This study investigated the independent and interactive effects of dietary behaviors and physical activity on poor sleep quality among 15,059 Chinese adolescents. Using a cross-sectional design, we assessed sleep quality (Pittsburgh Sleep Quality Index, PSQI), dietary habits, and physical activity. Logistic regression and interaction analysis were performed to examine associations, adjusting for covariates. The prevalence of poor sleep quality (PSQI score ≥ 7) was 9.72%. Seven healthy dietary behaviors were identified as protective (e.g., regular diet, abstaining from alcohol; ORs=0.49–0.56). While physical activity showed no independent association, limiting screen-based sedentary screen time(≤2h/day) reduced poor sleep odds by 31% (OR = 0.69). Two significant interactions emerged: abstaining from alcohol combined with limiting sugary beverages synergistically reduced the odds of poor sleep quality by 42% (OR = 0.58), whereas the combination of healthy dining out and high physical activity was associated with a 181% increased odds of poor sleep quality (OR = 2.81). While healthy dietary patterns are strongly associated with better sleep quality, the interplay between behaviors is complex, demonstrating both synergistic protective association and antagonistic outcomes. Findings highlight the need for integrated lifestyle interventions that account for behavioral interactions in promoting adolescent sleep quality.

Recent studies showing that some outcome variables do not statistically significantly differ between real-stakes and hypothetical-stakes conditions have raised methodological challenges to experimental economics’ disciplinary norm that experimental choices should be incentivized with real stakes. I show that the hypothetical bias measures estimated in these studies do not econometrically identify the hypothetical biases that matter in most modern experiments. Specifically, traditional hypothetical bias measures are fully informative in ‘elicitation experiments’ where the researcher is uninterested in treatment effects (TEs). However, in ‘intervention experiments’ where TEs are of interest, traditional hypothetical bias measures are uninformative; real stakes matter if and only if TEs differ between stakes conditions. I demonstrate that traditional hypothetical bias measures are often misleading estimates of hypothetical bias for intervention experiments, both econometrically and through re-analyses of three recent hypothetical bias experiments. The fact that a given experimental outcome does not statistically significantly differ on average between stakes conditions does not imply that all TEs on that outcome are unaffected by hypothetical stakes. Therefore, the recent hypothetical bias literature does not justify abandoning real stakes in most modern experiments. Maintaining norms that favor completely or probabilistically providing real stakes for experimental choices is useful for ensuring externally valid TEs in experimental economics.

Fear of crime among older people has been a frequent topic in ageing research, criminology and urban studies. The ‘environmental docility hypothesis’ assumes that older people are more vulnerable to adverse neighbourhood conditions than younger age groups. Yet, few studies have tested this influential hypothesis using samples of respondents covering the complete adult lifespan. Looking at fear of crime, we investigated the person–environment interaction of age and neighbourhood disadvantage, using two independent surveys comprising 12,620 respondents aged 25–90 years residing in 435 neighbourhoods in four cities in Germany and Australia. We used multi-level analysis and cross-level interactions to model age-differential effects of neighbourhood disadvantage on fear. Contrary to the hypothesis, we found a weakening of neighbourhood effects on fear with age. The strong effect of neighbourhood disadvantage on fear of crime dropped by around half from the youngest (25 years) to the oldest age (90 years) in both countries. Younger people were almost as fearful as older people in the most disadvantaged neighbourhoods, but older people were considerably more fearful than younger ages in better-off neighbourhoods. We found limited empirical support for the assumption that this diminished association between neighbourhood disadvantage and fear can be explained by the stronger neighbourhood attachment of older people. The limitations of the analysis and potential future directions of research are discussed.

Models testing interactive and quadratic hypotheses are common in Political Science but control strategies for these models have received little attention. Common practice is to simply include additive control variables, without relevant product terms, into models with interaction or quadratic terms. In this paper, we show in Monte Carlos that interaction terms can absorb the effects of other un-modeled interaction and non-linear effects and analogously, that included quadratic terms can reflect omitted interactions and non-linearities. This problem even occurs when included and omitted product terms do not share any constitutive terms. We show with Monte Carlo experiments that regularized estimators, the adaptive Lasso, Kernel Regularized Least Squares (KRLS), and Bayesian Additive Regression Trees (BART) can prevent the misattribution of interactive/quadratic effects, minimize the problems of efficiency loss and overfitting, and have low false-positive rates. We illustrate how inferences drawn can change when relevant product terms are used in the control strategy using a recent paper. Implementing the recommendations of this paper would increase the reliability of conditional and non-linear relationships estimated in many papers in the literature.