Predicting the Effect of a Predictor When Controlling for Baseline

Prospective effects of mindfulness on anxiety and depressive symptoms may be spurious: Simulated reanalysis of a meta-analytic cross-lagged panel analysis

A recent meta-analysis claimed decreasing prospective effects of acting with awareness and non-reacting, two facets of dispositional mindfulness, on subsequent anxiety and depressive symptoms. However, the meta-analytic cross-lagged effects were estimated while adjusting for a prior measurement of the outcome variable and it is known that such adjusted cross-lagged effects may be spurious due to correlations with residuals and regression to the mean. We fitted competing models on simulations of the same meta-analytic data and found that prospective effects of the mindfulness facets on anxiety and depressive symptoms probably were spurious. It is important for researchers to be aware of limitations of adjusted cross-lagged effects, meta-analytically estimated or not, in order not to overinterpret findings.

Spurious prospective effects between general and domain-specific self-esteem: A reanalysis of a meta-analysis of longitudinal studies

A recent meta-analysis, of 38 studies with data from 43 independent samples (total N = 24,668), claimed evidence for positive reciprocal prospective effects, and hence for both top-down and bottom-up processes, between general and domain-specific self-esteem. However, the meta-analytic cross-lagged effects were estimated while adjusting for a prior measurement of the outcome variable and it is known that such adjusted cross-lagged effects may be spurious due to correlations with residuals and regression to the mean. In the present reanalyses, we found all of the prospective effects to be spurious. Consequently, claims about increasing prospective effects and top-down and bottom-up processes between general and domain-specific self-esteem can be questioned. It is important for researchers to be aware of the limitations of cross-lagged panel analyses, and of analyses of correlational data in general, in order not to overinterpret findings.

Predictors of homework engagement in group CBT for social anxiety: client beliefs about homework, its consequences, group cohesion, and working alliance

OBJECTIVE

Group cognitive behaviour therapy (CBT) for social anxiety disorder (SAD) is effective, but little data exist on generic relational components of the therapeutic process, such as group cohesion and therapy alliance, and central CBT-specific components such as homework engagement, beliefs, and perceived consequences. The aim of this study was to investigate the relationships between homework, group cohesion, and working alliance during group CBT for social anxiety disorder.

METHOD

Participants (N = 105) with SAD engaged in 12 sessions of group CBT. Measures of homework, working alliance, and group cohesion were completed at multiple points throughout treatment. Random-intercept cross-lagged panel models were used to evaluate the prospective relationships between measures.

RESULTS

Prospective relationships between the homework outcomes did not vary throughout the treatment period, with the only significant relationships seen between the random intercepts ("trait" levels). Homework beliefs were a significant negative predictor of future group cohesion, but only in mid- to late-treatment. Homework consequences and working alliance were significantly and positively predictive of each other throughout therapy.

CONCLUSION

Early homework engagement is associated with higher engagement throughout therapy. Working alliance and homework engagement are important to bolster early in group CBT.Trial registration: Australian New Zealand Clinical Trials Registry identifier: ACTRN12616000579493..

Prospective associations between social support and posttraumatic stress disorder may be spurious: A re-meta-analysis of longitudinal studies and a simulation

A recent meta-analysis concluded to have found proof for both a social causation model, according to which social support protects against posttraumatic stress disorder (PTSD), and a social selection model, which claims that PTSD erodes social support. However, the prospective cross-lagged effects were estimated while adjusting for a prior measurement of the outcome and this method is vulnerable for spurious findings due to correlations with residuals and regression toward the mean. The present re-analyses of the meta-analytic effects indicated that depending on used model one can choose to claim that social support has either a decreasing, an increasing, or no prospective effect on subsequent change in PTSD symptom severity, and vice versa. Therefore, claims over and above a negative cross-sectional correlation between social support and PTSD, including the social causation and social selection models, can be questioned. The findings were validated by analyses of simulated data, which indicated that prospective effects were not necessary for the observed meta-analytic associations.

Distorted meta-analytic findings on peer influence: A reanalysis

In a recent meta-analysis, Giletta et al. (2021) [1] found a positive effect of peers' behavior at time 1 on target youths' behavior at time 2 while adjusting for target youths' behavior at time 1 and claimed to have quantified peer influence. However, it is established that controlled cross-lagged effects could be due to correlations with measurement errors and reversion in the direction of the mean rather than due to true decreasing or increasing effects. Here, in a reanalysis of the same meta-analytic data as used by Giletta et al., we found that peer influence, as operationalized by Giletta et al., may have been distorted (i.e. spurious). We do not claim that peer influence does not exist, but it may be hard, maybe not even possible, to prove by analyses of observational data that it does exist. Difficulties to prove causal effects by analyses of observational data is common for all areas of research and not specific for research on peer influence.

Unmasking artifactual links: A reanalysis reveals No direct causal relationship between self-esteem and quality of social relations

A meta-analysis conducted by Harris and Orth (2020) found positive prospective cross-lagged effects between quality of social relations and self-esteem in included longitudinal studies. Harris and Orth concluded that the link between self-esteem and quality of social relations is reciprocal and characterized by a positive feedback loop. However, meta-analytic effects were estimated while controlling for a prior measurement of the outcome and such effects are known to be susceptible to artifactual (i.e. spurious) effects due to correlations with measurement errors and reversion to mediocrity. We reanalyzed the same data and found paradoxical effects indicating, simultaneously, both increasing and decreasing effects between self-esteem and social relations. These findings suggest that prospective effects between self-esteem and quality of social relations are artifactual rather than due to a true reciprocal effect. Thus, these findings have important theoretical implications and challenge both the risk regulation model, which posits that self-esteem has a causal effect on quality of social relations, and the sociometer theory, which claims that quality of relations is the cause and self-esteem the effect. The present results prompt further investigation into the underlying mechanisms driving these artifactual associations. Additionally, the study highlights the importance of considering methodological limitations in future meta-analyses to improve the accuracy of causal inferences.

Dangers of including outcome at baseline as a covariate in latent change score models: Results from simulations and empirical re-analyses

Latent change score modeling is a type of structural equation modeling used for estimating change over time. Often change is regressed on the initial value of the outcome variable. However, similarly to other regression analyses, this procedure may be susceptible to regression to the mean. The present study employed simulations as well as re-analyses of previously published data, claimed to indicate reciprocal promoting effects of vocabulary and matrix reasoning on each other's longitudinal development. Both in simulations and empirical re-analyses, when adjusting for initial value on the outcome, latent change score modeling tended to indicate an effect of a predictor on the change in an outcome even when no change had taken place. Furthermore, analyses tended to indicate a paradoxical effect on change both forward and backward in time. We conclude that results from latent change score modeling are susceptible to regression to the mean when adjusting for the initial value on the outcome. Researchers are recommended not to regress change on the initial value included in the calculation of the change score when employing latent change score modeling but, instead, to define this parameter as a covariance.

The predictive value of brief measures of externalizing behavior and internalizing problems in young people receiving substance use treatment: A secondary analysis

BACKGROUND

Identifying people at risk of poor outcomes following treatment for substance use disorders is important for developing tailored services. The aim of this study was to test whether a brief measure of internalizing and externalizing behavior could identify young adults at high risk of psychiatric care episodes and criminal offending up to four years after enrolment in treatment for substance use disorder.

METHODS

Clients aged 15-25 years from a randomized multicenter study were included (N = 457). At baseline, all completed the YouthMap12 screener, a measure of internalizing symptoms (IP6) and externalizing problems (EP6). We used accelerated failure time regression to assess time to psychiatric care and criminal offending, adjusting for baseline occurrence, gender, age, treatment group, and uptake area. Youden's J was used to assess optimal cut-points for risk of events.

RESULTS

The IP6 was associated with shorter time to psychiatric care following treatment enrolment (beta = -0.71, 95% confidence interval [CI] = -0.94 to -0.48; adjusted beta = -0.45, 95% CI = -0.66 to -0.25). The EP6 was associated with shorter time to criminal offending, coefficient = -0.32, 95% CI = -0.44 to -0.19; adjusted coefficient = -0.18, 95% CI = -0.30 to -0.06). Optimal cut-points were two or more for the IP6 and three or more for the EP6.

CONCLUSIONS

The IP6 and the EP6, two simple and easily administered instruments, can identify young adults who are at an increased risk of future criminal offending or in need of psychiatric care. The findings lend support to using the 12-item YouthMap, as it identifies relevant risks, is compatible with local service delivery needs, and is theoretically and empirically supported.

Questioning the vulnerability model: Prospective associations between low self-esteem and subsequent depression ratings may be spurious

BACKGROUND

According to the vulnerability model, low self-esteem makes people more depressed. Support for the vulnerability model comes almost exclusively from analyses using cross-lagged panel models, showing a negative effect of initial self-esteem on subsequent depression ratings when adjusting for initial depression. However, it is well known that such adjusted effects are susceptible to regression toward the mean.

METHODS

Data from four waves of measurements in five different samples (total N = 2703) were analyzed with two different cross-lagged panel models, two different random intercept cross-lagged panel models, and two different latent change score models, predicting change forwards as well as backwards in time.

RESULTS

High initial self-esteem predicted both decreased and increased depression ratings between measurements and an increase in self-esteem between measurements predicted a concurrent decrease in depression ratings.

LIMITATIONS

Only data from two western countries, Switzerland and USA, were analyzed. Whether the main finding, that a prospective effect of self-esteem on subsequent depression ratings might be spurious, applies to other countries and cultures remains an open question.

CONCLUSIONS

Due to the incongruent results, any causal effect of self-esteem on depression ratings, and thus the vulnerability model as such, cannot be corroborated by the data and models analyzed here. Instead, we propose, tentatively, that prospective associations between self-esteem and depression ratings may be spurious due to a combination of reasons, including regression toward the mean. The indication that depression might not be affected by measures to improve individuals' self-esteem is of clinical relevance.

Regression to the mean in latent change score models: an example involving breastfeeding and intelligence

BACKGROUND

Latent change score models are often used to study change over time in observational data. However, latent change score models may be susceptible to regression to the mean. Earlier observational studies have identified a positive association between breastfeeding and child intelligence, even when adjusting for maternal intelligence.

METHOD

In the present study, we investigate regression to the mean in the case of breastfeeding and intelligence of children. We used latent change score modeling to analyze intergenerational change in intelligence, both from mothers to children and backward from children to mothers, in the 1979 National Longitudinal Survey of Youth (NLSY79) dataset (N = 6283).

RESULTS

When analyzing change from mothers to children, breastfeeding was found to have a positive association with intergenerational change in intelligence, whereas when analyzing backward change from children to mothers, a negative association was found.

CONCLUSIONS

These discrepant findings highlight a hidden flexibility in the analytical space and call into question the reliability of earlier studies of breastfeeding and intelligence using observational data.