The cross-lagged panel network (CLPN) model is a version of the classic cross-lagged panel model (CLPM). The CLPN can be used to model a large number of cross-lagged effects between nodes (such as symptoms of ill health) across two waves of measurement. In spite of a robust debate about the pitfalls of using correlational data to infer causality, researchers using the CLPN often interpret findings in causal terms. We show with simulations that CLPN can indicate cross-lagged effects even if data have been generated without any direct effects between nodes/symptoms. Hence, findings from CLPNs may be spurious and should not be interpreted in causal terms if used to model non-experimental data. We have previously proposed a method of triangulation to scrutinize findings from the CLPM. Triangulation can also be used to reduce the false-positive risk when using the CLPN. We show by reanalysis of data from a previous study how triangulation can be applied, finding that positive cross-lagged effects between some symptoms of depression and anxiety probably were spurious, rather than due to genuine increasing effects, as alternative models indicated simultaneous and discrepant increasing and decreasing effects.

Increased waste clearance in the brain is thought to occur most readily during deep sleep (stage N3). Sleep deprivation disrupts time spent in deeper sleep stages, fragmenting the clearance process. Here, we have utilized the publicly available Stockholm Sleepy Brain Study to investigate whether various sleep-related measures are associated with changes in perivascular space (PVS) volume fraction following a late-night short-sleep experiment. The study sample consisted of 60 participants divided into old (65–75 years) and young (20–30 years) age groups. We found that partial sleep deprivation was not significantly associated with major PVS changes. In our centrum semiovale models, we observed an interaction between percentage of total sleep time spent in N3 and sleep deprivation status on PVS volume fraction. In our basal ganglia models, we saw an interaction between N2 (both percentage of total sleep time and absolute time in minutes) and sleep deprivation status. However, the significance of these findings did not survive multiple comparisons corrections. This work highlights the need for future longitudinal studies of PVS and sleep, allowing for quantification of within-subject morphological changes occurring in PVS due to patterns of poor sleep. Our findings here provide insight on the impact that a single night of late-night short-sleep has on the perivascular waste clearance system.

Exhaustion disorder (ED) was introduced to the Swedish version of the International Classification of Diseases, 10th edition (ICD-10) 2005. Primarily characterized by general fatigue and cognitive deficits, ED has become one of the most common mental health diagnoses in Sweden. Little is still known regarding the discriminative validity of the ED diagnosis and how it relates to other diagnostic constructs. The study aimed to investigate the discriminative validity of ED compared with two similar diagnoses, major depressive disorder (MDD) and adjustment disorder (AD). Using data from a sample of patients with a principal diagnosis of either ED (n = 352), MDD (n = 99), or AD (n = 302), we compared demographic and clinical variables and scores on self-report symptom scales. Results showed that ED patients were of a higher age and had a higher frequency of sickness absence than MDD and AD patients. There was a substantial overlap of symptoms between ED and MDD, only differing on two of nine self-report symptom scales, with ED patients rating lower work ability d = −0.37 and alcohol consumption d = −0.57. Compared with AD patients, ED patients reported more severe symptoms in every symptom domain. Given the prevalent use of ED diagnosis, its diagnostic validity and clinical usefulness merit further attention.

Marsh et al. (Educational Psychology Review, 36(2), 53, 2024) recently reported associations between academic achievement and self-concept (i.e., self-perceived academic competence). Marsh et al. claimed that their analyses supported a reciprocal effects model, according to which academic achievement and self-concept reinforce one another. Marsh et al. (Educational Psychology Review, 36(2), 53, 2024) further recommended to test alternative models and juxtapose their results and interpretations. Here, we followed this recommendation and tested different models using data simulated to resemble the data they used. However, contrary to Marsh et al. (Educational Psychology Review, 36(2), 53, 2024), in the present analyses we found contradictory positive, negative, and null effects between within-individual math self-concept and subsequent change in within-individual math achievement and vice versa. This suggests that the findings by Marsh et al. (Educational Psychology Review, 36(2), 53, 2024) may have been spurious and that the reciprocal effects model can be challenged.

Objectives: To systematically evaluate timely reporting of clinical trial results at medical universities and university hospitals in the Nordic countries. Study Design and Setting: In this cross-sectional study, we included trials (regardless of intervention) registered in the European Union (EU) Clinical Trials Registry and/or ClinicalTrials.gov, completed 2016–2019 and led by a university with medical faculty or university hospital in Denmark, Finland, Iceland, Norway, or Sweden. We identified summary results posted at the trial registries and conducted systematic manual searches for results publications (eg, journal articles, preprints). We present proportions with 95% confidence intervals (CI) and medians with interquartile range (IQR). Protocol: https://osf.io/wua3r. Results: Among 2112 included clinical trials, 1650 (78.1%, 95% CI 76.3%–79.8%) reported any results during our follow-up; 1097 (51.9%, 95% CI 49.8%-54.1%) reported any results within 2 years of the global completion date; and 48 (2.3%, 95% CI 1.7%–3.0%) posted summary results in the registry within 1 year. The median time from global completion date to results reporting was 690 days (IQR 1103). 856/1681 (50.9%) of ClinicalTrials.gov registrations were prospective. Denmark contributed approximately half of all trials. Reporting performance varied widely between institutions. Conclusion: Missing and delayed results reporting of academically led clinical trials are a pervasive problem in the Nordic countries. We relied on trial registry information, which can be incomplete. Institutions, funders, and policymakers need to support trial teams, ensure regulation adherence, and secure trial reporting before results are permanently lost. Plain Language Summary: Reporting of results from clinical trials is necessary for evidence-based clinical decision-making. We followed up reporting of clinical trials in the Nordic countries sponsored by medical universities and university hospitals. Of 2112 studies completed 2016–2019 in two major trials registries, about half reported results in any form within 24 months, and more than one in five did not report results at all. These results show that there is a need for improvement in the reporting of Nordic clinical trials.

In a recent response, Núñez-Regueiro et al. (2025) criticized our findings (Sorjonen et al. 2025) that were inconsistent with the reciprocal effects model (REM) of self-concepts and achievement. Here we respond to points raised. We show again that data used to support the REM may also be used to support an inconsistent decreasing effect of self-concept on achievement. We also show that an extended version of the REM, endorsed by Marsh et al. (2024), may seemingly be supported by data generated without any direct effects between self-concept and achievement. This means that such effects in observational data can arise under non-causal data-generating processes and do, therefore, not provide strong evidence for a causal effect of self-concept on achievement.

Ability tilts are within-individual differences between scores on two ability measures, e.g., math – verbal ability. We have shown in a series of reports that correlations between tilts and other variables are spurious consequences of associations to the constituent variables. Recently, Woodley of Menie et al. suggested that findings of incremental validity of tilts, over and above one of the constituent variables, refuted our claims of spuriousness. However, we show here that incremental validity of tilts are spurious consequences of incremental validity of the constituent variables. Moreover, Woodley of Menie et al. presented new results where so-called “tilt super-residuals” were attributable to shared environmental factors and they concluded that this finding confirmed a hypothesis that individuals specialize with respect to cognitive niches as an effort to adapt to stable environmental factors, alternatively do not specialize in the case of an unstable environment. However, we show that variance on “super-residualized” tilts attributable to shared environmental factors is a spurious consequence of adjusting for a variable (e.g., age) that is identical within twin couples. In summary, findings involving ability tilts still appear to be spurious.

Analysis of longitudinal data often relies on models which can be prone to statistical artifacts. We have previously shown that several published prospective associations can be explained by a combination of a general association between constructs, imperfect measurement reliability, and regression to the mean. Here, we formalize our analysis of this type of statistical artifact and introduce the Spurious Prospective Associations Model (SPAM). We show that the SPAM performs better than adjusted cross-lagged effects models to explain several observed prospective associations, including new examples involving loneliness and social anxiety and resilience and depressive symptoms, without assuming any true increasing or decreasing effects between constructs over time. Moreover, unlike the models we challenge, the SPAM is consistent with seemingly paradoxical findings indicating simultaneous increasing and decreasing effects between constructs. We conclude that the SPAM agrees well with observed data and is better supported than competing adjusted cross-lagged effects models in the cases investigated here.

The effect of higher education on intelligence has been examined using longitudinal data. Typically, these studies reveal a positive effect, approximately 1 IQ point per year of higher education, particularly when pre-education intelligence is considered as a covariate in the analyses. However, such covariate adjustment is known to yield positively biased results if the covariate has measurement errors and is correlated with the predictor. Simultaneously, a negative bias may emerge if the intelligence measure after higher education has non-classical measurement errors as in data from the 1970 British Cohort Study that were used in a previous study of the effect of higher education. In response, we have devised an estimation method that used iterated simulations to account for both classical measurement errors in the covariate and non-classical errors in the dependent variable. Upon applying this method in a reanalysis of the data from the 1970 British Cohort Study, we find that the estimated effect of higher education diminishes to 0.4 IQ points per year. Additionally, our findings suggest that the impact of higher education is somewhat more pronounced in the initial 2 years of higher education, aligning with the notion of diminishing marginal cognitive benefits.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.