Longitudinal bidirectional associations between internalizing mental disorders and cardiometabolic disorders in the general adult population.

PURPOSE: This prospective population-based study investigated whether having any internalizing mental disorder (INT) was associated with the presence and onset of any cardiometabolic disorder (CM) at 3-year follow-up; and vice versa. Furthermore, we examined whether observed associations differed when using longer time intervals of respectively 6 and 9 years. METHODS: Data were used from the four waves (baseline and 3-, 6- and 9-year follow-up) of the Netherlands Mental Health Survey and Incidence Study-2, a prospective study of a representative cohort of adults. At each wave, the presence and first onset of INT (i.e. any mood or anxiety disorder) were assessed with the Composite International Diagnostic Interview 3.0; the presence and onset of CM (i.e. hypertension, diabetes, heart disease, and stroke) were based on self-report. Multilevel logistic autoregressive models were controlled for previous-wave INT and CM, respectively, and sociodemographic, clinical, and lifestyle covariates. RESULTS: Having any INT predicted both the presence (OR 1.28, p = 0.029) and the onset (OR 1.46, p = 0.003) of any CM at the next wave (3-year intervals). Having any CM was not significantly related to the presence of any INT at 3-year follow-up, while its association with the first onset of any INT reached borderline significance (OR 1.64, p = 0.06), but only when examining 6-year intervals. CONCLUSIONS: Our findings indicate that INTs increase the risk of both the presence and the onset of CMs in the short term, while CMs may increase the likelihood of the first onset of INTs in the longer term. Further research is needed to better understand the mechanisms underlying the observed associations.

The temporal order of fluctuations in atopic disease symptoms and attention-deficit/hyperactivity disorder symptoms: a time-series study in ADHD patients.

In a recent meta-analysis, we found that atopic diseases, like asthma and allergic rhinitis, occur more frequently prior to the onset of attention-deficit/hyperactivity disorder (ADHD). Our aim was to determine the temporal order of the association between daily fluctuations in atopic disease symptoms and in ADHD symptoms in individual participants. In this observational study among 21 participants, age 7-16 years, we performed a replicated time-series analysis of symptom fluctuations in asthma and/or allergic rhinitis and ADHD. Data were collected through parents who filled in a daily online questionnaire during up to 50 days. In each individual, we investigated the temporal order of fluctuations in atopic disease symptoms and ADHD symptoms using a vector autoregressive (VAR) model while using sleep problems and medication use as covariates. For 16 out of 21 participants, we constructed a VAR model. For a majority of the participants, significant associations were detected between atopic disease symptoms and ADHD symptoms. The results were heterogeneous; the direction, sign, and timing of the relationship between ADHD, atopy, sleep problems, and medication use varied between individuals. This study provides additional evidence that the symptom expression of atopy and ADHD are related. However, the connection between both diseases in children is found to be heterogeneous within our study population.

Predicting antidepressant response by monitoring early improvement of individual symptoms of depression: individual patient data meta-analysis.

BACKGROUND: Improvement in depression within the first 2 weeks of antidepressant treatment predicts good outcomes, but non-improvers can still respond or remit, whereas improvers often do not.AimsWe aimed to investigate whether early improvement of individual depressive symptoms better predicts response or remission. METHOD: We obtained individual patient data of 30 trials comprising 2184 placebo-treated and 6058 antidepressant-treated participants. Primary outcome was week 6 response; secondary outcomes were week 6 remission and week 12 response and remission. We compared models that only included improvement in total score by week 2 (total improvement model) with models that also included improvement in individual symptoms. RESULTS: For week 6 response, the area under the receiver operating characteristic curve and negative and positive predictive values of the total improvement model were 0.73, 0.67 and 0.74 compared with 0.77, 0.70 and 0.71 for the item improvement model. Model performance decreased for week 12 outcomes. Of predicted non-responders, 29% actually did respond by week 6 and 43% by week 12, which was decreased from the baseline (overall) probabilities of 51% by week 6 and 69% by week 12. In post hoc analyses with continuous rather than dichotomous early improvement, including individual items did not enhance model performance. CONCLUSIONS: Examining individual symptoms adds little to the predictive ability of early improvement. Additionally, early non-improvement does not rule out response or remission, particularly after 12 rather than 6 weeks. Therefore, our findings suggest that routinely adapting pharmacological treatment because of limited early improvement would often be premature.Declaration of interestNone.

Associations of Positive Affect and Negative Affect With Allostatic Load: A Lifelines Cohort Study.

OBJECTIVE: Allostatic load (AL) reflects the deteriorating influences of stress on the body and comprises a selection of biological markers. AL is associated with negative life events, stress, and negative affect (NA), as well as poor health outcomes. However, whether AL is also associated with positive affect (PA) is not clear. The present study therefore explores the association between PA and AL, accounting for age, sex, NA, and health behaviors. METHODS: Data of 45,225 individuals from the first wave of the multidisciplinary prospective population-based cohort study Lifelines were used. AL was operationalized as the sum of 12 inflammatory, cardiovascular, and metabolic markers. The association between PA and AL was tested in a cross-sectional study design using multiple linear regression analysis, adjusting for NA, confounders, and health behaviors. In addition, we explored whether the relation was moderated by age, sex, and NA. RESULTS: The AL profile was inversely associated with PA (B = -0.083, p < .001) when adjusted for NA, age, and sex. The association between AL and PA remained significant after adjusting for health behaviors (B = -0.076, p < .001). A significant moderating effect was found for sex (PA by sex: B = 0.046, p = .001), indicating that the association between PA and AL was stronger in women than in men. CONCLUSIONS: PA was associated with a more favorable AL profile, especially in women. These results add to the evidence that PA might be of relevance to the etiology of disease.

A qualitative approach to guide choices for designing a diary study.

BACKGROUND: Electronic diaries are increasingly used in diverse disciplines to collect momentary data on experienced feelings, cognitions, behavior and social context in real life situations. Choices to be made for an effective and feasible design are however a challenge. Careful and detailed documentation of argumentation of choosing a particular design, as well as general guidelines on how to design such studies are largely lacking in scientific papers. This qualitative study provides a systematic overview of arguments for choosing a specific diary study design (e.g. time frame) in order to optimize future design decisions. METHODS: During the first data assessment round, 47 researchers experienced in diary research from twelve different countries participated. They gave a description of and arguments for choosing their diary design (i.e., study duration, measurement frequency, random or fixed assessment, momentary or retrospective assessment, allowed delay to respond to the beep). During the second round, 38 participants (81%) rated the importance of the different themes identified during the first assessment round for the different diary design topics. RESULTS: The rationales for diary design choices reported during the first round were mostly strongly related to the research question. The rationales were categorized into four overarching themes: nature of the variables, reliability, feasibility, and statistics. During the second round, all overarching themes were considered important for all diary design topics. CONCLUSIONS: We conclude that no golden standard for the optimal design of a diary study exists since the design depends heavily upon the research question of the study. The findings of the current study are helpful to explicate and guide the specific choices that have to be made when designing a diary study.

Using bundle embeddings to predict daily cortisol levels in human subjects.

BACKGROUND: Many biological variables sampled from human subjects show a diurnal pattern, which poses special demands on the techniques used to analyze such data. Furthermore, most biological variables belong to nonlinear dynamical systems, which may make linear statistical techniques less suitable to analyze their dynamics. The current study investigates the usefulness of two analysis techniques based on nonlinear lagged vector embeddings: sequentially weighted global linear maps (SMAP), and bundle embeddings. METHODS: Time series of urinary cortisol were collected in 10 participants, in the morning ('night' measurement) and the evening ('day' measurement), resulting in 126 consecutive measurements. These time series were used to create lagged vector embeddings, which were split into 'night' and 'day' bundle embeddings. In addition, embeddings were created based on time series that were corrected for the average time-of-day (TOD) values. SMAP was used to predict future values of cortisol in these embeddings. Global (linear) and local (non-linear) predictions were compared for each embedding. Bootstrapping was used to obtain confidence intervals for the model parameters and the prediction error. RESULTS: The best cortisol predictions were found for the night bundle embeddings, followed by the full embeddings and the time-of-day corrected embeddings. The poorest predictions were found for the day bundle embeddings. The night bundle embeddings, the full embeddings and the TOD-corrected embeddings all showed low dimensions, indicating the absence of dynamical processes spanning more than one day. The dimensions of the day bundles were higher, indicating the presence of processes spanning more than one day, or a higher amount of noise. In the full embeddings, local models gave the best predictions, whereas in the bundles the best predictions were obtained from global models, indicating potential nonlinearity in the former but not the latter. CONCLUSIONS: Using a bundling approach on time series of cortisol may reveal differences between the predictions of night and day cortisol that are difficult to find with conventional time-series methods. Combination of this approach with SMAP may especially be useful when analyzing time-series data with periodic components.

The Temporal Order of Changes in Physical Activity and Subjective Sleep in Depressed Versus Nondepressed Individuals: Findings From the MOOVD Study.

Epidemiological studies have shown an association between physical activity and sleep, but it is unclear what the temporal order of this association is and whether it differs for depressed patients and healthy controls. Using a multiple repeated observations design, 27 depressed and 27 pair-matched nondepressed participants completed daily measurements of subjective sleep quality and duration during 30 consecutive days while an accelerometer continuously registered their physical activity. Changes in sleep duration, not quality, predicted next-day changes in physical activity (B = -0.21, p < .001), but not the other way around. Significant heterogeneity between individuals was observed, but the effect was not different for depressed and nondepressed participants. The findings underline the strength of a multiple repeated observations design in observational sleep research.

The Reciprocity of Prosocial Behavior and Positive Affect in Daily Life.

OBJECTIVE: To examine whether prosocial behaviors help sustain a positive mood, we tested the dynamic reciprocal associations between prosocial behavior and positive affect (PA) in daily life. A second aim was to examine whether the personality traits Neuroticism and Extraversion moderate these associations. METHOD: The study included a community sample (N = 553). Participants completed an electronic diary assessing prosocial behavior and PA three times a day over 30 days. A subsample of 322 participants filled out the NEO Five-Factor Inventory to assess Neuroticism and Extraversion. Multilevel autoregressive models were performed to examine the within-person bidirectional associations between prosocial behavior and PA and possible moderation by Neuroticism and Extraversion. RESULTS: Within individuals, more PA was followed by more prosocial behavior at the next assessment, and more prosocial behavior was followed by more PA. The effect of prosocial behavior on PA was stronger for individuals high on Neuroticism. Extraversion did not moderate the associations under study. CONCLUSIONS: The findings indicate that prosocial behavior and PA reinforce each other in daily life. Prosocial behavior seems most beneficial for individuals high on Neuroticism.

Exploring the relation between visual mental imagery and affect in the daily life of previously depressed and never depressed individuals.

Previously depressed individuals experience disturbances in affect. Affective disturbances may be related to visual mental imagery, given that imagery-based processing of emotional stimuli causes stronger affective responses than verbal processing in experimental laboratory studies. However, the role of imagery-based processing in everyday life is unknown. This study assessed mental imagery in the daily life of previously and never depressed individuals. Higher levels of visual mental imagery was hypothesised to be associated with more affective reactivity to both negatively and positively valenced mental representations. This study was the first to explore mental imagery in daily life using experience sampling methodology. Previously depressed (n = 10) and matched never depressed (n = 11) individuals participated in this study. Momentary affect and imagery-based processing were assessed using the "Imagine your mood" smartphone application. Participants recorded on average 136 momentary reports over a period of 8 weeks. The expected association between visual mental imagery and affective reactivity was not found. Unexpectedly, in both previously and never depressed individuals, higher levels of imagery-based processing of mental representations in daily life were significantly associated with better momentary mood and more positive affect, regardless of valence. The causality of effects remains to be examined in future studies.

Bidirectionality Between Sleep Symptoms and Core Depressive Symptoms and Their Long-Term Course in Major Depression.

OBJECTIVE: To investigate the bidirectional dynamic relationship between sleep symptoms and core depressive symptoms and to identify subgroups differing with respect to their course. METHODS: The weekly state of depressive symptoms in depressed primary care patients (N = 267) was assessed retrospectively every 3 months for 3 consecutive years. The bidirectional relationship between sleep and core symptoms was estimated by means of manifest Markov modeling. Data-driven subgroups were estimated with parallel processes-latent class growth analyses to identify differences in courses of sleep and core symptoms. RESULTS: In total, core symptoms were associated with next-week development (odds = 1.42; 95% confidence interval [CI] = 1.20-1.67; p < .001) and remission of sleep symptoms (odds = 0.86; 95% CI 0.75 to 0.99, p = .033).Evidence was also found for a reverse pathway such that sleep symptoms were associated with the development (odds = 1.26; 95% CI = 1.05-1.50; p = .012) and remission of core symptoms (odds = 0.87; 95% CI = 0.76-0.99; p = .038). Three classes with different 3-year courses were derived. In class 1, the likelihood that core symptoms remitted was reduced if sleep symptoms were present, and symptoms remained present over 3 years. In class 2, symptoms were bidirectionally related and remitted over 3 years. In class 3, symptoms were not associated, and sleep symptoms declined less steeply than core depressive symptoms. CONCLUSIONS: The results suggest that sleep symptoms should be treated alongside core depressive symptoms in patients with an asynchronic decrease of sleep and core symptoms and in patients that do not respond to treatment to increase the chance of complete remission.

Temporal Dynamics of Health and Well-Being: A Crowdsourcing Approach to Momentary Assessments and Automated Generation of Personalized Feedback.

OBJECTIVE: Recent developments in research and mobile health enable a quantitative idiographic approach in health research. The present study investigates the potential of an electronic diary crowdsourcing study in the Netherlands for (1) large-scale automated self-assessment for individual-based health promotion and (2) enabling research at both the between-persons and within-persons level. To illustrate the latter, we examined between-persons and within-persons associations between somatic symptoms and quality of life. METHODS: A website provided the general Dutch population access to a 30-day (3 times a day) diary study assessing 43 items related to health and well-being, which gave participants personalized feedback. Associations between somatic symptoms and quality of life were examined with a linear mixed model. RESULTS: A total of 629 participants completed 28,430 assessments, with a mean (SD) of 45 (32) assessments per participant. Most participants (n = 517 [82%]) were women and 531 (84%) had high education. Almost 40% of the participants (n = 247) completed enough assessments (t = 68) to generate personalized feedback including temporal dynamics between well-being, health behavior, and emotions. Substantial between-person variability was found in the within-person association between somatic symptoms and quality of life. CONCLUSIONS: We successfully built an application for automated diary assessments and personalized feedback. The application was used by a sample of mainly highly educated women, which suggests that the potential of our intensive diary assessment method for large-scale health promotion is limited. However, a rich data set was collected that allows for group-level and idiographic analyses that can shed light on etiological processes and may contribute to the development of empirical-based health promotion solutions.

Using State Space Methods to Reveal Dynamical Associations Between Cortisol and Depression.

Despite extensive research, the link between etiological factors and depression remains poorly understood. This may in part be due to a focus on strictly linear definitions of causality, derived at the group level. However, etiological relations in depression are likely to be dynamical, nonlinear and potentially unquantifiable with traditional statistics. Therefore the aim of this study was to evaluate the use of the convergent cross-mapping (CCM) method in investigating possible nonlinear relationships between supposed etiological factors and depressive symptomatology. Time series data from six healthy individuals were used to model the relationship between 24-h urinary free cortisol and negative affect using CCM and dewdrop embeddings. CCM is a nonlinear measure of causality, based on state space reconstruction with lagged coordinate embeddings. The results showed that nonlinear dynamical relationships between cortisol and negative affect may be present within participants, as demonstrated by a positive cross-map convergence from negative affect to cortisol. However, analyses also showed that noise and influential points had considerable impact on the results. Convergent crossmapping can be used to reveal possible nonlinear dynamical relationships between etiological factors and psychopathology that may remain undetected with traditional linear causality measures.

Systematic Review and Individual Patient Data Meta-Analysis of Sex Differences in Depression and Prognosis in Persons With Myocardial Infarction: A MINDMAPS Study.

OBJECTIVE: Using combined individual patient data from prospective studies, we explored sex differences in depression and prognosis post-myocardial infarction (MI) and determined whether disease indices could account for found differences. METHODS: Individual patient data analysis of 10,175 MI patients who completed diagnostic interviews or depression questionnaires from 16 prospective studies from the MINDMAPS study was conducted. Multilevel logistic and Cox regression models were used to determine sex differences in prevalence of depression and sex-specific effects of depression on subsequent outcomes. RESULTS: Combined interview and questionnaire data from observational studies showed that 36% (635/1760) of women and 29% (1575/5526) of men reported elevated levels of depression (age-adjusted odds ratio = 0.68, 95% confidence interval [CI] = 0.60-0.77). The risk for all-cause mortality associated with depression was higher in men (hazard ratio = 1.38, 95% CI = 1.30-1.47) than in women (hazard ratio = 1.22, 95% CI = 1.14-1.31; sex by depression interaction: p < .001). Low left ventricular ejection fraction (LVEF) was associated with higher depression scores in men only (sex by LVEF interaction: B = 0.294, 95% CI = 0.090-0.498), which attenuated the sex difference in the association between depression and prognosis. CONCLUSIONS: The prevalence of depression post-MI was higher in women than in men, but the association between depression and cardiac prognosis was worse for men. LVEF was associated with depression in men only and accounted for the increased risk of all-cause mortality in depressed men versus women, suggesting that depression in men post-MI may, in part, reflect cardiovascular disease severity.

Decomposing the heterogeneity of depression at the person-, symptom-, and time-level: latent variable models versus multimode principal component analysis.

BACKGROUND: Heterogeneity of psychopathological concepts such as depression hampers progress in research and clinical practice. Latent Variable Models (LVMs) have been widely used to reduce this problem by identification of more homogeneous factors or subgroups. However, heterogeneity exists at multiple levels (persons, symptoms, time) and LVMs cannot capture all these levels and their interactions simultaneously, which leads to incomplete models. Our objective is to briefly review the most widely used LVMs in depression research, illustrating their use and incompatibility in real data, and to consider an alternative, statistical approach, namely multimode principal component analysis (MPCA). METHODS: We applied LVMs to data from 147 patients, who filled out the Quick Inventory of Depressive Symptomatology (QIDS) at 9 time points. Compatibility of the results and suitability of the LVMs to capture the heterogeneity of the data were evaluated. Alternatively, MPCA was used to simultaneously decompose depression on the person-, symptom- and time-level and to investigate the interactions between these levels. RESULTS: QIDS-data could be decomposed on the person-level (2 classes), symptom-level (2 factors) and time-level (2 trajectory-classes). However, these results could not be integrated into a single model. Instead, MPCA allowed for decomposition of the data at the person- (3 components), symptom- (2 components) and time-level (2 components) and for the investigation of these components' interactions. CONCLUSIONS: Traditional LVMs have limited use when trying to define an integrated model of depression heterogeneity at the person, symptom and time level. More integrative statistical techniques such as MPCA can be used to address these relatively complex data patterns and could be used in future attempts to identify empirically-based subtypes/phenotypes of depression.

Major depressive disorder as a nonlinear dynamic system: bimodality in the frequency distribution of depressive symptoms over time.

BACKGROUND: A defining characteristic of Major Depressive Disorder (MDD) is its episodic course, which might indicate that MDD is a nonlinear dynamic phenomenon with two discrete states. We investigated this hypothesis using the symptom time series of individual patients. METHODS: In 178 primary care patients with MDD, the presence of the nine DSM-IV symptoms of depression was recorded weekly for two years. For each patient, the time-series plots as well as the frequency distributions of the symptoms over 104 weeks were inspected. Furthermore, two indicators of bimodality were obtained: the bimodality coefficient (BC) and the fit of a 1- and a 2-state Hidden Markov Model (HMM). RESULTS: In 66% of the sample, high bimodality coefficients (BC>.55) were found. These corresponded to relatively sudden jumps in the symptom curves and to highly skewed or bimodal frequency distributions. The results of the HMM analyses classified 90% of the symptom distributions as bimodal. CONCLUSIONS: A two-state pattern can be used to describe the course of depression symptoms in many patients. The BC seems useful in differentiating between subgroups of MDD patients based on their life course data.

The temporal order of change in daily mindfulness and affect during mindfulness-based stress reduction.

Increases in mindfulness are assumed to lead to improvements in psychological well-being during mindfulness-based treatments. However, the temporal order of this association has received little attention. This intensive longitudinal study examines whether within-person changes in mindfulness precede or follow changes in negative affect (NA) and positive affect (PA) during a mindfulness based stress reduction (MBSR) program. This study also examines interindividual differences in the association between mindfulness and affect and possible predictors of these differences. Mindfulness, NA, and PA were assessed on a daily basis in 83 individuals from the general population who participated in an MBSR program. Multilevel autoregressive models were used to investigate the temporal order of changes in mindfulness and affect. Day-to-day changes in mindfulness predicted subsequent day-to-day changes in both NA and PA, but reverse associations did not emerge. Thus, changes in mindfulness seem to precede rather than to follow changes in affect during MBSR. The magnitude of the effects differed substantially between individuals, showing that the strength of the relationship between mindfulness and affect is not the same for all participants. These between-subjects differences could not be explained by gender, age, level of education, average level of mindfulness home practice, or baseline levels of mindfulness and affect. Mindfulness home practice during the day did predict subsequent increases in mindfulness. The findings suggest that increasing mindfulness on a daily basis can be a beneficial means to improve daily psychological well-being.

Self-attributed seasonality of mood and behavior: a report from the Netherlands study of depression and anxiety.

BACKGROUND: Seasonal changes in mood and behavior are considered to be common in the general population and in patients with psychiatric disorders. However, in several studies this seasonality could not be demonstrated. The present study examined self-attributed seasonality of depressive symptoms among patients with a lifetime diagnosis of a depressive disorder (D), an anxiety disorder (A), a comorbid depressive and anxiety disorder (DA), and healthy controls (HC). METHODS: The CIDI was used to establish diagnoses according to DSM-IV criteria in 2,168 participants of the Netherlands Study of Depression and Anxiety (NESDA). The Seasonal Pattern Assessment Questionnaire (SPAQ) was administered to assess variation in mood and behavior. RESULTS: Of the 2,168 participants 53.5% reported seasonality of mood. Highest percentages of low mood were seen in the winter months. Although all groups showed this pattern of lowered mood during the winter months, D, A, and DA were significantly (P < .001) more likely to experience seasonality is this respect. This was also shown for seasonal changes in energy, social activities, sleeping, eating, weight and for the Global Seasonality Score. A limitation of this study was the cross-sectional design. CONCLUSIONS: Seasonal variation in mood and behavior was demonstrated for both participants with a lifetime diagnosis of depression and/or anxiety disorder and for healthy controls, but patients with anxiety and/or depression were more likely to experience this seasonal variation. Clinicians should take into account that the time of the year could influence the feelings of well- and ill-being of their patients.

Mindfulness training in a heterogeneous psychiatric sample: outcome evaluation and comparison of different diagnostic groups.

OBJECTIVES: To examine outcome after mindfulness training in a heterogeneous psychiatric outpatient population and to compare outcome in different diagnostic groups. METHOD: One hundred and forty-three patients in 5 diagnostic categories completed questionnaires about psychological symptoms, quality of life, and mindfulness skills prior to and immediately after treatment. RESULTS: The mixed patient group as a whole improved significantly on all outcome measures. Differential improvement was found for different diagnostic categories with respect to psychological symptoms and quality of life: Bipolar patients did not improve significantly on these measures. This finding could be explained by longer illness duration and lower baseline severity in the bipolar category. CONCLUSION: Mindfulness training is associated with overall improvement in a heterogeneous outpatient population. Differences in outcome between diagnostic categories may be ascribed to differences in illness duration and baseline severity.

Pitfalls in the assessment, analysis, and interpretation of routine outcome monitoring (ROM) Data: results from an outpatient clinic for integrative mental health.

There is considerable debate about routine outcome monitoring (ROM) for scientific or benchmarking purposes. We discuss pitfalls associated with the assessment, analysis, and interpretation of ROM data, using data of 376 patients. 206 patients (55 %) completed one or more follow-up measurements. Mixed-model analysis showed significant improvement in symptomatology, quality of life, and autonomy, and differential improvement for different subgroups. Effect sizes were small to large, depending on the outcome measure and subgroup. Subtle variations in analytic strategies influenced effect sizes substantially. We illustrate how problems inherent to design and analysis of ROM data prevent drawing conclusions about (comparative) treatment effectiveness.

Age differences in hedonic adaptation to societal restrictions? Positive and negative affect trajectories during the first wave of the COVID-19 pandemic in 33 nations.

We examined age group differences in hedonic adaptation trajectories of positive and negative affect (PA/NA) at different arousal levels during the severe societal restrictions that governments implemented to contain the first wave of the COVID-19 pandemic (March to June 2020). Data from 10,509 participants from 33 countries and 12 weekly assessments were used (67% women, aged 18 to 85 +, on average 318 participants per country (SD = 434) and 5.6 assessments (SD = 2.5) per participant). Multilevel models (level 1: assessments, level 2: participants, level 3: countries) were fit to examine trajectories of low to high arousal PA and NA during the phase of tightening societal restrictions, the phase of stable peak restrictions, and the phase of easing restrictions separately. During the entire study period mean levels of PA were lower in emerging and young adults (aged 18-44) than older adults, whereas mean NA levels were higher. During peak societal restrictions, participants reported increasingly more PA, especially high-arousal emotions (d = .36 per month vs. .19 unaroused). NA levels decreased over time, especially high-arousal emotions (d = .35 vs. .14 p/month). These hedonic adaptation trajectories were largely similar across age groups. Nevertheless, up to 30% of the participants increased in NA and up to 6% decreased in PA, against the general trend, demonstrating substantial individual differences in emotional adaptation. Finally, heterogeneity in the effects of time on affect was larger on the individual level than the country level. Emotional recovery trajectories during the first lockdown in the COVID-19 pandemic were virtually similar across age groups in 33 countries, across valence and arousal levels, suggesting age advantages in emotional well-being remain restricted to mean-level differences rather than emotion dynamics. (PsycInfo Database Record (c) 2023 APA, all rights reserved).