Are perfectionistic strivings beneficial or detrimental to well-being and achievement? Tests of procrastination and emotion regulation as moderators.

OBJECTIVE: Researchers have called for an approach that examines the conditions under which perfectionistic strivings (PS) may be beneficial or detrimental to psychological functioning. We adopted a self-regulation perspective and tested whether individual differences in self-regulation (procrastination, emotion regulation) moderate PS's relationships with achievement and well-being in an academic/work-related achievement context. METHOD: A sample of 183 preservice teachers participated in a study that combined "traditional" longitudinal assessment (six performance situations over a 9-month period) with repeated ambulatory assessment (measuring well-being, procrastination, and emotion regulation during a total of 910 preparation phases that preceded performance situations). RESULTS: Mean levels of achievement, well-being, and emotion regulation were found to be stable over time, whereas procrastination decreased on average across preparation phases. Results from latent variable interaction models indicated that individual differences in intraindividual change in procrastination over time moderated the relationship between PS and well-being (but not achievement) in the expected direction: The less individuals decreased in procrastination over time, the more negative the relationship between PS and well-being was. Contrary to expectations, we found no evidence of a moderating effect of emotion regulation. CONCLUSION: The study contributes to a nuanced perspective on the adaptiveness of PS.

The Effects of Questionnaire Length on the Relative Impact of Response Styles in Ambulatory Assessment.

Ambulatory assessment (AA) is becoming an increasingly popular research method in the fields of psychology and life science. Nevertheless, knowledge about the effects that design choices, such as questionnaire length (i.e., number of items per questionnaire), have on AA data quality is still surprisingly restricted. Additionally, response styles (RS), which threaten data quality, have hardly been analyzed in the context of AA. The aim of the current research was to experimentally manipulate questionnaire length and investigate the association between questionnaire length and RS in an AA study. We expected that the group with the longer (82-item) questionnaire would show greater reliance on RS relative to the substantive traits than the group with the shorter (33-item) questionnaire. Students (n = 284) received questionnaires three times a day for 14 days. We used a multigroup two-dimensional item response tree model in a multilevel structural equation modeling framework to estimate midpoint and extreme RS in our AA study. We found that the long questionnaire group showed a greater reliance on RS relative to trait-based processes than the short questionnaire group. Although further validation of our findings is necessary, we hope that researchers consider our findings when planning an AA study in the future.

Exploring Within-Person Variability in Qualitative Negative and Positive Emotional Granularity by Means of Latent Markov Factor Analysis.

Emotional granularity (EG) is an individual's ability to describe their emotional experiences in a nuanced and specific way. In this paper, we propose that researchers adopt latent Markov factor analysis (LMFA) to investigate within-person variability in qualitative EG (i.e., variability in distinct granularity patterns between specific emotions across time). LMFA clusters measurement occasions into latent states according to state-specific measurement models. We argue that state-specific measurement models of repeatedly assessed emotion items can provide information about qualitative EG at a given point in time. Applying LMFA to the area of EG for negative and positive emotions separately by using data from an experience sampling study with 11,662 measurement occasions across 139 participants, we found three latent EG states for the negative emotions and three for the positive emotions. Momentary stress significantly predicted transitions between the EG states for both the negative and positive emotions. We further identified two and three latent classes of individuals who differed in state trajectories for negative and positive emotions, respectively. Neuroticism and dispositional mood regulation predicted latent class membership for negative (but not for positive) emotions. We conclude that LMFA may enrich EG research by enabling more fine-grained insights into variability in qualitative EG patterns.

Measurement reactivity in ambulatory assessment: Increase in emotional clarity over time independent of sampling frequency.

Ambulatory assessment (AA) studies are frequently used to study emotions, cognitions, and behavior in daily life. But does the measurement itself produce reactivity, that is, are the constructs that are measured influenced by participation? We investigated individual differences in intraindividual change in momentary emotional clarity and momentary pleasant-unpleasant mood over the course of an AA study. Specifically, we experimentally manipulated sampling frequency and hypothesized that the intraindividual change over time would be stronger when sampling frequency was high (vs. low). Moreover, we assumed that individual differences in dispositional mood regulation would moderate the direction of intraindividual change in momentary pleasant-unpleasant mood over time. Students (n = 313) were prompted either three or nine times a day for 1 week (data collection took place in 2019 and 2020). Multilevel growth curve models showed that momentary emotional clarity increased within participants over the course of the AA phase, but this increase did not differ between the two sampling frequency groups. Pleasant-unpleasant mood did not show a systematic trend over the course of the study, and mood regulation did not predict individual differences in mood change over time. Again, results were not moderated by the sampling frequency group. We discuss limitations of our study (e.g., WEIRD sample) and potential practical implications regarding sampling frequency in AA studies. Future studies should further systematically investigate the circumstances under which measurement reactivity is more likely to occur.

Feeling lonely during the pandemic: Towards personality-tailored risk profiles.

This is the first study to disentangle associations of within- and between-person fluctuations in loneliness and their effect on evening mood during a nationwide lockdown due to COVID-19. To contribute to the development of personality-tailored risk profiles, we additionally explored the moderating role of trait neuroticism and extraversion on the association of within- and between-person loneliness and mood. We employed an ambulatory assessment design during 21 days of nationwide lockdown in Germany (13/04/2020-03/05/2020) with two interval-based assessments. The final sample comprised 322 participants (74.5% women) aged between 15 and 82 years (M = 30.7, SD = 14.9) providing 6,084 evening assessments. Linear mixed models were used to evaluate the effects of within- and between-person fluctuations in loneliness on evening mood while controlling for unspecific effects of time, sex, and age. Moderation analysis was used to investigate the influence of neuroticism and extraversion on the relation between loneliness and mood, respectively. Results indicate that especially higher between-person loneliness (i.e. participants felt lonelier compared to the average participant) but also higher within-person loneliness (i.e. participants felt lonelier compared to their individual mean) were associated with a more unpleasant mood. Neuroticism augmented the effect of within-person loneliness, while extraversion seemed to buffer the effect of between-person loneliness on mood. Our findings underline the importance of carefully monitoring loneliness during COVID-19. The findings contribute towards the development of personality-tailored risk profiles (e.g. among newly arising risk groups for loneliness due to COVID-19). We discuss how the differential consideration of within- and between-psychological processes might help to elucidate currently mixed findings on psychological coping during the COVID-19 pandemic.

The effects of assessment intensity on participant burden, compliance, within-person variance, and within-person relationships in ambulatory assessment.

Considering the very large number of studies that have applied ambulatory assessment (AA) in the last decade across diverse fields of research, knowledge about the effects that these design choices have on participants' perceived burden, data quantity (i.e., compliance with the AA protocol), and data quality (e.g., within-person relationships between time-varying variables) is surprisingly restricted. The aim of the current research was to experimentally manipulate aspects of an AA study's assessment intensity-sampling frequency (Study 1) and questionnaire length (Study 2)-and to investigate their impact on perceived burden, compliance, within-person variability, and within-person relationships between time-varying variables. In Study 1, students (n = 313) received either 3 or 9 questionnaires per day for the first 7 days of the study. In Study 2, students (n = 282) received either a 33- or 82-item questionnaire three times a day for 14 days. Within-person variability and within-person relationships were investigated with respect to momentary pleasant-unpleasant mood and state extraversion. The results of Study 1 showed that a higher sampling frequency increased perceived burden but did not affect the other aspects we investigated. In Study 2, longer questionnaire length did not affect perceived burden or compliance but yielded a smaller degree of within-person variability in momentary mood (but not in state extraversion) and a smaller within-person relationship between state extraversion and mood. Differences between Studies 1 and 2 with respect to the type of manipulation of assessment intensity are discussed.

The blenderFace method: video-based measurement of raw movement data during facial expressions of emotion using open-source software.

This article proposes an optical measurement of movement applied to data from video recordings of facial expressions of emotion. The approach offers a way to capture motion adapted from the film industry in which markers placed on the skin of the face can be tracked with a pattern-matching algorithm. The method records and postprocesses raw facial movement data (coordinates per frame) of distinctly placed markers and is intended for use in facial expression research (e.g., microexpressions) in laboratory settings. Due to the explicit use of specifically placed, artificial markers, the procedure offers the simultaneous measurement of several emotionally relevant markers in a (psychometrically) objective and artifact-free way, even for facial regions without natural landmarks (e.g., the cheeks). In addition, the proposed procedure is fully based on open-source software and is transparent at every step of data processing. Two worked examples demonstrate the practicability of the proposed procedure: In Study 1(N= 39), the participants were instructed to show the emotions happiness, sadness, disgust, and anger, and in Study 2 (N= 113), they were asked to present both a neutral face and the emotions happiness, disgust, and fear. Study 2 involved the simultaneous tracking of 14 markers for approximately 12 min per participant with a time resolution of 33 ms. The measured facial movements corresponded closely to the assumptions of established measurement instruments (EMFACS, FACSAID, Friesen & Ekman, 1983; Ekman & Hager, 2002). In addition, the measurement was found to be very precise with sub-second, sub-pixel, and sub-millimeter accuracy.

Does the distribution frequency matter? A subgroup specific analysis of the effectiveness of the EU School Fruit and Vegetable Scheme in Germany comparing twice and thrice weekly deliveries.

OBJECTIVE: The present study aimed to examine the effectiveness of two different implementation forms of the EU School Fruit and Vegetable Scheme (SFVS). DESIGN: A quasi-experimental design was applied including a thrice as well as a twice weekly intervention group. Repeated 24 h dietary recalls were used to measure children's fruit and vegetable (F&V) intake. Effects were analysed on days with and without F&V deliveries using hierarchical linear regression models. SETTING: Twelve primary schools in North Rhine-Westphalia, Germany. SUBJECTS: Third and fourth graders (n 664). RESULTS: Average daily F&V intake at pre-intervention was 0·84 frequencies in the thrice weekly intervention group, 0·90 frequencies in the twice weekly intervention group and 1·25 frequencies in the control group. Providing children thrice weekly with F&V increased children's F&V intake on average by 0·96 (P<0·001) frequencies/d. The effects were higher on days with (1·07; P<0·001) than on days without (0·75; P<0·001) F&V deliveries. Distributing F&V twice weekly resulted in an increase of 0·75 (P<0·001) frequencies/d on average, again with higher effects on days with (1·30; P<0·001) than without (0·48; P<0·003) F&V deliveries. Subgroup analysis revealed some indications for differential effectiveness only in the twice weekly intervention group. CONCLUSIONS: The SFVS with thrice or twice weekly deliveries of F&V led to a significant increase in children's F&V intake on days with and without deliveries. The latter might provide an indication of positive long-term effects of the scheme. The scheme shows equal efficiency for almost all subgroups.

The assessment of emotional clarity via response times to emotion items: shedding light on the response process and its relation to emotion regulation strategies.

Researchers have begun to use response times (RTs) to emotion items as an indirect measure of emotional clarity. Our first aim was to scrutinise the properties of this RT measure in more detail than previously. To be able to provide recommendations as to whether (and how) emotional intensity - as a possible confound - should be controlled for, we investigated the specific form of the relation between emotional intensity and RTs to emotion items. In particular, we assumed an inverted U-shaped relation at the item level. Moreover, we analysed the RT measure's convergent validity with respect to individuals' confidence in their emotion ratings. As a second aim, we compared the predictive validity of emotional clarity measures (RT measure, self-report) with respect to daily emotion regulation. The results of three experience sampling studies showed that the association between emotional intensity and RT followed an inverted U shape. RT was in part related to confidence. Emotional clarity measures were unrelated to reappraisal. There was some evidence that lower emotional clarity was related to a greater use of suppression. The findings highlight that emotional intensity and squared emotional intensity should be controlled for when using the RT measure of emotional clarity in future research.

Modeling careless responding in ambulatory assessment studies using multilevel latent class analysis: Factors influencing careless responding.

As the number of studies using ambulatory assessment (AA) has been increasing across diverse fields of research, so has the necessity to identify potential threats to AA data quality such as careless responding. To date, careless responding has primarily been studied in cross-sectional surveys. The goal of the present research was to identify latent profiles of momentary careless responding on the occasion level and latent classes of individuals (who differ in the distribution of careless responding profiles across occasions) on the person level using multilevel latent class analysis (ML-LCA). We discuss which of the previously proposed indices seem promising for investigating careless responding in AA studies, and we show how ML-LCA can be applied to model careless responding in intensive longitudinal data. We used data from an AA study in which the sampling frequency (3 vs. 9 occasions per day, 7 days, n = 310 participants) was experimentally manipulated. We tested the effect of sampling frequency on careless responding using multigroup ML-LCA and investigated situational and respondent-level covariates. The results showed that four Level 1 profiles ("careful," "slow," and two types of "careless" responding) and four Level 2 classes ("careful," "frequently careless," and two types of "infrequently careless" respondents) could be identified. Sampling frequency did not have an effect on careless responding. On the person (but not the occasion) level, motivational variables were associated with careless responding. We hope that researchers might find the application of an ML-LCA approach useful to shed more light on factors influencing careless responding in AA studies. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Exploring dynamics in mood regulation--mixture latent Markov modeling of ambulatory assessment data.

OBJECTIVE: To illustrate how fluctuation patterns in ambulatory assessment data with features such as few categorical items, measurement error, and heterogeneity in the change pattern can adequately be analyzed with mixture latent Markov models. The identification of fluctuation patterns can be of great value to psychosomatic research concerned with dysfunctional behavior or cognitions, such as addictive behavior or noncompliance. In our application, unobserved subgroups of individuals who differ with regard to their mood regulation processes, such as mood maintenance and mood repair, are identified. METHODS: In an ambulatory assessment study, mood ratings were collected 56 times during 1 week from 164 students. The pleasant-unpleasant mood dimension was assessed by the two ordered categorical items unwell-well and bad-good. Mixture latent Markov models with different number of states, classes, and degrees of invariance were tested, and the best model according to information criteria was interpreted. RESULTS: Two latent classes that differed in their mood regulation pattern during the day were identified. Mean classification probabilities were high (>0.88) for this model. The larger class showed a tendency to stay in and return to a moderately pleasant mood state, whereas the smaller class was more likely to move to a very pleasant mood state and to stay there with a higher probability. CONCLUSIONS: Mixture latent Markov models are suitable to obtain information about interindividual differences in stability and change in ambulatory assessment data. Identified mood regulation patterns can serve as reference for typical mood fluctuation in healthy young adults.

Coping under a COVID-19 lockdown: patterns of daily coping and individual differences in coping repertoires.

BACKGROUND: Polyregulation-the concurrent or sequential use of multiple strategies to regulate affect or cope with stressors-is a frequent but understudied phenomenon. OBJECTIVES: We aimed to identify patterns of daily coping and individuals' coping repertoires (i.e., range of coping patterns employed across situations) during a COVID-19 pandemic lockdown. We investigated day-level covariates (appraisals, worrying, mood) of daily coping patterns and person-level covariates (psychopathology, average mood) of coping repertoires. Design: A non-representative community sample (n = 322, 15-82 years old) participated in a 21-day ambulatory assessment study. METHODS: We applied multilevel latent class analysis.. RESULTS: We identified seven daily coping patterns and ten classes of individuals differing in the size of their coping repertoire and their propensity for polyregulation. Daily coping patterns differed in daily perceived controllability and mood (but not in daily worrying or stress). At the person level, individuals with a higher level of average coronavirus-related worrying more frequently engaged in a high degree of polyregulation. The size of individuals' coping repertoire was unrelated to psychopathology and average mood. CONCLUSION: The findings provide insights into the composition of daily coping patterns and individuals' coping repertoires during crisis periods and contribute to a new polyregulation perspective on coping.

Individual differences in contingencies between situation characteristics and personality states.

Contingencies between situational variables and psychological states have been proposed as key individual difference variables by many theoretical approaches to personality. Despite their relevance, the basic properties, nomological correlates, and factor structure of individual differences in contingencies have not been examined so far. We address these fundamental questions in five studies with overall N = 952 participants and N = 32,052 unique assessments. Individual differences in situation characteristic-state contingencies (SCSCs) between DIAMONDS situation characteristics and Big Five personality states were examined in everyday life. SCSCs showed substantial variation across participants, and individual differences in them were moderately reliable (average meta-analytic reliability = .47) and short-term stable (average meta-analytic latent stability = .43). They were weakly and inconsistently related to average personality states, self-reported personality traits, subjective happiness, and sociodemographic variables across studies. However, there were meaningful intercorrelations among SCSCs that could be described by four factors: contingencies involving (1) positive states and situational problems, (2) positive states and situational rewards, (3) thinking/work and requirements of thinking/work, and (4) neurotic states. Overall, our findings support the notion of SCSCs as potentially important individual difference variables, and we sketch future lines of research on contingencies. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Negative Emotion Differentiation Attenuates the Within-Person Indirect Effect of Daily Stress on Nightly Sleep Quality Through Calmness.

The ability to differentiate between negative emotional states [negative emotion differentiation (NED)] has been conceptualized as a trait that facilitates effective emotion regulation and buffers stress reactivity. In the present research, we investigated the role of NED in within-person processes of daily affect regulation and coping during times of stress (the first COVID-19-related pandemic lockdown in April 2020). Using intensive longitudinal data, we analyzed whether daily stress had an indirect effect on sleep quality through calmness in the evening, and we tested whether NED moderated this within-person indirect effect by buffering the link between daily stress and calmness in the evening. A non-representative community sample (n = 313, 15-82 years old) participated in a 21-day ambulatory assessment with twice-daily surveys. The results of multilevel mediation models showed that higher daily stress was related to within-day change in calmness from morning to evening, resulting in less calmness in the evening within persons. Less calmness in the evening, in turn, was related to poorer nightly sleep quality within persons. As expected, higher NED predicted a less negative within-person link between daily stress and calmness in the evening, thereby attenuating the indirect effect of daily stress on nightly sleep quality through calmness. This effect held when we controlled for mean negative emotions and depression. The results provide support for a diathesis-stress model of NED, and hence, for NED as a protective factor that helps to explain why some individuals remain more resilient during times of stress than others.

Development of a Novel Method of Emotion Differentiation That Uses Open-Ended Descriptions of Momentary Affective States.

Emotion differentiation (ED) has been conceptualized as a trait that facilitates emotion regulation and increases well-being. Yet basic questions remain unanswered about how best to assess it and whether favorable outcomes can be observed only during times of stress. The goal of the present research was to develop a novel behavioral (specificity) index of ED. We conducted two daily diary studies (N = 111-190) in which we included different measures of ED, well-being, and emotion regulation. The different ED measures were largely unrelated to each other. In both studies, the specificity index of ED showed a positive association with daily well-being, but in Study 2, this association held only on days with a negative event. Results regarding ED and the use of emotion-regulation strategies were inconsistent across strategies and studies. Possible reasons for these mixed results (e.g., sample selection, context sensitivity of regulation strategies) are discussed.

Is it better not to think about it? Effects of positive and negative perfectionistic cognitions when there is increased pressure to perform.

With the present research, we aimed to extend prior knowledge on the associations between dispositional perfectionism, perfectionistic cognitions and indicators of distress by considering both the level of between-person differences and the level of within-person fluctuations. We conducted two studies in which we assessed dispositional perfectionism once, plus we assessed perfectionistic cognitions across a predefined period of time (Study 1) and on a daily level (Study 2) during a highly demanding period of time. We found evidence for differential bivariate and unique associations of perfectionistic strivings cognitions (PSC) and perfectionistic concerns cognitions (PCC) with dispositional perfectionistic strivings (DPS) and dispositional perfectionistic concerns (DPC), perfectionism-specific cues, and indicators of distress. Beyond this, PCC emerged as an important mediator of the effects of DPS and DPC on distress.

Modeling individual differences in emotion regulation repertoire in daily life with multilevel latent profile analysis.

Emotion regulation (ER) repertoire-the range of different ER strategies an individual utilizes across situations-is assumed to enable more adaptive ER and greater well-being. ER repertoire has been operationalized by a quantitative index (sum of ER strategies across situations) or by applying a person-centered approach to global self-reports of dispositional ER. We aimed to assess ER repertoire in daily life by using an experience sampling methodology (ESM) and a person-centered approach that could account for nested data. We used multilevel latent profile analyses of ESM data (N = 179, 9-10 prompts per day over 21 days) to (a) group the occasions into latent profiles of momentary ER strategies, (b) group individuals whose distributions of ER profiles differed across occasions into latent classes, and (c) examine well-being correlates of class membership at the person level. At the occasion level, we identified nine ER profiles that differed in degree of use (e.g., no use of any vs. strong use of all strategies) and in specific combinations of strategies (e.g., situation selection and acceptance vs. suppression and ignoring). At the person level, we identified 5 classes of individuals differing in the degree to which they used various momentary ER profiles versus one predominant profile across situations. Well-being was highest for individuals who used multiple ER profiles of active strategies and lowest for individuals who used ER profiles focused on suppression. Hence, both ER repertoire width and the specific make-up of the ER repertoire were relevant for the relation between ER repertoire and well-being. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Structural equation modeling of multitrait-multimethod data: different models for different types of methods.

The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods used) should guide the choice of the statistical model to analyze the data. In this respect, the authors distinguish between (a) interchangeable methods, (b) structurally different methods, and (c) the combination of both kinds of methods. The authors present an appropriate model for each type of method. All models allow separating measurement error from trait influences and trait-specific method effects. With respect to interchangeable methods, a multilevel confirmatory factor model is presented. For structurally different methods, the correlated trait-correlated (method-1) model is recommended. Finally, the authors demonstrate how to appropriately analyze data from MTMM designs that simultaneously use interchangeable and structurally different methods. All models are applied to empirical data to illustrate their proper use. Some implications and guidelines for modeling MTMM data are discussed.

Illegitimate tasks reach into afterwork hours: A multilevel study.

This study examines illegitimate tasks as a specific type of job stressors. Illegitimate tasks comprise unreasonable and unnecessary tasks and refer to inappropriate task assignments that go beyond an employee's role requirements. Building on the stressor-detachment model, we hypothesized that illegitimate tasks experienced during the day predict high negative affect and low self-esteem at the end of the workday, which in turn should predict poor psychological detachment from work during evening hours, resulting in sustained high levels of negative affect and low self-esteem at bedtime. Over the course of 1 workweek, 137 employees completed daily surveys at the end of the workday and at bedtime (total of 567 days). Multilevel path modeling revealed a distinct pattern of findings at the day and the person level. At the day level, unnecessary tasks predicted high negative affect and low self-esteem at the end of the workday, with low self-esteem predicting poor psychological detachment from work during afterwork hours. Poor psychological detachment predicted a further increase in negative affect and a decrease in self-esteem over evening hours. At the between-person level, unreasonable tasks were related to high negative affect and low self-esteem at the end of the workday, with negative affect being related to poor psychological detachment from work. Overall, the findings demonstrate that illegitimate tasks are associated with unfavorable states at the end of the workday and are indirectly related to poor psychological detachment from work, undermining recovery from the stressful events experienced at work. (PsycINFO Database Record

Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results?

Convergent and discriminant validity of psychological constructs can best be examined in the framework of multitrait-multimethod (MTMM) analysis. To gain information at the level of single items, MTMM models for categorical variables have to be applied. The CTC(M-1) model is presented as an example of an MTMM model for ordinal variables. Based on an empirical application of the CTC(M-1) model, a complex simulation study was conducted to examine the sample size requirements of the robust weighted least squares mean- and variance-adjusted chi(2) test of model fit (WLSMV estimator) implemented in Mplus. In particular, the simulation study analysed the chi(2) approximation, the parameter estimation bias, the standard error bias, and the reliability of the WLSMV estimator depending on the varying number of items per trait-method unit (ranging from 2 to 8) and varying sample sizes (250, 500, 750, and 1000 observations). The results showed that the WLSMV estimator provided a good -- albeit slightly liberal -- chi(2) approximation and stable and reliable parameter estimates for models of reasonable complexity (2-4 items) and small sample sizes (at least 250 observations). When more complex models with 5 or more items were analysed, larger sample sizes of at least 500 observations were needed. The most complex model with 9 trait-method units and 8 items (72 observed variables) requires sample sizes of at least 1000 observations.