focus, BA may be particularly beneficial for adolescents with prominent anhedonia, a predictor of poor treatment response and common residual symptom. We applied group iterative multiple model estimation (GIMME) to ecological momentary assessment (EMA) treatment data to investigate common and person-specific processes during BA for anhedonic adolescents.
Method: Thirty-nine adolescents (Mage = 15.7 years old, 67% female, 81% White) with elevated anhedonia (Snaith-Hamilton Pleasure Scale) were enrolled in a 12-week BA trial, with weekly anhedonia assessments. EMA surveys were triggered every other week (2-3 surveys per day) throughout treatment assessing current positive affect (PA) and negative affect (NA), engagement in pleasurable activities and social interactions, anticipatory pleasure, rumination, and recent pleasurable and stressful experiences.
Results: A multilevel model revealed significant decreases in anhedonia, t(25.5) = -4.76, p < .001, over the 12-week trial. GIMME results indicated substantial heterogeneity in variable networks across patients. PA was the variable with the greatest number (22% of all paths vs. 11% for NA) of predictive paths to other symptoms (i.e., highest out-degree). Higher PA (but not NA) out-degree was associated with greater anhedonia improvement, t(25.8) = -2.22, p = .035.
Conclusions: Results revealed substantial heterogeneity in variable relations across patients, which may obscure the search for common processes of change in BA. PA may be a particularly important treatment target for anhedonic adolescents in BA. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
In recent years, there has been growing empirical interest in examining the role of affect dynamics in mental health. However, research on affect has largely progressed independently in the basic and applied sciences, yielding significant advances in each domain but little cross-disciplinary integration. This special issue addresses this gap by showcasing some of the most promising recent developments in the field. The articles featured in this special issue offer insights into key innovations in affect dynamics and their potential implications for mental health interventions. Comprising a total of 17 articles, the issue is divided into two sections: Daily Life Assessment of Affect, encompassing seven articles, and In-Treatment Assessment of Affect, comprising 10 articles. In this editorial, we synthesize the contributions of these articles and propose a set of fundamental principles for conducting and interpreting research on the role of affect dynamics as mechanisms of change in mental health interventions. These principles encompass (a) the content of affect research related to mental health and its treatment (the What), (b) the timing of the assessment (the When), (c) the target populations under investigation (the Who), and (d) the methodologies employed (the How). The synthesis presented here, along with the articles featured in this special issue, holds significant potential to inform clinical research and practice on the role of affect dynamics in mental health interventions and stimulate future scientific inquiry in this important area. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Objective: Interpersonal and emotional functioning are closely linked and reciprocally influence one another. Contemporary integrative interpersonal theory (CIIT) offers a useful framework to conceptualize these patterns and guide interventions in cases where these patterns result in dysfunction. Stress processes offer several dynamic frameworks to guide empirical investigations using methods that allow for fine-grained analyses in the context of daily life.
Method: Four samples of adults (Sample 1, N = 145; Sample 2, N = 160; Sample 3, N = 297; Sample 4 = 89 dyads, 178 individuals) completed ecological momentary assessment protocols focused on a variety of interpersonal and emotional experiences. Samples were enriched for aggressive and self-harming behavior (Sample 1), trait hostility (Sample 2), interpersonal problems (Sample 3), and personality disorder features (Sample 4).
Results: Using multilevel dynamic structural equation modeling, we investigated how emotions and interpersonal functioning operate over brief timescales in daily life. We found evidence for a vicious socioemotional cycle across all four samples, whereby negative emotions related to interpersonal conflict (i.e., perceptions of and enacting cold, antagonistic, or quarrelsome behavior; components that contribute to the interpersonal situation from the perspective of CIIT) which in turn related to increased negative emotions. Although individuals differed in the strength of this process, it was unrelated to trait negative affectivity.
Conclusions: Viewing these results through the lens of CIIT, we discuss multiple intervention points highlighted by these dynamic results whereby the vicious cycle might be changed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Objective: Meditation apps are the most widely used mental health apps. The precise mechanisms underlying their effects remain unclear. In particular, the degree to which affect experienced during meditation is associated with outcomes has not been established.
Method: We used the meditation app arm of a recently completed randomized controlled trial comparing a self-guided meditation app (Healthy Minds Program) to a waitlist control. Predominantly distressed public school employees (n = 243, 80.9% with clinically elevated depression and/or anxiety) reported positive and negative affect during meditation practice. Data were analyzed using two-level multivariate latent growth curve models (observations nested within participants) that simultaneously attended to both positive and negative affect. We examined whether positive and negative affect during meditation changed over time and whether these changes were associated with changes in psychological distress (parent trial's preregistered primary outcome) at posttest or 3-month follow-up.
Results: On average, participants reported decreased negative affect but no change in positive affect during meditation over time. Increased positive affect and decreased negative affect during meditation were associated with improvements in distress at posttest and follow-up. Change in positive affect was a stronger predictor of distress at follow-up than change in negative affect.
Conclusions: Despite notions embedded within mainstream mindfulness meditation training that deemphasize the importance of the affective experience of practice (i.e., nonjudgmental awareness of present moment experience, regardless of valence), results indicate that these experiences contain signals associated with outcomes. Monitoring affect during meditation may be worthwhile to guide intervention delivery (i.e., measurement-based care, precision medicine). (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Objective: To date, many prediction studies in psychotherapy research have used cross-sectional data to predict treatment outcome. The present study used intensive longitudinal assessments and continuous time dynamic modeling (CTDM) to investigate the temporal dynamics of affective states and emotion regulation in the early phase of therapy and their ability to predict treatment outcome.
Method: Ninety-one patients undergoing psychological treatment at a university outpatient clinic took part in a 2-week ecological momentary assessment (EMA) period. Participants answered self-report measures on positive affect (PA), negative affect, and emotion regulation (ER) four times a day. Hierarchical Bayesian CTDM was conducted to identify temporal effects within (autoregressive) and between (cross-regressive) PA, negative affect, and ER. The resulting CTDM parameters, simple EMA parameters (e.g., mean), and cross-sectional predictors were entered into a LASSO model to be examined as predictors of treatment outcome at Session 15.
Results: Two significant predictors were identified: initial impairment and the continuous time cross-effect of PA on ER. The final model explained 40% of variance in treatment outcome, with the cross-effect (PA-ER) accounting for 4% of variance beyond initial impairment.
Conclusions: The results demonstrate that temporal patterns of affective EMA data are valuable for the mapping of individual differences and the prediction of treatment outcome. This information can be used to provide therapists with feedback to personalize treatments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Objective: Motivational Interviewing (MI) is described as a method for improving clinical outcomes by reducing client ambivalence. If this is true, MI's focus on improving clients' motivational language should be most useful for clients with ambivalence about change and less valuable for those who are ready to implement new behaviors or are opposed to change. To address this hypothesis and potentially add precision to MI delivery in clinical settings, we tested whether the relationship between clients' in-session motivational language and posttreatment alcohol use depended on their baseline motivation to change.
Method: Client speech from 149 sessions from Project MATCH were analyzed. A cluster analysis of the percent change talk during the first decile of the session identified three motivational groups: opposed, ambivalent, and ready. The change in percent change talk (C-PCT) across the session was calculated for each group. Zero-inflated negative binomial analysis was used to test whether the effect of C-PCT on end-of-treatment drinking varied between motivational groups.
Results: The count part of the model revealed a significant interaction between C-PCT and membership in the ambivalent group (b = -17.710, 95% CI [-25.775, -9.645], p < .001), only for those who received MI. Favorable C-PCT was associated with less drinking (b = -15.735, p = .004). Only baseline drinking was a significant predictor of abstinence at follow-up (b = .032, 95% CI [0.012, 0.051], p = .001).
Conclusion: A putative MI mechanism-improved client motivational language-appears most important for clients who express ambivalence in the opening minutes of the session, with minimal value for those who do not. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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