Can we predict non-response in developmental tasks? Assessing the longitudinal relation between toddlers' non-response and early academic skills

To date, virtually no studies have examined toddlers' non-response in developmental tasks. This study investigates data from 3667 toddlers to address (1) whether two aspects of non-response (completion and engagement) are separable, (2) how stable these aspects are from ages two to three, (3) how non-response relates to background characteristics, and (4) whether non-response at ages two and three predicts early academic skills at age six. Structural equation modelling shows that completion and engagement are separable constructs, relatively stable across age, and related to several background characteristics. Especially engagement predicts later academic performance. Results show that non-response in behavioural tasks in toddlers is not random, increasing the likelihood of sampling bias and lack of generalizability in developmental studies.     

The role of effort type and intensity in children's decisions about effort-based outcomes

Despite the importance of persistence in early learning, we know little about how children reason about outcomes that result from their efforts. Here we examined the role of effort type (i.e., physical vs. cognitive) and intensity (i.e., high vs. low effort) in shaping children's decision making about effort-based rewards. Five- to 7-year-olds (N = 133) were assigned to one of four conditions (High Physical Effort, Low Physical Effort, High Cognitive Effort, Low Cognitive Effort) and completed a series of tasks to construct a toy. Tasks varied in the type (physical/cognitive) and intensity (high/low) of effort required to complete them. After constructing their toy, children completed a series of tasks to probe how much they valued that toy. Across conditions, children preferred their toy and gave it a higher monetary value, relative to a stranger's. However, when choosing their toy came at a cost, children no longer preferred it. Only children who built their toy through either cognitive or low effort were willing to incur a cost for their toy. Older children, across conditions, were also more likely to incur a cost for their toy. These findings demonstrate that by age five, children are sensitive to variations in effort type and intensity, and these factors shape how they evaluate effort-based rewards.     

Behavioral Activation Disseminated by Non–Mental Health Professionals,Paraprofessionals, and Peers: A Systematic Review

There is a striking disparity between the number of individuals with significant mental health concerns and those who are able to access care globally. One promising solution to expanding the mental health taskforce is task-sharing, or employing nonspecialists in the delivery of evidence-based interventions. Behavioral activation (BA), a brief intervention that focuses on scheduling rewarding activities into one’s daily life, may have promise for delivery using task-sharing approaches due to its straightforward, flexible nature. The aim of this systematic review was to examine the current state of the literature on non-specialist-delivered BA and evaluate the evidence base of this approach. Three databases (Pubmed, PsycInfo, and Cochrane) were searched, and all articles were screened for inclusion criteria by two research assistants, included the review of titles, abstracts, and full-text. The final dataset consisted of 13 research studies, represented through 15 articles. A meta-analysis was conducted to examine the overall pooled effects of peer-delivered BA on depressive symptoms (the most widely examined clinical outcome). Studies reported on effectiveness and implementation outcomes of non-specialist-delivered BA for depression, substance use, loneliness, trauma survivors, and individuals with comorbid physical health conditions. Results provide initial support for the effectiveness of BA utilizing a task-sharing approach, and highlight the feasibility and acceptability of using nonspecialists to deliver BA in a variety of contexts, including low-resource settings.     

Treating Young Adult Depression With Text-Delivered Cognitive Behavioral Therapy: A Pilot Randomized Clinical Trial

Young adults (ages 18 to 25) in the U.S. suffer from the highest rates of past-year major depressive episode and are the least likely to receive treatment compared to other age groups. As such, we examined the feasibility, acceptability, and efficacy of a text-message delivered cognitive behavioral therapy: CBT-txt with young adults. The study was a 2-month pilot RCT to test a 4-week intervention for depression that contained 197 text messages (average 12 texts every other day). The sample, recruited via Facebook and Instagram, was 102 U.S. young adults who presented with at least moderate depressive symptomatology. Assessments occurred at baseline prior to randomization and at 1 and 2 months post enrollment. The primary outcome, severity of depressive symptoms, was assessed using the Beck Depression Inventory II. Feasibility benchmarks were met and participants reported high levels of engagement with and acceptability of the intervention. Logistic regression indicated that treatment participants were three times as likely to have minimal or mild depression symptoms at 2 months compared to waitlist control participants. Latent change score modeling found that the strongest significant treatment effect appeared at the 1-month follow-up period, particularly for participants who began with severe depressive symptoms. Mediation analysis revealed significant indirect treatment effects of increases in behavioral activation on reducing depressive symptoms, suggesting a mechanism of change. Limitations were that the sample was relatively small and consisted of primarily women. These results provide initial evidence for the feasibility, acceptability, and efficacy of a text-delivered treatment for young adult depression.     

Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.     

Penalized optimal scaling for ordinal variables with an application to international classification of functioning core sets

Ordinal data occur frequently in the social sciences. When applying principal component analysis (PCA), however, those data are often treated as numeric, implying linear relationships between the variables at hand; alternatively, non-linear PCA is applied where the obtained quantifications are sometimes hard to interpret. Non-linear PCA for categorical data, also called optimal scoring/scaling, constructs new variables by assigning numerical values to categories such that the proportion of variance in those new variables that is explained by a predefined number of principal components (PCs) is maximized. We propose a penalized version of non-linear PCA for ordinal variables that is a smoothed intermediate between standard PCA on category labels and non-linear PCA as used so far. The new approach is by no means limited to monotonic effects and offers both better interpretability of the non-linear transformation of the category labels and better performance on validation data than unpenalized non-linear PCA and/or standard linear PCA. In particular, an application of penalized optimal scaling to ordinal data as given with the International Classification of Functioning, Disability and Health (ICF) is provided.     

Inoculation against conspiracy theories: A consumer side approach to India's fake news problem

We attempt to replicate Roozenbeek and van der Linden's Western-based study in India by employing the Bad News Game, an online game, in which players take on the role of a misinformation tycoon. They are exposed to weakened doses of the strategies employed in conspiracy and fake news production with the aim to cognitively inoculate them against misinformation. The proliferation of inexpensive mobile connections coupled with a lack of digital literacy has resulted in a conspiratorial pandemic in developing countries like India. We test the game's impact on an Indian sample (n = 1002) using a within-subject design. We provide evidence of significant improvement in the ability of participants to identify the misinformation produced using Conspiracy, Impersonation, and to a lesser extent, the Discrediting technique, while observing greater truth discernment in correctly identifying true news. We also conduct sub-sample analyses. These findings have positive implications for methods that protect users from malignant online content.     

Insights into computational thinking from think-aloud interviews: A systematic review

This systematic review examines 35 empirical studies featuring the use of think-aloud interviews in computational thinking (CT) research. Findings show that think-aloud interviews (1) are typically conducted in Computer Science classrooms and with K-12 students; (2) are usually combined with other exploratory CT assessment tools; (3) have the potential to benefit learners with special needs and identify the competency gaps through involving diverse participants; (4) are conducted in the absence of cognitive models and standard procedures; and (5) display insufficient definitional and methodological rigor. Theoretically, this review presents a systematic assessment about the application of think-aloud interviews in CT studies and identifies the limitations in existing CT-related think-aloud studies. Practically, this review serves as a reference for studying the cognitive processes during CT problem-solving and provides suggestions for CT researchers who intend to incorporate think-aloud interviews in their studies.     

Structural connectivity between the hippocampus and cortical/subcortical area relates to cognitive impairment in schizophrenia but not in mood disorders

Cognitive impairment in schizophrenia and other psychiatric disorders is a challenge to be overcome in order to maintain patients' quality of life and social function. The neurological pathogenesis of cognitive impairment requires further elucidation. In general, the hippocampus interacts between the cortical and subcortical areas for information processing and consolidation and has an important role in memory. We examined the relationship between structural connectivity of the hippocampus and cortical/subcortical areas and cognitive impairment in schizophrenia, major depressive disorder and bipolar disorder. Subjects comprised 21 healthy controls, 19 patients with schizophrenia, 20 patients with bipolar disorder and 18 patients with major depressive disorder. Diffusion-weighted tensor images data were processed using ProbtrackX2 to calculate the structural connectivity between the hippocampus and cortical/subcortical areas. Cognitive function was assessed using the Brief Assessment of Cognition in schizophrenia composite score. Hippocampal structural connectivity index was significantly correlated with composite score in the schizophrenia group but not in the healthy control, major depressive disorder or bipolar disorder groups. There were no statistically significant differences in hippocampal structural connectivity index between the four groups. Structural connectivity between the hippocampus and cortical/subcortical areas is suggested to be a pathophysiological mechanism of comprehensive cognitive impairment in schizophrenia.     

The factor structure of the Multiple Affect Adjective Check List-Revised (MAACL-R): Some statistical considerations

In response to Zuckerman's comments on my factor analyses of the MAACL-R, I focus on the statistical issues of the cutoff criterion for factor loadings and the evidence for the discriminant validity of the five-factor solution. Based upon the conclusions I draw in these two areas, I recommend that researchers either (a) use the two factor solution to the MAACL-R represented in the summary scores of Dysphoria and Positive Affect + Sensation Seeking or (b) include all MAACL-R scales in their studies and analyze their data to determine whether it is statistically appropriate to report results from a single scale (A, D, H, PA, or SS) rather than from the summary scores.