Valence refers to the positive or negative quality of an emotion, feeling or mood. Much has been written about the structure of valence, particularly regarding the relationship between positive and negative valence. However, far less is known about the structure of positive valence itself. Improving our understanding of positive valence in itself is an important step towards clarifying the structure of valence more broadly. In this study, we investigated whether positive valence is best conceptualized as unidimensional (i.e., a single spectrum ranging from minimally positive to maximally positive) or multidimensional (i.e., a complex construct that accommodates multiple distinct ways an emotion can be experienced as positive). To do this, we examined the structure of positive valence through exploratory factor analyses of participants’ (N = 380) evaluations of positive emotions along positive aspects that served as candidate valence dimensions, as assessed through questionnaires. Across analyses of positive valence structure in both aspect space and emotion space, together with several supplementary robustness analyses, our results supported a single-factor model, suggesting a unidimensional structure in participants’ judgements of positive valence. Further, cross-validated regression models showed that this single positive valence factor accounted for variations in participants’ preference-based rankings of positive emotions better than any other factor or individual aspect, establishing predictive validity and providing further support for the unidimensionality of positive valence in participants’ judgements of positive emotional experiences. These findings constrain models of valence by reducing the plausibility of accounts that posit multiple orthogonal positive dimensions.

Daily life methods help us understand emotion regulation as it occurs in people’s natural environment. However, these methods rarely capture emotionally salient situations where emotion regulation is most needed. One common and often distressing experience in daily life is awaiting uncertain and potentially undesirable news. But there is mixed evidence as to the effectiveness of emotion regulation strategies during these uncertain waiting periods. Therefore, we wondered whether variations in the intensity of distress during waiting periods might explain this mixed evidence. Lab experiments consistently show that people prefer disengagement strategies (e.g., distraction) to regulate their emotions in high-intensity situations, and engagement strategies (e.g., reappraisal) in low-intensity situations. Building on these findings, we ran a daily-diary study investigating how distress intensity predicts the selection and (short-term) effectiveness of distraction and reappraisal while people awaited a personally significant uncertain outcome. Each evening for two weeks, 254 Prolific participants rated their distress, emotion regulation strategies, positive and negative emotion, and perceived regulatory success regarding an uncertain outcome. Distress intensity was not related to the selection of distraction, whereas it predicted increased selection of reappraisal. While both distraction and reappraisal were associated with increased positive emotion and regulatory success, intensity did not moderate the effectiveness of either strategy. Our findings suggest that while awaiting uncertain news, people may find it easier to boost positive than negative emotions, and that distress intensity does not change the effectiveness of emotion regulation strategies.

Music listening can serve an affect-regulatory function. For instance, someone who feels anxious may listen to music with the goal of evoking a different, desired feeling (e.g., calmness), labelled 'compensatory' listening. However, music therapists recommend starting with music matching one's current feelings before gradually shifting to music that evokes desired feelings, following the 'iso principle'. Some evidence supports the effectiveness of the iso principle for affect regulation in clinical populations. However, randomised experiments comparing the iso principle with other music-listening interventions are rare, especially with non-clinical participants. To address this gap, the current study compared the effectiveness of iso-principle, compensatory-principle, and unguided music listening for modulating anxiety among healthy participants (N = 193) in a randomised experiment. Participants completed an anxiety induction before listening to a Spotify playlist in one of three randomly assigned conditions: participants in the iso and compensatory conditions listened to five-song iso- and compensatory-principle playlists respectively, curated by the researchers using participants' self-selected songs, whereas participants in the unguided condition self-ordered their songs. Participants rated their momentary affect at baseline, post-anxiety-induction, and post-listening. Our pre-registered analyses revealed no significant difference in the affect-regulatory consequences of iso versus compensatory listening. However, post-hoc exploratory analyses revealed that participants in the guided (iso, compensatory) conditions reported significantly greater increases in calmness than unguided participants. Moreover, exploratory analyses of unguided listening sequences revealed seven distinct patterns of spontaneous music listening, which differed in perceived effectiveness. Findings from this study may inform the development of (digital) music interventions to improve well-being.

Exposure therapy is an effective treatment for anxiety disorders, but its mechanisms remain unclear. We explored the violation of threat-predictions during exposure, which has been hypothesized as necessary for symptom change. Forty-three adults undergoing exposure therapy for social anxiety disorder recorded their experiences during 523 in- and between-session exposures by completing smartphone surveys. Participants rated their threat-predictions, threat-outcomes, anxiety levels, surprise, and learning outcome for each exposure. We used multilevel models to explore the effect of prediction error (threat-prediction from outcome) during exposure on anxiety symptoms at the next session, and on symptom change from baseline to three months follow-up. Exposures successfully generated threat-prediction error and unexpected exposure outcomes were experienced as more surprising and likely to stimulate learning. However, larger threat-prediction error during exposure did not predict lower symptoms at the next session, nor overall symptom improvement. These findings suggest that the magnitude of threat-prediction error is not, in itself, sufficient for successful exposure therapy.

A common maxim holds that “context is everything”. This perspective transformed the field of emotion-regulation, which evolved from understanding which regulation strategies people use, to understanding how strategy use varies by context (i.e., strategy-situation fit). Theoretical accounts suggest contextual features are crucial in guiding people’s selection of emotion-regulation strategies. However, empirical evidence is isolated in piecemeal studies with inconclusive results. To comprehensively explore context-dependent emotion-regulation, we need data on emotion-regulation across many contexts, at scale. Combining 11 experience-sampling datasets in an integrative analysis (NID=1,720, Nobservations=134,470), we examined how regulation strategy use varies as a function of three theory-derived contextual features—intensity, controllability, and social features (i.e., the presence and closeness of others). We found limited support that context matters for daily emotion-regulation strategy use. Our study provides a well-powered foundational step to test a theory central to emotion-regulation research, and highlights the complexity of capturing strategy-situation fit in daily life.

Public debate around whether social media is detrimental to well-being often (implicitly) assumes a unidirectional effect of social media use on emotions. Specifically, social media use is assumed to reduces people’s well-being by making them feel more negative and/or less positive emotions. Equally likely, yet overlooked, possibilities are that people’s emotional states influence their social media use, or that social media use and emotions are reciprocally related. Empirical studies have begun to investigate reciprocal relationships between social media and emotions. But these studies largely rely on (retrospective) self-reported estimates of social media use, which are inaccurate. In the current study, we will combine objective, real-time Instagram use data with data on synchronous emotional experience to investigate whether, and how, Instagram use and emotions are reciprocally related. We will test whether such relationships differ by use type (e.g., content consumption vs. creation) or are moderated by individual differences (e.g., depression symptoms). To investigate how short-term effects accumulate over time, we will examine medium-term (2-week, 4-week) relationships between social media use and emotions. We will focus on Australian young adults, because this age group is one considered most “at risk” of experiencing detrimental effects of social media use (Spies Shapiro and Margolin, 2014). This research will shed light on the links between social media and everyday emotional experience—a key building block of mental health.

A primary objective of intensive longitudinal studies is to investigate within- person dynamics. In this context, item heterogeneity plays a critical role, as within-person processes may vary across items within a scale. A common exam- ple is the assessment of momentary affect using adjective lists (e.g., sad, angry, anxious, stressed), where each item captures different facets of positive or neg- ative affect, providing unique and non-interchangeable information. However, standard practices often overlook item heterogeneity by aggregating item scores or assuming a single within-person factor in dynamic structural equation mod- els. This simplification does not permit a fine-grained analysis of within-person dynamics and compromises cross-study comparability when item pools differ across studies. In this article, we reanalyze five large-scale intensive longitudinal datasets assessing momentary affect to illustrate how item heterogeneity can be explicitly modeled. We introduce a flexible modeling approach that accommo- dates item-specific and person-specific dynamics while improving comparability across studies, based on residualized dynamic structural equation modeling with reference items. We compare this method to conventional modeling strategies and provide practical guidance for addressing item heterogeneity in the analysis of intensive longitudinal data.

Abstract A primary objective of intensive longitudinal studies is to investigate within-person dynamics. In this context, item heterogeneity plays a critical role, as within-person processes may vary across items within a scale. A common example is the assessment of momentary affect using adjective lists (e.g., sad, angry, anxious, stressed), where each item captures different facets of positive or negative affect, providing unique and non-interchangeable information. However, standard practices often overlook item heterogeneity by aggregating item scores or assuming a single within-person factor in dynamic structural equation models. This simplification does not permit a fine-grained analysis of within-person dynamics and compromises cross-study comparability when item pools differ across studies. In this article, we reanalyze five large-scale intensive longitudinal datasets assessing momentary affect to illustrate how item heterogeneity can be explicitly modeled. We introduce a flexible modeling approach that accommodates item-specific and person-specific dynamics while improving psychometric comparability across studies, based on residual dynamic structural equation modeling with reference items. We compare this method to conventional modeling strategies and provide practical guidance for addressing item heterogeneity in the analysis of intensive longitudinal data.

People often predict how they might feel in the future, with varying degrees of accuracy. Such affective forecasts can centre around periods of time (e.g., tomorrow, next week) and/or specific events (e.g., an upcoming meeting). Affective forecasts for everyday events or periods of time are the building blocks of everyday decision-making. Yet, most affective forecasting research has focused on forecasting accuracy for rare and consequential events, such as election results and romantic break-ups. Therefore, in two intensive longitudinal datasets, we tested everyday forecasting accuracy in general (e.g., “tomorrow”) and for specific unpleasant events. In Study 1—a week-long experience sampling study—participants (N = 209) provided (i) one weekly forecast about their feelings over the next week, and (ii) daily forecasts about their feelings the next day. Participants also rated their (i) daily affect each evening, and (ii) their momentary affect nine times each day. In Study 2—a two-week daily diary study—participants (N = 69) nominated an upcoming unpleasant event each day and forecasted their affect related to that event. Each evening, participants rated how they felt when this event occurred. We found that participants could predict when a day/event would make them feel better/worse than usual, showing relative accuracy, but sometimes made small errors in forecasting their absolute affect levels, showing absolute inaccuracy. These findings suggest people make smaller forecasting errors in everyday life than for major events, which likely aids everyday decision making, for example by informing the use of future-oriented regulation strategies.

Emotions do not simply turn on and off again in an instant; rather, emotions rise and fall gradually, often persisting for a considerable period. Although it is normative for emotions to show a degree of momentum—a phenomenon known as emotional inertia—the tendency for emotions to be overly persistent has been associated with psychological maladjustment. However, the mechanisms underlying emotional inertia remain unclear. We aimed to fill this gap in the current study by investigating how the persistence of affect over time (emotional inertia) is mediated—at the within-person level—by the use of emotion-regulation strategies in daily life. We ran secondary analyses on eight experience-sampling datasets collected between 2009 and 2021 (total N = 948 participants measured at 73,472 occasions), in which participants reported their momentary experiences of positive affect (PA) and negative affect (NA), and their recent use of four emotion-regulation strategies (distraction, cognitive reappraisal, rumination, and expressive suppression). We used dynamic structural equation modelling (DSEM) to estimate indirect effects of each strategy on the inertia of PA and NA. All four strategies reliably mediated both NA and (to a lesser extent) PA inertia, supporting the notion that the use of emotion-regulation strategies represents a mechanism underpinning emotional inertia, at least among highly educated, non-clinical, Australian and Belgian young adults. However, each regulation strategy reduced the total autoregressive slope of affect at t–1 predicting affect at t by no more than 13%, suggesting factors other than emotion- regulation strategies also play important roles in emotional inertia.

OBJECTIVE:Youth depression disrupts the social and vocational transition into adulthood. Most depression burden is caused by recurring or chronic episodes. Identifying young people at risk for relapsing, recurring, or chronic depression is critical. We systematically reviewed and meta-analyzed the literature on prognostic factors for relapsing, recurrent, and chronic depression in young people. METHOD:We searched the literature up (MEDLINE, PsycINFO, CINAHL, Embase, CENTRAL, WHO ICTRP, ClinicalTrials.gov, bioRxiv, MedRxiv) to March 6, 2024, and included cohort studies and randomized trials that assessed any prognostic factor for relapse, recurrence, or chronicity of depression in young people (aged 10-25 years at baseline) with a minimum of a 3-month follow-up. We assessed individual study risk of bias using the QUIPS tool and the certainty of evidence via the GRADE approach. We conducted random-effects meta-analyses with Hartung-Knapp-Sidik-Jonkman adjustment when 3 or more estimates on the same prognostic factor were available. Qualitative synthesis was conducted to identify promising prognostic factors that could not be meta-analyzed. RESULTS:A total of 76 reports of 46 studies (unique cohorts or trials) were included that tested 388 unique prognostic factors in 7,488 young people experiencing depression. The majority of the reports were at high risk of bias (87%). We conducted 22 meta-analyses on unadjusted, and 7 on adjusted, prognostic factors of a poor course trajectory (ie, combined relapse, recurrence, and chronicity). Female sex (adjusted; odds ratio [95% CI] = 1.49 [1.15, 1.93], p = .003), higher severity of depressive symptoms (unadjusted; standardized mean difference [95% CI] = 0.53 [0.33, 0.73], p < .001), lower global functioning (unadjusted; standardized mean difference [95% CI] = -0.35 [-0.60, -0.10], p = .005), more suicidal thoughts and behaviors (unadjusted; standardized mean difference [95% CI] = 0.52 [0.03, 1.01], p = .045), and longer sleep-onset latency (unadjusted; mean difference [95% CI] = 6.96 [1.48, 12.44] minutes, p = .013) at baseline predicted a poor course trajectory of depression. The certainty of the evidence was overall very low to moderate. Promising prognostic factors that could not be meta-analyzed included relational/interpersonal factors (friend relationships and family relationships/structure). CONCLUSION:Our findings demonstrate the prognostic value of demographic and clinical factors for poor course trajectories of depression in young people. More research is needed to confirm the potential value of relational/interpersonal factors in predicting poor depression course. Limitations of the literature include the high risk of bias of included studies, which indicates that future studies should include large sample sizes and wider diversity of prognostic markers (eg, genetic and neurobiological) in multivariable models. The critical next step is to combine the identified prognostic factors and to evaluate their clinical value in identifying individuals at risk for a poor course trajectory of depression during youth, a life stage in which most of the disability and burden attributable to depression can be averted. PLAIN LANGUAGE SUMMARY:This systematic review and meta-analysis summarized the evidence for factors that can be used to identify relapsing, recurrent, and chronic depression in young people. Data from 76 reports of 46 unique cohorts, including a total of 7,488 young people experiencing depression, found that female sex, more severe depressive symptoms, suicidal thoughts and behaviors, lower global functioning, and longer sleep-onset latency were predictive of a poor course trajectory of depression. This information has the potential to identify youth at risk for a poor course of depression, a life stage in which most of the disability and burden attributable to depression can be averted. STUDY PREREGISTRATION INFORMATION:Prognostic factors for relapsing, recurrent or chronic depression in youth: a systematic review with meta-analysis; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023458646.

Affective, behavioral, and cognitive (i.e., personality) states fluctuate across situations and context, yet the biological mechanisms regulating them remain unclear. Here, we report two large, longitudinal studies that investigate patterns of change in personality states and affect as a function of the menstrual cycle, ovarian hormones, and hormonal contraceptive use. Study 1 (N = 757) is an online diary study with a worldwide sample, whereas Study 2 (N = 257) is a laboratory study including repeated hormone assays. Both studies came to somewhat diverging conclusions. In Study 1, we found that dynamics of daily affect and personality were very similar among naturally cycling women and hormonal contraceptive users, with two exceptions: Hormonal contraceptive users showed greater variability in negative affect than naturally cycling women, and, naturally cycling women showed a descriptive, but nonsignificant decrease in positive affect in the premenstrual phase. Results of Study 2 indicated robust premenstrual increases in neuroticism and negative affect but decreases in extraversion and positive affect. High extraversion and low neuroticism were positively related to conception risk and the estradiol-to-progesterone ratio, suggesting potentially adaptive effects consistent with a fertility-induced shift in motivational priorities. We discuss how differences in methods likely account for differences in results between both studies and suggest methodological and theoretical guidelines for future research. Taken together, our results suggest that hormonal variation across the menstrual cycle-and discrete menstrual cycle events, such as premenstruation-represent potential biological sources of personality state variation. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Rumination and negative affect are mutually reinforcing experiences. Their dynamic relation can confer vulnerability to psychopathology. Cultivating mindfulness has been proposed to buffer against such downward spirals of negativity. However, it remains unclear whether practicing mindfulness in daily life causally impacts rumination, negative affect, and their dynamics. We investigated this using a micro-randomized intensive longitudinal trial. Participants (N = 91) were prompted eight times per day for 10 days using a smartphone app. At each prompt, participants were randomized to complete a brief mindfulness intervention or an active-control task and then reported levels of rumination and negative affect. Results of dynamic structural equation models showed that the mindfulness intervention led to lower levels of rumination and negative affect but that it had no reliable impact on their dynamics. Thus, cultivating mindfulness in daily life may be a promising approach for decreasing rumination and negative affect but not their dynamical relation.

Over half a billion people around the globe listen to music via music streaming apps. Research shows that, for many users, these apps are tools for managing everyday moods and emotions. Music streaming apps support this goal by offering mood-based music categories and playlists. More recently, researchers have built music recommender systems that aim to support users’ emotional needs by recommending songs based on their self-reported emotions. However, no studies to date have investigated whether their potential incorporation into existing streaming apps is considered acceptable or ethical by users. We conducted a design fiction study, in which 22 participants discussed an imagined Spotify plugin that generates emotion-regulation playlists in response to users’ current and desired emotional states. Participants foresaw potential benefits to well-being, but also raised numerous ethical concerns. We contribute suggestions for mitigating these ethical concerns in the design of emotion-regulation plugins for music streaming apps.

INTRODUCTION:Existing psychological and pharmacological interventions for young people at ultra-high risk (UHR) for psychosis have shown benefit in at least delaying the transition to psychosis, but they have limited benefit for comorbid disorders or social dysfunction, which are prominent for those at UHR. We developed a moderated online social therapy platform (named Momentum) including: (1) transdiagnostic therapeutic interventions targeting social functioning, depression, generalised anxiety and social anxiety; (2) a moderated, peer-led online community and (3) specialised human support from clinicians, career consultants and peer workers. The aim of this trial is to determine whether, in addition to treatment as usual (TAU), Momentum, a 12-month digital intervention, informed by the complex intervention framework, is superior to 12 months of TAU in improving social functioning in UHR young people. METHODS AND ANALYSIS:The study design is a prospective, parallel group, rater-masked randomised controlled trial. We will recruit young people aged 14-27 years, meeting one or more UHR for psychosis criteria. Participants are randomly assigned to the condition using randomly permutated blocks with a 1:1 allocation ratio. Participants are stratified by age (<18 years and ≥18 years), sex at birth and recruitment site. A total of 220 young people will be recruited, allowing for an 18% attrition rate following randomisation. The study includes a 12-month treatment phase, with assessment points at baseline, and 4 months, 8 months and 12 months. The primary outcome is social functioning, as measured by the Global Functioning Social Scale. Secondary outcomes include the severity of depressive and anxiety symptoms, social anxiety, role functioning, study and employment outcomes and cost-effectiveness. We will also examine potential mechanisms to understand Momentum's therapeutic impact on social functioning. Primary analyses will be undertaken on an intention-to-treat basis. Mixed-model repeated measures analyses will be used to compare change in social functioning between the two treatment groups over the 12-month follow-up for primary, secondary and exploratory outcomes. ETHICS AND DISSEMINATION:Melbourne Health Human Research Ethics Committee (HREC/42964/MH-2018) provided ethics approval for this study. Findings will be made available through scientific journals and forums and to the public via social media and the Orygen website. De-identified individual participant data will be available after publication for 3 years via the Health Data Australia catalogue (https://www.researchdata.edu.au/health). Requests must include a methodologically sound proposal. Specific conditions of use may apply and will be specified in a data sharing agreement (or similar) that the requester must agree to before access is granted. Supplementary material including study protocol, informed consent material and statistical analysis plan will also be available. TRIAL REGISTRATION NUMBER:Australian New Zealand Clinical Trial Registry (ANZCTR), ACTRN12619001411134.

Intensive longitudinal designs allow researchers to study the dynamics of psychological processes in daily life. Yet, because these methods are usually observational, they do not allow strong causal inferences. A promising solution is to incorporate (micro-)randomized interventions within intensive longitudinal designs to uncover within-person (Wp) causal effects. However, it remains unclear whether (or how) the resulting Wp causal effects translate into between-person (Bp) differences in outcomes. In this work, we show analytically and using simulated data that Wp causal effects translate into Bp differences if there are no counteracting forces that modulate this cross-level translation. Three possible counteracting forces that we consider here are (a) contextual effects, (b) correlated random effects, and (c) cross-level interactions. We illustrate these principles using empirical data from a 10-day microrandomized mindfulness intervention study (n = 91), in which participants were randomized to complete a treatment or control task at each occasion. We conclude by providing recommendations regarding the design of microrandomized experiments in intensive longitudinal designs, as well as the statistical analyses of data resulting from these designs. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Traditionally, behavioral, social, and health science researchers have relied on global/retrospective survey methods administered cross-sectionally (i.e., on a single occasion) or longitudinally (i.e., on several occasions separated by weeks, months, or years). More recently, social and health scientists have added daily life survey methods (also known as intensive longitudinal methods or ambulatory assessment) to their toolkit. These methods (e.g., daily diaries, experience sampling, ecological momentary assessment) involve dense repeated assessments in everyday settings. To facilitate research using daily life survey methods, we present SEMA3 ( http://www.SEMA3.com ), a platform for designing and administering intensive longitudinal daily life surveys via Android and iOS smartphones. SEMA3 fills an important gap by providing researchers with a free, intuitive, and flexible platform with basic and advanced functionality. In this article, we describe SEMA3’s development history and system architecture, provide an overview of how to design a study using SEMA3 and outline its key features, and discuss the platform’s limitations and propose directions for future development of SEMA3.

Prominent theories of gender suggest that gender can be variable, rather than static. For example, a person may experience changes in their masculinity and femininity in daily life, which we refer to as 'state gender variability.' Theory and research suggest that the degree to which masculinity and femininity fluctuate may have implications for body satisfaction. In this study, we analysed intensive longitudinal data to gain nuanced insights into how masculinity and femininity vary in everyday life among a sample of majority cis-gender sexual minority men. We first present a comprehensive descriptive analysis of gender variability. Second, we test whether individual differences in gender variability are associated with body satisfaction. Masculinity and femininity were moderately stable, with substantial within-person variability. Masculinity and femininity tended to be more variable than state body satisfaction and negative affect. Further, variability and instability in masculinity were associated with lower body satisfaction. Conversely, variability in femininity was associated with higher scores on body satisfaction. Our study contributes to a growing literature examining the implications of masculinity and femininity for sexual minority men's body image and opens up new lines of inquiry focused on state gender variability.