Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-02T19:24:04.126Z Has data issue: false hasContentIssue false

Let’s Work Together: Assessing the Impact of Intergenerational Dynamics on Young Workers’ Ageism Awareness and Job Satisfaction

Published online by Cambridge University Press:  07 September 2020

Najat Firzly
Affiliation:
Faculty of Social Sciences, School of Psychology, University of Ottawa, Ottawa, Ontario.
Lise Van de Beeck
Affiliation:
Faculty of Social Sciences, School of Psychology, University of Ottawa, Ottawa, Ontario.
Martine Lagacé*
Affiliation:
Faculty of Arts, Department of Communication, University of Ottawa, Ottawa, Ontario.
*
La correspondance et les demandes de tirés-à-part doivent être adressées à : / Correspondence and requests for offprints should be sent to: Martine Lagacé, PhD Faculty of Arts Department of Communication University of OttawaOttawa, OntarioCanada ([email protected])
Rights & Permissions [Opens in a new window]

Abstract

Previous studies suggest that intergroup contact has a positive effect on older workers’ perception of ageism and satisfaction. This study aims at assessing such relationships amongst Canadian younger workers. Precisely, in light of the intergroup contact theory (ICT), it was first hypothesized that a positive perception of intergenerational workplace climate (IWC) and knowledge sharing practices (KSP) increase younger workers’ awareness of ageist behaviors targeting older peers. Second, it was hypothesized that such awareness has a positive effect on young workers’ level of satisfaction. Relying on a cross-sectional design composed of 612 participants, path analysis was conducted. Findings suggest that whereas KSP increases younger workers’ awareness of ageist behaviors towards older workers, this is not the case for IWC. On the other hand, both IWC and KSP have a direct and positive impact on younger workers’ level of satisfaction. Theoretical and practical implications of findings are discussed.

Résumé

RÉSUMÉ

Des études antérieures suggèrent que les contacts intergroupes ont un effet positif sur la perception de l’âgisme et la satisfaction des travailleuses âgées et des travailleurs âgés. La présente recherche examine ces liens auprès de jeunes travailleuses canadiennes et travailleurs canadiens. À la lumière de la théorie des contacts intergroupes, la première hypothèse émise est qu’une perception positive du climat intergénérationnel au travail et des pratiques de partage des connaissances accroissent la sensibilisation des jeunes travailleuses et travailleurs aux comportements âgistes, visant leurs pairs plus âgés. La deuxième hypothèse est qu’une telle prise de conscience exerce un effet positif sur le niveau de satisfaction des jeunes travailleuses et travailleurs. S’appuyant sur un devis transversal, des analyses acheminatoires ont été menées sur les données fournies par 612 participantes et participants. Les résultats suggèrent que les pratiques de partage des connaissances sensibilisent les jeunes travailleuses et les jeunes travailleurs aux comportements âgistes envers les travailleuses âgées et les travailleurs âgés alors que la perception positive du climat intergénérationnel au travail n’exerce pas un tel effet. D’autre part, les pratiques de transfert des connaissances et la perception positive du climat intergénérationnel au travail ont un effet direct et positif sur le niveau de satisfaction des jeunes travailleuses et travailleurs. Les contributions théoriques et pratiques des résultats sont discutées.

Type
Article
Copyright
© Canadian Association on Gerontology 2020

Population aging is a global trend around the world resulting partly from improvements in life expectancy and decreased fertility rates over the past century (United Nations, 2017). Canada’s population echoes such a trend as individuals 65 years of age and older outnumber individuals 14 years of age and under (Statistics Canada, 2017). The Canadian workforce also reveals a similar pattern as the proportion of Canadians 55–64 years of age peaked at 21.0 per cent in 2016. Also, the latest census data from Statistics Canada show that more and more older workers want to remain in the workforce for health and/or financial reasons (Statistics Canada, 2017). In the face of the shortfall of workers in sectors such as health care, transportation, and education (Conference Board of Canada, 2018), the fact that older workers want to remain in the workforce comes as good news. However, older workers continue to face major obstacles in terms of workplace participation and retention in the form of negative age-based attitudes and behaviours (Berger & Hodgins, Reference Berger and Hodgins2012; Posthuma & Campion, Reference Posthuma and Campion2009). Starting as early as 45 years of age, workers may be the target of age-based stereotypes, and employers rationalize discrimination towards them by referring to profitability and business costs (Malinen & Johnston, Reference Malinen and Johnston2013; Roscigno, Mong, Byron, & Tester, Reference Roscigno, Mong, Byron and Tester2007)Footnote 1 . Even more, results of previous studies suggest that a workplace free of age-based attitudes increases older workers’ satisfaction and decreases intentions to retire, which are both correlated to actual retirement (Bal et al., Reference Bal, de Lange, Van der Heijden, Zacher, Oderkerk and Otten2015; Browne, Carr, Fleischmann, Xue, & Stanfeld, Reference Browne, Carr, Fleischmann, Xue and Stanfeld2018; Lagacé, Tougas, Laplante, & Neveu, Reference Lagacé, Tougas, Laplante and Neveu2010; Porcellato, Carmichael, Hulme, Ingham, & Prashar, Reference Porcellato, Carmichael, Hulme, Ingham and Prashar2010). Consequently, it is plausible to think that one of the means of increasing workforce participation is to counteract expressions of ageist stereotypes and discriminatory age-based practices. Ageism refers to prejudice and discrimination against older people based on the belief that aging makes people less attractive, intelligent, adaptable, and productive (Nelson, Reference Nelson2016; Wilkinson & Ferraro, Reference Wilkinson, Ferraro and Nelson2002). Levy and Banaji (Reference Levy, Banaji and Nelson2002) sustain that although ageism is quite prevalent (mostly in the workplace), it is one of the most tolerated forms of prejudice in that there are no social consequences for people who express ageism towards older individuals. Even more, research on ageism lags behind when compared with research conducted on other types of prejudice, such as racism and sexism. Consequently, evidence-based knowledge about the sources and impact of ageism remains limited. One of the means by which ageism could be counteracted is to increase younger and older workers’ awareness of the prevalence and negative consequences of this form of stigma. In light of the intergroup contact theory (ICT; Allport, Reference Allport1954), it is plausible to think that quality contact between members of different age groups could be one such means in terms of increasing ageism awareness in the workplace. In the following section, we turn to ICT.

Intergroup Contact Theory (ICT)

Conceptualized by Allport (Reference Allport1954), ICT states that intergroup contact can decrease prejudice when the four following conditions are met: (1) equal status between groups, which implies that members of both groups engage equally in the relationship and that major background differences are minimized; (2) common goals, also sometimes referred to as “superordinate goals,” entail that members must pool their expertise, resources, and efforts to attain such goals; (3) intergroup cooperation, which implies that members of both groups must work together in the pursuit of common goals; and (4) support from authorities. This fourth condition states that both groups must acknowledge some authority, be it social or institutional, that supports the contact and interactions between groups. Interestingly, studies show that even in sub-optimal conditions, contact between members of different groups can still reduce negative stereotypes (Pettigrew, Reference Pettigrew1998; Pettigrew & Tropp, Reference Pettigrew and Tropp2006). For example, Pettigrew and Tropp (Reference Pettigrew and Tropp2006) conducted a meta-analysis in order to assess the impact of intergroup contact on prejudice reduction. Relying on 515 studies (based on 713 independent samples), findings revealed a significant and negative relationship between intergroup contact and prejudice (mean r = -0.215). Even more, although this effect significantly increases when the four key conditions are met, it remains notwithstanding their absence; and more so, the effect can be generalized to different forms of prejudice, such as culture and gender.

The reduction of prejudice stemming from quality intergroup contact can be explained by the following: when members of different social groups interact with one another (e.g., when younger and older workers collaborate on a work project), the feeling of uncertainty resulting from perceived differences is outbalanced by increased feelings of familiarity (Pettigrew & Tropp, Reference Pettigrew and Tropp2008). As such, through intergroup contact, individuals can learn from out-group members, which paves the way to affective tie building, behavior change, and in-group reappraisal (Pettigrew, Reference Pettigrew1998). In sum, intergroup contact reduces prejudice at the cognitive (learning and reappraising), behavioral (attitudes and practices), and affective (friendship and positive emotions) level. ICT is particularly relevant in the context of the current study, as age is a social criterion that people often use to categorize and one that possibly facilitates a stereotyping of individuals (Nelson, Reference Nelson2002).

There is a growing body of work on the impact of age-based intergroup contact (e.g., Caspi, Reference Caspi1984; Kalisch, Coughlin, Ballard, & Lamson, Reference Kalisch, Coughlin, Ballard and Lamson2013; Lamont, Swift, & Abrams, Reference Lamont, Swift and Abrams2015; Levy & Macdonald, Reference Levy and Macdonald2016; McCleary, Reference McCleary2014; Pettigrew & Tropp, Reference Pettigrew and Tropp2006; Van Dussen & Weaver, Reference Van Dussen and Weaver2009), precisely in the context of work (Choi, Jarrott, & Naar, Reference Choi, Jarrott and Naar2017; Iweins, Desmette, Yzerbyt, & Stinglhamber, Reference Iweins, Desmette, Yzerbyt and Stinglhamber2013; Novak, Feyes, & Christensen, Reference Novak, Feyes and Christensen2011; Rast, Gaffney, & Yang, Reference Rast, Gaffney and Yang2017). For example, Iweins et al. (Reference Iweins, Desmette, Yzerbyt and Stinglhamber2013) have assessed the effect of intergenerational contacts among Belgian workers. Findings suggest that such contacts significantly reduce ageist attitudes towards older workers through dual identity building. Precisely, intergroup contact resulted in young employees acknowledging that although older employees may belong to a different generation, both groups share a common workplace identity. In turn, identity sharing fostered feelings of admiration on the part of young employees towards older peers.

Within the Canadian context, results of a study conducted among older workers (Lagacé, Van de Beeck, & Firzly, Reference Lagacé, Van de Beeck and Firzly2019) suggest that positive perception of an intergenerational work climate reduces older workers’ feeling of being the target of ageist practices; in turn, this leads to greater job satisfaction. In this study, workplace intergenerational climate relates to workers’ attitudes and perceptions about ages and generations in the workplace (King & Bryant, Reference King and Bryant2016) whereas satisfaction relates to workers’ affective or attitudinal reaction to a job (Spector, Reference Spector1985). Even more, a positive perception of work climate is correlated with knowledge-sharing practices, defined as providing and/or receiving information and feedback on work-related tasks and processes (Foss, Husted, & Michailova, Reference Foss, Husted and Michailova2010). However, one limitation of Lagacé et al.’s study (Reference Lagacé, Van de Beeck and Firzly2019) is that it does not include the perspective of younger workers regarding the impact of age-based intergroup contact on ageism awareness. Precisely, the study does not allow for assessing the extent to which a positive perception of an intergenerational workplace climate and knowledge-sharing practices increase younger workers’ awareness of ageist attitudes targeting their older peers. In the face of labour shortages that can partly be addressed through hiring and retaining workers of all ages (Mérette, Georges, & Zhang, Reference Mérette, Georges and Zhang2011), it is important to understand the perspective of both younger and older workers on intergenerational workplace climate and how it relates to ageism.

The goal of the current study is to determine the impact of age-based intergroup relations in the workplace on younger workers’ ageism awareness targeting older peers. In continuity with findings from previous studies (Iweins et al., Reference Iweins, Desmette, Yzerbyt and Stinglhamber2013; Lagacé et al., Reference Lagacé, Van de Beeck and Firzly2019), and relying on ICT’s postulates, it is expected that a positive perception of the workplace intergenerational climate and knowledge-sharing practices will increase younger workers’ awareness of ageist attitudes targeting older peers. In turn, such awareness will have a positive effect on job satisfaction. Indeed, by communicating and interacting with older colleagues, younger workers are able to understand and appreciate older workers’ situation and challenges; in turn, such intergroup connection plausibly increases satisfaction at work. Hypotheses are summarized in the following list and illustrated in Figure 1.

H1: The more that young workers have a positive perception of an intergenerational climate, the greater their awareness of ageism targeting older workers.

H2: The more that young workers take part in knowledge sharing practices, the greater their awareness of ageism targeting older workers.

H3: A positive perception of an intergenerational climate is positively correlated with knowledge sharing and donating practices.

H4: Younger workers’ awareness of ageism toward older workers increases the level of job satisfaction.

Figure 1: Path diagram of the hypothesized model. E = error terms.

Methodology

Recruitment

Once ethics approval was obtained,Footnote 2 participants were recruited online through a research portal at a Canadian University whereby students are offered compensation for taking part in scholarly studies (1% of their final grade). Participants completed an online, anonymous and confidential questionnaire. Inclusion criteria were as follows: working part-time or full-time, being less than 45 years old, and understanding French or English.

Participants

A total of 741 participants took part in this cross-sectional study by completing an online questionnaire (129 of these were discarded as will be explained in the data analysis section). The final sample (n = 612) was composed of 447 women and 165 men (M age = 20.34 years old; SD age = 3.79). All participants were undergraduate university students and the majority (n = 503) worked part-time, less than 30 hours a week.

Questionnaire

The questionnaire, available in French and English, included measures of each variable under study (intergenerational climate, intergenerational knowledge donating and collecting, awareness of ageism targeting older workers, job satisfaction) and a short demographic section as described in the following section.

Demographic information

Participants were asked about their age, gender, and mother tongue (see Table 1). The majority of participants were women 25 years of age or younger (n = 569). A total of 160 participants indicated French as their mother tongue, while 147 indicated English and 133 indicated other.

Table 1: Frequencies per demographic characteristics of the sample

Note. Missing data are not included in the table.

Intergenerational climate

Participants responded to the Workplace Intergenerational Climate Scale (WICS) (King & Bryant, Reference King and Bryant2016) which is composed of 20 items, designed to assess the extent to which one’s workplace builds on an age-based inclusive environment, as well as the quality of contact between workers of different generations. Following confirmatory factor analysis (CFA) (see section on Data Analysis), 16 items were retained, composing four subscales: lack of generational stereotypes – five items (e.g., Co-workers outside my generation complain more than co-workers my age do), workplace generational inclusiveness – three items (e.g., I believe that my work environment is a healthy one for people of all ages), positive intergenerational affect – five items (e.g., I feel comfortable when co-workers outside my generation try to make conversation with me), and intergenerational contact – three items (e.g., How often do I have conversations with co-workers outside my generation?). Participants responded to these statements on a Likert scale ranging from 1 (Strongly disagree) to 4 (Strongly agree) except for the intergenerational contact subscale on which participants responded on a Likert scale ranging from 1 (Never) to 4 (Very often). The Cronbach’s α value was 0.81, which was similar to the original scale (α = 0.85). King and Bryant (Reference King and Bryant2016) have assessed construct validity (precisely convergent and discriminant validity) respectively through Stereotypes about Older Workers (St-O) and Stereotypes about Younger Workers (St-Y) scales and the Job Satisfaction Survey (Bellingham, Reference Bellingham2004). A composite score was calculated relying on the overall mean of all subscales. A higher score on this scale indicated a positive perception of the workplace’s intergenerational climate.

Intergenerational knowledge donating and collecting

Participants also completed the Knowledge Sharing Behavior Measures (KSBM) inspired by Kim and Lee (Reference Kim and Lee2013). The scale includes 16 items measuring knowledge sharing (donation and collection behaviours) between older and younger workers. The scale includes two subscales: knowledge collecting – eight items (e.g., When I need certain knowledge, I ask my younger colleagues about it/When I need certain knowledge, I ask my older colleagues about it) and knowledge donating – eight items (e.g., I share information I have with my younger colleagues/I share information I have with my older colleagues). Participants responded to these statements on a Likert scale ranging from 1 (Strongly disagree) to 4 (Strongly agree). The scale has a good overall internal consistency with an α value of 0.86, similar to the original scale (α = 0.85) on which Kim and Lee (Reference Kim and Lee2013) have assessed convergent and discriminant validity. The overall mean of the two subscales was used to calculate a composite score. A higher overall score on this scale indicated higher levels of intergenerational knowledge collection and donation practices.

Ageism towards older workers

Participants also completed the Nordic Age Discrimination Scale (NADS) (Furunes & Mykletun, Reference Furunes and Mykletun2010) to assess how ageism is expressed towards older workers through human resources practices (such as promotion, training, and performance appraisal). The scale is composed of six items (e.g., Elderly workers do not have equal opportunities for training during work time) and respondents indicated their degree of agreement on a Likert type scale ranging from 1 (Disagree) to 4 (Strongly agree). Internal reliability of the scale is acceptable with an α value of 0.84, which is similar to the original scale (α = between 0.82 and 0.87). Construct validity of the original scale was assessed relying on life satisfaction criterion (Furunes & Mykletun, Reference Furunes and Mykletun2010). Scores on the six items were averaged to create a computed score. A higher score indicated greater awareness of ageist practices in the workplace.

Job satisfaction

Participants completed a 10-item Job Satisfaction Survey (JSS) (Spector, Reference Spector1985) scale measuring the level of overall job satisfaction. This scale was adapted by King (Reference King2010). Participants indicated their agreement with each statement (e.g., I find meaning in my work; The work I do is related to my personal values) using a four-point Likert scale ranging from 1 (Strongly disagree) to 4 (Strongly agree). The Cronbach’s α value was high (0.88), which is similar to the original scale (α = 0.91). Validity and reliability of the JSS scale has been evaluated in previous studies. Furthermore, King (Reference King2010) tested the discriminant validity with separate but related latent variables (satisfaction at work and work intergenerational climate). A composite score was calculated by averaging the score on each of the 10 items. Higher scores indicated stronger feelings of satisfaction at work.

All scales were validated in French by research team members. A parallel back-translation procedure (Vallerand, Reference Vallerand1989) ensured accuracy of the translation.

Data Analyses

Data screening and statistical analysis were conducted with the Statistical Package for Social Sciences (IBM SPSS software, version 25) and path analysis was conducted using IBM SPSS AMOS software, version 25. Variables were examined for accuracy of data entry and fit between their distributions and the assumptions of multivariate analysis. Univariate outliers on all variables were assessed using histograms and standardized values, which revealed no standardized scores greater than 3.29 standard deviations above and below the mean (Tabachnick & Fidell, Reference Tabachnick and Fidell2007).

Screening

A total of 129 participants were discarded based on age, response frequency, and invariance. Participants 45 years of age and older were removed from the original sample. In addition, participants were removed from the analysis when their completion rate was below 80 per cent. Finally, response invariance was checked and participants whose standard deviation was below 0.50 were discarded. The final sample was composed of 612 participants.

Missing data

Given that the percentage of missing data for each scale was below 5 per cent, patterns of missing data were not taken into consideration. However, to preserve consistency in sample size through analyses, mean substitution was used on missing data.

Factorial analyses

First, data analyses consisted in retrieving the underlying structure of each scale using CFA structure based on previous results (Lagacé et al., Reference Lagacé, Van de Beeck and Firzly2019). Descriptive statistics and correlational analyses were then completed (see Table 2). Finally, path analysis was conducted to assess the hypothesized model. Indicators of goodness of fit (Cheung & Rensvold, Reference Cheung and Rensvold2002) were examined in CFA and in model testing with the following cut-off values: the Chi-Square (p > 0.05); the minimum discrepancy divided by the degrees of freedom (CMIN/DF), the root mean square error of approximation (RMSEA) (< 0.05); the comparative fit index (CFI) (> 0.90) and the Tucker–Lewis Index (TLI) (> 0.90).

Table 2: Means, standard deviations, and inter-correlations matrix for all scales

Note. n = 612. For all scales, higher scores indicate more extreme responding in the direction of the construct assessed.

*p < 0.05.

WICS = Workplace Intergenerational Climate Scale; KSBM = Knowledge Sharing Behavior Measures; NADS = Nordic Age Discrimination Scale; JSS = Job Satisfaction Survey; M = Mean; SD = Standard Deviation.

Model testing and selection

Models were tested using stepwise selection; direct effects between predictors and outcome variables were added or removed from the hypothesized model. Modifications were made according to statistical fit indices provided by AMOS and in light of previous findings assessing similar variables (Lagacé et al., Reference Lagacé, Van de Beeck and Firzly2019). Once model fit was obtained, several interaction terms were added to determine the effect of demographic factors such as age, gender, and mother tongue on results previously obtained.

Results

Descriptive Statistics and Correlations

Means, standard deviations and inter-correlations for scales are presented in Table 2. In this study, mean values for each scale ranged from 2.14 and 3.11 out of a possible total score of 4. Skewness and kurtosis values were within satisfactory range, from -0.544 to 0.215 and from -0.538 to 1.32 respectively, indicating normal distributions. The correlation matrix revealed that intergenerational climate, intergenerational knowledge donating and collecting, and satisfaction at work are positively correlated (r values varying between 0.37 and 0.47, p < 0.05). However, awareness of ageist practices targeting older workers was negatively correlated with all other scales (r values ranging from -0.09 to -0.29, p < 0.05) except for knowledge donating and collecting.

Path Analysis

The hypothesized model (Figure 1) was assessed relying on path analysis. Goodness of fit indicators suggested that the hypothesized model did not adequately fit the data χ² (3) = 183.24, p = < 0.001 (CMIN = 183.29, DF = 2, CMIN/DF = 91.62, RMSEA = 0.38, CFI = 0.2, TLI = -5.69). As such, a stepwise selection process allowed determination of best model-data fit. This final model also included several interaction terms to determine the potential effect of demographic factors, such as age, gender, and mother tongue. The final model is illustrated in Figure 2 and reveals a good fit to the data: χ² (2) = 0.28, p = 0.872 (CMIN = 0.28, DF = 2, CMIN/DF = 0.14, RMSEA = 0.00, CFI = 1, TLI = 1.1).

Figure 2: Final path diagram and hypotheses testing. Model fit. χ² (2) = 0.28; root mean square error of approximation (RMSEA) = 0.00; comparative fit index (CFI) = 1; Tucker– Lewis Index (TLI)= 1.1. *p < 0.01.

The final model does not confirm the predicted relationship between awareness of ageist practices towards older workers and job satisfaction. More, the model suggests that positive intergenerational climate decreases awareness of ageist practices targeting older workers in the workplace (β = -0.35, p < 0.001). On the other hand, a positive intergenerational climate increases job satisfaction (β = 0.39, p < 0.001). In addition, intergenerational climate is positively correlated with sharing and donating knowledge behaviors (β = 0.41, p < 0.001). Finally, such behaviours, while directly increasing job satisfaction (β = 0.22, p < 0.001), also increase awareness of ageist practices towards older workers (β = 0.18, p < 0.001). The model explains 27 per cent of the job satisfaction variance ( = 0.27) and 15 per cent of the variable awareness of ageism towards older workers ( = 0.15).

Neither age nor gender had significant direct effects on ageism awareness or satisfaction. However, mother tongue had a significant effect on ageism towards older workers (β = -0.16, p < 0.001) with native English speakers reporting greater awareness of ageist stereotypes in the workplace than French native speakers. The interaction term modeling the effect of gender and mother tongue on ageism towards older worker was significant (β = -0.09, p < 0.05) with a strengthened negative relationship between native language (with English as a lower score) and ageist perception for females. The interaction terms modeling the effect of gender and age on ageism towards older workers (β = 0.07, p < 0.1) but also on satisfaction (β = 0.07, p < 0.1), were significant at the 90 per cent level. As such, age seems to dampen the negative relationship between gender and ageist practices towards older worker as well as job satisfaction.

Discussion

The current study examined the impact of an intergenerational work climate and knowledge sharing practices on younger workers’ level of awareness of ageism towards older workers. It also assessed the impact of awareness of ageism on job satisfaction.

According to Abrams, Eilola, and Swift (Reference Abrams, Eilola and Swift2009), ageism is the most common type of prejudice in the workplace and older workers are the main target of age-based stereotypes. Even more, the negative impact of ageism on the retention of older workers is well documented (Brooke & Taylor, Reference Brooke and Taylor2005; Heisler & Bandow, Reference Heisler and Bandow2018; Statistics Canada, 2017; Voss, Bodner, & Rothermund, Reference Voss, Bodner, Rothermund, Ayalon and Tesch-Römer2018). Taking into account the fact that modern organizations are more age diversified than ever, it is important to better understand factors that may help counteract ageism; for example, through greater awareness of such types of discrimination, especially on the part of younger workers. Relying on the ICT, it was posited that younger workers’ positive perception of an intergenerational workplace climate and knowledge-sharing practices would increase ageism awareness (H1, H2). It was also anticipated that both an intergenerational workplace climate and knowledge collecting/donating behaviors would be correlated with one another (H3). In turn, it was hypothesized that younger workers’ awareness of ageism would lead to higher job satisfaction (H4). Results of the path analysis partly supported these hypotheses. In the following sections, findings are discussed in detail.

Contrary to what was predicted (H1), a positive perception of an intergenerational workplace climate decreases ageism awareness. This comes as an interesting result that can partly be explained from an intergroup dynamic perspective. The WICS scale’s average score is rather high (above the median point), suggesting that younger workers generally perceive their workplace intergenerational climate to be healthy. In other words, they seem to feel good about their work environment. Such a perception may have been driven solely by an in-group bias perspective (Tajfel & Turner, Reference Tajfel, Turner, Worchel and Austin1986); that is, when younger workers believe that things are going rather well for their own group, they believe that it must also be the case for members of other groups (precisely, older workers). In other words, younger workers may have perceived the intergenerational workplace climate through an in-group favoritism lens, which made them less aware of ageist practices towards their older peers. The negative link between the variables “intergenerational climate” and “ageism towards older workers” could also be explained by the nature of the former scale itself, which is mostly composed of beliefs about the workplace climate and less focused on intergenerational behaviours. As such, beliefs may not constitute strong enough factors to increase awareness of ageism when compared with intergenerational knowledge-sharing behaviors. In fact, as discussed in the following sections, knowledge-sharing practices are significantly and positively linked to greater ageism awareness.

As predicted in the second hypothesis (H2), when younger workers share knowledge (donating and receiving) they become more aware of ageism targeting older peers. This result is particularly interesting in light of the negative link between the variables “intergenerational climate” and “ageism towards older workers”. The KSBM scale is behaviour-based (in contrast to the perception of an intergenerational climate scale), which suggests that concrete and effective interactions (through teamwork, mentoring, and exchange of information) between younger and older workers seem to change the formers’ perception of the latter, at least in the sense of a greater understanding and awareness of ageist practices. In other words, intergenerational contacts (beyond the mere perception of a positive intergenerational climate) may be a key factor whereby younger workers adopt an out-group perspective and hence, better understand their older peers’ work conditions. As suggested by Song and Teng (Reference Song and Teng2011), and Fleig-Palmer and Schoorman (Reference Fleig-Palmer and Schoorman2011), workplace knowledge interactions build on a social bond and on trust that again may render younger workers more aware of ageist practices towards older workers. From a theoretical perspective, this result sheds further light on ICT’s main postulates, precisely on its applicability to age-based group biases. It does suggest that concrete and positive intergenerational contact, through knowledge-sharing practices, can improve younger workers’ attitude towards older workers.

The positive and significant relationship between intergenerational climate and knowledge sharing (H3) suggests that knowledge processes are important components of the perception of intergenerational dynamics in today’s workplace environment (Starks, Reference Starks2013). It falls into continuity with previous studies suggesting that perceptions in this case, perceptions of workplace intergenerational climate, guide human interactions and are important for understanding the workplace relationships measured in the current study, in other words,  through the concept of knowledge sharing (Buyens, van Dijk, Dewilde, & De Vos, Reference Buyens, van Dijk, Dewilde and De Vos2009; Cuddy & Fiske, Reference Cuddy, Fiske and Nelson2002;).

Contrary to what was predicted, awareness of ageist practices targeting older workers does not seem to affect younger workers’ level of job satisfaction (H4). Similar to the absence of an effect of the workplace intergenerational climate on ageism awareness, it may be that younger workers favour an in-group perspective whereby they are not aware of negative stereotypes targeting older workers. Even more, the fact of public discourses (as well as human resources policies and practices) being quite focused on adapting the workplace to younger individuals entering the workforce may also enhance such an in-group perspective.

Finally, although not predicted, findings reveal that perception of the workplace intergenerational climate as well as knowledge-sharing practices directly and positively influence job satisfaction. These are quite interesting results, as job satisfaction has been assessed as an important component linked with workplace engagement and retention (Das & Baruah, Reference Das and Baruah2013; Karatepe & Karadas, Reference Karatepe and Karadas2015; Lu & Gursoy, Reference Lu and Gursoy2013; O’Conner, Reference O’Conner2018; Reukauf, Reference Reukauf2017). Here again, they reveal the powerful role that intergenerational dynamics can play in the workplace. In the case of knowledge-sharing practices, these do not only raise awareness of ageism targeting older workers, they also directly influence younger workers’ level of job satisfaction. Moreover, those results corroborate previous findings by King (Reference King2010), and King and Bryant (Reference King and Bryant2016) that highlighted the positive relationship between an intergenerational climate at work and job satisfaction, which taken together might enhance workplace retention.

Overall, the aging of the workforce and the concurrent entering of younger individuals into this same workforce are important demographic and sociological phenomena that have major implications for modern organizations. Hiring and retaining younger and older workers is one path to explore in addressing labor shortages as well as issues stemming from ageism. The current study shows that effective and positive intergenerational collaborations do have a significant impact on younger workers’ awareness of ageist practices. In other words, it is only through concrete and effective age-based interaction opportunities that younger workers become more aware of their older colleagues’ work conditions.

Limitations

There are methodological limitations to this study, including the use of a cross-sectional design that forbids causal inferences regarding the links between variables. Even more, although attitudes remain reliable predictors of behaviours (Glasman & Albarracín, Reference Glasman and Albarracín2006), another limitation pertains to the measurement of attitudes and opinions but not of behaviours per se. Following the same train of thought, the scale used to measure ageism towards older workers solely captures ageist human resources practices. However, ageism is a complex and multidimensional concept, often expressed through implicit and unconscious modes. Future studies assessing the association between age-based intergroup contact and ageism should indeed include measurements of implicit ageist beliefs and stereotypes. Future studies should also include manipulation checks regarding the frequency of contacts between younger and older workers as, plausibly, little contact may bias responses with regard to ageism and job satisfaction. Regarding this aspect, it is important to remember that most participants in the current study worked part time which, plausibly, may not have allowed for frequent contacts with older workers and therefore might reinforce in-group bias. The study did not take into account ageism stemming from older workers towards younger ones. Future studies should test if, and the extent to which, older workers subscribe to ageist stereotypes, and assess the role of age-based intergroup contact to counteract such stereotypes. Finally, the non-random and small sample (students who mostly worked part time in Ontario and Quebec) is another limitation of the study that forbids generalization of the results to the Canadian context.

Theoretical and Practical Implications

Despite these limitations, this study contributes to the advancement of knowledge from a theoretical and practical perspective. Regarding the former, it has allowed testing of ICT’s postulates as for age-based prejudice in the context of the Canadian workplace. Findings reveal the key role that intergroup contact plays (in this case, through knowledge-sharing practices) as a means to increase awareness of ageism in the workplace. Regarding the latter, findings suggest that modern organizations could greatly benefit from putting in place age-based formal mentoring programs between younger and older workers when aiming to increase job satisfaction. Even more, although employee retention was not measured in the study, previous studies have shown that job satisfaction is positively correlated with retention (Das & Baruah, Reference Das and Baruah2013; O’Conner, Reference O’Conner2018; Reukauf, Reference Reukauf2017). Ageism remains is a complex, prevalent, and disruptive form of stigma. What the findings of the current study suggest, in combination with findings from previous studies conducted amongst older workers (e.g., Iweins et al., Reference Iweins, Desmette, Yzerbyt and Stinglhamber2013; Lagacé et al., Reference Lagacé, Van de Beeck and Firzly2019), is that any means undertaken to combat ageism must include younger and older workers. Indeed, awareness of ageism on the part of young workers and low subscription to ageist stereotypes on the part of older workers has a positive impact in terms of job satisfaction. In the face of current and future labour shortages, one cannot underestimate the cost of ageism in the workplace and consequently, the importance of reducing it. Finally, it is important to note that top and mid-level managers play an important role in facilitating younger/older worker intergroup group contact; for example, through mentoring programs. And more, through the type of aging discourse that they convey, top and mid-managers can be facilitators of an age-based inclusive workplace and conversely, be important barriers to an inclusive age-based workplace. Future studies should actually factor in managers’ role, precisely their discourse, as to valuing younger and older workers, and as such, countering ageism.

Footnotes

1 In this study, “older workers” refers to workers 45 years old or older. This cut-point was an inclusion criterion. Although chronological age is one factor amongst others used to define the concept of “older worker”, previous studies suggest that workplace ageist stereotypes and behaviors often target workers as early as 45 years of age.

2 Ethics approval was provided by the research ethics office of the academic institution to which researchers are affiliated.

References

Abrams, D., Eilola, T., & Swift, H. S. (2009). Attitudes to age in Britain 2004–08. Retrieved 9 February 2020 from http://kar.kent.ac.uk/23668/1/abrams_attitudes_age.pdf Google Scholar
Allport, G. W. (1954). The nature of prejudice. Boston: Addison-Wesley.Google Scholar
Bal, P. M., de Lange, A. H., Van der Heijden, B. I. J. M., Zacher, H., Oderkerk, F. A., & Otten, S. (2015). Young at heart, old at work? Relations between age, (meta-) stereotypes, self-categorization, and retirement attitudes. Journal of Vocational Behavior, 91, 3545. doi: 10.1016/j.jvb.2015.09.002 CrossRefGoogle Scholar
Bellingham, R. (2004). Job satisfaction survey. Retrieved 9 February 2020 from http://www.welcoa.org/freeresources/pdf/job_satisfaction_survey.pdf Google Scholar
Berger, E. D., & Hodgins, D. W. (2012). Age discrimination and paid work. Retrieved 9 February 2020 from http://ir.lib.uwo.ca/pclc_rpb/vol1/iss3/2 Google Scholar
Brooke, L., & Taylor, P. (2005). Older workers and employment: Managing age relations. Aging & Society, 25(3), 415429. doi: 10.1017/S0144686X05003466 CrossRefGoogle Scholar
Browne, P., Carr, E., Fleischmann, M., Xue, B., & Stanfeld, S. A. (2018). The relationship between workplace psychosocial environment and retirement intentions and actual retirement: A systematic review. European Journal of Ageing, 16(1), 7382. doi: 10.1007/s10433-018-0473-4 CrossRefGoogle ScholarPubMed
Buyens, D., van Dijk, H., Dewilde, T., & De Vos, A. (2009). The aging workforce: Perception of career ending. Journal of Managerial Psychology, 24(2), 102117. doi: 10.1108/02683940910928838 CrossRefGoogle Scholar
Caspi, A. (1984). Contact hypothesis and inter-age attitudes: A field study of cross-age contact. Social Psychology Quarterly, 47(1), 7480. doi: 10.2307/3033890 CrossRefGoogle Scholar
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233255. doi: 10.1207/S15328007SEM0902_5 CrossRefGoogle Scholar
Choi, M., Jarrott, S. E., & Naar, J. (2017). Application of intergroup contact theory to managing age-diverse teams. Innovation in Aging, 1(1), 837838. doi: 10.1093/geroni/igx004.3017 CrossRefGoogle Scholar
Conference Board of Canada. (2018). Global labor market outlook 2018: Finding ways to counteract labor shortages. Retrieved 9 February 2020 from https://www.conference-board.org/topics/global-labor-market-outlook Google Scholar
Cuddy, A. J. C., & Fiske, S. T. (2002). Doddering but dear: Process, content, and function in stereotyping of older persons. In Nelson, T. D. (Ed.), Ageism: Stereotyping and prejudice against older persons (pp. 326). Cambridge, MA: MIT Press.Google Scholar
Das, B. L., & Baruah, M. (2013). Employee retention: A review of literature. Journal of Business and Management, 14(2), 816. doi: 10.9790/487X-1420816 Google Scholar
Fleig-Palmer, M. M., & Schoorman, F. D. (2011). Trust as a moderator of the relationship between mentoring and knowledge transfer. Journal of Leadership & Organizational Studies, 18(3), 334343. doi: 10.1177/1548051811408615 CrossRefGoogle Scholar
Foss, N. J., Husted, K., & Michailova, S. (2010). Governing knowledge sharing in organizations: Levels of analysis, governance mechanisms, and research directions. Journal of Management Studies, 47(3), 455482. doi: 10.1111/j.1467-6486.2009.00870.x CrossRefGoogle Scholar
Furunes, T., & Mykletun, R. J. (2010). Age discrimination in the workplace: Validation of the Nordic Age Discrimination Scale (NADS). Scandinavian Journal of Psychology, 51(1), 2330. doi: 10.1111/j.1467-9450.2009.00738.x CrossRefGoogle Scholar
Glasman, L. R., & Albarracín, D. (2006). Forming attitudes that predict future behavior: A meta-analysis of the attitude-behavior relation. Psychological Bulletin, 132(5), 778822. doi: 10.1037/0033-2909.132.5.778 CrossRefGoogle ScholarPubMed
Heisler, W., & Bandow, D. (2018). Retaining and engaging older workers: A solution to worker shortages in the US. Business Horizons, 61(3), 421430. doi: 10.1016/j.bushor.2018.01.008 CrossRefGoogle Scholar
Iweins, C., Desmette, D., Yzerbyt, V., & Stinglhamber, F. (2013). Ageism at work: The impact of intergenerational contact and organizational multi-age perspective. European Journal of Work and Organizational Psychology, 22(3), 331346. doi: 10.1080/1359432X.2012.748656 CrossRefGoogle Scholar
Kalisch, H. R., Coughlin, D. R., Ballard, S. M., & Lamson, A. (2013). Old age is a part of living: Student reflections on intergenerational service-learning. Gerontology & Geriatrics Education, 34(1), 99113. doi: 10.1080/02701960.2012.753440 CrossRefGoogle ScholarPubMed
Karatepe, O. M., & Karadas, G. (2015). Do psychological capital and work engagement foster frontline employees’ satisfaction? A study in the hotel industry. International Journal of Contemporary Hospitality Management, 27(6), 12541278. doi: 10.1108/IJCHM-01-2014-0028 CrossRefGoogle Scholar
Kim, T. T., & Lee, G. (2013). Hospitality employee knowledge-sharing behaviors in the relationship between goal orientations and service innovative behavior. International Journal of Hospitality Management, 34(1), 324337. doi: 10.1016/j.ijhm.2013.04.009 CrossRefGoogle Scholar
King, S. (2010). Development and validation of the Workplace Intergenerational Atmosphere Scale (Unpublished doctoral dissertation). Loyola University, Chicago.Google Scholar
King, S. P., & Bryant, F. B. (2016). The Workplace Intergenerational Climate Scale (WICS): A self‐report instrument measuring ageism in the workplace. Journal of Organizational behavior, 38(1), 124151. doi: 10.1002/job.2118 CrossRefGoogle Scholar
Lagacé, M., Tougas, F., Laplante, J., & Neveu, J.-F. (2010). Communication âgiste au travail: Une voie vers le désengagement psychologique et la retraite des infirmières d’expérience ? International Review of Social Psychology, 23(4), 91121.Google Scholar
Lagacé, M., Van de Beeck, L., & Firzly, N. (2019). Building on intergenerational climate to counter ageism in the workplace? A cross-organizational study. Journal of Intergenerational Relationships, 17(2), 201219. doi: 10.1080/15350770.2018.1535346 CrossRefGoogle Scholar
Lamont, S. R. A., Swift, H. J., & Abrams, D. (2015). A review and meta-analysis of age-based stereotype threat: Negative stereotypes, not facts, do the damage. Psychology and Aging, 30(1), 180193. doi: 10.1037/a0038586 CrossRefGoogle Scholar
Levy, B. R., & Banaji, M. R. (2002). Implicit ageism. In Nelson, T. D. (Ed.), Ageism: Stereotyping and prejudice against older persons (pp. 4975). Cambridge, MA: MIT Press.Google Scholar
Levy, S. R., & Macdonald, J. L. (2016). Progress on understanding ageism. Journal of Social Issues, 72(1), 525. doi: 10.1111/josi.12153 CrossRefGoogle Scholar
Lu, A., & Gursoy, D. (2013). Impact of job burnout on satisfaction and turnover intention: Do generational differences matter? Journal of Hospitality & Tourism Research, 40(2), 210235. doi: 10.1177/1096348013495696 CrossRefGoogle Scholar
Malinen, S., & Johnston, L. (2013). Workplace ageism: Discovering hidden bias. Experimental Aging Research, 39(4), 445465. doi: 10.1080/0361073X.2013.808111 CrossRefGoogle ScholarPubMed
McCleary, R. (2014). Using film and intergenerational colearning to enhance knowledge and attitudes toward older adults. Educational Gerontology, 40(6), 414426. doi: 10.1080/03601277.2013.844034 CrossRefGoogle Scholar
Mérette, M., Georges, P., & Zhang, Q. (2011). A population aging analysis for Canada using the national transfer accounts approach. Retrieved 9 February 2020 from https://ecomod.net/system/files/NTA%20paper-EcoMod2011-Qi%20Zhang.pdf Google Scholar
Nelson, T. D. (2002). Ageism: Stereotyping and prejudice against older persons. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Nelson, T. D. (2016). The age of ageism. Journal of Social Issues, 72(1), 191198. doi: 10.1111/josi.12162 CrossRefGoogle Scholar
Novak, J., Feyes, K. J., & Christensen, K. A. (2011). Application of intergroup contact theory to the integrated workplace: Setting the stage for inclusion. Journal of Vocational Rehabilitation, 35(3), 211226. doi: 10.3233/JVR-2011-0573 CrossRefGoogle Scholar
O’Conner, J. (2018). The impact of job satisfaction on the turnover intent of executive level central office administrators in Texas public school districts: A quantitative study of work related constructs. Education Sciences, 8(2), 69. doi: 10.3390/educsci8020069 CrossRefGoogle Scholar
Pettigrew, T. F. (1998). Intergroup contact theory. Annual Review of Psychology, 49(1), 6585. doi: 10.1146/annurev.psych.49.1.65 CrossRefGoogle ScholarPubMed
Pettigrew, T. F., & Tropp, L. R. (2006). A meta-analytic test of intergroup contact theory. Journal of Personality and Social Psychology, 90(5), 751783. doi: 10.1037/0022-3514.90.5.751 CrossRefGoogle ScholarPubMed
Pettigrew, T. F., & Tropp, L. R. (2008). How does intergroup contact reduce prejudice? Meta-analytic tests of three mediators. European Journal of Social Psychology, 38(6), 922934. doi: 10.1002/ejsp.504 CrossRefGoogle Scholar
Porcellato, L., Carmichael, F., Hulme, C., Ingham, B., & Prashar, A. (2010). Giving older workers a voice: Constraints on the employment of older people in the North West of England. Work, Employment & Society, 24(1), 85103. doi: 10.1177/0950017009353659 CrossRefGoogle Scholar
Posthuma, R. A., & Campion, M. A. (2009). Age stereotypes in the workplace: Common stereotypes, moderators, and future directions. Journal of Management, 35(1), 158188. doi: 10.1177/0149206308318617 CrossRefGoogle Scholar
Rast, D. E., Gaffney, A. M., & Yang, F. (2017). The effect of stereotype content on intergroup uncertainty and interactions. The Journal of Social Psychology, 158(6), 711720. doi: 10.1080/00224545.2017.1407285 CrossRefGoogle Scholar
Reukauf, J. A. (2017). The correlation between job satisfaction and turnover intention in small business. (Unpublished doctoral dissertation). Walden University, Minneapolis.Google Scholar
Roscigno, V. J., Mong, J., Byron, R., & Tester, G. (2007). Age discrimination, social disclosure and employment. Social Forces, 86(1), 313334. doi: 10.1353/sof.2007.0109 CrossRefGoogle Scholar
Spector, P. (1985). Measurement of human service staff satisfaction: Development of the Job Satisfaction Survey. American Journal of Community Psychology, 13(6), 693713. doi: 10.1007/bf00929796 CrossRefGoogle ScholarPubMed
Starks, A. (2013). The forthcoming generational workforce transition and rethinking organizational knowledge transfer. Journal of Intergenerational Relationships, 11(3), 223237. doi: 10.1080/15350770.2013.810494 CrossRefGoogle Scholar
Statistics Canada. (2017). Portrait de la population active canadienne. Retrieved 9 February 2020 from http://www12.statcan.gc.ca/nhs-enm/2011/as-sa/99-012-x/99-012-x2011002-fra.cfm Google Scholar
Song, S., & Teng, J. T. C. (2011). An exploratory examination of knowledge-sharing behaviors: Solicited and voluntary. Journal of Knowledge Management, 15(1), 104117. doi: 10.1108/13673271111108729 Google Scholar
Vallerand, R. J. (1989). Vers une méthodologie de validation transculturelle des questionnaires psychologiques: Implication pour la recherche en langue française. Canadian Psychology, 30(4), 662680. doi: 10.1037/h0079856 CrossRefGoogle Scholar
Van Dussen, D. J., & Weaver, R. R. (2009). Undergraduate students’ perception and behaviors related to the aged and to aging processes. Educational Gerontology, 35(4), 342357. doi: 10.1080/03601270802612255 CrossRefGoogle Scholar
Voss, P., Bodner, E., & Rothermund, K. (2018). Ageism: The relationship between age stereotypes and age discrimination. In Ayalon, L., & Tesch-Römer, C. (Eds.), Contemporary perspectives on ageism (pp. 1131). Berlin: Springer.CrossRefGoogle Scholar
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th edition). Boston: Allyn and Bacon.Google Scholar
Tajfel, H., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In Worchel, S. & Austin, W. (Eds.), Psychology of intergroup relations (2nd edition, pp. 724). Wokingham, UK: Nelson-Hall.Google Scholar
United Nations. (2017). World population ageing. Retrieved 9 February 2020 from https://www.un.org/en/development/desa/population/publications/pdf/ageing/WPA2017_Highlights.pdf Google Scholar
Wilkinson, J. A., & Ferraro, K. F. (2002). Thirty years of ageism research. In Nelson, T. D. (Ed.), Ageism: Stereotyping and prejudice against older persons (pp. 339358). Cambridge, MA: MIT Press.Google Scholar
Figure 0

Figure 1: Path diagram of the hypothesized model. E = error terms.

Figure 1

Table 1: Frequencies per demographic characteristics of the sample

Figure 2

Table 2: Means, standard deviations, and inter-correlations matrix for all scales

Figure 3

Figure 2: Final path diagram and hypotheses testing. Model fit. χ² (2) = 0.28; root mean square error of approximation (RMSEA) = 0.00; comparative fit index (CFI) = 1; Tucker– Lewis Index (TLI)= 1.1. *p < 0.01.