On the joys of missing data

Prospective relations between stigma, guilt, shame, posttraumatic stress and prolonged grief symptoms among overdose and suicide loss survivors

BACKGROUND

Bereavement following suicide and fatal overdose is associated with posttraumatic stress disorder (PTSD) and prolonged grief (PG). However, information about plausible explanations for these associated symptoms is scarce. Leveraging data from two assessment points, we examine the prospective roles of stigmatization, guilt, shame, and avoidant coping on PTSD and PG symptom severity and whether these relations are similar across groups.

METHODS

We analyzed data (N = 212) from suicide- and overdose-bereaved adults who completed two waves of data collection (T1 and T2; six months apart) as part of a larger study of traumatic loss. Multigroup path analysis with serial mediation was used to estimate models of PTSD and PG symptomatology. Stigmatization (T1) and guilt (T1) were modeled as predictors, while shame (T1) and avoidant coping (T2) were modeled as mediators explaining PTSD (T2) and PG symptoms (T2).

RESULTS

Prospective relations between T1 stigma, T1 guilt, T2 PTSD and T2 PG symptoms were mediated by T1 shame and serially mediated by T2 avoidant coping. Multigroup analyses indicated similar relations across suicide and overdose-bereaved adults, but a stronger effect from T2 avoidant coping on outcomes for overdose bereaved adults.

LIMITATIONS

Online self-report and use of a convenience sample are limitations.

CONCLUSION

Our results suggest shame and avoidance may help explain elevated symptoms of PTSD and PG in the context of suicide and overdose bereavement. Accordingly, transdiagnostic interventions that concurrently target shame-related cognitions and behavioral avoidance may be promising and warrant further attention.

Does motivation lead to academic success, or conversely? Reciprocal relations between autonomous and controlled motivation, and mathematics achievement

BACKGROUND

While it's clear that autonomous motivation significantly boosts academic success, there are conflicting findings regarding the opposite relation. Besides, the reciprocal relations among controlled motivation and achievement present mixed results. Adequately distinguishing between variations among individuals and within individuals results key to acknowledge such relations.

AIM

This longitudinal study examines the reciprocal relations between controlled and autonomous forms of motivation and academic achievement using the RI-CLPM methodology.

SAMPLE

Participants were 1042 high school students (M = 16 years, 52% male adolescents) from 16 different high schools in urban and rural areas.

METHODS

A random intercept cross-lagged panel model (RI-CLPM) was tested to estimate whether students' autonomous and controlled motivation predicted achievement and/or vice versa. Independent models were estimated for the two types of motivation.

RESULTS

Overall, the RI-CLPM results indicated a unidirectional relationship between autonomous motivation and achievement. As for controlled motivation, the results of RI-CLPM models showed no reciprocal relationship between this type of motivation and achievement.

CONCLUSIONS

These results underline the importance of taking within- and between-person processes into account when analysing reciprocal relations and provide crucial insights for enhancing student motivation and achievement in diverse educational contexts.

Psychosocial factors associated with the trajectories of interparental conflict for Australian fathers of autistic children: A longitudinal study across 10 years of child development

Limited research exists on fathers' experiences of interparental conflict (IPC) in families with autistic children. We aimed to identify: (1) the extent to which these fathers report IPC across 10 years of child development (4-14 years) and how this compares to fathers of non-autistic children; (2) distinct trajectories of IPC for fathers of autistic children and (3) factors associated with trajectories of IPC among fathers of autistic children. This is a retrospective study using a national dataset. Participants were 281 fathers of autistic children and 7046 fathers of non-autistic children. Although small effect sizes, fathers of autistic children, on average, reported significantly higher IPC when their child was 4-5, 6-7, 8-9 and 10-12 years of age, compared to fathers of non-autistic children. For fathers of autistic children, longitudinal latent class analysis revealed three profiles reflecting 'low and stable', 'moderate and stable' and 'persistently elevated' levels of IPC over time. Regression analysis revealed a range of predictors (e.g. co-parenting support, father age) for fathers of autistic children experiencing 'moderate and stable' and 'persistently elevated' IPC as compared to fathers who experienced low levels of IPC. There is a significant portion of fathers of autistic children who experience ongoing and heightened IPC, highlighting the need for targeted support.Lay AbstractNot much is known about how fathers experience conflict with their partners (either verbal or physical) while raising an autistic child. This study focused on understanding these experiences over 10 years, following children from the age of 4 to 14 years. The study had two main goals: (1) to track how fathers experience conflict with their partners over this time and identify different patterns to these experiences; and (2) to find psychosocial factors in early childhood that might impact these patterns. The study included 281 fathers of autistic children and 7046 fathers of non-autistic children who took part in 'Growing Up in Australia: Longitudinal Study of Australian Children'. Using a statistical method to group fathers based on the partner conflict they reported over the 10 years, results showed that there were three groups: (1) 'low and stable', (2) 'moderate and stable' and (3) 'persistently elevated' experiences of partner conflict. Additional analysis showed that fathers' confidence in their parenting, perceived support from their partners and concerns about their child's language skills were associated with ongoing moderate levels of partner conflict. On the other hand, fathers who were older, had lower perceived support from their partners, partners experiencing psychological distress and higher parent-reported child social functioning were more likely to experience consistently high levels of conflict over time. In our study, we described different levels of conflict with their partners reported by fathers of autistic children. We also identified some of the factors that were associated with different levels of conflict. These might be used to inform interventions to reduce parental conflict in the future.

BMI trajectories, changes and their potential associations with the risk of depression during adulthood: A cross-sectional study from NHANES 2005-2018

BACKGROUND

Body mass index (BMI) levels have been proven to have a significant relationship with depression. However, there is limited evidence regarding the impact of BMI trajectories and the average annual changes among adults aged 40-74 years on the risk of developing depression.

METHODS

In this cross-sectional study, participants aged 40-74 were retrieved from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. The latent class trajectory model (LCTM) was employed to identify BMI trajectories. Depression was evaluated using the validated Patient Health Questionnaire (PHQ-9). Multinomial logistic regression models were conducted to explore the associations between BMI trajectories, its average annual changes and depression.

RESULTS

A total of 17, 171 participants were included. Five BMI trajectories were identified and labeled as the slight increase trajectory (n = 7830, 45.60 %), stable trajectory (n = 5605, 32.64 %), moderate increase trajectory (n = 2562, 14.92 %), rapid increase trajectory (n = 685, 3.99 %) and increase-to-decrease trajectory (n = 489, 2.85 %), respectively. Compared to individuals with stable trajectory, those who experienced a rapid increase trajectory (OR = 2.39, 95%CI 1.72-3.34) and an increase-to-decrease trajectory (OR = 2.07, 95%CI 1.51-2.84) had a higher risk of developing depression. During early adulthood, absolute (OR = 1.46, 95%CI 1.23-1.73) and relative (OR = 1.47, 95%CI 1.25-1.71) average annual BMI growths were associated with depression. In recent adulthood, average annual BMI loss was shown to increase the risk of developing depression.

CONCLUSIONS

This study highlights an increased risk of depression among participants aged 40-74 years with non-stable BMI trajectories, particularly among females. These findings emphasize the importance of maintaining a stable weight to reduce the risk of depression, especially in middle-aged and older adults.

Avoidant and Approach-Oriented Coping Strategies, Meaning Making, and Mental Health Among Adults Bereaved by Suicide and Fatal Overdose: A Prospective Path Analysis

Adults bereaved by the suicide or overdose death of someone close to them are vulnerable to adverse mental health outcomes, but little is known about how these individuals utilize avoidance- and approach-based coping strategies, how these strategies relate to outcomes, and what accounts for these associations. Informed by contemporary theories of bereavement, we utilize prospective data from suicide- and overdose-bereaved adults (N = 212) who completed two waves of online data collection approximately two years following the death (T1 and T2; six months apart) to examine the mediating role of meaning making in the relationship between coping strategies and grief-related mental health outcomes, such as prolonged grief (PG), posttraumatic stress (PTS), and depression. Path analysis with mediation was used to investigate the relations between coping strategies at T1, meaning making at T2, and mental health outcomes at T2. The results indicated direct effects of avoidant coping at T1 in predicting higher PG and PTS symptoms at T2, while approach-based coping at T1 indirectly predicted an improvement in all three T2 outcomes due to increased meaning making. These results suggest that avoidance-based strategies directly and indirectly contribute to poorer outcomes and impaired meaning making processes, while approach-based strategies lead to increased meaning making and adaptation to loss among suicide and overdose loss survivors. The clinical implications and future directions for research are discussed.

Avoidance behavior mediates the relationship between concern about falling and impaired mobility in multiple sclerosis

BACKGROUND

Concern about falling (CAF) is common in multiple sclerosis (MS) and affects mobility and activity, even without a history of a falls.

OBJECTIVES

This study aimed to assess how avoidance behavior contributes to CAF-related mobility impairments and whether this association is consistent for fallers and non-fallers.

METHODS

Participants completed questionnaires regarding CAF, avoidance behavior, and self-reported walking impairment, and laboratory walking and balance assessments. Applied structural equation modeling tested a hypothesized mediation model in which the relationship between CAF and mobility impairments would be partially mediated by avoidance behavior. Walking and balance assessments were used to construct a mobility latent factor. The model was subsequently stratified by fallers and non-fallers.

RESULTS

Participants included 52 individuals with MS. 46.96 % of the significant total effect of CAF on mobility was accounted for by avoidance behaviors. No significant differences were found between fallers and non-fallers, suggesting a consistent mediation effect across both groups.

CONCLUSIONS

Our findings underscore the role of avoidance behavior in partially accounting for the effects of CAF on mobility deficits among persons with MS. This effect was statistically equivalent across fall status, highlighting the pervasive impact of avoidance behavior on mobility impairments in MS.

The role of social problem-solving in emerging adult healthcare transition

Objective

Transitioning to independent self-management is an observed challenge for emerging adults with chronic medical conditions (CMCs). Strong healthcare management skills are linked with better health-related quality of life (HRQoL). Social problem-solving skills also contribute to HRQoL, but limited research exists on the role of these skills among emerging adults with CMCs. Therefore, the current study examines the potential mediating role of problem-solving abilities between healthcare management skills and HRQoL among emerging adults with CMCs.

Methods

Emerging adults (N = 279; Mean Age=19.37, SD=1.33; 84.9 % Female; 79.2 % White; 26.9 % first generation student) with a CMC completed online measures of demographics, transition readiness, social problem-solving, and HRQoL. A path analysis estimated the direct and indirect effects of transition readiness on HRQoL, with demographic and illness-related covariates (e.g., sex, illness controllability, COVID time).

Results

The overall path analysis was significant (p < 0.001) and accounted for 28.0 % of the variance in mental (M=-1.46, SD=1.12) and 20.5 % of the variance in physical HRQoL (M=-0.65, SD=0.96). Transition readiness had a significant indirect effect through dysfunctional problem-solving skills on mental (β=0.07, SE=0.03, p = 0.02) and physical HRQoL (β=0.04 SE=0.02, p = 0.04). Constructive problem-solving did not mediate the relationships (ps>0.05).

Conclusions

Findings indicate that dysfunctional problem-solving may impede emerging adults' ability to effectively apply healthcare management skills, and interventions that reduce dysfunctional problem-solving may be needed to improve HRQoL. College campuses may be a suitable environment for providing problem-solving training, and future research should explore opportunities to engage these communities in healthcare transition support.

Dynamic Associations between Self-Efficacy and Depressive Symptoms During the Transition to Adolescence: A 3-year Longitudinal Study

The transition to adolescence is a critical period for the onset of depressive symptoms, making it crucial to examine the risk factors and consequences related to their development and maintenance. Although previous studies have suggested a negative relationship between self-efficacy and depressive symptoms, it is unclear how these two variables evolve together over time during the transition to adolescence and how these relationships vary dynamically within-person and between-person. This study used a latent curve model with structured residuals to examine whether a bidirectional relationship involving academic, social, and emotional self-efficacy and depressive symptoms exists during the transition to adolescence. A sample of 3748 Chinese early adolescents (48.2% girls; initial Mage = 9.77 years, SDage = 0.31) participated in six assessments over three years. The results revealed that, at the between-person level, the initial states and changes in the three dimensions of self-efficacy were significantly and negatively associated with those of depressive symptoms. At the within-person level, when individuals' social and emotional self-efficacy fell below their expected trajectories they followed, they experienced a subsequent increase in depressive symptoms six months later, and when individuals' depressive symptoms exceeded their expected trajectories they followed, they experienced a decrease in academic, social, and emotional self-efficacy six months later. Notably, the paths from depressive symptoms to self-efficacy were stronger and more reliable than the opposite paths. These findings revealed an asymmetric vicious cycle between self-efficacy and depressive symptoms.

Missing Data in Discrete Time State-Space Modeling of Ecological Momentary Assessment Data: A Monte-Carlo Study of Imputation Methods

When using ecological momentary assessment data (EMA), missing data is pervasive as participant attrition is a common issue. Thus, any EMA study must have a missing data plan. In this paper, we discuss missingness in time series analysis and the appropriate way to handle missing data when the data is modeled as an idiographic discrete time continuous measure state-space model. We found that Missing Completely at Random, Missing At Random, and Time-dependent Missing At Random data have less bias and variability than Autoregressive Time-dependent Missing At Random and Missing Not At Random. The Kalman filter excelled at handling missing data under most conditions. Contrary to the literature, we found that using a variety of methods, multiple imputations struggled to recover the parameters.

Development and Psychometric Evaluation of the Thriving in Nursing Questionnaire (THINQ)

AIM

To develop and evaluate a questionnaire for measuring factors that contribute to thriving at work among nurses.

DESIGN

A cross-sectional study.

METHODS

An online questionnaire was administered in March 2024 to nurses in a community teaching hospital in Michigan, US. Questionnaire content was based on a literature search and was pilot tested among nursing professionals within the hospital system. Questionnaire factor structure was examined with exploratory and confirmatory factor analyses with split-half sample validation.

RESULTS

Based on exploratory and confirmatory factor analysis, a three-factor solution presented the best model, with factors comprised of 15 items measuring individual resources (3 items), work resources (6 items) and interpersonal aspects of the nursing work environment (6 items). Reliability estimates for all three factors exceeded 0.80, indicating good internal homogeneity. The questionnaire also demonstrated acceptable split-half validity and reliability.

CONCLUSION

The questionnaire presented here provides a potentially useful tool for measuring and evaluating thriving at work among nurses.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

A better understanding of factors that enhance nurse thriving would lay the foundation for targeted interventions aimed at improving the nursing work environment and nurse well-being. Enhancing nurse thriving could have a potentially positive impact on patient care.

IMPACT

This study addressed the need to understand factors that contribute to thriving in nursing work. The questionnaire that was developed revealed a three-factor solution measuring individual nurse resources, work environment resources and work interpersonal resources. By measuring thriving among nurses, hospitals and other healthcare organisations are taking an important first step in identifying interventions to enhance the nursing work environment, nurse well-being and potentially the quality of patient care.

REPORTING METHOD

We followed the STROBE checklist in reporting this study. No patient or public contribution.

Is Emotion the Engine? Positive Affect as the Mediator Between Employee Mindset and Performance in a Three-Wave Study

Research in the educational and organizational fields theoretically suggests that individuals' implicit beliefs are deeply connected with their performance. This study provides insight into the emotional mechanism that connects employees' mindsets regarding growth (growth vs. fixed mindset) and stress (stress-is-enhancing vs. stress-is-debilitating mindset) to job performance. We hypothesized that employees with a stress-as-enhancing and a growth-oriented mindset (T1) would experience more positive affect (T2), increasing their job performance (T3). We tested these hypotheses using three-wave survey data from a sample of employees in various occupations. Our results showed that employees with a growth mindset and those who viewed stress as an experience that enhances learning, vitality, and productivity experienced more positive emotions one month later. The data also showed that performance was significantly predicted by growth mindset both directly and indirectly, while stress mindset was linked only to positive affect.

A generative model for evaluating missing data methods in large epidemiological cohorts

BACKGROUND

The potential value of large scale datasets is constrained by the ubiquitous problem of missing data, arising in either a structured or unstructured fashion. When imputation methods are proposed for large scale data, one limitation is the simplicity of existing evaluation methods. Specifically, most evaluations create synthetic data with only a simple, unstructured missing data mechanism which does not resemble the missing data patterns found in real data. For example, in the UK Biobank missing data tends to appear in blocks, because non-participation in one of the sub-studies leads to missingness for all sub-study variables.

METHODS

We propose a tool for generating mixed type missing data mimicking key properties of a given real large scale epidemiological data set with both structured and unstructured missingness while accounting for informative missingness. The process involves identifying sub-studies using hierarchical clustering of missingness patterns and modelling the dependence of inter-variable correlation and co-missingness patterns.

RESULTS

On the UK Biobank brain imaging cohort, we identify several large blocks of missing data. We demonstrate the use of our tool for evaluating several imputation methods, showing modest accuracy of imputation overall, with iterative imputation having the best performance. We compare our evaluations based on synthetic data to an exemplar study which includes variable selection on a single real imputed dataset, finding only small differences between the imputation methods though with iterative imputation leading to the most informative selection of variables.

CONCLUSIONS

We have created a framework for simulating large scale data with that captures the complexities of the inter-variable dependence as well as structured and unstructured informative missingness. Evaluations using this framework highlight the immense challenge of data imputation in this setting and the need for improved missing data methods.

Mental health and sociodemographic influences during COVID-19: Longitudinal findings from Iceland

The COVID-19 pandemic introduced numerous stressors and challenges that have had profound implications for mental health. This study examined the effects of the pandemic on mental health among Icelandic adults (n = 1766), using longitudinal survey data spanning three waves of data collection from 2019 to 2022. Symptoms of depression, anxiety, and stress increased from the beginning of the pandemic to the second time point, approximately one year into the pandemic, coinciding with reductions in happiness and social support. By the third time point, mental health remained slightly poorer than pre-pandemic levels, even after all COVID-19-related restrictions had been lifted. Unlike some other countries, COVID-19 infections in Iceland did not rise significantly until after the summer of 2021. Overall, participants perceived that the pandemic most adversely affected their social relationships and mental health. Prolonged periods in quarantine were predictive of these perceptions, albeit effect sizes were small. During the pandemic, women and younger participants reported slightly poorer mental health, while social support predicted better mental health outcomes. These results show that large societal stressors can significantly impact the mental health of populations. While social support is a prominent predictor of better mental health, additional variables may be needed to explain these effects fully.

Adolescent mental well-being in time of crises: The role of social and residential contexts

BACKGROUND

The extent of the impact and the interconnections among factors within social and residential contexts during the COVID-19 lockdowns on mental well-being remain to be elucidated. We identified latent classes of each of social and residential context during the lockdown and examined their associations with mental well-being among adolescents in France 1-year after the first lockdown.

METHODS

We used data collected in 2021 in a cross-sectional school-based pilot study for EXIST, from 387 participants ages 12-15 years. Participants reported retrospectively on characteristics of their social and residential contexts during the lockdown, and their current mental well-being in self-report questionnaires. We used latent class analysis to identify latent classes of social and residential contexts, and linear regression models to examine the associations between these contexts and mental well-being.

RESULTS

Four social context classes were identified: class 1 "Low opportunity for social contact at home," class 2 "Moderate opportunity for social contact at home," class 3 "High opportunity for social contact at home," and class 4 "Very high opportunity for social contact at home." Relative to class 4, lower levels of mental well-being were observed among adolescents in class 1 (b = -4.08, 95% CI [-8.06; -0.10]) 1 year after the lockdown. We identified four residential context classes based on proximity to nature, type of residence (e.g., apartment, house), and level of neighborhood deprivation. No association was detected between residential context during the lockdown and adolescent mental well-being one-year later.

CONCLUSION

A limited social context may negatively impact adolescent mental well-being during crises.

Examining the Relation Between Early Violence Exposure and Firearm-Related Experiences in Emerging Adulthood: A Longitudinal Cohort Study

Firearms are a leading cause of death among adolescents and young adults in the United States. Early exposure to violence, as a victim or witness, is associated with increased risk of firearm-related experiences, including carrying and threatening others with a gun. These experiences, in turn, increase the risk of both fatal and non-fatal firearm injuries. Using an ethnically diverse sample of emerging adults, we build on prior research by examining the link between early violence exposure at multiple contexts of the social-ecological model and multiple firearm-related experiences (i.e., firearm-threatening victimization, firearm-threatening perpetration, and firearm carriage). We analyzed data from a 10-year longitudinal study of 1042 youth in the Southern United States. Experiencing childhood physical abuse was associated with both firearm-threatening victimization and perpetration in emerging adulthood. Additionally, exposure to neighborhood and interparental violence were linked to threatening others with firearms and carrying firearms, respectively. Counter to expectations, bullying victimization did not emerge as a predictor of any firearm-related experiences. Findings highlight the importance of cross-cutting violence prevention efforts to prevent high-risk firearm-related behaviors among emerging adults. Programs for children and adolescents that address these types of violence exposure should highlight coping skills and sources of positive social support to bolster protective factors against firearm-related outcomes.

Factors associated with newly graduated nurses' work readiness during a pandemic: A cross-sectional study

BACKGROUND

Newly graduated nurses may experience reality shock and leave the career early, if not adequately prepared. The pandemic has significantly impacted nursing education, clinical placements, working conditions and employment opportunities, leaving newly graduated nurses' work readiness unknown.

AIM

To investigate the work readiness and its associated factors of newly graduated nurses who studied and graduated during a pandemic.

DESIGN

A descriptive, cross-sectional correlational study design was employed.

SETTINGS

The study was conducted at a large public health service in Victoria, Australia.

PARTICIPANTS

Newly graduated registered nurses who studied during the pandemic and graduated between January 2022 and June 2023 (N = 206).

METHODS

Participants were recruited between November 2022 and June 2023. Participants' self-perceived work readiness was measured using the Work Readiness Scale for Graduate Nurses, covering personal work characteristics, work competence, social intelligence and organisational acumen. Pearson correlation, multiple regression and hierarchical logistic regression analysis were applied to test the relationship between explanatory variables and participants' work readiness.

RESULTS

Mean (SD) values were 50.7 (14.6) for personal work characteristics, 100.5 (18.8) for work competence, and 58.2 (12.4) for social intelligence. Median (IQR) for organisational acumen was 145.5 (18.0). Prior Australian registered nurse or enrolled nurse experience significantly predicted personal work characteristics (β = 0.16, p = 0.037), while previous overseas registered nurse experience significantly predicted work competence (β = 0.14, p = 0.049). Participants who were native-English speakers had a significantly lower work competence (β = -0.15, p = 0.032). Being a female (p = 0.002, 95 % CI = 1.75, 13.21) and the length of a final clinical placement (p = 0.033, 95 % CI = 1.02, 1.59) significantly predicted organisational acumen.

CONCLUSION

Despite challenges encountered during the pandemic, participants reported a relatively high self-perceived work readiness. Influencing factors include individual characteristics, clinical placement experiences, and previous healthcare employment.

Environmental enrichment is associated with favorable memory-related functional brain activity patterns in older adults

Background

In humans, environmental enrichment (EE), as measured by the engagement in a variety of leisure activities, has been associated with larger hippocampal structure and better memory function. The present cross-sectional study assessed whether EE during early life (13-30 years) and midlife (30-65 years) is associated with better preserved memory-related brain activity patterns in older age.

Methods

In total, 372 cognitively unimpaired older adults (aged ≥60 years old) of the DZNE-Longitudinal Study on Cognitive Impairment and Dementia (DELCODE; DRKS00007966) were investigated. EE was operationalized using items of the Lifetime of Experiences Questionnaire (LEQ), which measures the self-reported participation in a variety of leisure activities in early life and midlife. The preservation of memory-related functional brain activity was assessed using single-value scores, which relate older adults' brain activity patterns in the temporo-parieto-occipital memory network to those of young adults during visual memory encoding (FADE and SAME scores).

Results

EE during early life and midlife was significantly associated with higher SAME scores during novelty processing (n = 372, β = 0.13, p = 0.011). Thus, older participants with higher EE showed greater similarity of functional brain activity patterns during novelty processing with young adults. This positive association was observed most strongly in participants with subjective cognitive decline (SCD, n = 199, β = 0.20, p = 0.006).

Conclusion

More frequent participation in a variety of leisure activities in early life and midlife is associated with more successful aging of functional brain activity patterns in the memory network of older adults, including participants at increased risk for dementia. Longitudinal studies are needed to clarify whether higher EE during life could help preserve memory network function in later life.

Exploring the Nature of Arhopalus ferus (Coleoptera: Cerambycidae: Spondylidinae) Pheromone Attraction

Cerambycid species of the Spondylidinae subfamily are distributed worldwide and are known for being prolific invaders that infest conifers. In New Zealand, Arhopalus ferus (Mulsant), the burnt pine longhorn beetle, is well-established and requires monitoring at high-risk sites such as ports, airports, and sawmills as part of the requirements to meet pine log export standards set by the New Zealand Ministry of Primary Industries (MPI). Currently, its surveillance relies on traps baited with host volatiles (i.e., ethanol and α-pinene). We used volatile collections from adult beetles, electroantennograms, and field trapping bioassays to identify the pheromones emitted by the burnt pine longhorn beetle A. ferus and their effects on its behaviour. We show that A. ferus males emit mainly (E)-fuscumol and geranylacetone, as well as the minor components, α-terpinene and p-mentha-1,3,8-triene, and that all four compounds elicit a dose-dependent response in antennae of both sexes. Traps baited with the binary combination of geranylacetone plus fuscumol captured significantly more female A. ferus than did unbaited traps in two of three field experiments. α-Terpinene did not affect A. ferus trap catches and effects of p-mentha-1,3,8-triene on trap catch were not determined. Our findings provide further evidence of the use of fuscumol and geranylacetone as aggregation-sex pheromones by longhorn beetles in the Spondylidinae subfamily, and suggest that their deployment in survey traps may improve the efficacy of A. ferus monitoring in New Zealand and elsewhere.

A data integration method for new advances in development cognitive neuroscience

Combining existing datasets to investigate key questions in developmental cognitive neuroscience brings exciting opportunities and unique challenges. However, many data pooling methods require identical or harmonized methodologies that are often not feasible. We propose Integrative Data Analysis (IDA) as a promising framework to advance developmental cognitive neuroscience with secondary data analysis. IDA serves to test hypotheses by combining data of the same construct from commensurate (but not identical) measures. To overcome idiosyncrasies of neuroimaging data, IDA explicitly evaluates if measures across studies assess the same construct. Moreover, IDA allows investigators to examine meaningful individual variability by de-confounding source-specific differences. To demonstrate IDA's potential, we explain foundational concepts, outline necessary steps, and apply IDA to volumetric measures of hippocampal subfields from 443 4- to 17-year-olds across three independent studies. We identified commensurate measures of Cornu Ammonis (CA) 1, dentate gyrus (DG)/CA3, and Subiculum (Sub). Model testing supported use of IDA to create IDA factor scores. We found age-related differences in DG/CA3, not but CA1 and Sub volume in the integrated dataset. By successfully demonstrating IDA, our hope is that future innovations come from the combination of existing neuroimaging data to create representative integrated samples when testing critical developmental questions.

Adverse childhood experiences (ACEs) and emotion dysregulation phenotypes: An intersectional analysis of race/ethnicity and gender in a nationally representative U.S. sample

BACKGROUND

Adverse childhood experiences (ACEs) are strong, preventable risk factors for emotion dysregulation in adolescence, but whether ACEs-emotion dysregulation associations differ by race/ethnicity or gender remains unclear.

OBJECTIVE

We examined (a) how race/ethnicity and gender jointly impact latent ACEs classes and emotion dysregulation phenotypes, and (b) how these ACEs classes in childhood (by age 9) transition to latent emotion dysregulation phenotypes in adolescence (at age 15).

PARTICIPANTS AND SETTING

Participants were 3,273 children from two waves of data from the Future of Families and Child Wellbeing Study, a large, nationally representative cohort. The sample consisted of 26.6% non-Hispanic (NH) Black boys, 25.4% NH Black girls, 12.9% Hispanic boys, 12.6% Hispanic girls, 11.8% NH White boys, and 10.7% NH White girls.

METHOD

We estimated latent class models to identify ACEs patterns across ten indicators and dysregulation phenotypes across affective, attentional, and behavioral domains. Latent transition analysis was used to examine how ACEs classes transitioned into dysregulation phenotypes from childhood into adolescence.

RESULTS

The findings revealed significant variation in the number and nature of latent classes of both ACEs and emotion dysregulation across the intersection of race/ethnicity and gender. NH Black and Hispanic children were more likely to be in the Poverty and Parental Separation class than NH White children. Hispanic boys had the highest prevalence of Severe Dysregulation (16%), whereas NH White boys had the highest prevalence of Low Symptoms (52%). Individuals in the Poverty and Parental Separation class had a higher probability of transitioning to the Low Symptoms class. In contrast, those in the Abuse and Family Dysfunction class were more likely to transition to the Severe Dysregulation class, with NH White girls showing the highest probability (.34), nearly twice that of NH Black girls (.19). These gender differences in these transition probabilities were observed for Whites but not Blacks.

CONCLUSIONS

These findings thus highlight the need for adopting an intersectional, person-centered approach when studying the effects of ACEs on adolescent development.

Intolerance of Uncertainty as a Central Influence on Social Media Use: A School-Based Program for Adolescents

This study evaluated a classroom program to address Intolerance of uncertainty (IU) in secondary school students in Australia. IU is a transdiagnostic vulnerability factor for a range of psychological difficulties. A universal classroom program aimed to increase student understanding of feelings of uncertainty and explored socioemotional factors that could influence behaviors when facing uncertainty. Classroom teachers in two high schools were trained to deliver an 18-lesson program under naturalistic classroom conditions. Relative to the control group, the intervention lowered IU at post-test, but not at a later follow-up. The only socioemotional outcome measure to demonstrate a concurrent change was social media use. Limitations of the study were associated with the naturalistic classroom intervention, including the high level of attrition. Future studies may need to address broader factors in the students' context that could influence intolerance of uncertainty.

Handling missing data in longitudinal clinical trials: three examples from the pediatric psychology literature

Researchers by default tend to choose complex models when analyzing nonindependent response variable data, this may be particularly applicable in the analysis of longitudinal trial data, possibly due to the ability of such models to easily address missing data by default. Both maximum-likelihood (ML) estimation and multiple imputation (MI) are well-known to be acceptable methods for handling missing data, but much of the recently published quantitative literature has addressed questions regarding the research designs and circumstances under which one should be chosen over the other. The purpose of this article is threefold. First, to clearly define the assumptions underlying three common longitudinal trial data analysis models for continuous dependent variable data: repeated measures analysis of covariance (RM-ANCOVA), generalized estimating equation (GEE), and a longitudinal linear mixed model (LLMM). Second, to clarify when ML or MI should be chosen, and to introduce researchers to an easy-to-use, empirically well-validated, and freely available missing data multiple imputation program: BLIMP. Third, to show how missing longitudinal trial data can be handled in the three data analysis models using three popular statistical analysis software packages (SPSS, Stata, and R) while keeping the published quantitative research in mind.

The Social Failure Model: Do Classroom Norms Play a Role in the Development of Antisocial Behavior and Depressive Symptoms?

This study examined the moderating role of descriptive and status norms in the stability of youth's antisocial behavior, and the link between initial antisocial behavior and the development of depressive symptoms over the course of one academic year, while controlling for initial depression levels. A total of 1081 students (51.06% girls; grades 4 through 6) in schools in low to average socio-economic status neighborhoods completed self-reports and a peer nomination inventory in the fall (T1) and spring (T2) of one year. Descriptive norms were operationalized as the classroom- and sex-specific mean level of antisocial behavior. Status norms were operationalized as the classroom- and sex-specific correlation between antisocial behavior and social preference. Descriptive norms moderated the link between T1 and T2 antisocial behavior, such that youth exhibiting high levels of antisocial behavior showed a greater increase in antisocial behavior in classrooms where descriptive norms strongly favored such behavior (i.e., + 1 SD) than in classrooms with neutral or weak descriptive norms (i.e., - 1 SD). Status norms moderated the association between T1 antisocial behavior and T2 depressive symptoms, such that youth with high levels of antisocial behavior had higher depressive symptoms in classrooms where status norms disfavored antisocial behavior than in classrooms with neutral or favorable norms. No moderating effects of sex or grade were observed. These results suggest that both descriptive norms and status norms play important, albeit distinct, roles in exacerbating youth's depressive symptoms and antisocial behavior, but they may also mitigate these same outcomes in favorable contexts.

A (sub)field guide to quality control in hippocampal subfield segmentation on high-resolution T2-weighted MRI

Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.

Testing the combined effects of the PAX Good Behavior Game and MyTeachingPartner™ coaching for early career teachers: Impacts on teacher-student interaction quality and teachers' occupational health

Early career teachers experience exceptionally high rates of attrition from the profession, often due in part to elevated concerns about student behavior and poor occupational health. This study reports findings from a randomized controlled trial testing the combined effect of the PAX Good Behavior Game and MyTeachingPartner™ for 188 early career, early elementary teachers (Grades K-3). Of primary focus were observations of the quality of teachers' interactions with students and their self-reported occupational health over 2 consecutive school years. Results indicated that relative to comparison teachers, those in the intervention condition reported lower distress at follow-up (d = -0.23) and less decline in teacher affiliation across the 2-year period (d = 0.50). In addition, the intervention teachers who were highly distressed at baseline and who experienced high levels of disruptive behavior had higher quality interactions with students around emotional support (d = 0.27), classroom organization (d = 0.32), and instructional support (d = 0.69) at the end of 2 years than comparison teachers. This subgroup of intervention teachers also experienced more favorable changes over time in distress (d = -2.47) and teacher affiliation (d = 3.00) over the course of the study. Professional development focused on classroom management with coaching support may be particularly impactful for early career teachers experiencing higher levels of distress and in classrooms with higher rates of behavior problems.

Social ties and social identification: Influences on well-being in young adults

Research highlights the positive impact of social connectedness on subjective well-being. In this paper, we test a model in which an identity-based mechanism links a structural form of connectedness (significant social ties) with two psychological well-being outcomes, life satisfaction and self-esteem. Using data from the LIVES Longitudinal Lausanne Youth Study (LIVES-LOLYS, N = 422), a longitudinal mediation path model tests direct and indirect effects, via the strength of social identification, of the number of significant social ties in two life domains (friends and family) on life satisfaction and self-esteem. Results showed positive associations between the number of significant ties and social identification in the concordant domain, empirically linking the structural and subjective forms of social connectedness. Moreover, our model displays significant indirect effects in the friend domain, but not in the family domain. Having more friends as significant social ties predicted higher social identification with friends, and this was longitudinally associated with higher life satisfaction and self-esteem. Findings show a new mechanism linking structural and subjective forms of social connectedness, unpacking their concerted impact in protecting well-being. The differences between the friend and family domains are discussed in the framework of both life-course and social identity perspectives.

A longitudinal study on the relation between parenting and Toddler's disruptive behavior: what is the role of Toddler's negative emotionality and physiological stress reactivity?

Harsh and unsupportive parenting is a risk factor for the development of disruptive behavior in children. However, little is known about how children's temperament and stress reactivity influence this relation. In a three-wave longitudinal study, we examined whether the associations between parenting practices (supportive parenting, positive discipline, and harsh discipline) and child disruptive behavior were mediated by child temperament (negative emotionality) and stress reactivity (heart rate reactivity). In 72 families (Mage child = 14.6 months), living in the Netherlands, parents reported on their parenting practices and their children's disruptive behavior and negative emotionality. Children's heart rate reactivity was assessed through a series of stress-inducing tasks. Results from regression-based mediation analyses with bootstrapping showed that negative emotionality and stress reactivity did not mediate the relation between parenting and disruptive behavior. The results overall demonstrate that in a group of children this age, a reinforcing dynamic between parenting, child stress and disruptive behavior is not yet firmly established.

Which Psychosocial Strengths Could Combat the Adolescent Suicide Spectrum? Dissecting the Covitality Model

Objective: Covitality is a meta-construct of positive intra/interpersonal self-schemas that organize and process life experiences. Its synergy favors psychosocial adjustment and prevents mental health problems during adolescence. At these ages, suicide is one of the leading causes of death worldwide. The purpose of this study was to determine which psychosocial strengths of the covitality model could combat adolescent suicide spectrum. Method: Participants were 5,528 Spanish adolescents aged 12-18 years, 50.74% females. The assessment protocol was completed in schools, under the supervision of the research staff. Statistical analyses were conducted using hurdle models, i.e., modeling zero-inflated count data. This process provided two sets of outcomes: the association - in probabilistic terms - between psychosocial strengths and the absence of suicide indicators (i.e., non-occurrence) and the association of these assets - via regression coefficients - with increased experimentation (i.e., duration/quantity). Results: All psychosocial strengths of the covitality model were related to the non-ocurrence of suicidal thoughts and behaviors, but not all to a shorter duration/quantity of their phenotypic manifestations. Covitality obtained greater association values on suicidal tendencies than its components analyzed independently. Belief in self and engaged living were the second-order factors with the higher estimating capacity. Specifically, emotional self-awareness, enthusiasm, gratitude, family support, and behavioral self-control were key first-order assets. Conclusions: These findings suggest that training adolescents in covitality assets could be an effective strategy for universal prevention against premature suicide. Moreover, this study provide evidence on which psychosocial strengths could counteract each phenotypic manifestation of suicide in order to customize selective and indicated preventive actions.

A Latent Class Analysis on Indicators of Early Prolonged Grief Disorder and Well-Being Among Dutch Adults Bereaved During the First Year of the COVID-19 Pandemic

Most studies examining prolonged grief disorder (PGD) in people bereaved during the COVID-19 pandemic are focused on psychopathology. However, mental health encompasses both absence of psychopathology and presence of well-being. This is the first study examining symptom profiles of early PGD and subjective mental well-being in 266 Dutch adults recently bereaved during the pandemic. Early PGD and well-being indicators were assessed with the Traumatic Grief Inventory-Self Report Plus and the World Health Organization-Five Well-Being Index, respectively. Latent class analysis identified four classes: low PGD/high well-being (32%), low PGD/moderate well-being (24%), moderate PGD/high well-being (23%) and high PGD/low well-being class (21%). People in the poorer mental health classes were more likely to be female, lower educated, suffering from a mental disorder, have a poor health status, closer kinship to the deceased, and higher risk of severe COVID-19. Classifying adults according to symptom profiles of negative and positive outcomes provides a more complete picture of mental health in bereaved people and offers potential intervention targets.

Long-term effects of unintended pregnancy on children: Findings from the Dutch prospective birth-cohort Amsterdam born children and their development study

Several studies investigated short-term risks of children born from unintended pregnancies, however evidence about long-term risks is lacking. We aimed to examine whether children born from unintended pregnancies experience psychosocial problems up into adolescence. This study is based on the longitudinal birth cohort study 'Amsterdam Born Children and their Development' (n = 7784). Unintended pregnancy was measured as a multidimensional construct, based on self-reports on the extent of pregnancy mistiming ('This pregnancy happened too soon'), unwantedness ('I did not want to be pregnant (anymore)') and unhappiness ('I am happy to be pregnant'; recoded). Further, children's psychosocial problems were measured with the Strengths and Difficulties Questionnaire, at 5-6, 11-12 and 15-16 years old. Multiple over-time associations between unintended pregnancy and children's psychosocial problems were analysed using Structural Equation Modelling, while controlling for confounders. Results showed that pregnancy mistiming was a significant predictor of internalizing (β = 0.10, p < 0.001) and externalizing problems (β = 0.07, p = 0.006) and unwanted pregnancy of internalizing problems (β = 0.13, p < 0.001) at 5-6 years. These associations were substantially mediated by maternal mental health and poorer maternal bonding. Associations were no longer present at 11-12 and 15-16 years. Thus, we conclude that children born from unintended pregnancies experience more psychosocial problems at 5-6 years, but no longer at 11-12 and 15-16 years. Unintended pregnancies often coincide with maternal mental health problems and socioeconomic factors. Most importantly, the associations between unintended pregnancy and children's psychosocial problems are influenced by maternal mental health and poorer bonding. Therefore it is important to improve maternal mental health and bonding for the benefit of both mother and child, rather than on the isolated effect of unintended pregnancy per se.

Trajectories of Housing Insecurity From Infancy to Adolescence and Adolescent Health Outcomes

BACKGROUND AND OBJECTIVES

Housing insecurity is associated with adverse effects on child growth and development cross-sectionally; less is known about its cumulative, long-term effects. This study describes longitudinal experiences of housing insecurity during childhood from infancy (age 1 year) to adolescence (age 15 years) and examines their associations with adolescent health outcomes.

METHODS

Using data from the Future of Families and Child Wellbeing Study, we created a composite measure of housing insecurity using 5 indicators (eg, skipping a rent or mortgage payment, eviction) for participants at ages 1, 3, 5, 9, and 15 years. We used group-based trajectory modeling to identify distinct patterns of housing insecurity, sociodemographic predictors of these patterns, and how these patterns relate to adolescent health outcomes.

RESULTS

We identified 3 trajectories of housing insecurity from infancy to adolescence: secure, moderately insecure, and highly insecure. Adolescents who experienced moderately and highly insecure housing had decreased odds of excellent health (adjusted odds ratio, 0.81; 95% confidence interval [CI], 0.69-0.95; adjusted odds ratio, 0.67; 95% CI, 0.50-0.92, respectively) and more depressive symptoms (adjusted incidence rate ratio, 1.05; 95% CI, 1.02-1.08; 1.13; 95% CI, 1.08-1.19, respectively) than adolescents with secure housing. Adolescents who experienced highly insecure housing reported significantly higher anxiety symptoms (adjusted incidence rate ratio, 1.05; 95% CI, 1.003-1.113).

CONCLUSIONS

Housing insecurity starting in infancy was associated with poorer adolescent health outcomes. These longitudinal patterns emphasize the need for novel screening mechanisms to identify housing insecurity when it emerges, as well as policies to prevent housing insecurity and its associated health outcomes.

Transparency and reproducibility in the Adolescent Brain Cognitive Development (ABCD) study

BACKGROUND

Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.

METHODS

Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor.

RESULTS

There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30 % of full-length articles. The number of participants excluded due to missing data was reported in 60 % of articles, and information on missing data for individual variables (e.g., household income) was provided in 38 % of articles. A table describing the analytic sample was included in 83 % of articles. A race and/or ethnicity variable was included in 78 % of reviewed articles, while its inclusion was justified in only 41 % of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10 % of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10 % of LOC scores (β=-0.77, 95 % -1.02, -0.51; p-value < 0.0001).

CONCLUSION

These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

A prospective longitudinal study of depression, perceived stress, and perceived control in resettled Syrian refugees' mental health and psychosocial adaptation

This prospective study examined the psychosocial adaptation of a community sample of newly resettled Syrian refugees in Canada (N = 235). Specifically, depressive symptoms, perceived stress, and perceived control were collected in Arabic at baseline and 1-year follow-up. Two theory-informed, cross-lagged panel models demonstrated that higher baseline depressive symptoms predicted lower perceived self-efficacy and lower perceived control at 1-year follow-up. Similarly, baseline depressive symptoms were concurrently correlated with higher perceived helplessness, lower perceived self-efficacy, and lower perceived control. Secondary regression analyses further demonstrated that baseline depressive symptoms predicted lower perceived social support and higher anxiety symptoms, though neither were assessed at baseline. Empirical results identify a potentially broad, precipitating, and persistent effect of depressive symptoms on Syrian refugees' psychosocial resources and adaptation post-migration, which is consistent with both the transactional model of stress and coping and the self-efficacy theory of depression, respectively. Clinically, the study results highlight the importance of early screening for depressive symptoms among refugee newcomers within a culturally and trauma-informed, integrated health setting. Furthermore, this study underscores the value and need for theoretically guided longitudinal studies to advance future research on refugee mental health and psychosocial adaptation.

The impact of perceived injustice on pain and psychological outcomes after traumatic injury: a longitudinal analysis

ABSTRACT

Individuals' appraisals regarding the injustice of their pain or physical injury have emerged as a significant risk factor for worse physical and psychological outcomes. Injustice appraisals are defined by perceptions of external blame for pain or injury and viewing pain or injury as a source of irreparable loss. To date, research on the impact of injustice appraisal has been primarily cross sectional, and existing longitudinal studies have examined injustice appraisals at only 2 time points in the context of rehabilitation treatment. This study examined the trajectory of injustice appraisals in 171 patients admitted for traumatic injury at admission, as well as 3, 6, and 12 months after discharge and examined injustice appraisals as a potential moderator of recovery after injury. Findings can be summarized as follows: First, injustice perception was largely stable in the 12 months after hospital discharge. Second, elevated injustice perception was associated with decreased recovery in pain intensity and depressive symptomatology over the study period but did not moderate changes in pain catastrophizing or posttraumatic stress symptomatology over time. This study is the first naturalistic prospective analysis of injustice appraisal following trauma admission within the American healthcare system. Findings indicate that injustice appraisals do not naturally decrease in the aftermath of traumatic injury and may be a risk factor for poorer physical and psychological recovery. Future research should examine additional sociodemographic and psychosocial factors that may contribute to elevated injustice appraisal, as well as ways of addressing the potential deleterious impact of injustice appraisals in treatment settings.

Dyadic Prenatal Coparenting Interaction Behaviors Predicting Postpartum Depressive Symptoms during the Transition to Parenthood

Postpartum depressive symptoms constitute a common yet serious complication of pregnancy and childbirth, but research on its association with coparenting is scarce. Furthermore, although coparenting dynamics start forming prior to the child's birth, no research has explored dyadic prenatal coparenting dynamics as a predictor of postpartum depressive symptoms. The current study assessed how dyadic prenatal coparenting behaviors predicted postpartum depressive symptoms in first-time parents. We conducted a dyadic mixed-method longitudinal study of 107 expectant couples with data collected prenatally, and at 3, 6, and 24 months post-birth. The results indicated that prenatal coparenting dyadic synchrony predicted low levels of depressive symptoms among first-time fathers 3 and 6 months after the birth, and a prenatal coparenting dynamic of dyadic negative escalation predicted high levels of depressive symptoms among first-time mothers at 3 and 24 months postpartum. The theoretical and practical implications are discussed.

The Growth of Complex Syntax in School-Age African American Children Who Speak African American English

PURPOSE

Syntax provides critical support for both academic success and linguistic growth, yet it has not been a focus of language research in school-age African American children. This study examines complex syntax performance of African American children in second through fifth grades.

METHOD

The current study explores the syntactic performances of African American children (N = 513) in Grades 2-5 on the Test of Language Development-Intermediate who speak African American English. Multilevel modeling was used to evaluate the growth and associated changes between dialect density and syntax. Analyzed data were compared both to the normative sample and within the recruited sample.

RESULTS

The results suggest that dialect density exerted its impact early but did not continue to influence syntactic growth over time. Additionally, it was not until dialect density was accounted for in growth models that African American children's syntactic growth resembled normative expectations of a standardized language instrument.

CONCLUSION

The current study suggests that failure to consider cultural language differences obscures our understanding of African American students' linguistic competence on standardized language assessments.

Parent attitudes towards data sharing in developmental science

Background

Data sharing in developmental science is increasingly encouraged, supported by funder and publisher mandates for open data access. Data sharing can accelerate discovery, link researchers with high quality analytic expertise to researchers with large datasets and democratise the research landscape to enable researchers with limited funding to access large sample sizes. However, there are also significant privacy and security concerns, in addition to conceptual and ethical considerations. These are particularly acute for developmental science, where child participants cannot consent themselves. As we move forward into a new era of data openness, it is essential that we adequately represent the views of stakeholder communities in designing data sharing efforts.

Methods

We conducted a comprehensive survey of the opinions of 195 parents on data sharing in developmental science. Survey themes included how widely parents are willing to share their child's data, which type of organisations they would share the data with and the type of consent they would be comfortable providing.

Results

Results showed that parents were generally supportive of curated, but not open, data sharing. In addition to individual privacy and security concerns, more altruistic considerations around the purpose of research were important. Parents overwhelmingly supported nuanced consenting models in which preferences for particular types of data sharing could be changed over time. This model is different to that implemented in the vast majority of developmental science research and is contrary to many funder or publisher mandates.

Conclusions

The field should look to create shared repositories that implement features such as dynamic consent and mechanisms for curated sharing that allow consideration of the scientific questions addressed. Better communication and outreach are required to build trust in data sharing, and advanced analytic methods will be required to understand the impact of selective sharing on reproducibility and representativeness of research datasets.

The Mediating Role of Sleep Quality, Regularity, and Insomnia on the Relationship Between Adverse Childhood Experiences and Resilience

Adverse childhood experiences (ACEs) have been linked to many negative outcomes in prior psychological literature. Previous studies have shown that ACEs are related to sleep problems (e.g., trouble falling and staying asleep) and sleep problems are related to resilience outcomes. However, there are far fewer studies that examine whether sleep quality, regularity, and insomnia symptoms mediate the relationship between ACEs and resilience. Therefore, the purpose of the current study was to analyze the mediating role of sleep problems on the relationship between ACEs and resilience. Emerging adult participants between the ages of 18-25 (N = 501) were recruited online via Mechanical Turk (n = 243) and from a mid-size university research participant pool in the Northwestern United States (n = 258). Participants completed questionnaires online concerning ACEs, sleep problems (i.e., quality, regularity, and insomnia symptoms), and resilience (i.e., psychological well-being, social well-being, life satisfaction, and effortful control). Structural equation modeling was used to analyze the data cross-sectionally. The latent construct of sleep problems was found to mediate the relationship between ACEs and the latent construct of resilience. These results suggest that sleep quality, regularity, and insomnia symptoms may be important targets for intervention when treating individuals with ACEs to increase their resilience.

Randomised controlled trial of the Healthy Living Triple P-Positive Parenting Program for families of children with type 1 diabetes

This randomised controlled trial examined the efficacy of a brief, group-based parenting program in improving child and family outcomes for families of children with type 1 diabetes. Families (N = 50) of children (2-10 years) with type 1 diabetes were randomly allocated to intervention (n = 22) or care-as-usual (n = 28). Assessments (pre-intervention, post-intervention and 6-month follow-up) evaluated parent- and child-reported parenting behaviour, child behaviour/adjustment and child quality of life (primary outcomes); and metabolic control (routinely-collected blood glucose data), parents' self-efficacy with diabetes management, diabetes-specific child behaviour difficulties, family quality of life, parents' diabetes-related and general parenting stress and observed parent and child behaviour (secondary outcomes). Intent-to-treat analyses indicated greater rate of improvement over time for families allocated to intervention compared to care-as-usual for use of corporal punishment (primary caregivers only), and confidence with managing children's emotions/behaviours, parent-rated child quality of life and adjustment to the child's illness (secondary caregivers only). There were no other intervention effects. Although families found the intervention useful, low levels of psychosocial problems at baseline limited the scope for group-level improvement and there was limited evidence for intervention efficacy. Individually-tailored measures of goal-specific behaviour change may be considered in future research.

Transparency and Reproducibility in the Adolescent Brain Cognitive Development (ABCD) Study

Background

Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.

Methods

Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor.

Results

There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30% of full-length articles. The number of participants excluded due to missing data was reported in 60% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38% of articles. A table describing the analytic sample was included in 83% of articles. A race and/or ethnicity variable was included in 78% of reviewed articles, while its inclusion was justified in only 41% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10% of LOC scores (β=-0.77, 95% -1.02, -0.51; p-value < 0.0001).

Conclusion

These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

REFORMS: Consensus-based Recommendations for Machine-learning-based Science

Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of validity, reproducibility, and generalizability. These failures can hinder scientific progress, lead to false consensus around invalid claims, and undermine the credibility of ML-based science. ML methods are often applied and fail in similar ways across disciplines. Motivated by this observation, our goal is to provide clear recommendations for conducting and reporting ML-based science. Drawing from an extensive review of past literature, we present the REFORMS checklist (recommendations for machine-learning-based science). It consists of 32 questions and a paired set of guidelines. REFORMS was developed on the basis of a consensus of 19 researchers across computer science, data science, mathematics, social sciences, and biomedical sciences. REFORMS can serve as a resource for researchers when designing and implementing a study, for referees when reviewing papers, and for journals when enforcing standards for transparency and reproducibility.

A Description of Missing Data in Single-Case Experimental Designs Studies and an Evaluation of Single Imputation Methods

Missing data is inevitable in single-case experimental designs (SCEDs) studies due to repeated measures over a period of time. Despite this fact, SCEDs implementers such as researchers, teachers, clinicians, and school psychologists usually ignore missing data in their studies. Performing analyses without considering missing data in an intervention study using SCEDs or a meta-analysis study including SCEDs studies in a topic can lead to biased results and affect the validity of individual or overall results. In addition, missingness can undermine the generalizability of SCEDs studies. Considering these drawbacks, this study aims to give descriptive and advisory information to SCEDs practitioners and researchers about missing data in single-case data. To accomplish this task, the study presents information about missing data mechanisms, item level and unit level missing data, planned missing data designs, drawbacks of ignoring missing data in SCEDs, and missing data handling methods. Since single imputation methods among missing data handling methods do not require complicated statistical knowledge, are easy to use, and hence are more likely to be used by practitioners and researchers, the present study evaluates single imputation methods in terms of intervention effect sizes and missing data rates by using a real and hypothetical data sample. This study encourages SCEDs implementers, and also meta-analysts to use some of the single imputation methods to increase the generalizability and validity of the study results in case they encounter missing data in their studies.

Autonomic nervous system reactivity to emotion and childhood trajectories of relational and physical aggression

This study investigated the role of autonomic nervous system (ANS) coordination in response to emotion in girls' and boys' development of relational (e.g., ignoring, excluding) and physical (e.g., hitting, kicking) aggression. Caregivers reported on children's relational and physical aggression at ages 6, 7, 8, and 10 years (N = 232, 50.4% girls, 46.6% Latinx). Sympathetic nervous system (assessed via pre-ejection period) and parasympathetic nervous system (assessed via respiratory sinus arrhythmia) reactivity were measured in response to video clips depicting fear, happiness, and sadness at age 7. Growth curve models indicated that ANS reactivity to sadness, but not to fear or happiness, was related to trajectories of relational aggression. In contrast, ANS reactivity to all three emotions was associated with trajectories of physical aggression. Effects differed across genders, indicating that distinct patterns of ANS reactivity to emotion may be involved in girls' and boys' development of aggression. Overall, these findings contribute to a growing literature documenting the role of ANS reactivity to emotion in aggressive behavior. Moreover, this study considers ANS reactivity to specific emotions, as related to both relational and physical aggression, and as differentially expressed among girls versus boys.

Reciprocal Associations Between Language Ability and Social Functioning Development in Pre-verbal Autistic Children

Longitudinal research on language abilities and social functioning in young children suggests that gains in one domain affect gains in the other. However, few studies have examined inter-relations of language and social functioning jointly among young children diagnosed with autism spectrum disorder (ASD). Pre-verbal toddlers with ASD are a group of particular clinical relevance, given that greater language abilities at school entry have been associated with positive long-term adjustment in many areas, including adaptive and social functioning. Reduced attention to and engagement in social interactions among autistic toddlers who are not yet speaking may interfere with language development concurrently and over time. The present study examined reciprocal associations between language ability and social functioning over a 2-year period across three time points in a sample of 90 pre-verbal autistic toddlers using cross-lagged panel analyses conducted in MPlus. Cross-lagged panel analyses revealed significant within-timepoint synchronous correlations, within-domain autoregressive paths over time, and as hypothesized, reciprocal significance in all cross-lagged paths. For very young pre-verbal children with ASD, language ability and social functioning appear to exert concurrent and cascading developmental influences on one another. Targeting both language and social functioning simultaneously may enhance intervention efficacy for very young pre-verbal children with ASD.

Use of psychoactive substances and alcohol during the first three waves of the COVID-19 pandemic: Croatian experience

Increased prevalence and severity of both substance and behavioral addictions are among the most harmful consequences of the COVID-19 outbreak.

To determine the sociodemographic characteristics, COVID-19-related stressors, and stress, anxiety, and depression symptoms that may predict the use and changes in the use of psychoactive substances (PS) during the first three COVID-19 waves in Croatia.

The cross-sectional online survey included 1,118 adult participants (220 men and 898 women; mean age: 35.1 [SD = 12.3] years; age range: 18-78) from general adult population. Sociodemographic data were collected, and ad-hoc developed questionnaires on COVID-19-related stressors, PS use before and during the pandemic, CAGE Alcohol Questionnaire, Impact of Event Scale, and Hospital Anxiety Depression Scale were applied.

The PS use increased in 31% of participants. The use of tobacco, caffeine, alcohol, cannabinoids, and anxiolytics showed the greatest increase in the last year (tobacco 7.1%; caffeine 5.8%; alcohol 6.4%; cannabinoids 2.5%; and anxiolytics 3.9%). Alcohol consumption during the pandemic increased in 16.8% of participants who consumed alcohol before the pandemic, with 4.5% of them reporting problematic alcohol use (PAU). The tested model demonstrated relatively good model-data fit and significantly predicted 11.8% increase in the use of PS and 9.8% of PAU.

Being married or in a relationship and severe anxiety and depression symptoms predicted increased use of PS and PAU, while higher education level and ever being diagnosed with COVID-19 predicted only increased use of PS.

A preliminary investigation of the mediating roles of self-compassion and emotion dysregulation in the relationship between maladaptive perfectionism and obsessive-compulsive behaviors

INTRODUCTION

Recent research has highlighted an association between maladaptive perfectionism and obsessive-compulsive disorder (OCD). However, the mechanisms underlying this relationship are not well understood. The primary aim of this preliminary study was to investigate whether self-compassion and emotion dysregulation independently mediated this relationship. The secondary aim was to determine whether serial mediation existed between these factors. Whether these relations held for overall obsessive-compulsive (OC) symptoms, versus distinct dimensions of OCD, was also of interest.

METHOD

Three hundred and ninety-two university students (Mage  = 21.81, SD = 8.01), predominantly female (79.18%), participated in an online questionnaire that included a dimensional measure of OCD. Scales assessing maladaptive perfectionism, self-compassion, emotion dysregulation, and negative emotion states were also included.

RESULTS

Greater maladaptive perfectionism was related to more severe OCD. Emotion dysregulation, but not self-compassion, independently mediated this relationship. A serial mediation relationship was found, in that greater maladaptive perfectionism was associated with lower self-compassion, which was linked to greater emotion dysregulation, and in turn related to more severe OC behaviors. In addition, distinct patterns emerged for separate OC dimensions.

CONCLUSIONS

These findings highlight emotion regulation and self-compassion as potential targets for OCD prevention, especially in individuals with symptoms in the symmetry and unacceptable thoughts dimensions.

Characteristics of Missing Data in Single-Case Experimental Designs: An Investigation of Published Data

Single-case experimental designs (SCEDs) have grown in popularity in the fields such as education, psychology, medicine, and rehabilitation. Although SCEDs are valid experimental designs for determining evidence-based practices, they encounter some challenges in analyses of data. One of these challenges, missing data, is likely to be occurred frequently in SCEDs research due to repeated measurements over time. Since missing data is a critical factor that can weaken the validity and generalizability of a study, it is important to determine the characteristics of missing data in SCEDs, which are especially conducted with a small number of participants. In this regard, this study aimed to describe missing data features in SCEDs studies in detail. To accomplish this goal, 465 published SCEDs studies within the recent 5 years in six journals were included in the investigation. The overall results showed that the prevalence of missing data among SCEDs articles in at least one phase, as at least one data point, was approximately 30%. In addition, the results indicated that the missing data rates were above 10% within most studies where missing data occurred. Although missing data is so common in SCEDs research, only a handful of studies (5%) have handled missing data; however, their methods are traditional. In analyzing SCEDs data, several methods are proposed considering missing data ratios in the literature. Therefore, missing data rates determined in this study results can shed light on the analyses of SCEDs data with proper methods by improving the validity and generalizability of study results.

Characterizing Human Habits in the Lab

Habits pose a fundamental puzzle for those aiming to understand human behavior. They pervade our everyday lives and dominate some forms of psychopathology but are extremely hard to elicit in the lab. In this Registered Report, we developed novel experimental paradigms grounded in computational models, which suggest that habit strength should be proportional to the frequency of behavior and, in contrast to previous research, independent of value. Specifically, we manipulated how often participants performed responses in two tasks varying action repetition without, or separately from, variations in value. Moreover, we asked how this frequency-based habitization related to value-based operationalizations of habit and self-reported propensities for habitual behavior in real life. We find that choice frequency during training increases habit strength at test and that this form of habit shows little relation to value-based operationalizations of habit. Our findings empirically ground a novel perspective on the constituents of habits and suggest that habits may arise in the absence of external reinforcement. We further find no evidence for an overlap between different experimental approaches to measuring habits and no associations with self-reported real-life habits. Thus, our findings call for a rigorous reassessment of our understanding and measurement of human habitual behavior in the lab.

Comparison of the effects of imputation methods for missing data in predictive modelling of cohort study datasets

BACKGROUND

Missing data is frequently an inevitable issue in cohort studies and it can adversely affect the study's findings. We assess the effectiveness of eight frequently utilized statistical and machine learning (ML) imputation methods for dealing with missing data in predictive modelling of cohort study datasets. This evaluation is based on real data and predictive models for cardiovascular disease (CVD) risk.

METHODS

The data is from a real-world cohort study in Xinjiang, China. It includes personal information, physical examination data, questionnaires, and laboratory biochemical results from 10,164 subjects with a total of 37 variables. Simple imputation (Simple), regression imputation (Regression), expectation-maximization(EM), multiple imputation (MICE) , K nearest neighbor classification (KNN), clustering imputation (Cluster), random forest (RF), and decision tree (Cart) were the chosen imputation methods. Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) are utilised to assess the performance of different methods for missing data imputation at a missing rate of 20%. The datasets processed with different missing data imputation methods were employed to construct a CVD risk prediction model utilizing the support vector machine (SVM). The predictive performance was then compared using the area under the curve (AUC).

RESULTS

The most effective imputation results were attained by KNN (MAE: 0.2032, RMSE: 0.7438, AUC: 0.730, CI: 0.719-0.741) and RF (MAE: 0.3944, RMSE: 1.4866, AUC: 0.777, CI: 0.769-0.785). The subsequent best performances were achieved by EM, Cart, and MICE, while Simple, Regression, and Cluster attained the worst performances. The CVD risk prediction model was constructed using the complete data (AUC:0.804, CI:0.796-0.812) in comparison with all other models with p<0.05.

CONCLUSION

KNN and RF exhibit superior performance and are more adept at imputing missing data in predictive modelling of cohort study datasets.

Fall Risk Prediction for Community-Dwelling Older Adults: Analysis of Assessment Scale and Evaluation Items without Actual Measurement

The frequency of falls increases with age. In Japan, the population is aging rapidly, and fall prevention measures are an urgent issue. However, assessing fall risk during the coronavirus disease pandemic was complicated by the social distancing measures implemented to prevent the disease, while traditional assessments that involve actual measurements are complicated. This prospective cohort study predicted the risk of falls in community-dwelling older adults using an assessment method that does not require actual measurements. A survey was conducted among 434 community-dwelling older adults to obtain data regarding baseline attributes (age, sex, living with family, use of long-term care insurance, and multimorbidity), Frailty Screening Index (FSI) score, and Questionnaire for Medical Checkup of Old-Old (QMCOO) score. The participants were categorized into fall (n = 78) and non-fall (n = 356) groups. The binomial logistic regression analysis showed that it is better to focus on the QMCOO sub-item score, which focuses on multiple factors. The items significantly associated with falls were Q5 (odds ratio [OR] 1.95), Q8 (OR 2.33), and Q10 (OR 3.68). Our results were similar to common risk factors for falls in normal times. During the pandemic, being able to gauge the risk factors for falls without actually measuring them was important.