Individual longitudinal changes in DNA-methylome identify signatures of early-life adversity and correlate with later outcome.

Adverse early-life experiences (ELA) affect a majority of the world's children. Whereas the enduring impact of ELA on cognitive and emotional health is established, there are no tools to predict vulnerability to ELA consequences in an individual child. Epigenetic markers including peripheral-cell DNA-methylation profiles may encode ELA and provide predictive outcome markers, yet the interindividual variance of the human genome and rapid changes in DNA methylation in childhood pose significant challenges. Hoping to mitigate these challenges we examined the relation of several ELA dimensions to DNA methylation changes and outcome using a within-subject longitudinal design and a high methylation-change threshold. DNA methylation was analyzed in buccal swab/saliva samples collected twice (neonatally and at 12 months) in 110 infants. We identified CpGs differentially methylated across time for each child and determined whether they associated with ELA indicators and executive function at age 5. We assessed sex differences and derived a sex-dependent 'impact score' based on sites that most contributed to methylation changes. Changes in methylation between two samples of an individual child reflected age-related trends and correlated with executive function years later. Among tested ELA dimensions and life factors including income to needs ratios, maternal sensitivity, body mass index and infant sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, high early-life unpredictability interacted with methylation changes to presage executive function. Thus, longitudinal, within-subject changes in methylation profiles may provide a signature of ELA and a potential predictive marker of individual outcome.

The impact of an immersive digital therapeutic tool on experimental pain: a pilot randomized within-subject experiment with an active control condition.

Background: Pain is a complex and multifaced sensory and emotional experience. Virtual reality (VR) has shown promise in reducing experimental pain and chronic pain. This study examines an immersive VR environment initially designed for endometriosis patients, which demonstrated short-term analgesic effects. The research aims to determine the impact of the VR environment on experimental pain intensity and unpleasantness both during and after VR exposure (3D with binaural beats), while using an active control condition (2D with no binaural beats). Additionally, a secondary objective of the study was to identify the psychological and psychophysical factors that predict the analgesic effects of the immersive digital therapeutic tool. Methods: The study involved twenty-one healthy individuals and used a within-subject design, comparing a VR treatment with an active control condition. Continuous heat stimulation was applied to the left forearm with a Peltier thermode. Pain ratings were collected for immediate and short-term effects. Results: In both the VR and Control conditions, there were no significant differences in pain intensity before, during, and after exposure. However, during VR exposure, there was a significant decrease in pain unpleasantness as compared to before exposure (p < 0.001), with a 27.2% pain reduction. In the Control condition, there were no significant differences in pain unpleasantness during and after exposure. Furthermore, no psychological and psychophysical factors predicted the analgesic effects. Discussion: The study investigated how a VR environment affected experimentally induced pain in healthy volunteers. It showed that VR reduced pain unpleasantness during exposure but had no lasting impact. The VR environment mainly influenced the emotional aspect of pain, possibly due to its inclusion of binaural beats and natural stimuli. The study suggests that the VR environment should be tested in chronic pain population with high distress levels. Registration number clinicaltrialsgov: NCT06130267.

Does Watching Videos With Natural Scenery Restore Attentional Resources?

Existing studies have shown that direct exposure to a real nature environment has a restorative effect on attentional resources after a mentally fatiguing task. However, it remains unclear whether virtual nature simulations can serve as a substitute for real nature experienced in the outdoors to restore executive attention. Given the mixed findings in the literature, the present study sought to examine if viewing videos with natural scenery (vs. a control with urban scenery) restores participants' working memory capacity - measured by an operation span task - in a high-powered pre-registered within-subject experimental study. Overall, our within-subject experiment did not find any evidence to support the benefit of watching videos with natural scenery on restoration of executive attention. Moreover, the results from our Bayesian analyses further showed substantial support for the null hypothesis. Our study suggests that virtual nature simulations, even with the use of videos, may not be able to replicate the experiences of nature in the outdoors and restore attentional resources.

Selecting a Within- or Between-Subject Design for Mediation: Validity, Causality, and Statistical Power.

Researchers with mediation hypotheses must consider which design to use: within-subject or between-subject? In this paper, I argue that three factors should influence design choice: validity, causality, and statistical power. Threats to validity include carry-over effects, participant awareness, measurement, and more. Causality is a core element of mediation, and the assumptions required for causal inference differ between the two designs. Between-subject designs require more restrictive no-confounder assumptions, but within-subject designs require the assumption of no carry-over effects. Statistical power should be higher in within-subject designs, but the degree and conditions of this advantage are unknown for mediation analysis. A Monte Carlo simulation compares designs under a broad range of sample sizes, effect sizes, and correlations among repeated measurements. The results show within-subject designs require about half the sample size of between-subject designs to detect indirect effects of the same size, but this difference can vary with population parameters. I provide an empirical example and R script for conducting power analysis for within-subject mediation analysis. Researchers interested in conducting mediation analysis should not select within-subject designs merely because of higher power, but they should also consider validity and causality in their decision, both of which can favor between-subject designs.

Within-subject changes in methylome profile identify individual signatures of early-life adversity, with a potential to predict neuropsychiatric outcome.

Background: Adverse early-life experiences (ELA), including poverty, trauma and neglect, affect a majority of the world's children. Whereas the impact of ELA on cognitive and emotional health throughout the lifespan is well-established, it is not clear how distinct types of ELA influence child development, and there are no tools to predict for an individual child their vulnerability or resilience to the consequences of ELAs. Epigenetic markers including DNA-methylation profiles of peripheral cells may encode ELA and provide a predictive outcome marker. However, the rapid dynamic changes in DNA methylation in childhood and the inter-individual variance of the human genome pose barriers to identifying profiles predicting outcomes of ELA exposure. Here, we examined the relation of several dimensions of ELA to changes of DNA methylation, using a longitudinal within-subject design and a high threshold for methylation changes in the hope of mitigating the above challenges. Methods: We analyzed DNA methylation in buccal swab samples collected twice for each of 110 infants: neonatally and at 12 months. We identified CpGs differentially methylated across time, calculated methylation changes for each child, and determined whether several indicators of ELA associated with changes of DNA methylation for individual infants. We then correlated select dimensions of ELA with methylation changes as well as with measures of executive function at age 5 years. We examined for sex differences, and derived a sex-dependent 'impact score' based on sites that most contributed to the methylation changes. Findings: Setting a high threshold for methylation changes, we discovered that changes in methylation between two samples of an individual child reflected age-related trends towards augmented methylation, and also correlated with executive function years later. Among the tested factors and ELA dimensions, including income to needs ratios, maternal sensitivity, body mass index and sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, an interaction was observed between a measure of high early-life unpredictability and methylation changes, in presaging executive function. Interpretation: These findings establish longitudinal, within-subject changes in methylation profiles as a signature of some types of ELA in an individual child. Notably, such changes are detectable beyond the age-associated DNA methylation dynamics. Future studies are required to determine if the methylation profile changes identified here provide a predictive marker of vulnerabilities to poorer cognitive and emotional outcomes.

Non-normal Data in Repeated Measures ANOVA: Impact on Type I Error and Power / Datos no Normales en el ANOVA de Medidas Repetidas: Impacto en el Error Tipo I y Potencia

Background: Repeated measures designs are commonly used in health and social sciences research. Although there are other, more advanced, statistical analyses, the F-statistic of repeated measures analysis of variance (RM-ANOVA) remains the most widely used procedure for analyzing differences in means. The impact of the violation of normality has been extensively studied for between-subjects ANOVA, but this is not the case for RM-ANOVA. Therefore, studies that extensively and systematically analyze the robustness of RM-ANOVA under the violation of normality are needed. This paper reports the results of two simulation studies aimed at analyzing the Type I error and power of RM-ANOVA when the normality assumption is violated but sphericity is fulfilled. Method: Study 1 considered 20 distributions, both known and unknown, and we manipulated the number of repeated measures (3, 4, 6, and 8) and sample size (from 10 to 300). Study 2 involved unequal distributions in each repeated measure. The distributions analyzed represent slight, moderate, and severe deviation from normality. Results: Overall, the results show that the Type I error and power of the F-statistic are not altered by the violation of normality. Conclusions: RM-ANOVA is generally robust to non-normality when the sphericity assumption is met.(AU)

Antecedentes: El diseño de medidas repetidas es uno de los más usados en ciencias sociales y de la salud. Aunque hay otras alternativas más avanzadas, el análisis de varianza de medidas repetidas (ANOVA-MR) sigue siendo el procedimiento más empleado para analizar las diferencias de medias. El impacto de la violación de la normalidad ha sido muy estudiado en el ANOVA intersujeto, pero los estudios son muy escasos en el ANOVA-MR. Por ello, el objetivo de este trabajo es realizar dos estudios de simulación Monte Carlo para analizar el error de Tipo I y la potencia cuando se incumple este supuesto bajo el cumplimiento de la esfericidad. Método: El estudio 1 incluye 20 distribuciones, tanto conocidas como desconocidas, manipulando el número de medidas repetidas (3, 4, 6 y 8) y el tamaño muestral (de 10 a 300). El estudio 2 incluye diferentes distribuciones en cada medida repetida. Las distribuciones analizadas representan desviación leve, moderada y severa de la normalidad. Resultados: En general, los resultados muestran que tanto el error Tipo I como la potencia del estadístico F no se alteran con la violación de la normalidad. Conclusiones: El ANOVA-MR es generalmente robusto a la no normalidad cuando la esfericidad se satisface.(AU)

The Evolution of Behavior Analysis: Toward a Replication Crisis?

The Open Science Collaboration (Science, 349(6251), 1-8, 2015) produced a massive failure to replicate previous research in psychology-what has been called a "replication crisis in psychology." An important question for behavior scientists is: To what extent is behavior science vulnerable to this type of massive replication failure? That question is addressed by considering the features of a traditional approach to behavior science. Behavior science in its infancy was a natural science, inductive, within-subject approach that encouraged both direct and systematic replication. Each of these features of behavior science increased its resistance to three factors identified as responsible for the alleged replication crisis: (1) failures to replicate procedures, (2) low-power designs, and (3) publication bias toward positive results. As behavior science has evolved, the features of the traditional approach have become less ubiquitous. And if the science continues to evolve as it has, it will likely become more vulnerable to a massive replication failure like that reported by the Open Science Collaboration (Science, 349(6251), 1-8, 2015).

Clozapine Treatment and Offending: A Within-Subject Study of Patients With Psychotic Disorders in Sweden.

Clozapine treatment may have beneficial effects on behavioral outcomes in psychotic disorders, including violent offending. Although clozapine and other antipsychotics have been linked to lower levels of violent behavior, these have been primarily in small selected samples, and population-based estimates have been limited and imprecise. We aimed to assess the effect of clozapine treatment on the rate of violent and nonviolent offending. We carried out a within-person mirror-image study of the Swedish population with linked prescription, hospitalization, and sociodemographic registers. Outcomes were violent, nonviolent, and overall offences occurring before and after clozapine, or olanzapine, initiation. Comparison of effects of clozapine and olanzapine on key variables was modeled with interaction terms. We found periods of mirror-image observation time with clozapine treatment were associated with a much lower rate of violent offending compared to periods before treatment (rate ratio [RR]: 0.13 (95% CI: 0.05, 0.34). Reductions in nonviolent offences were smaller in magnitude (RR: 0.37, 95% CI: 0.17, 0.80). There was a statistically greater rate reduction effect on violent offences for clozapine than olanzapine (RR for interaction: 4.84, 95% CI: 1.56, 14.86, P = .002). In patients with psychotic disorders, clozapine treatment is associated with a lower rate of violent offending compared to olanzapine.

Randomized, double-blind, placebo-controlled, crossover study of the effects of repeated-dose caffeine on neurobehavioral performance during 48 h of total sleep deprivation.

RATIONALE: Caffeine is widely used as a countermeasure against neurobehavioral impairment during sleep deprivation. However, little is known about the pharmacodynamic profile of caffeine administered repeatedly during total sleep deprivation. OBJECTIVES: To investigate the effects of repeated caffeine dosing on neurobehavioral performance during sleep deprivation, we conducted a laboratory-based, randomized, double-blind, placebo-controlled, crossover, multi-dose study of repeated caffeine administration during 48 h of sleep deprivation. Twelve healthy adults (mean age 27.4 years, six women) completed an 18-consecutive-day in-laboratory study consisting of three 48 h total sleep deprivation periods separated by 3-day recovery periods. During each sleep deprivation period, subjects were awakened at 07:00 and administered caffeine gum (0, 200, or 300 mg) at 6, 18, 30, and 42 h of wakefulness. The Psychomotor Vigilance Test and Karolinska Sleepiness Scale were administered every 2 h. RESULTS: The 200 and 300 mg doses of caffeine mitigated neurobehavioral impairment across the sleep deprivation period, approaching two-fold performance improvements relative to placebo immediately after the nighttime gum administrations. No substantive differences were noted between the 200 mg and 300 mg caffeine doses, and adverse effects were minimal. CONCLUSIONS: The neurobehavioral effects of repeated caffeine dosing during sleep deprivation were most evident during the circadian alertness trough (i.e., at night). The difference between the 200 mg and 300 mg doses, in terms of the mitigation of performance impairment, was small. Neither caffeine dose fully restored performance to well-rested levels. These findings inform the development of biomathematical models that more accurately account for the time of day and sleep pressure-dependent effects of caffeine on neurobehavioral performance during sleep loss.

Assessing the repeatability of resurgence in humans: Implications for the use of within-subject designs.

Resurgence refers to the recurrence of a previously reinforced response following the worsening of reinforcement conditions (e.g., extinction) for an alternative response. Because of the implications for treatment relapse, researchers have become particularly interested in mitigating resurgence of human behavior. Some studies have employed reversal designs and varied parameters across replications (e.g., ABCADC) to compare effects of second-phase variables. Although resurgence is generally repeatable within and between subjects, the extent to which similar levels of resurgence occur across replications is less clear. To assess the repeatability of resurgence, we conducted a secondary analysis of 62 human-operant data sets using ABCABC reversal designs from two laboratories in the United States. We found significant reductions in the magnitude of resurgence during the second exposure to extinction relative to the first exposure when all other phase variables were held constant. These results suggest that researchers should exercise caution when using within-subject, across-phase replications to compare resurgence between variable manipulations with human participants.

Within vs. between-subject effects of intranasal oxytocin on the neural response to cooperative and non-cooperative social interactions.

The neuropeptide oxytocin (OT) plays a critical role in modulating social behavior across a wide range of vertebrate species. In humans, intranasal oxytocin (INOT) has been shown to modulate various aspects of social behavior, such as empathy, trust, in-group preference, and memory of socially relevant cues. Most INOT studies employ cross-sectional designs despite the enhanced statistical power and reduction in error variance associated with individual differences characteristic of within-subject designs. Using the Prisoner Dilemma task, which models a real-life dyadic social interaction, our group has systematically explored the effect of INOT on social cooperation and non-cooperation using a cross-sectional design. In the current study, we investigated if the main findings from our cross-sectional study could be replicated in a within-subject design using the same paradigm and whether new findings would emerge. We found OT to attenuate the ventral tegmental area response to reciprocated cooperation in women, an effect that is also present in our cross-sectional sample. However, other cross-sectional findings, especially those found in men, were not observed in this within-subject study. We hypothesize that the discrepancy can be explained by differing OT effects based on the degree of stimulus novelty/familiarity. Our within-subject study also revealed new effects not found previously in our cross-sectional study. Most importantly, OT treatment on scan 2 blocked amygdala habituation to unreciprocated cooperation found in a group that received placebo on both scans among men. Our results suggest that exogenous OT reduces the salience of positive social interactions among women and prevents habituation to negative social interactions among men. These findings may have implications for the potential clinical utility of OT as a treatment for psychiatric disorders.

Neural correlates of 12-h abstinence-induced craving in young adult smokers: a resting-state study.

Studying the neural correlates of craving to smoke in young adulthood is of great importance to improve treatment outcomes in nicotine dependence. Previous nicotine dependence studies mainly focused on the neural substrates of craving elicited by smoking-related cues. More explicit attention to abstinence-induced craving during resting state in nicotine dependence has the potential to yield valuable information about craving, and characterizing this kind of craving is critical for developing effective interventions. Twenty-five young male smokers were enrolled in the present study. A within-subject experiment design was carried out to compare regional homogeneity (ReHo) between 12-h smoking abstinence and smoking satiety conditions during resting state in young adult smokers. Then, the ReHo changes associated with smoking abstinence (compared with satiety) were further examined for correlations with abstinence-induced changes in subjective craving. We found young adult smokers in abstinence state (compared with satiety) had higher ReHo in brain regions in fronto-striatal circuits including bilateral caudate, anterior cingulate cortex (ACC) and bilateral dorsal lateral prefrontal cortex (DLPFC), as well as brain regions in default mode network (DMN) including posterior cingulate cortex (PCC)/precuneus and angular gyrus. Additionally, we found the ReHo changes of the ACC and the bilateral caudate were positively correlated with the changes in craving induced by abstinence (i.e., abstinence minus satiety) in young adult smokers. The present findings improve the understanding of the effects of acute smoking abstinence on spontaneous brain activity and may contribute new insights into the neural mechanism of abstinence-induced craving in nicotine dependence.

The short-term effects of television advertisements of cariogenic foods on children's dietary choices.

OBJECTIVE: To investigate the short-term influence of the advertising of cariogenic foods on children's dietary preferences, and the possible moderating effect of several factors on this influence. METHODS: One-hundred and eighty-three children, 11-12 years of age, were exposed to advertisements showing sugary food and non-food items, in a within-subject counterbalanced design. Their preferences for unhealthy and healthy foods, and their ability to recall or recognise the advertisements, were measured following both sessions. Information on their dietary habits, leisure activities and sociodemographic details were obtained through a questionnaire completed by their parents. Their decayed, missing and filled teeth (DMFT) index, body weight and height were also recorded. A generalised linear mixed model was used to examine the differences in food preferences between experimental conditions, and the associations between children's preferences and the other factors assessed. RESULTS: Exposure to food advertisements significantly decreased the selection of healthy foods. Children with a higher DMFT index chose a higher percentage of unhealthy foods, and children who spent more time watching television chose an increased number of healthy foods, after their exposure to food advertisements. Regardless of condition, girls selected fewer foods than boys. Children with a higher DMFT index selected more unhealthy foods than children with a lower DMFT index. Obese children chose an increased number of healthy foods than those who were overweight and normal weight. CONCLUSIONS: Food advertisements can divert, for a short time, children's preference over healthy food choices, and could lead to changes in their eating habits, which may put them at higher risk of dental diseases and obesity.

Generalizability Theory With One-Facet Nonadditive Models.

In generalizability theory (G theory), one-facet models are specified to be additive, which is equivalent to the assumption that subject-by-facet interaction effects are absent. In this article, the authors first derive estimators of variance components (VCs) for nonadditive models and show that, in some cases, they are different from their counterparts in additive models. The authors then demonstrate and later confirm with a simulation study that when the subject-by-facet interaction exists, but the additive-model formulas are used, the VC of subjects is underestimated. Consequently, generalizability coefficients are also underestimated. Thus, depending on the nature of interaction effects, an appropriate model, either additive or nonadditive, should be used in applications of G theory. The nonadditive G theory developed in this article generalizes current G theory and uses data at hand to determine when additive or nonadditive models should be used to estimate VCs. Finally, the implications of the findings are discussed in light of an analysis of real data.

A cautionary note on the use of the Analysis of Covariance (ANCOVA) in classification designs with and without within-subject factors.

A number of statistical textbooks recommend using an analysis of covariance (ANCOVA) to control for the effects of extraneous factors that might influence the dependent measure of interest. However, it is not generally recognized that serious problems of interpretation can arise when the design contains comparisons of participants sampled from different populations (classification designs). Designs that include a comparison of younger and older adults, or a comparison of musicians and non-musicians are examples of classification designs. In such cases, estimates of differences among groups can be contaminated by differences in the covariate population means across groups. A second problem of interpretation will arise if the experimenter fails to center the covariate measures (subtracting the mean covariate score from each covariate score) whenever the design contains within-subject factors. Unless the covariate measures on the participants are centered, estimates of within-subject factors are distorted, and significant increases in Type I error rates, and/or losses in power can occur when evaluating the effects of within-subject factors. This paper: (1) alerts potential users of ANCOVA of the need to center the covariate measures when the design contains within-subject factors, and (2) indicates how they can avoid biases when one cannot assume that the expected value of the covariate measure is the same for all of the groups in a classification design.