On the Use of Beta Coefficients in Meta-Analysis.

Peterson, Robert A.; Brown, Steven P.

doi:10.1037/0021-9010.90.1.175

Cited by 1,237 publications

(860 citation statements)

References 14 publications

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“…contacted authors to obtain bivariate data. However, because it has been demonstrated that r can be accurately estimated from ␤-coefficients in multiple regression, even when covariates are present, we estimated r in one case (i.e., 19) using the formula r ϭ 0.98␤ ϩ 0.05, where is an indicator variable that equals 1 when ␤ is nonnegative and 0 when ␤ is negative (20).…”

Section: Discussionmentioning

confidence: 99%

Depression and Diabetes Treatment Nonadherence: A Meta-Analysis

et al. 2008

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OBJECTIVE -Depression is common in patients with diabetes and is associated with worse treatment outcomes. Its relationship to treatment adherence, however, has not been systematically reviewed. We used meta-analysis to examine the relationship between depression and treatment nonadherence in patients with type 1 and type 2 diabetes.RESEARCH DESIGN AND METHODS -We searched MEDLINE and PsycINFO databases for all studies published by June 2007 and reviewed references of published articles. Meta-analytic procedures were used to estimate the effect size r in a random effects model. Significance values, weighted effect sizes, 95% CIs, and tests of homogeneity of variance were calculated.RESULTS -Results from 47 independent samples showed that depression was significantly associated with nonadherence to the diabetes treatment regimen (z ϭ 9.97, P Ͻ 0.0001). The weighted effect size was near the medium range (r ϭ 0.21, 95% CI 0.17-0.25). Moderator analyses showed that the effect was significantly larger in studies that measured self-care as a continuous versus categorical variable (P ϭ 0.001). Effect sizes were largest for missed medical appointments and composite measures of self-care (r values ϭ 0.31, 0.29). Moderation analyses suggest that effects for most other types of self-care are also near the medium range, especially in studies with stronger methodologies.CONCLUSIONS -These findings demonstrate a significant association between depression and treatment nonadherence in patients with diabetes. Studies that used stronger methodologies had larger effects. Treatment nonadherence may represent an important pathway between depression and worse diabetes clinical outcomes.

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Section: Discussionmentioning

confidence: 99%

Depression and Diabetes Treatment Nonadherence: A Meta-Analysis

et al. 2008

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“…We also included two studies which provided only standardized regression coefficients, following the method in Peterson and Brown (2005). Additionally, we incorporated studies reporting odds ratios (OR) or risk ratios (the latter were transformed into OR using the formula in Howell, 2006), in line with Darr and Johns (2008).…”

Section: Methods the Meta-analytic Databasesmentioning

confidence: 99%

Going to work ill: A meta-analysis of the correlates of presenteeism and a dual-path model.

Miraglia

Johns²

2016

Journal of Occupational Health Psychology

383

679

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Interest in presenteeism, attending work while ill, has flourished in light of its consequences for individual well-being and organizational productivity. Our goal was to identify its most significant causes and correlates by quantitatively summarizing the extant research. Additionally, we built an empirical model of some key correlates and compared the etiology of presenteeism versus absenteeism. We used meta-analysis (in total, K=109 samples, N=175,965) to investigate the correlates of presenteeism and meta-analytic structural equation modeling to test the empirical model. Salient correlates of working while ill included general ill health, constraints on absenteeism (e.g., strict absence policies, job insecurity), elevated job demands and felt stress, lack of job and personal resources (e.g., low support and low optimism), negative relational experiences (e.g., perceived discrimination), and positive attitudes (satisfaction, engagement, commitment). Moreover, our dual process model clarified how job demands and job and personal resources elicit presenteeism via both health impairment and motivational paths, and they explained more variation in presenteeism than absenteeism. The study sheds light on the controversial act of presenteeism, uncovering both positive and negative underlying mechanisms.The greater variance explained in presenteeism as opposed to absenteeism underlines the opportunities for researchers to meaningfully investigate the behavior and for organizations to manage it.Keywords: presenteeism; absenteeism; meta-analysis; health; demands. The term presenteeism has been used in several ways in the literature over the years, and Johns (2010) reviewed nine distinct definitions of the concept (see also Wężyk & Merecz, 2013).However, recent scholarly treatment has converged on two main definitions. The first of these is attending work while ill (Aronsson, Gustafsson, & Dallner, 2000). The second definition, which dominates the occupational medicine literature, is productivity loss stemming from attending while ill (Turpin et al., 2004). Although affirming the importance of the latter phenomenon, Johns (2010Johns ( , 2012 questioned this definition for conflating cause with effect and pre-empting the study of the causes of going to work ill. In the meta-analyses to be reported here we restrict the purview to the causes and correlates of the act of presenteeism-going to work ill. Most research on productivity loss has concentrated on its association with various medical conditions. Perhaps the most interesting thing about presenteeism is that it represents a muchoccupied but only recently studied state between being absent (and ostensibly exhibiting no productivity) and fully productive work engagement. Presentees will vary in their productivity due to a host of personal and contextual circumstances, such as the exact nature of their health Presenteeism correlates: A meta-analysis 4 problems. Nonetheless, they are unlikely to be fully engaged and fully productive. Hence, the causes and corre...

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“…When such effect size information is missing, primary studies have to report sufficient statistics to allow the conversion into effect sizes. We applied Lipsey and Wilson's (2001) and Peterson and Brown's (2005) methods to complete effect size conversions. Third, primary studies must use real employee samples.…”

Section: Inclusion Criteriamentioning

confidence: 99%

Leader emotional intelligence and subordinate job satisfaction: A meta-analysis of main, mediator, and moderator effects

Cai

Humphrey

Qian

2016

Personality and Individual Differences

169

157

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S. (2016). Leader emotional intelligence and subordinate job satisfaction: A meta-analysis of main, mediator, and moderator effects. Personality and Individual Differences, 102, 13-24. http://dx.doi.org/10.1016Differences, 102, 13-24. http://dx.doi.org/10. /j.paid.2016 LEADER EMOTIONAL INTELLIGENCE 2 ABSTRACTBased on a meta-analysis, leaders' emotional intelligence (EI) positively relates to subordinates' job satisfaction (̂ = .308). All three EI streams (ability, self-report, mixed) exhibit significant incremental validity and relative importance (RW) in the presence of personality and cognitive ability in predicting subordinates' job satisfaction (ability EI: ΔR 2 = .002, RW% = 3.5%; self-

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On the Use of Beta Coefficients in Meta-Analysis.

Cited by 1,237 publications

References 14 publications

Depression and Diabetes Treatment Nonadherence: A Meta-Analysis

Depression and Diabetes Treatment Nonadherence: A Meta-Analysis

Going to work ill: A meta-analysis of the correlates of presenteeism and a dual-path model.

Leader emotional intelligence and subordinate job satisfaction: A meta-analysis of main, mediator, and moderator effects

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