The Mmogo-Method™: Discovering Symbolic Community Interactions

In this article the development and implementation of the Mmogo-Method? is discussed as a culture-sensitive data collection method. The Mmogo-Method? provides opportunities for social researchers to gain a deeper understanding of the cultural symbolism in which social life is embedded and that informs experiences, perceptions and behaviour. In this method, people create their own data by making visual presentations that reflect contextually grounded symbolic meanings. Theoretical underpinnings of social constructionism, symbolic interactionism and community psychology are discussed and applied as the rationale for the development and implementation of the Mmogo-Method?. Examples of research using the Mmogo-Method? are provided to illustrate its value and various different application possibilities. The Mmogo-Method? attempts to produce community-based knowledge that is gathered and disseminated in a coherent way; thereby contributing to the possibility that indigenous knowledge may form part of national and international discussions.     

Is dispositional optimism or dispositional pessimism predictive of ideal cardiovascular health? The Young Finns Study

Objective: We examined the independent association between dispositional optimism compared to dispositional pessimism and ideal cardiovascular health (defined by the American Heart Association).

Design: A prospective design with a study sample of 1113 participants aged 24–39 years from the longitudinal Young Finns Study.

Main outcome measures: Ideal cardiovascular health (comprised of seven ideal cardiovascular health metrics) was measured in 2001. The ideal cardiovascular health metrics were reassessed in 2007.

Results: Low pessimism rather than high optimism was a better predictor of ideal cardiovascular health in 2007. When examining the association between optimism and pessimism and the seven ideal cardiovascular health metrics in 2007 (BMI, diet, physical activity, smoking status, blood pressure, total cholesterol and plasma glucose), low pessimism predicted non-smoking status, ideal physical activity and eating a healthy diet, while high optimism was associated with eating a healthy diet.

Conclusion: Our findings suggest that low pessimism rather than high optimism is associated with ideal cardiovascular health, especially with health behaviours such as not smoking, being physically active and eating a healthy diet. Socio-economic status was the potential mediating or confounding factor. Future studies should examine the differential meaning of the optimism/pessimism concepts to further clarify their relation to health outcomes.     

Social Exclusion Predicts Impaired Self‐Regulation: A 2‐Year Longitudinal Panel Study Including the Transition from Preschool to School

The need‐to‐belong theory stipulates that social exclusion (i.e., being rejected by peers) impairs the ability to self‐regulate, and experimental studies with adults support this contention, at least on a short‐term basis. Few studies have investigated whether social exclusion affects the development of self‐regulation of children in a more enduring manner. By using data from a community sample of 762 children, we investigated reciprocal relations between social exclusion and self‐regulation from age 4 to age 6. Social exclusion was reported by teachers, whereas self‐regulation was reported by parents. Autoregressive latent cross‐lagged analyses showed that social exclusion predicted impaired development of dispositional self‐regulation and, reciprocally, that poor self‐regulation predicted enhanced social exclusion. In other words, social exclusion undermines children's development of self‐regulation, whereas poor self‐regulation increases the likelihood of exclusion. Results illuminate the applied relevance of the need‐to‐belong theory.     

A latent class distance association model for cross‐classified data with a categorical response variable

In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low‐dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented.     

Patterns of engagement: the relationship between efficacy beliefs and task engagement at the individual versus collective level

This study examines the relationship between efficacy beliefs and task engagement in and over time, at both the individual and collective levels. We conducted latent growth curve analyses using data from 372 university students (individual level) who were assigned to one of 79 e‐work groups (collective level). The participants carried out three collaborative tasks in a laboratory setting. Results reveal, at both levels, that the level of task engagement of participants and groups with high initial levels of efficacy beliefs remained stable, whereas the level of task engagement of participants and groups with low initial levels of efficacy beliefs decreased significantly over time. Moreover, the relationships linking the parallel constructs were functionally equivalent across levels. Theoretical and practical implications are discussed from the perspective of Bandura's social cognitive theory.     

Impairment of Cognitive Function in Different Domains Early After Lung Transplantation

Journal of Clinical Psychology in Medical Settings - In this prospective observational pilot study patients with the diagnosis of end-stage lung disease and listed for lung transplantation...     

Varieties of Resilience in MIDUS

Population‐based studies of health typically focus on psychosocial contributors to illness and disease. We examine findings from a national longitudinal study of American adults, known as MIDUS (Midlife in the U.S.) to examine the role of psychosocial factors in promoting resilience, defined as the maintenance, recovery, or improvement in health following challenge. Classic studies of resilience are briefly noted, followed by a look at three categories of resilience in MIDUS. The first pertains to having good health and well‐being in the face of low socioeconomic standing. The second pertains to maintaining good health and well‐being despite the challenges that accompany aging. The third pertains to resilience in the face of targeted life challenges such as abuse in childhood, loss of spouse in adulthood, or having cancer. Across each area, we summarize evidence of positive health, and where possible, highlight protective influences that account for such salubrious outcomes. We conclude with opportunities for future research in MIDUS such as examining cultural and genetic influences on resilience as well as utilizing laboratory challenge data to illuminate underlying mechanisms.     

“R U Mad?”: Computerized text analysis of affect in social media relates to stress and substance use among ethnic minority emerging adult males

Objective: This study examined the interactive role of affectivity and stress in substance use severity among ethnic minority, emerging adult males, using linguistic indicators of affect obtained through social media.

Method: Participants were 119 emerging adult, ethnic minority males (ages 18–25) who provided access to their mobile phone text messaging and Facebook activity for 6-months. Computerized text analysis (LIWC2015) was used to obtain linguistic indices of positive and negative affect from texts and Facebook posts. The Perceived Stress Scale was used to measure stress, and items from the Drug Abuse Screening Test were used to measure substance use severity.

Results: Generalized estimating equations showed that higher negative affect in texts was associated with greater substance use severity. Stress moderated the relationship between positive affect expressed in Facebook posts and substance use such that higher positive affect in Facebook posts was associated with less substance use at higher stress and greater substance use at lower stress.

Conclusions: Findings highlight the complexities of interactions between stress and affectivity. Findings could inform development of substance use interventions for young males that employ social technologies.