Cross-Lagged Analyses of Prolonged Grief and Depression Symptoms With Insomnia Symptoms

Prolonged grief disorder, characterized by severe, persistent and disabling grief, has recently been added to the DSM-5-TR and ICD-11. Treatment for prolonged grief symptoms shows limited effectiveness. It has been suggested that prolonged grief symptoms exacerbate insomnia symptoms, whereas insomnia symptoms, in turn, may fuel prolonged grief symptoms. To help clarify if treating sleep disturbances may be a viable treatment option for prolonged grief disorder, we examined the proposed reciprocal relationship between symptoms of prolonged grief and insomnia. On three time points across 6-month intervals, 343 bereaved adults (88% female) completed questionnaires to assess prolonged grief, depression, and insomnia symptoms. We applied random intercept cross-lagged panel models (RICLPMs) to assess reciprocal within-person effects between prolonged grief and insomnia symptoms and, as a secondary aim, between depression and insomnia symptoms. Changes in insomnia symptoms predicted changes in prolonged grief symptoms but not vice versa. Additionally, changes in depression and insomnia symptoms showed a reciprocal relationship. Our results suggest that targeting insomnia symptoms after bereavement is a viable option for improving current treatments for prolonged grief disorder.     

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.     

“均”与“寡”阶段性变动下中国居民公平感的变迁

利用中国综合社会调查和中国社会状况综合调查重复截面数据,通过年龄-时期-队列模型对居民公平感的时代变化进行分析。研究发现公平感在年龄上呈“J”型趋势;从时期效应看, 2008年公平感较高, 2010～2013年在低谷徘徊,2015年以后又开始回升;从队列视角看,建国前出生队列公平感偏低,建国后初期的队列相对较高,“50”后有所下滑,从“60”后开始公平感持续走低,到“80”后跌入低谷,但“90”后又开始升高。从1949年前后“寡且不均”到建国初期阶段的“寡且均”,再到改革开放40年快速经济增长下“不寡但不均”的社会变迁过程影响了居民的公平感。     

Stolen elections: How conspiracy beliefs during the 2020 American presidential elections changed over time

Conspiracy beliefs have been studied mostly through cross-sectional designs. We conducted a five-wave longitudinal study (N = 376; two waves before and three waves after the 2020 American presidential elections) to examine if the election results influenced specific conspiracy beliefs and conspiracy mentality, and whether effects differ between election winners (i.e., Biden voters) versus losers (i.e., Trump voters) at the individual level. Results revealed that conspiracy mentality kept unchanged over 2 months, providing first evidence that this indeed is a relatively stable trait. Specific conspiracy beliefs (outgroup and ingroup conspiracy beliefs) did change over time, however. In terms of group-level change, outgroup conspiracy beliefs decreased over time for Biden voters but increased for Trump voters. Ingroup conspiracy beliefs decreased over time across all voters, although those of Trump voters decreased faster. These findings illuminate how specific conspiracy beliefs are, and conspiracy mentality is not, influenced by an election event.     

Implicit and explicit COVID-19-vaccine harmfulness/helpfulness associations predict vaccine beliefs,intentions, and behaviors

We investigated the role of implicit and explicit associations between harm and COVID-19 vaccines using a large sample (N = 4668) of online volunteers. The participants completed a brief implicit association test and explicit measures to evaluate the extent to which they associated COVID-19 vaccines with concepts of harmfulness or helpfulness. We examined the relationship between these harmfulness/helpfulness COVID-19 vaccine associations and vaccination status, intentions, beliefs, and behavior. We found that stronger implicit and explicit associations that COVID-19 vaccines are helpful relate to vaccination status and beliefs about the COVID-19 vaccine. That is, stronger pro-helpful COVID-19 vaccine associations, both implicitly and explicitly, related to greater intentions to be vaccinated, more positive beliefs about the vaccine, and greater vaccine uptake.     

Self-control: An integrative framework

Research on self-control has flourished within the last two decades, with many researchers trying to answer one of the most fundamental questions regarding human behaviour—how do we successfully regulate desires in the pursuit of long-term goals? While recent research has focused on different strategies to enhance self-control success, we still know very little about how strategies are implemented or where the need for self-control comes from in the first place. Drawing from parallel fields (e.g., emotion regulation, health) and other theories of self-regulation, we propose an integrative framework that describes self-control as a dynamic, multi-stage process that unfolds over time. In this review, we first provide an overview of this framework, which poses three stages of regulation: the identification of the need for self-control, the selection of strategies to regulate temptations, and the implementation of chosen strategies. These regulatory stages are then flexibly monitored over time. We then expand this framework by outlining a series of growth points to guide future research. By bridging across theories and disciplines, the present framework improves our understanding of how self-control unfolds in everyday life.     

Testing a stochastic foraging model in an operant simulation: Agreement with qualitative but not quantitative predictions

An operant simulation of foraging through baited and empty patches was studied with 4 pigeons. On a three-key panel, side keys were designated as patches, and successive opportunities to complete 16 fixed-ratio 10 schedules on side keys were defined as encounters with feeders. In a random half of the patches in any session, some of the fixed-ratio 10 schedules yielded reinforcement (baited feeders) and the other schedules yielded nonreinforcement (empty feeders). In the other half of the patches, all feeders were empty. Pigeons could travel between patches at any time by completing a fixed-ratio schedule on the center key. An optimal foraging model was tested in Experiments 1 and 2 by varying center-key travel time and number of baited feeders in baited patches. The ordinal predictions that number of feeders visited in empty patches would increase with travel time and decrease as number of baited feeders increased were supported, but pigeons visited far more feeders in empty patches than the optimal number predicted by the model to maximize energy/time. In Experiment 3, evidence was found to suggest that the number of empty feeders encountered before the first baited feeder in baited patches is an important factor controlling leaving empty patches.