The Impact of Supervision on Worker Outcomes: A Meta‐analysis

Barak, Michàlle E. Mor; Travis, Dnika J.; Pyun, Harold; Xie, Bin

doi:10.1086/599028

Cited by 212 publications

(140 citation statements)

References 56 publications

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“…In addition, we presented a set of recommendations for the meta-analyst interested in synthesizing these indices. Although meta-analysts have combined partial effect sizes with bivariate correlations (e.g., Mor-Barak et al, 2009), partial effect sizes and bivariate correlations should not be combined as they represent a different population parameter and overall results may be misleading.…”

Section: Discussionmentioning

confidence: 99%

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The Synthesis of Partial Effect Sizes

Aloe¹,

Thompson²

2013

Journal of the Society for Social Work and Research

114

121

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In this article we focus on three partial effect sizes for the correlation ( family of effects: the standardized slope , the partial correlation , and the semi-partial correlation . These partial effect sizes are useful for meta-analyses in two common situations: when primary studies reporting regression models do not report bivariate correlations, and when it is of specific interest to partial out the effects of other variables. We clarify the use of these three indices in the context of meta-analysis and describe how the indices can be estimated and analyzed. We provide examples of syntheses of these partial effect sizes using a published social work meta-analysis. Finally, we share practical recommendations for meta-analysts wanting to use such indices. Key words: meta-analysis, research synthesis, partial effect sizes, regression analysisMeta-analysis is the statistical analysis of empirical results of a series of studies (Glass, 1977). Quantitative procedures in meta-analysis typically begin by transforming study results to a common metric, which often represents results as effect sizes. An effect size is a scale-free index that assesses the magnitude and direction of some relationship between variables. Almost two decades ago researchers argued that results from regression models can be treated as effect-size indices (e.g., Becker & Schram, 1994;Cooper & Hedges, 1994;Greenwald, Hedges, & Laine, 1996;Valentine, DuBois, & Cooper, 2004). More recently, different approaches have been proposed to synthesize regression models (Aloe & Becker, 2012;Becker & Wu, 2007;Peterson & Brown, 2005;Wu & Becker, 2013). These approaches can be organized into three methodological groups. The first group focuses on methods that combine full regression models (e.g., Wu & Becker, 2013), the second group focuses on attempting to approximate the bivariate correlation when it is not directly reported (e.g., Peterson & Brown, 2005), and the third group focuses on methods that combine partial effect sizes that have been extracted from regression models (e.g., Aloe & Becker, 2012;Keef & Roberts, 2004).This article focuses on the estimation and use of the partial effect sizes for the family of effects, which can be computed when multiple predictor variables are included in a primary study. A partial effect size is an index that describes the magnitude of an effect after controlling for the influence of other variables in a model. Part of our rationale for focusing on partial effect sizes is that they are quantities that researchers typically find familiar. Furthermore, partial effect sizes are often directly reported or easily estimated from results found in primary studies. Finally, typical meta-analysis techniques can be used once partial effects are extracted or computed from primary studies.We begin by briefly introducing the meta-analysis of correlational data. Next we introduce required notation for effects and meta-analytic models, including three partial effect sizes (partial correlation, semi-partial correlation, and standardiz...

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Section: Discussionmentioning

confidence: 99%

“…Because this is a subset of the original data set, results presented here are solely illustrative and strong interpretations of the relationships found are not warranted. Analysis of the complete data set is interpreted by Mor-Barak et al (2009).…”

Section: Synthesis Examplesmentioning

confidence: 99%

The Synthesis of Partial Effect Sizes

Aloe¹,

Thompson²

2013

Journal of the Society for Social Work and Research

114

121

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“…Common problems identified include the use of small sample sizes (Bogo & McKnight, 2006;Pront, Gillham, & Schuwirth, 2016), unrepresentative samples (Mor Barak, Travis, Pyun, & Xie, 2009), poor conceptualization (Milne et al, 2008), dependence on one source of data (Crow, 2008), interventions poorly described (Dawson et al, 2013a), and reliance on measures that were not psychometrically robust (Creaner, 2014). In some studies, the intervention being applied is not being implemented in ways consistent with best practice.…”

Section: Effectiveness Of Clinical Supervisionmentioning

confidence: 99%

“…The educational function of supervision is considered to be central to facilitating the supervisee's capacity to develop new skills and knowledge (Kadushin & Harkness, 2014). Also defined as "task assistance", this function requires the supervisor to have a high level of practice expertise and supervisory capacity to effectively provide advice and direction to the supervisee (Mor Barak et al, 2009). It may be that findings of supervision ineffectiveness derive from studies where supervisors lacked the expertise to fulfill the educational function, resulting in the delivery of sub-standard supervision.…”

Section: Effectiveness Of Clinical Supervisionmentioning

confidence: 99%

Clinical supervision, burnout and intent to leave: an Australian mixed methods study of community-based allied health professionals

Saxby¹

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ObjectiveClinical supervision is widely recognised for providing professional support, professional development and clinical governance for healthcare workers. Despite the growing uptake of clinical supervision, there have been few studies about the effectiveness of supervision for allied health professionals and fewer studies conducted within the Australian health context. This study aims to identify the perceived effectiveness of clinical supervision of allied health professionals in an Australian metropolitan community health setting. The study also sought to identify those factors that contribute to effectiveness and the relationship between clinical supervision effectiveness, burnout and intention to leave, as well as any profession-specific differences. MethodologyThe research has a two-phase, explanatory-sequential, mixed methods design. In Study 1, participants (n = 82) anonymously completed an on-line questionnaire, administered through the health service's intranet at 8 months post-implementation of the intervention, a structured model of clinical supervision. Study 2, commenced 12 months postimplementation and comprised several focus groups (n = 26), separately attended by supervisees (n = 15), and supervisors (n = 11). The sample was drawn from the population of allied health professionals (N = 120) who were receiving or providing supervision within the study location.The on-line questionnaire sought demographic data, work history and the number and length of supervision sessions. Clinical supervision effectiveness was operationalised using the Manchester Clinical Supervision Scale-26 (MCSS-26©); burnout was measured using the Maslach Burnout Inventory; and intention to leave was operationalised using the Intent to Leave Scale. ResultsEighty-two allied health professionals participated in Study 1, resulting in a 68% response rate. Ages ranged from 24 to 66 years, and females accounted for 89% (n = 71) of all respondents. The professions of occupational therapy, physiotherapy and social work together comprised 73% of the total number of participants. Twenty-six allied health ii professionals participated in the five focus groups of Study 2. All participants were female, with 81% belonging to the professions of occupational therapy, physiotherapy and social work.Overall, clinical supervision was perceived as effective. In the main, supervisee's responses illustrated that supervision provided effective professional support, education and guidance for professional practice.'Time', as well as specific procedural factors, were found to be important in relation to Significant associations were found between clinical supervision effectiveness and burnout and intention to leave. Highly efficacious supervision was significantly and negatively associated with Emotional Exhaustion and Depersonalization. In addition, higher scores on "Finding Time" were significantly correlated with lower scores of Emotional Exhaustion.Effective supervision was significantly and positively associated with Personal Accomp...

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“…Management support: the support of managers from training is another known factor in training transfer (Landsman, 2007;Brook and Hotchains, 2008;Morbarak, 2009;Auerbach, McGowan & LaPorte, 2008;Shams & Daneshmandi, 2014). The research suggest that when employees find that their managers support the application of new knowledge and skills in workplace, they have more tendency to transfer the training to workplace (Velada & Caetano, 2007).…”

Section: Environment Factors Affecting Transfer Processmentioning

confidence: 99%

The Environmental Factors Affecting Transfer of Training: Tehran Municipality Employees

Abdollahi

Daneshmandi

2017

IJLD

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The present study explored the effect of environmental factors on transfer of training from training courses to the workplace. The study is a quantitative method. The population contained all of the employees participated in the training courses of the population consisted of all Employees who participated in in-service training courses in Tehran Municipality in 2015 (N= 385). The sample included 193 persons selected by simple random sampling technique. The tools used for data collection were questionnaire. The data gathered was analyzed using t-test and exploratory factor analysis. The results showed that the most important factor influencing transfer of training was Opportunity to use capabilities.

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The Impact of Supervision on Worker Outcomes: A Meta‐analysis

Cited by 212 publications

References 56 publications

The Synthesis of Partial Effect Sizes

The Synthesis of Partial Effect Sizes

Clinical supervision, burnout and intent to leave: an Australian mixed methods study of community-based allied health professionals

The Environmental Factors Affecting Transfer of Training: Tehran Municipality Employees

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