Variation in emotion dynamics over time is associated with future relationship outcomes.

Romantic relationships are defined by emotion dynamics, or how the emotions of one partner at a single timepoint can affect their own emotions and the emotions of their partner at the next timepoint. Previous research has shown that the level of these emotion dynamics plays a role in determining the state and quality of the relationship. However, this research has not examined whether the estimated emotion dynamics change over time, and how the change in these dynamics might relate to relationship outcomes, despite changes in dynamics being likely to occur. We examined whether the magnitude of variation in emotion dynamics over time was associated with relationship outcomes in a sample of 148 couples. Time-varying vector autoregressive models were used to estimate the emotion dynamics for each couple, and the average and standard deviation of the dynamics over time was related to relationship quality and relationship dissolution 1-2 years later. Our results demonstrate that certain autoregressive and cross-lagged parameters do show significant variation over time, and that this variation is associated with relationship outcomes. Overall, this study demonstrates the importance of accounting for change in emotion dynamics over time, and the relevance of this change to the prediction of future outcomes.

Detecting Cohort Effects in Accelerated Longitudinal Designs Using Multilevel Models.

Accelerated longitudinal designs allow researchers to efficiently collect longitudinal data covering a time span much longer than the study duration. One important assumption of these designs is that each cohort (a group defined by their age of entry into the study) shares the same longitudinal trajectory. Although previous research has examined the impact of violating this assumption when each cohort is defined by a single age of entry, it is possible that each cohort is instead defined by a range of ages, such as groups that experience a particular historical event. In this paper we examined how including cohort membership in linear and quadratic multilevel models performed in detecting and controlling for cohort effects in this scenario. Using a Monte Carlo simulation study, we assessed the performance of this approach under conditions related to the number of cohorts, the overlap between cohorts, the strength of the cohort effect, the number of affected parameters, and the sample size. Our results indicate that models including a proxy variable for cohort membership based on age at study entry performed comparably to using true cohort membership in detecting cohort effects accurately and returning unbiased parameter estimates. This indicates that researchers can control for cohort effects even when true cohort membership is unknown.

Consequences of sampling frequency on the estimated dynamics of AR processes using continuous-time models.

Continuous-time (CT) models are a flexible approach for modeling longitudinal data of psychological constructs. When using CT models, a researcher can assume one underlying continuous function for the phenomenon of interest. In principle, these models overcome some limitations of discrete-time (DT) models and allow researchers to compare findings across measures collected using different time intervals, such as daily, weekly, or monthly intervals. Theoretically, the parameters for equivalent models can be rescaled into a common time interval that allows for comparisons across individuals and studies, irrespective of the time interval used for sampling. In this study, we carry out a Monte Carlo simulation to examine the capability of CT autoregressive (CT-AR) models to recover the true dynamics of a process when the sampling interval is different from the time scale of the true generating process. We use two generating time intervals (daily or weekly) with varying strengths of the AR parameter and assess its recovery when sampled at different intervals (daily, weekly, or monthly). Our findings indicate that sampling at a faster time interval than the generating dynamics can mostly recover the generating AR effects. Sampling at a slower time interval requires stronger generating AR effects for satisfactory recovery, otherwise the estimation results show high bias and poor coverage. Based on our findings, we recommend researchers use sampling intervals guided by theory about the variable under study, and whenever possible, sample as frequently as possible. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Visual search guidance uses coarser template information than target-match decisions.

When searching for an object, we use a target template in memory that contains task-relevant information to guide visual attention to potential targets and to determine the identity of attended objects. These processes in visual search have typically been assumed to rely on a common source of template information. However, our recent work (Yu et al., 2022) argued that attentional guidance and target-match decisions rely on different information during search, with guidance using a "fuzzier" version of the template compared with target decisions. However, that work was based on the special case of search for a target amongst linearly separable distractors (e.g., search for an orange target amongst yellower distractors). Real-world search targets, however, are infrequently linearly separable from distractors, and it remains unclear whether the differences between the precision of template information used for guidance compared with target decisions also applies under more typical conditions. In four experiments, we tested this question by varying distractor similarity during visual search and measuring the likelihood of attentional guidance to distractors and target misidentifications. We found that early attentional guidance is indeed less precise than that of subsequent match decisions under varying exposure durations and distractor set sizes. These results suggest that attentional guidance operates on a coarser code than decisions, perhaps because guidance is constrained by lower acuity in peripheral vision or the need to rapidly explore a wide region of space while decisions about selected objects are more precise to optimize decision accuracy.

Comparing estimation methods for psychometric networks with ordinal data.

Ordinal data are extremely common in psychological research, with variables often assessed using Likert-type scales that take on only a few values. At the same time, researchers are increasingly fitting network models to ordinal item-level data. Yet very little work has evaluated how network estimation techniques perform when data are ordinal. We use a Monte Carlo simulation to evaluate and compare the performance of three estimation methods applied to either Pearson or polychoric correlations: extended Bayesian information criterion graphical lasso with regularized edge estimates ("EBIC"), Bayesian information criterion model selection with partial correlation edge estimates ("BIC"), and multiple regression with p-value-based edge selection and partial correlation edge estimates ("MR"). We vary the number and distribution of thresholds, distribution of the underlying continuous data, sample size, model size, and network density, and we evaluate results in terms of model structure (sensitivity and false positive rate) and edge weight bias. Our results show that the effect of treating the data as ordinal versus continuous depends primarily on the number of levels in the data, and that estimation performance was affected by the sample size, the shape of the underlying distribution, and the symmetry of underlying thresholds. Furthermore, which estimation method is recommended depends on the research goals: MR methods tended to maximize sensitivity of edge detection, BIC approaches minimized false positives, and either one of these produced accurate edge weight estimates in sufficiently large samples. We identify some particularly difficult combinations of conditions for which no method produces stable results. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Ethnocultural influences in how people prefer to obtain and receive health information.

AIMS AND OBJECTIVES: To develop an understanding of south Asian and Chinese people's preferences about where to find health information and how best to receive health information, relative to their white counterparts. BACKGROUND: South Asian and Chinese ethnic groups represent the largest proportion of Canada's growing visible minorities. There may be challenges to ensuring that south Asian and Chinese people have access to health information in the same way that others do. DESIGN: Qualitative descriptive. METHODS: Fifty-two participants (12 white, 16 south Asian and 24 Chinese) engaged in six focus groups (two for each ethnocultural group). Focus groups were conducted in English, Punjabi and Cantonese, with the assistance of Punjabi and Cantonese interpreters. Questions were focused on how participants have preferred or would prefer to receive health information (e.g., when, where, what format, from whom), as well as the facilitators and barriers to understanding the health information. RESULTS: Participants agreed that although physicians were their primary source for health information, they also used written materials, media and the Internet to glean information. Participants identified concerns regarding the use of technical jargon by healthcare providers. South Asians and Chinese referred to their English language fluency and the lack of ethnoculturally specific information as additional challenges to understanding information they were offered. Whether and how family members were included in the communication process, also varied by ethnocultural group. CONCLUSIONS: As Canada welcomes immigrants from other countries, and its population becomes more diverse, healthcare providers need to have an understanding of the potential diversity in how to approach offering health information. RELEVANCE TO CLINICAL PRACTICE: Healthcare providers need to consider what people of different ethnocultural backgrounds need when developing effective health communication strategies.

Do statin users adhere to a healthy diet and lifestyle? The Australian Diabetes, Obesity and Lifestyle Study.

Background Lifestyle and dietary advice typically precedes or accompanies the prescription of statin medications. However, evidence for adherence to this advice is sparse. The objective was to compare saturated fat intake, exercise, alcohol consumption and smoking between statin users and non-users in Australia. Methods Data were analysed for 4614 participants aged ≥37 years in the Australian Diabetes, Obesity and Lifestyle study in 2011-2012. Statin use, smoking status and physical activity were self-reported. Saturated fat and alcohol intake were measured via a food frequency questionnaire. Multinomial logistic regression was used to compute adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between statin use and the four lifestyle factors. All models were adjusted for age, sex, education, number of general practitioner visits, body mass index, hypertension, diabetes and prior cardiovascular diseases. Results In total 1108 (24%) participants used a statin. Statin users were 29% less likely to be within the highest quartile versus the lowest quartile of daily saturated fat intake compared to non-users (OR 0.71, 95% CI 0.54-0.94). There were no statistically significant associations between statin use and smoking, physical activity or alcohol consumption. Conclusions Smoking status, alcohol consumption and exercise level did not differ between users and non-users of statins. However, statin users were less likely to consume high levels of saturated fat than non-users. We found no evidence that people took statins to compensate for a poor diet or lifestyle.

Vitamin D supplementation: we must not fail our children!

There is increasing concern that vitamin D deficiency poses a major health problem for children. Deficiency can cause hypocalcemic seizures, growth disturbances, and rickets and may influence diabetes, cardiovascular dysfunction, autoimmune diseases, and attention deficit hyperactivity disorders. Reduced vitamin D levels in children presenting to pediatric orthopedic services are common.In the United Kingdom, recommendations on vitamin D supplementation are set by the Department of Health (DoH) and the National Institute of Health and Clinical Excellence. These state that all children aged 6 months to 5 years ought to receive 7 to 8.5 µg of vitamin D daily.We carried out a survey of 203 parents attending our pediatric and pediatric orthopedic and fracture clinics to evaluate parental awareness of the DoH recommendations on vitamin D supplementation for children and to assess the extent to which children were receiving vitamin D supplements.About 85.71% of parents were not aware of the recommendations. Only 14.29% stated that they were aware of the benefits of vitamin D for their children and just 17.73% of children were receiving vitamin D supplementation; 17 via formula milk and 18 via multivitamin formulations.Parents are generally not aware about vitamin D supplementation because of a lack of information with the high rates of reported suboptimal vitamin D levels amongst children not being addressed resulting in increased health risks to our children. Major improvements are needed in the implementation of supplementation at all points of contact between parents and health-care professionals.