Dataset Information

Age and Employee Green Behaviors: A Meta-Analysis.

ABSTRACT: Recent economic and societal developments have led to an increasing emphasis on organizational environmental performance. At the same time, demographic trends are resulting in increasingly aging labor forces in many industrialized nations. Commonly held stereotypes suggest that older workers are less likely to be environmentally responsible than younger workers. To evaluate the degree to which such age differences are present, we meta-analyzed 132 independent correlations and 336 d-values based on 4676 professional workers from 22 samples in 11 countries. Contrary to popular stereotypes, age showed small positive relationships with pro-environmental behaviors, suggesting that older adults engaged in these workplace behaviors slightly more frequently. Relationships with age appeared to be linear for overall, Conserving, Avoiding Harm, and Taking Initiative pro-environmental behaviors, but non-linear trends were observed for Transforming and Influencing Others behaviors.

SUBMITTER: Wiernik BM

PROVIDER: S-EPMC4773609 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Age and Employee Green Behaviors: A Meta-Analysis.

Wiernik Brenton M BM Dilchert Stephan S Ones Deniz S DS

Frontiers in psychology 20160302

Recent economic and societal developments have led to an increasing emphasis on organizational environmental performance. At the same time, demographic trends are resulting in increasingly aging labor forces in many industrialized nations. Commonly held stereotypes suggest that older workers are less likely to be environmentally responsible than younger workers. To evaluate the degree to which such age differences are present, we meta-analyzed 132 independent correlations and 336 d-values based ...[more]

PMID: 26973550

Similar Datasets

Project description:BackgroundThe number of people with noncommunicable diseases is increasing. Noncommunicable diseases are the major cause of disability and premature mortality worldwide, associated with negative workplace outcomes such as sickness absence and reduced work productivity. There is a need to identify scalable interventions and their active components to relieve disease and treatment burden and facilitate work participation. eHealth interventions have shown potential in clinical and general populations to increase well-being and physical activity and could be well suited for workplace settings.ObjectiveWe aimed to provide an overview of the effectiveness of eHealth interventions at the workplace targeting employee health behaviors and map behavior change techniques (BCTs) used in these interventions.MethodsA systematic literature search was performed in PubMed, Embase, PsycINFO, Cochrane CENTRAL, and CINAHL in September 2020 and updated in September 2021. Extracted data included participant characteristics, setting, eHealth intervention type, mode of delivery, reported outcomes, effect sizes, and attrition rates. Quality and risk of bias of the included studies were assessed using the Cochrane Collaboration risk-of-bias 2 tool. BCTs were mapped in accordance with the BCT Taxonomy v1. The review was reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist.ResultsIn total, 17 randomized controlled trials met the inclusion criteria. The measured outcomes, treatment and follow-up periods, content of eHealth interventions, and workplace contexts had high heterogeneity. Of the 17 studies, 4 (24%) reported unequivocally significant findings for all primary outcomes, with effect sizes ranging from small to large. Furthermore, 53% (9/17) of the studies reported mixed results, and 24% (4/17) reported nonsignificant results. The most frequently targeted behavior was physical activity (15/17, 88% of the studies); the least frequently targeted behavior was smoking (2/17, 12% of the studies). Attrition varied greatly across the studies (0%-37%). Risk of bias was high in 65% (11/17) of the studies, with some concerns in the remaining 35% (6/17). Interventions used various BCTs, and the most frequently used were feedback and monitoring (14/17, 82%), goals and planning (10/17, 59%), antecedents (10/17, 59%), and social support (7/17, 41%).ConclusionsThis review suggests that, although eHealth interventions may have potential, there are still unanswered questions regarding their effectiveness and what drives the mechanism behind these effects. Low methodological quality, high heterogeneity and complexity, the characteristics of the included samples, and often high attrition rates challenge the investigation of the effectiveness and the making of sound inferences about the effect sizes and significance of the results. To address this, new studies and methods are needed. A megastudy design in which different interventions are evaluated in the same population over the same period on the same outcomes may solve some of the challenges.Trial registrationPROSPERO CRD42020202777; https://www-crd-york-ac-uk/prospero/display_record.php?RecordID=202777.

Project description:There has been a great deal of interest in identifying potential biomarkers of aging (Butler et al. 2004). Biomarkers of aging would be useful to predict potential vulnerabilities in an individual that may arise well before they are chronologically expected, due to idiosyncratic aging rates that occur between individuals. Prior attempts to identify biomarkers of aging have often relied on the comparisons of long-lived animals to a wild-type control (Dhahbi et al. 2004). However, the effect of interventions in model systems that prolong lifespan (such as single gene mutations, or caloric restriction) can sometimes be difficult to interpret due to the manipulation itself having multiple unforeseen consequences on physiology, unrelated to aging itself (Gems et al. 2002; Partridge & Gems 2006). The search for predictive biomarkers of aging therefore is problematic, and the identification of metrics that can be used to predict either physiological or chronological age would be of great value (Butler et al. 2004). One methodology which has been used to identify biomarkers for numerous pathologies is gene expression profiling. Here, we report whole-genome expression profiles of individual wild-type Caenorhabditis elegans covering the entire wild-type nematode life span. Individual nematodes were scored for either age-related behavioral phenotypes, or survival, and then subsequently associated with their respective gene expression profiles. This facilitated the identification of transcriptional profiles that were highly associated with either physiological or chronological age. Overall, our approach serves as a paradigm for identifying potential biomarkers of aging in higher organisms that can be repeatedly sampled throughout their lifespan. The full normalized data set with expression values for all genes of all individual worms at all ages (104 worms/arrays) is available as a 28Mb download as a supplementary file on this page (GSE12290.txt). Keywords: time couse Time course of aging in C. elegans. 7 ages were assayed, with a minimum of 9 biological replicates per timepoint, and as many as 17 biological replicates. All ages were compared to an independent 4 day old (young) pooled control.

Dataset Information

Age and Employee Green Behaviors: A Meta-Analysis.

Publications

Age and Employee Green Behaviors: A Meta-Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets