The main effect model versus buffering model of shop steward social support: A study of rank-and-file auto workers in the U.S.A

1993 ◽  
Vol 14 (5) ◽  
pp. 481-493 ◽  
Author(s):  
Yitzhak Fried ◽  
Robert B. Tiegs
Keyword(s):  
Social Support ◽  
Auto Workers ◽  
Main Effect Model ◽  
Shop Steward ◽  
Effect Model ◽  
Main Effect ◽  
Model Versus

Childhood Physical Abuse, Perceived Social Support, and Socioemotional Status in Adult Women

1995 ◽  
Vol 10 (4) ◽  
pp. 273-283 ◽  
Author(s):  
Julie L. Crouch ◽  
Joel S. Milner ◽  
John A. Caliso
Keyword(s):  
Social Support ◽  
Child Abuse ◽  
Physical Abuse ◽  
Perceived Social Support ◽  
Abuse Potential ◽  
Adult Women ◽  
Child Abuse Potential ◽  
Main Effect Model ◽  
Effect Model ◽  
Main Effect

This study investigated the extent to which an interactional model, relative to a main effect model, predicts the relationship between childhood physical abuse, perceived social support, and various aspects of socioemotional functioning in adult women. The results indicated that perceived social support during childhood was significantly related to subsequent levels of adult depression, trait anxiety, and child abuse potential in a manner consistent with a main effect model. Childhood history of physical abuse was related only to adult child abuse potential. Implications and study limitations are discussed.

Soutien social et symptômes dépressifs au sein des personnes âgées

1992 ◽  
Vol 11 (4) ◽  
pp. 322-346 ◽  
Author(s):  
Philippe Landreville ◽  
Philippe Cappeliez
Keyword(s):  
Social Support ◽  
Depressive Symptoms ◽  
The Elderly ◽  
Elderly Persons ◽  
Social Variables ◽  
Buffering Effect ◽  
Main Effect Model ◽  
Effect Model ◽  
Main Effect ◽  
The Relationship

ABSTRACTThere is great interest in identifying psychological and social variables associated with depressive symptoms in older adults. The goal of this article is to review the literature on the relationship between social support and depressive symptoms in the elderly and to identify the mechanisms involved in this relationship. The review indicates that both structural and functional dimensions of social support are inversely related to depressive symptoms in elderly persons. In addition, there is evidence supporting both the main effect model and the buffering effect model of social support. It is unclear, however, whether observation of these effects depends on the type of measure used to assess social support. A better understanding of the relationship between social support and depression requires the consideration of more precise dimensions of social support as well as the nature of the Stressors experienced by older people.

scholarly journals Incident atrial fibrillation and its risk prediction in patients developing COVID-19: A machine learning based algorithm approach

2021 ◽  
Author(s):  
Ash Genaidy
Keyword(s):  
Machine Learning ◽  
The Elderly ◽  
Adverse Outcomes ◽  
Good Prediction ◽  
Main Effect Model ◽  
Effect Model ◽  
Main Effect ◽  
Index Value ◽  
Treat All ◽  
Better Than

Background The elderly multi-morbid patient is at high risk of adverse outcomes with COVID-19 complications, and in the general population, the development of incident AF is associated with worse outcomes in such patients. We therefore investigated incident AF risks in a large prospective population of elderly patients with/without incident COVID-19 cases and baseline cardiovascular/non-cardiovascular multi-morbidities. We used two approaches: main-effect modeling and secondly, a machine-learning (ML) approach accounting for complex dynamic relationships. Methods We studied a prospective elderly US cohort of 280592 patients from medical databases in a 8-month investigation of new COVID19 cases. Incident AF outcomes were examined in relationship to diverse multi-morbid conditions, COVID-19 status and demographic variables, with ML accounting for the dynamic nature of changing multimorbidity risk factors. Results Multi-morbidity contributed to the onset of confirmed COVID-19 cases with cognitive impairment (OR 1.69; 95%CI 1.52-1.88), anemia (OR 1.41; 95%CI 1.32-1.50), diabetes mellitus (OR 1.35; 95%CI 1.27-1.44) and vascular disease (OR 1.30; 95%CI 1.21-1.39) having the highest associations. A main effect model (C-index value 0.718) showed that COVID-19 had the highest association with incident AF cases (OR 3.12; 95%CI 2.61-3.710, followed by congestive heart failure (1.72; 95%CI 1.50-1.96), then coronary artery disease (OR 1.43; 95%CI 1.27-1.60) and valvular disease (1.42; 95%CI 1.26-1.60). The ML algorithm demonstrated improved discriminatory validity incrementally over the statistical main effect model (training: C-index 0.729, 95%CI 0.718-0.740; validation: C-index 0.704, 95%CI 0.687-0.72). Calibration of ML based formulation was satisfactory and better than the main-effect model. Decision curve analysis demonstrated that the clinical utility for the ML based formulation was better than the ‘treat all’ strategy and the main effect model. Conclusion COVID-19 status has major implications for incident AF in a cohort with diverse cardiovascular/non-cardiovascular multi-morbidities. Our approach accounting for dynamic multimorbidity changes had good prediction for incident AF amongst incident COVID19 cases.

scholarly journals Everyday social support processes: Household members’ instrumental and emotional support of entrepreneurs

2022 ◽  
pp. 026624262110540 ◽  
Author(s):  
Aviel Cogan ◽  
Tobias Pret ◽  
Melissa S. Cardon
Keyword(s):  
Social Support ◽  
Emotional Support ◽  
Everyday Activities ◽  
Effect Model ◽  
Start Up ◽  
Main Effect ◽  
The Everyday ◽  
Buffering Hypothesis ◽  
Household Members ◽  
Entrepreneurial Action

While it is well-established that entrepreneurs benefit from social support, little is known about how and when instrumental and emotional support from household members facilitate entrepreneurial action and persistence. Through a longitudinal, qualitative study, we develop a conceptual framework that shows how social support from the household becomes an integral part of the everyday activities of entrepreneurs. In contrast to the perception of social support as static, our findings illustrate it as a dynamic, ongoing process which is core to business start-up and growth over time. We also challenge the perspectives that households are simply repositories of resources and entrepreneurs passive recipients of support by demonstrating that social support is necessarily interactive, whereby entrepreneurs and households play a collaborative role in entrepreneurship. Finally, we join the debate concerning mechanisms of social support by suggesting that the main effect model and buffering hypothesis are not contradictory, but are instead interdependent.

On the Marginal Dependency of Cohen’s κ

2008 ◽  
Vol 13 (4) ◽  
pp. 305-315 ◽  
Author(s):  
Alexander von Eye ◽  
Maxine von Eye
Keyword(s):  
Probability Distributions ◽  
Null Model ◽  
Marginal Probability ◽  
Rater Agreement ◽  
Marginal Distributions ◽  
Linear Interaction ◽  
Main Effect Model ◽  
Effect Model ◽  
Main Effect ◽  
Log Linear

Cohen’s κ (kappa) is typically used as a measure of degree of rater agreement. It is often criticized because it is marginal-dependent. In this article, this characteristic is explained and illustrated in the context of (1) nonuniform marginal probability distributions, (2) odds ratios that remain constant while κ changes in the presence of varying marginal distributions, and (3) percentages of raw agreement that remain constant while κ changes in the presence of varying marginal distributions. The meaning and interpretation of κ are explained with reference to the log-linear main effect model of variable independence. This model is used for the estimation of the expected cell frequencies of agreement tables. It is shown that the interpretation of κ as a measure of degree of agreement is incorrect. The correct interpretation is that κ assesses the degree of agreement beyond that expected based on a statistical model such as the independence or the null model. Based on Goodman’s (1991) distinction between marginal-free and marginal-dependent measures, it is shown that κ is marginal-dependent. It shares this characteristic with the well-known χ2-statistic and the correlation coefficient for cross-classifications. In contrast, the odds ratio, the unweighted log-linear interaction, and the percentage of raw agreement are marginal-free. Therefore, the expectation that marginal-dependent κ would reflect the same data characteristics as some of the marginal-free measures is misguided. It is recommended that researchers report both measures of degree of agreement and measures of agreement beyond some expectation.

scholarly journals Impact of Violent Experiences and Social Support on R-NSSI Behavior among Middle School Students in China

2021 ◽  
Vol 18 (7) ◽  
pp. 3347
Author(s):  
Kun Liu ◽  
Xueyan Yang ◽  
Moye Xin
Keyword(s):  
Social Support ◽  
Influencing Factors ◽  
Empirical Support ◽  
Female Students ◽  
Male Students ◽  
Male And Female ◽  
Self Injury ◽  
Significant Difference ◽  
Main Effect ◽  
Nonsuicidal Self Injury

Repetitive nonsuicidal self-injury (R-NSSI) is an extreme manifestation of nonsuicidal self-injury (NSSI) behavior that causes bodily harm and emotional and personality disorders. It is a growing concern, especially among adolescents; therefore, this study aims to provide empirical support for effective interventions on R-NSSI behavior among adolescents in China. We used data of about 1180 students from a survey conducted in seven middle schools in Xi’an, China, and applied multiple logistic regression to analyze NSSI and R-NSSI among male and female students, including their influencing factors. We found no significant difference between male and female students’ R-NSSI; however, regarding influencing factors, male students had more violent experiences and less social support than female students. Parental and familial factors played the most prominent role in social support. Social support was found to be a main-effect mechanism in the effect of violent experiences on R-NSSI among male students, whereas the mechanism had both a main effect and a certain buffer effect among female students. R-NSSI was found to be more prevalent among younger children, children with siblings, and those with romantic relationship experiences. We also found that healthy adolescent development involves the participation of families and schools. Health education should be conducted according to the students’ sex and characteristics.

scholarly journals Self-Efficacy and Subjective Norms as Moderators in the Networking Competence–Social Entrepreneurial Intentions Link

SAGE Open ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 215824402093487
Author(s):  
Anthony Igwe ◽  
Anastasia Ogbo ◽  
Emmanuel Agbaeze ◽  
James Abugu ◽  
Charity Ezenwakwelu ◽  
...  
Keyword(s):  
Social Support ◽  
Interaction Effect ◽  
Self Efficacy ◽  
Moral Obligation ◽  
Significant Interaction ◽  
Perceived Social Support ◽  
Subjective Norms ◽  
Additive Models ◽  
Entrepreneurial Intentions ◽  
Main Effect

This study examines self-efficacy and subjective norms (moral obligation, empathy, and perceived social support) as moderators of the effect networking competence has on social entrepreneurial intentions. Using Nigeria as a study area, a survey was conducted on 541 budding entrepreneurs, which were students with a high entrepreneurial propensity. With the use of Andrew Hayes’s PROCESS macro, a simultaneous regression analysis was performed to establish the interaction effect of the selected moderators. The results show a positive main effect of networking competence on social entrepreneurial intentions, statistically significant interaction effects of empathy and perceived social support, no interaction effect of moral obligation, and a poor self-efficacy fit. This study extends theories of entrepreneurial intentions and the mediation (additive) models of Mair & Noboa, Krueger, and Hockerts. Suggestions are that other studies should be carried out using self-efficacy among actual early-level entrepreneurs, with a likelihood that results could explain what role self-efficacy could have in predicting social entrepreneurial intentions.

scholarly journals Revue Critique D'Etudes Sur Le Soutien Social Et Sa Relation Avec Le Bien-Etre De Personnes Atteintes De Demence

1991 ◽  
Vol 10 (2) ◽  
pp. 65-93 ◽  
Author(s):  
Louise Levesque ◽  
Sylvie Cossette
Keyword(s):  
Social Support ◽  
Family Member ◽  
Ad Hoc ◽  
Well Being ◽  
Effect Model ◽  
Inadequate Sample Size ◽  
Measurement Tools ◽  
Methodological Problems ◽  
The Impact ◽  
At Home

Many people suffering from dementia live at home, in spite of the demands that such a situation puts on those who care for them. The role of helper is usually assumed by a particular family member who is therefore more likely to feel the impact of the caregiving responsibility. Researchers are concerned with the relationship between the well-being of these helpers and their informal social support. This article presents a critical review of 21 studies of that relationship. The various dimensions of social support considered in the studies are analyzed, as are the methodological limits. A discussion of findings about the relationships between social support and wellbeing completes the analysis. It appears that researchers have a limited conception of social support and assess only a few of its many dimensions in a variety of ways. Very few authors explicitly specify underlying assumptions or a theory relevant to their conceptualization of social support. The weakness and the diversity of this conceptualization are reflected in the measurement tools which consist of a few ad hoc questions on social support in nearly 50% of the studies. Few studies consider the support availability, duration, conflict, and reciprocity. The buffering effect model of support is examined in one study. Inadequate sample size, unrepresentative samples, and lack of control in regard to confounding variables are among the methodological problems identified. When researchers use an evaluative approach to measure social support, the relationships between support and well-being are more often significant than when a descriptive approach is used. In future studies, researchers should be careful to better articulate the theoretical notions proposed in studies on caring for a family member with dementia at home with those coming from studies on social support in general. It is important for researchers to strengthen their study design and to carry out longitudinal studies; they must also try to understand how the influence of society works. From this perspective, one avenue for the future might involve studying the sequence of relationships between stress, support, coping strategies, and well-being. This is all the more important because at the present time certain studies on the caring of persons with dementia are based on a conceptual framework of stress. Such a framework considers support as a mediating factor.

scholarly journals Effects of Social Support and Socioeconomic Status on Mental Health in College Students

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
Chaurasia, K
Keyword(s):  
Mental Health ◽  
Social Support ◽  
College Students ◽  
Socioeconomic Status ◽  
Total Sample ◽  
Main Effect ◽  
Two Factors ◽  
Questionnaire Result ◽  
Age Range

Mental Health plays a very significant role to decide the quality of life. In the present competitive scenario students feel stress and face mental illness which is becoming very severe with time. In present investigation effort has been made to ascertain the effect of Social Support and Socioeconomic Status on Mental health in College Students. A 2×3 factorial design was employed. The two factors studied were: Social Support (varied at two level high and low) and socioeconomic status (varied at three level high, middle & low). There were six cells with 30 subjects in each cell (total sample consisted of 180 subjects and age range 18-22 years). Measurement of Mental Health was furnished through Mental Health Battery developed by Arun Kumar Singh & Alpnana Sen Gupta. Social Support and Socioeconomic status was also collected by a self-made questionnaire. Result: Result of ANOVA show the main effect of Social support and Socioeconomic Status were found significant (p<.01) on total mental health scores.

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