Dynamic Structural Equation Modeling Research Articles

On liking how you look and feeling sexy: Quantifying the overlap between sexual desirability and body satisfaction in a sample of Australian Grindr users

The body image field aims to cultivate positive body image. To do so, it must appreciate factors contributing to positive body image. Sexual desirability is one such factor. Using experience sampling data from Australian Grindr users, we aimed to quantify the overlap between sexual desirability and body satisfaction. We found sexual desirability and body satisfaction correlated strongly between- (r = .90) and within-persons (rMedian =.60). Using dynamic structural equation modeling, we analyzed 238 participants' data (T = 9058), finding that sexual desirability and body satisfaction were bidirectionally related – previous sexual desirability predicted current body satisfaction (β = 0.22) and vice versa (β = 0.17). Participants’ average body satisfaction tended to be higher when sexual desirability contributed more to body satisfaction (r = .31) and was more stable across time (r = .19). We found sexual desirability and body satisfaction overlap considerably and that sexual desirability may contribute more to body satisfaction than vice versa. Our results suggest that (1) sexual desirability and its dynamics across time influence body satisfaction, and (2) research on sexual desirability and its relationship with body image should be a focus for the field. We discuss avenues for future research on sexual desirability.

Stress and emotion in a locked campus: the moderating effects of resilience and loneliness.

The aim of this study is to investigate the dynamic relationship between Chinese students' emotions and stress during a strict lockdown period in a university setting and the context of a global pandemic. Dynamic structural equation modeling was used to investigate the moderating role of resilience and loneliness in this relationship. The participants consisted of 112 students. Based on loneliness and resilience measures and the intensive tracking of emotional stress over a 21-day period, the results of data analysis indicated that the students' overall levels of positive emotions were low and relatively independent of negative emotions. Negative emotions were significantly autoregressive and their baseline was closely related to the individual's overall feelings of stress and loneliness levels, fluctuating with feelings of stress. The results confirm the hypothesis that resilience helps to stabilize emotions. Individuals with low resilience may be more emotionally sensitive in confined environments, while receiving social support may help to alleviate low moods.

Dynamic Structural Equation Models: Promising Yet Concerning

Dynamic Structural Equation Model (DSEM) is a powerful statistical modeling approach that has recently gained popularity among researchers studying intensive longitudinal data. Despite its exciting potential, the stability and replicability of DSEM is yet to be closely examined. This study empirically investigates DSEM using recently published data to explore its strengths and potential limitations. The results show that while some of its parameter estimates are stable, others are characterized by substantial variation as a function of seemingly innocuous initial model estimation conditions. Indeed, some parameters fluctuate between significance and non-significance for the same model estimated using the same data. The instability of DSEM estimates poses a serious threat to the internal and external validity of conclusions drawn from its analyses, challenging the reproducibility of findings from applied research. Given the recent focus on the replication crisis in psychology, it is critical to address these issues as the popularity of DSEM in psychological research continues to rise. Several potential solutions are investigated to address this problem and recommendations of best practice are offered to applied researchers who plan to use DSEM in intensive longitudinal data analysis. KEYWORDS: Dynamic Structural Equation Model; Bayesian; Robust Estimation; Intensive Longitudinal Data

From cross-lagged effects to feedback effects: Further insights into the estimation and interpretation of bidirectional relations.

Bidirectional relations have long been of interest in psychology and other social behavioral sciences. In recent years, the widespread use of intensive longitudinal data has provided new opportunities to examine dynamic bidirectional relations between variables. However, most previous studies have focused on the effect of one variable on the other (i.e., cross-lagged effects) rather than the overall effect representing the dynamic interplay between two variables (i.e., feedback effects), which we believe may be due to a lack of relevant methodological guidance. To quantify bidirectional relations as a whole, this study attempted to provide guidance for the estimation and interpretation of feedback effects based on dynamic structural equation models. First, we illustrated the estimation procedure for the average and person-specific feedback effects. Then, to facilitate the interpretation of feedback effects, we established an empirical benchmark by quantitatively synthesizing the results of relevant empirical studies. Finally, we used a set of empirical data to demonstrate how feedback effects can help (a) test theories based on bidirectional relations and (b) reveal correlates of individual differences in bidirectional relations. We also discussed the broad application prospects of feedback effects from a dynamic systems perspective. This study provides guidance for applied researchers interested in further examining feedback effects in bidirectional relations, and the shift from focusing on cross-lagged effects only to a comprehensive consideration of feedback effects may provide new insights into the study of bidirectional relations.

DYNAMIC IMPACTS OF FAMILY CONFLICT ON ELDER ABUSE AND NEGLECT AMONG ADRD CAREGIVERS

Abstract Conflict with other family members impacts dementia caregivers’ well-being and stress-appraisals and may also influence their use of elder abuse and neglect (EAN). To test this, we utilized latent class analysis to classify spouse, adult child, grandchild, and nontraditional (step- and in-laws) caregivers (N = 453) based on family conflict levels at baseline. Caregivers were classified into four groups: “low,” “moderate,” “high,” and “EAN accusations.” Spouses were significantly more likely to be in the “low” class compared to other classes. Nontraditional caregivers were more likely to be in the “EAN accusations” class versus the “moderate” class (β = 1.73, SE = .70, p < .05). Belonging to the EAN accusations class predicted EAN at baseline (t = 3.728, p < .001). Next, dynamic structural equation modeling was used to test whether stress from family conflict on a given day predicts use of EAN behaviors. Family conflict stress predicted EAN on the same day (β = 0.05, 95% CI = 0.03-0.07), but not the subsequent day (CL= -0.01, 95% CI = 0.03-0.02). Similar models were conducted for each relationship type. The effect of family conflict stress on EAN was not significant for spouse and grandchildren but remained significant for adult child and non-traditional caregivers. Findings suggest interventions related to conflict management and communication among caregiving families may be beneficial new intervention targets for reducing EAN in ADRD. Addressing family conflict may be most important when the caregiver is an adult child or nontraditional relationship.

Purpose and goal pursuit as a self‐sustaining system: Evidence of daily within‐person reciprocity among adolescents in self‐driven learning

AbstractObjectiveDespite long‐standing assumptions that a sense of purpose in life and goal pursuit are mutually supportive, empirical evidence of their reciprocity remains deficient. In the context of a unique out‐of‐school time program that empowers youth to pursue passions through self‐driven learning, we examined whether purpose and one aspect of goal pursuit—perceptions of goal progress—work together to sustain themselves and each other over time.MethodAdolescents (N = 321) completed daily surveys throughout program enrollment (Menrollment = 69.09 days). Through dynamic structural equation modeling, we derived within‐person patterns of day‐to‐day prediction as well as individual differences in these patterns.ResultsWe found purpose and perceived goal progress exhibited significant daily inertia (i.e., autoregressive prediction) and reciprocity (i.e., cross‐lagged prediction) at the within‐person level. We also found initial evidence suggesting (a) tighter reciprocity was related to greater perceived goal progress overall and (b) people with greater purpose inertia may rely less on making goal progress to sustain momentum.ConclusionsWith evidence of daily purpose‐progress reciprocity, the field can look forward to replicating this work in other contexts, diving deeper into interesting patterns of within‐person dynamics, and developing interventions to support youth striving.

Using learning analytics with temporal modeling to uncover the interplay of before-class video viewing engagement, motivation, and performance in an active learning context

Video learning is a crucial component in flipped learning related to learners' readiness to attend more complex face-to-face activities. However, instructors may not know students' preparedness and motivation for each class. This study intended to examine the underlying mechanism between students' before-class video-viewing engagement and performance. We investigated learners' motivation (i.e., autonomous and controlled motivation) based on self-determination theory and controlled for their gender, age, and prior performance. An integrated temporal model was built under the dynamic structural equation modeling framework. Participants were 118 Taiwanese graduate students (78 females and 40 males) with a mean age of 26.14 years old. Study findings showed that students engage with the video content in a consistent viewing pattern, which has a significant relationship with their motivation and academic performance from week to week. The frequency of skipping backward was negatively associated with controlled motivation, while the frequency of pauses was positively associated with autonomous and controlled motivation. A high frequency of skipping forward predicted lower learning performance. Besides, a higher ratio of skipping backward predicted higher controlled motivation. Male students, older students, and students with higher prior performance exhibited higher autonomous motivation, which was related to better learning performance. Understanding these relationships can help educators and instructional designers develop more effective strategies for fostering students’ preparedness, engagement and success in active learning contexts. The study findings were discussed considering theoretical advancement and practical implications for enhancing personalized and active learning in higher education to achieve educational equity.

Control-value appraisals and academic emotions: An intensive longitudinal examination of reciprocal effects.

This study examined the reciprocal relation between lesson-specific perceived cognitive appraisals and academic emotions on an intra-individual level. A daily diary study was conducted using a sample of 266 Chinese Han students (Grades 7-8; 56.8% boys; Mage = 13.70, SDage = 0.52) during 10 mathematics lessons in 2022. Standardized questionnaires were also administered to these students before the daily diary study. The results of the dynamic structural equation modeling revealed significant reciprocal relations between cognitive appraisals and academic emotions within early adolescents and highlighted the role of emotions in guiding cognitive appraisals. Additionally, the study identified similarities and differences in the inter-individual relation between appraisals and emotions across self-reported questionnaires and daily diary measures.

Examining Environmental Predictors of Behavioral Symptoms of Dementia Using Dynamic Structural Equation Modelling

AbstractBackgroundMost persons with Alzheimer’s disease and related dementias (ADRD) experience behavioral symptoms as a result of exposure to stressors in the environment. Daily diaries can capture fluctuations in behavioral symptoms in response to environmental stressors. The purpose of this multi‐time series longitudinal study was to determine whether potential protective factors, caregiver reciprocity and a shared activity were associated with the number of behavioral symptoms person with ADRD.MethodA community‐dwelling sample of 453 caregivers for persons with ADRD (age 18+) completed 21 days of once‐a‐day diary surveys. Caregiver perceived reciprocity was assessed using a question asking, “How satisfied were you with amount of affection or appreciation your relative with dementia showed towards you?” Responses were coded using a Likert scale with 1‐Not at all and 5‐Very much. Caregivers were asked whether they did a pleasant non‐care activity with their relative and about a presence of eight different behavioral symptoms in persons with ADRD. We used a two‐level dynamic structural equation model to examine the relationship between the number of different behavioral symptoms, caregiver reciprocity and a shared activity on a given day, and the following day.ResultCaregivers completed 7,783 diaries. Caregivers were mostly female (87.4%), non‐Hispanic white (51.4%) with a mean age of 53 years (SD = 14) caring for a parent/parent‐in‐law/stepparent (61.5%) with a mean age of 79 years (SD = 9). Caregiver perceived reciprocity had a significant direct effect on the number of behavioral symptoms experienced the same day and the next day. While no significant main or cross‐lagged effects were found between shared activity and behavioral symptoms, estimates suggest the impact was negligible (0.7% increase).ConclusionWe found that caregiver perceived reciprocity may reduce the number of behavioral symptoms a person with ADRD has that day and the following day. These findings support the growing body of theoretical and empirical work suggesting caregivers are an important feature of the environment and influence behavioral symptom presentation.

Novel machine learning approaches for improving the reproducibility and reliability of functional and effective connectivity from functional MRI

Objective. New measures of human brain connectivity are needed to address gaps in the existing measures and facilitate the study of brain function, cognitive capacity, and identify early markers of human disease. Traditional approaches to measure functional connectivity (FC) between pairs of brain regions in functional MRI, such as correlation and partial correlation, fail to capture nonlinear aspects in the regional associations. We propose a new machine learning based measure of FC ( ML.FC ) which efficiently captures linear and nonlinear aspects. Approach. To capture directed information flow between brain regions, effective connectivity (EC) metrics, including dynamic causal modeling and structural equation modeling have been used. However, these methods are impractical to compute across the many regions of the whole brain. Therefore, we propose two new EC measures. The first, a machine learning based measure of effective connectivity ( ML.EC ), measures nonlinear aspects across the entire brain. The second, Structurally Projected Granger Causality ( SP.GC ) adapts Granger Causal connectivity to efficiently characterize and regularize the whole brain EC connectome to respect underlying biological structural connectivity. The proposed measures are compared to traditional measures in terms of reproducibility and the ability to predict individual traits in order to demonstrate these measures’ internal validity. We use four repeat scans of the same individuals from the Human Connectome Project and measure the ability of the measures to predict individual subject physiologic and cognitive traits. Main results. The proposed new FC measure of ML.FC attains high reproducibility (mean intra-subject R 2 of 0.44), while the proposed EC measure of SP.GC attains the highest predictive power (mean R 2 across prediction tasks of 0.66). Significance. The proposed methods are highly suitable for achieving high reproducibility and predictiveness and demonstrate their strong potential for future neuroimaging studies.

Long-term aging trajectories of the accumulation of disease burden as predictors of daily affect dynamics and stressor reactivity.

Multiple-timescale studies provide new opportunities to examine how developmental processes that evolve at different cadences are intertwined. Developmental theories of emotion regulation suggest that the long-term, slowly evolving age-related accumulation of disease burden should shape short-term, faster evolving (daily) affective experiences. To empirically examine this proposition, we combined data from 123 old adults (65-69 years, 47% women) and 32 very old adults (85-88 years, 59% women) who provided 20 + year within-person longitudinal data on physician-rated morbidity and subsequently also completed repeated daily-life assessments of stress and affect six times a day over 7 consecutive days as they were going about their daily-life routines. Results from models that simultaneously articulate growth and intraindividual variability processes (in a dynamic structural equation modeling framework) revealed that individual differences in long-term aging trajectories of the accumulation of disease burden were indeed predictive of differences in three facets of affective dynamics that manifest in everyday life. In particular-over and above mean levels of disease burden-older adults whose disease burden had increased more over the past 20 years had higher base level of negative affect in their daily lives, more emotional reactivity to the experience of daily stressors, and more moment-to-moment fluctuations in negative affect that was unrelated to stressors (affective systemic noise). We highlight that developmental processes evolving over vastly different timescales are intertwined, and speculate how new knowledge about those relations can inform developmental theories of emotion regulation and daily-life functioning. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Investigating Moderation Effects at the Within-Person Level Using Intensive Longitudinal Data: A Two-Level Dynamic Structural Equation Modelling Approach in Mplus

Recent technological advances have provided new opportunities for the collection of intensive longitudinal data. Using methods such as dynamic structural equation modeling, these data can provide new insights into moment-to-moment dynamics of psychological and behavioral processes. In intensive longitudinal data (t > 20), researchers often have theories that imply that factors that change from moment to moment within individuals act as moderators. For instance, a person’s level of sleep deprivation may affect how much an external stressor affects mood. Here, we describe how researchers can implement, test, and interpret dynamically changing within-person moderation effects using two-level dynamic structural equation modeling as implemented in the structural equation modeling software Mplus. We illustrate the analysis of within-person moderation effects using an empirical example investigating whether changes in spending time online using social media affect the moment-to-moment effect of loneliness on depressive symptoms, and highlight avenues for future methodological development. We provide annotated Mplus code, enabling researchers to better isolate, estimate, and interpret the complexities of within-person interaction effects.

I feel smart today! A daily diary study on narcissism and self-assessed intelligence

While the objective level of intelligence is not associated with narcissism, relations to self-assessed intelligence (SAI) have been repeatedly reported. Existing research suggests that different facets of narcissism may have different associations with SAI. In the current daily diary study ( N = 176; N = 3975 total observations), we employed dynamic structural equation modeling to examine the relationships between facets of trait and state narcissism (i.e., agentic, antagonistic, and neurotic) and the level, variability, and instability of SAI assessed over 28 consecutive days. Both trait and state narcissism were consistently related to SAI: agentic narcissism showed a positive relationship, whereas antagonistic and neurotic narcissism showed negative relationships with SAI. Trait agentic and state antagonistic narcissism predicted greater variability of SAI scores throughout the study, while neither trait nor state narcissism predicted the instability of SAI. Finally, we found that experiencing increased agentic narcissism on one day, predicted perceiving oneself as more intelligent on the next day, but feeling smarter did not predict feeling narcissistic over time. Moreover, we demonstrated that differentiating between narcissism facets yielded more theoretically accurate results compared to distinguishing between grandiose and vulnerable narcissism.

The daily dynamics of basic psychological need satisfaction at work, their determinants, and their implications: An application of Dynamic Structural Equation Modeling

ABSTRACT Drawing on self-determination theory, this study focuses on the person- and occasion-specific components of the daily dynamics of employees’ global psychological need satisfaction at work. Predictors (job demands related to information and communication technologies, segmentation norms, and workload) and outcomes (perceived productivity, psychological detachment, work-family conflict, job satisfaction, and personal satisfaction) were also examined across both levels to better grasp the mechanisms underlying these short-term dynamics. A total of 129 French employees filled out questionnaire surveys at the end of each workday for five days (521 observations). Results from Dynamic Structural Equation Modeling (DSEM) showed clear associations between need satisfaction, the predictors, and the outcomes at the person-specific level. However, and although need satisfaction levels were found to fluctuate on a daily basis, they seemed immune to the effects of daily fluctuations in predictor levels, and unlikely to generate matching fluctuations in outcome levels. These results suggest strong homoeostatic processes protecting employees’ functioning against daily fluctuations, but that the accumulation of such fluctuations over the work week may jeopardize these processes.

Within-patient association between emotion regulation and outcome in prolonged exposure for posttraumatic stress disorder.

Difficulties with emotion regulation (ER) are a risk factor for the development and maintenance of posttraumatic stress disorder (PTSD). Less is known about temporal relations between ER and PTSD symptom change during treatment, including whether ER may represent a more potent change ingredient for some patients relative to others. This study examined the association between within-patient changes in ER and next-session PTSD symptom change and whether this association was more pronounced for patients with poorer baseline ER, more severe depression, or higher borderline personality disorder symptoms. Data derived from a randomized controlled trial (NCT01600456) in which 149 adults with PTSD received up to 10 sessions of prolonged exposure (PE) or PE + sertraline. Patients rated difficulties with ER and PTSD symptoms repeatedly during treatment. Moderators were assessed at baseline. Cross-lagged, dynamic structural equation models revealed that ER improvements were associated with next-session reductions in PTSD (standardized effect = 0.13). PTSD symptom reduction was also associated with next-session ER improvement (standardized effect = 0.34). Moderator analyses revealed that the within-person ER-PTSD symptoms association was stronger for patients with higher baseline depression (standardized effect = 0.39). Reductions in PTSD symptoms may facilitate ER improvements during PE and PE augmented with sertraline rather than improvements in ER producing changes in PTSD symptoms. For patients with higher severity co-occurring depression, ER may represent a more active change ingredient. PE therapists could therefore consider placing particular emphasis on improving ER capabilities when working with this subgroup of patients. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Parental investment or parenting stress? Examining the links between poverty and child development in Ireland

ABSTRACT This study investigates the relationship between multidimensional household poverty and cognitive and behavioural development during the formative years of childhood (from 9 months to 9 years), using nationally representative longitudinal data from Ireland for the cohort of children born in 2007-2008. The results indicate substantial inequalities in Irish children’s cognitive and behavioural outcomes at age 9 by multidimensional poverty duration. Children with at least one spell in poverty (out of four interviews) have worse cognitive and behavioural outcomes. Dynamic structural equation models provide evidence in support of a hybrid family investment/family stress model. Although family investment processes account for some of the cumulative effects of childhood poverty on cognitive outcomes, family stress processes help explain the links between poverty and both cognitive and behaviour outcomes in early childhood. Overall, poverty is strongly related to child outcomes over time via the direct effects of current poverty on child outcomes and path dependency in both poverty and child outcomes over time. There are also indirect effects via the two child outcomes reinforcing each other as children grow older (with the effects of behaviour problems dominating those of cognitive ability), even as the parental investment and maternal stress pathways become less pronounced.

A dynamic perspective on depressive symptoms during the first year postpartum.

The current study used novel methodology to characterize intraindividual variability in the experience of dynamic, within-person changes in postpartum depressive (PPD) symptoms across the first year postpartum and evaluated maternal and infant characteristics as predictors of between-person differences in intraindividual variability in PPD symptoms over time. With a sample of 322 low-income Mexican-origin mothers (Mage = 27.79; SD = 6.48), PPD symptoms were assessed at 11 time points from 3 weeks to 1 year postpartum (Edinburgh Perinatal Depression Scale; Cox & Holden, 2003). A prenatal cumulative risk index was calculated from individual psychosocial risk factors. Infant temperamental negativity was assessed via a maternal report at the infant age of 6 weeks (Infant Behavior Questionnaire; Putnam et al., 2014). Multilevel location scale analyses in a dynamic structural equation modeling (Asparouhov et al., 2018) framework were conducted. Covariates included prenatal depressive symptoms. On average, within-mother change in depressive symptoms at one time point was found to carry over to the next time point. Nonnull within-mother volatility in PPD symptoms reflected substantial ebbs and flows in PPD symptoms over the first year postpartum. Results of the between-level model demonstrated that mothers differed in their equilibriums, carryover, and volatility of their PPD symptoms. Mothers with more negative infants and those with higher prenatal cumulative risk exhibited higher equilibriums of PPD symptoms and more volatility in symptoms but did not differ in their carryover of PPD symptoms. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Workers' emotional exhaustion and mental well-being over the COVID-19 pandemic: a Dynamic Structural Equation Modeling (DSEM) approach.

The COVID-19 pandemic has presented significant challenges to the workforce, particularly concerning emotional and mental well-being. Given the prolonged periods of work-related stress, unexpected organizational changes, and uncertainties about work faced during the pandemic, it becomes imperative to study occupational health constructs under a dynamic methodological perspective, to understand their stable and unstable characteristics better. In this study, drawing on the Dynamic Structural Equation Modeling (DSEM) framework, we used a combination of multilevel AR(1) models, Residual-DSEM (RDSEM), multilevel bivariate VAR(1) models, and multilevel location-scale models to investigate the autoregression, trend, and (residual) cross-lagged relationships between emotional exhaustion (EmEx) and mental well-being (MWB) over the COVID-19 pandemic. Data were collected weekly on 533 workers from Germany (91.18%) and Italy (8.82%) who completed a self-reported battery (total number of observations = 3,946). Consistent with our hypotheses, results were as follows: (a) regarding autoregression, the autoregressive component for both EmEx and MWB was positive and significant, as well as it was their associated between-level variability; (b) regarding trend, over time EmEx significantly increased, while MWB significantly declined, furthermore both changes had a significant between-level variability; (c) regarding the longitudinal bivariate (cross-lagged) relationships, EmEx and MWB negatively and significantly affected each other from week to week, furthermore both cross-lagged relationships showed to have significant between-level variance. Overall, our study pointed attention to the vicious cycle between EmEx and MWB, even after controlling for their autoregressive component and trend, and supported the utility of DSEM in occupational health psychology studies.

Increases in negative affective arousal precede lower self-esteem in patients with borderline personality disorder but not in patients with depressive disorders: an experience sampling approach

BackgroundInstability in self-esteem and instability in affect are core features of borderline personality disorder (BPD). For decades, researchers and theorists have been interested in the temporal dynamics between these constructs. Some hypothesize that changes in affective states should precede changes in self-esteem (Linehan, Cognitive-behavioral treatment of borderline personality disorder. Diagnosis and treatment of mental disorders, 1993), while others suggest that changes in self-esteem should precede changes in affective states (Kernberg, Borderline conditions and pathological narcissism, 1975).MethodsIn this study, we investigated the temporal relations between negative affective arousal states and current self-esteem in daily life. Patients with BPD (n = 42) or depressive disorders (DD; n = 40), and non-clinical controls (NCC; n = 40) were assessed every 15 min for 13 h.ResultsAs expected, dynamic structural equation modeling showed higher levels of average daily negative affective arousal and lower levels of average daily self-esteem in the BPD group compared with the NCC group, and scores in the DD group were in-between the BPD and the NCC groups. In line with predictions based on Linehan’s (Cognitive-behavioral treatment of borderline personality disorder. Diagnosis and treatment of mental disorders, 1993) model of affective dysregulation in BPD, negative affective arousal (t) and subsequent self-esteem (t+ 1) were significantly linked only in the BPD group, implying that higher negative affective arousal is followed by lower current self-esteem in the next measurement (ca. 15 min later). Importantly, self-esteem (t) and subsequent negative affective arousal (t + 1) were not significantly related (Kernberg, Borderline conditions and pathological narcissism, 1975).ConclusionsOur findings suggest close dynamic temporal relations between affective instability and self-esteem instability in BPD, which highlights the importance of providing patients with means to effectively modulate high negative affective arousal states.

The direction of effects between parenting and adolescent affective well-being in everyday life is family specific

Numerous theories and empirical studies have suggested that parents and their adolescent children reciprocally influence each other. As most studies have focused on group-level patterns, however, it remained unclear whether this was true for every family. To investigate potential heterogeneity in directionality, we applied a novel idiographic approach to examine the effects between parenting and adolescent well-being in each family separately. For 100 days, 159 Dutch adolescents (Mage = 13.31, 62% female) reported on affective well-being and four parenting dimensions. The family-specific effects of pre-registered (https://osf.io/7n2jx/) dynamic structural equation models indeed revealed that a reciprocal day-to-day association between parenting and adolescent affective well-being was present only in some families, with the proportion of families displaying a reciprocal association varying across the four parenting dimensions (11–55%). In other families, either parenting predicted the adolescent’s affective well-being (8–43%) or vice versa (10–27%), or no day-to-day associations were found (16–60%). Adolescents with higher trait levels of environmental sensitivity and neuroticism were more strongly affected by parenting. Thus, findings suggest that the ways in which parents and adolescents influence each other in everyday life are unique, stressing the need to move towards an idiographic parenting science.