Is a Positive Intergenerational Workplace Climate Associated with Better Self-Perceived Aging and Workplace Outcomes? A Cross-Sectional Study of a Representative Sample of the Danish Working Population

Abstract

The aim of this study was to determine the association between intergenerational workplace climate (attitudes, feelings, and perceptions about workers of different ages in the workplace) and self-perceived aging, work engagement, and turnover intention. A cross-sectional study was conducted via an online survey including answers from a representative sample of 1571 individuals aged 18–74 years, living and working in Denmark. In line with our hypotheses, we found that a more positive intergenerational workplace climate was related to a better self-perceived aging as well as to more work engagement and less turnover intention. In addition, we found that these associations were similar in all age groups. The findings point to the potential benefits of initiatives aimed at strengthening the intergenerational climate in workplaces.

Keywords

ageism age stereotypes age discrimination aging work engagement turnover intention

What this paper adds

This study provides preliminary evidence about the role played by intergenerational workplace climate in affecting self-perceived aging, work engagement and turnover intention.

Based on a large, representative sample across all age groups (18–74 years) within the Danish working population, this study adds to previous research that often focuses on either younger or older workers only and is based on smaller, non-representative samples.

This study bridges a gap in existing research by contributing new knowledge on self-directed ageism and possible factors affecting it.

Applications of study findings

The results pave the way for further research on the importance of intergenerational interventions in the workplace.

An evidence-based approach to the design of intergenerational interventions in the workplace and in society is needed in order to effectively minimize ageism.

Interventions improving intergenerational workplace climate may also affect work engagement and turnover intention, which are essential factors for workplaces in relation to daily operations and competitiveness.

Introduction

Age is the personal characteristic based on which most people in Europe experience discrimination, even compared to gender and ethnicity (Ayalon, 2014). Still, the concept of ageism is new to many. Building on earlier research (Butler, 1969; Iversen et al., 2009), the World Health Organization (WHO) defines ageism as a tripartite concept that includes not only age discrimination (behavioral), but also stereotypes (cognitive) and prejudice (affective) based on any kind of age.

Though ageism can be directed towards any age, this study will focus on the negative attitudes and beliefs associated with old age. The wide consequences of this form of ageism have been observed in multiple studies (Levy, 2009; Levy et al., 2002b; Marchiondo et al., 2019; Weber et al., 2019). In the US alone, the health care costs of ageism due to negative self-perceived aging, negative age stereotypes, and age discrimination, were estimated to be 63 billion US dollars yearly, contributing to 17.04 million cases of disease.

In the workplace context, age stereotypes also abound and may have a variety of repercussions among older employees. Employment-related decisions like recruitment, promotion opportunities, and rating and performance interviews can be affected by negative age stereotypes held by decision makers (Abrams et al., 2016; Macdonald & Levy, 2016; Posthuma & Campion, 2009). A number of adverse consequences (e.g., decreased job satisfaction, self-efficacy, and work engagement and increased intentions to resign) for older workers due to negative age stereotypes in the workplace has been observed also in previous studies (Weber et al., 2019).

WHO points to intergenerational contact interventions as one of the three recommended initiatives against ageism (WHO, 2021). Such cross-age interactions might be complicated by the predominantly age-divided social structure of the Western societies, wherein almost no age-diverse relations occur outside the family context. In previous literature, it is argued that such a social separation between diverse age groups increases age stereotyping and ageism between generations (Hagestad & Uhlenberg, 2005, 2006).

Regarding the work context more specifically, an emerging body of evidence points to intergenerational dynamics within the organization as an important factor for decreasing ageism in the workplace (Iweins et al., 2013; Lagacé et al., 2019; Posthuma & Campion, 2009). This can be understood in the light of the Intergroup Contact Theory, which states that establishing high-quality intergroup interactions is an effective way to reduce intergroup prejudice (Allport, 1979; Pettigrew & Tropp, 2010). In this view, the workplace can potentially serve as an arena that provides the time and frame for establishing interactions across age groups that lead to reduced ageism in general and more specifically towards older workers. Supporting this, a study found that intergenerational contact between age groups in the workplace contributed to positive changes in how younger workers perceive their older colleagues (Iweins et al., 2013). Another study showed that older workers’ perceptions of their workplace climate as age-inclusive reduced their feelings of being subjected to ageist attitudes in the workplace (Lagacé et al., 2019). Previous research thus suggests that a more positive intergenerational workplace climate can reduce ageism in the workplace. In this present study, a positive intergenerational workplace climate is defined as an environment with a high level of age-based inclusiveness, cross-age contacts and intergenerational retention as well as a lack of generational stereotypes (King & Bryant, 2017).

We expect intergenerational workplace climate to be relevant for self-perceived aging as well. Self-perceived aging refers to an individual’s beliefs about one’s own aging (Levy & Banaji, 2002) and can be understood through the lens of Stereotype Embodiment Theory (Levy, 2009). This theory departs from a psychosocial perspective on aging by conceptualizing the aging process as not only defined by physiological processes, but also by cultural views of aging. Specifically, Stereotype Embodiment Theory contends that, by observing the age stereotypes about older people embedded in the culture (e.g., resistance to change, having lower ability to learn, and being less motivated and productive than younger people) (Posthuma & Campion, 2009) and the way older adults are treated, individuals internalize such stereotypes and behaviors across the life span, often unconsciously. In turn, such internalized stereotypes contribute to the shaping of individual self-perceptions of aging and the aging process, leading to self-directed ageism (when applying the internalized stereotypes to oneself). This affects not just older individuals, but individuals across age groups. Such an internalization has shown to have a wide range of negative consequences for the individual in terms of behavior and physical and mental health. For example, longitudinal studies suggest that younger individuals (aged 18–49 years) who hold negative age stereotypes are significantly more likely to experience cardiovascular disease in later life (Levy et al., 2009) and that individuals with more positive self-perceptions of aging increased longevity up to 7.5 years compared to those with less positive self-perceptions of aging (Levy et al., 2002b). In this perspective, self-perceived aging and self-directed ageism are important factors across all age groups, including the younger segments of the working population, and need to be taken into consideration when seeking to prevent the negative consequences of ageism directed towards old age. Therefore, ageism towards old age is not only prevalent and relevant in the older age groups but in the younger as well, as a factor influencing both the current and the future perception of aging. Based on this, in this study, we will explore the association between intergenerational workplace climate, self-perceived aging and workplace attitudes across a broad age span.

Despite the plethora of adverse consequences that negative self-perceived aging and self-directed ageism may have at different levels, little is still known about the determinants of self-directed ageism (WHO, 2021). Therefore, in the present study, we contribute bridging this gap by examining the relationship between intergenerational workplace climate and self-perceived aging. To our knowledge, no previous studies have hitherto been carried out examining such relationships.

In addition to self-perceived aging, previous research suggested that intergenerational workplace climate is related to workers’ attitudes towards their job, including work engagement, motivation, orientation towards further development and intention to leave the workplace (Weber et al., 2019). In the present study, we focus specifically on work engagement and intention to leave. Previous research suggested that a healthy intergenerational workplace climate is directly linked to work engagement among older workers (Rožman et al., 2020). In addition, earlier studies showed that more positive perceptions of organizational age climate (defined as the employees’ shared perception of age stereotypes in an organization) are associated with lower levels of intention to leave and higher levels of job satisfaction in both younger and older employees, even after controlling for an organization’s general social climate (Bilinska et al., 2016). Leaving a workplace often has several deleterious consequences for the organization, especially so when skilled employees quit. Indeed, hiring and training new employees are costly and the loss of skilled workers might jeopardize working processes and task solving in organizations (Bothma, 2011). Based on previous evidence, we thus expect a more positive intergenerational workplace climate to be associated with more work engagement and less turnover intention.

When investigating the effect of intergenerational contact, previous studies have often been based on non-representative samples comprising either younger or older participants (Bilinska et al., 2016; Iweins et al., 2013; Rožman et al., 2020). On the contrary, in the present study, we relied on a sample that was representative of the Danish working population also in terms of age groups (18–74 years), which enabled us to additionally explore whether the examined associations were age dependent.

In sum, in the present study, we aimed to examine the following hypotheses:

H1: A more positive intergenerational workplace climate is associated with a better self-perceived aging.

H2: A more positive intergenerational workplace climate is associated with higher levels of work engagement.

H3: A more positive intergenerational workplace climate is associated with lower levels of intention to leave the workplace.

Design and Methods

The present study relies on data from a large sample of the Danish working population (18–74 years), representative in terms of age, gender, Danish geographical regions, and type of sector (public/private). The data collection took place in July 2022 and was performed by a professional evaluation and research company via an online survey portal. All participants were recruited by the company and provided informed, written consent prior to participation.

The main sociodemographic characteristics of the participants are shown in Table 1. The final sample included 1571 participants (49% women, 51% men) with an average age of 51.0 years (Standard Deviation, SD = 14.2). The sample size was satisfactory in all age groups (18–39 years, n = 424; 40–54 years, n = 410; 55–64 years, n = 375; 6574 years, n = 362). When it comes to education, participants were distributed as follows: Elementary school or high school (12%), vocational education (27%), short-term higher education (10%), medium-term higher education (21%), and longer-term higher education (29%). Among the participants, 35% were employed in the public sector and 65% in the private sector. The distribution of occupational sectors was as follows: Building and construction (6%), wholesale and retail trade (8%), industry and manufacturing (13%), office and communication (10%), agriculture and food production (2%), social work and human health (16%), transportation (4%), education and research (8%), hotel, restaurant and tourism (3%), finance and insurance (4%), public service and administration (7%), private service (4%), other (14%). Most participants (81%) did not have leadership responsibilities. Finally, all five Danish regions were represented (10–32% of the samples came from each region).

Table 1.

Participant Characteristics.

	18–39 years (n = 424)	40–54 years (n = 410)	55–64 years (n = 375)	65–74 years (n = 362)	Total (N = 1571)^a
	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)
Age	31.4 (5.3)	48.6 (4.2)	59.5 (2.7)	67.7 (2.6)	51.0 (14.2)
	%	%	%	%	%
Gender
Men	49.3	51.7	49.6	53.9	51.1
Women	50.7	48.3	50.4	46.1	48.9
Education
Elementary/high school	17.2	10.7	9.6	10.8	12.2
Vocational	17.0	32.9	33.1	26.5	27.2
Short-term higher	7.1	12.0	13.9	8.6	10.3
Medium-term higher	17.2	18.8	22.7	26.2	21.0
Long-term higher	41.5	25.6	20.8	27.9	29.3
Leadership
Not leader	83.3	81.0	82.4	77.1	81.1
Leader	16.7	18.8	17.6	22.9	18.9
Sector
Public sector	32.3	37.3	44.0	27.3	35.3
Private sector	67.7	62.7	56.0	72.7	64.7
Occupation
Building/construction	6	6	5	6	6
Wholesale/retail trade	12	6	8	7	8
Industry/manufacturing	11	12	20	10	13
Office/communication	13	12	9	9	10
Agriculture/food production	2	1	1	2	2
Social work/human health	13	15	14	21	16
Transportation	4	7	3	4	4
Education/research	5	8	9	9	8
Hotel/restaurant/tourism	5	3	4	3	3
Finance/insurance	6	5	4	2	4
Public service/administration	6	8	8	5	7
Private service	3	3	4	7	4
Other	15	13	10	16	14
	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)
WICS
LGS	2.7 (0.5)	2.9 (0.5)	2.9 (0.5)	2.9 (0.5)	2.8 (0.5)
PIA	3.2 (0.5)	3.3 (0.4)	3.2 (0.5)	3.2 (0.5)	3.2 (0.5)
WGI	3.2 (0.5)	3.3 (0.5)	3.3 (0.5)	3.3 (0.4)	3.3 (0.5)
WIR	3.3 (0.6)	3.4 (0.5)	3.3 (0.5)	3.3 (0.5)	3.3 (0.5)
IC	2.9 (0.7)	3.0 (0.6)	2.9 (0.7)	2.8 (0.7)	2.9 (0.7)
Total score	15.2 (1.9)	15.8 (1.9)	15.6 (1.9)	15.5 (1.9)	15.5 (1.9)
B-APQ
TL-CHR	2.5 (0.7)	2.7 (0.7)	2.8 (0.6)	2.9 (0.7)	2.7 (0.7)
CONS-POS	3.9 (0.6)	3.9 (0.5)	3.9 (0.5)	3.8 (0.5)	3.9 (0.5)
EMO-REP	2.6 (0.8)	2.5 (0.8)	2.5 (0.7)	2.5 (0.6)	2.5 (0.7)
CONSCON-NEG	2.7 (0.6)	2.8 (0.6)	2.8 (0.5)	2.8 (0.5)	2.8 (0.5)
CONTR-POS	3.9 (0.6)	4.0 (0.6)	4.0 (0.6)	4.1 (0.6)	4.0 (0.6)
UWES	5.1 (1.1)	5.2 (1.0)	5.5 (0.9)	5.6 (0.9)	5.3 (1.0)
TIS	16.1 (4.9)	15.5 (5.6)	13.7 (4.9)	11.8 (4.1)	14.3 (5.2)

^a. Age, Gender, Education, and Sector: n = 1571; Leadership: n = 1570. WICS: n = 1559. B-APQ: n = 1551. UWES: n = 1550. TIS: n = 1556. M = Mean. SD = Standard Deviation. Missing data: Leadership = 1. WICS = 9. B-APQ = 20. UWES = 21. TIS = 15.

B-APQ = Brief Ageing Perceptions Questionnaire: CONTR-POS = Control-positive. CONS-POS = Consequences-positive. CONSCON-NEG = Consequences and control-negative. EMO-REP = Emotional representations. TL-CHR = Timeline-chronic. UWES = Utrecht Work Engagement Scale. WICS = Workplace Intergenerational Climate Scale. TIS = Turnover Intension Scale.

Measures

Intergenerational Workplace Climate (WICS)

The Workplace Intergenerational Climate Scale (King & Bryant, 2017) is a self-report instrument measuring age-based attitudes in the workplace rooted in the affective-behavioral-cognitive model for the construction of attitudes. Hence, the intergenerational workplace climate is measured in terms of attitudes, stereotypes and behaviors based on age. As opposed to many other scales measuring only perceptions of older adults (e.g., Attitude Towards Older Workers Scale, Gringart et al., 2013), the WICS measures attitudes and perceptions about workers of all ages in an intra-organizational perspective.

WICS is comprised of 20 items divided in the following five subscales, each consisting of four items: Lack of Generational Stereotypes (LGS; e.g., “Co-workers outside my generation usually talk about things that don’t interest me”); Positive Intergenerational Affect (PIA; e. g, “I enjoy interacting with co-workers of different generations”); Workplace Generational Inclusiveness (WGI; e.g., “I am able to communicate effectively with workers of different generations”); Workplace Intergenerational Retention (WIR; e.g., “I feel pressure from younger workers to step down”); Intergenerational Contact (IC; e.g., “How often do you talk with co-workers outside your generation about your personal lives?”). Each item is rated using a Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree), except for the IC subscale that ranges from 1 (never) to 4 (very often). For each subscale, we calculated the mean of the component items (note that some of the items are reversed before calculation), with higher scores indicating more positive ratings thereof. The total WICS score is obtained as the sum of the subscale means and ranged from 5 to 20, with higher scores indicating a more favorable intergenerational workplace climate. In the present study, the WICS showed a satisfactory internal consistency, with a Cronbach’s alpha (α) of .88.

The present study includes participants from a variety of sectors and workplace sizes, being these factors known to potentially influence age diversity in the workplace (Jensen et al., 2020). Furthermore, previous studies have found high levels of age homogeneity in non-kin friendship networks and that relationships outside the family occur often with people of similar age (Burt, 1991; Hagestad & Uhlenberg, 2005; Marsden, 1988). To improve clarity and ensure relevance for all participants, we decided to add a text ahead of the WICS items clarifying the meaning of generation in the present context: “In these questions, generation should be understood as colleagues/employees of your own age +/− approx. 5 years. I.e. if you are 35 years old your generation would be approx. 30–40 years.” This was approved by the corresponding author of the WICS (personal communication).

Self-Perceived Aging (B-APQ)

We used the self-report Brief Ageing Perceptions Questionnaire (Sexton et al., 2014), which is an abbreviated version of the Ageing Perceptions Questionnaire (Barker et al., 2007). The B-APQ consists of 17 items forming five subscales: Timeline-chronic/TL-CHR (e.g., “I feel my age in everything that I do”); Consequences-Positive/CONS-POS (e.g., “As I get older I get wiser”); Control-Positive/CONTR-POS (e.g., “Whether I continue living life to the full depends on me”); Consequences and Control Negative/CONSCON-NEG (e.g., “Getting older makes me less independent”); Emotional Representation/EMO-REP (e.g., “I feel angry when I think about getting older”). Each item is rated on a Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). We calculated a mean score for each subscale, since using an overall scale is not recommended (personal communication with the corresponding author, 2022).

B-APQ is especially suitable for assessing self-directed aging stereotypes (Burton et al., 2021). The subscales showed close to satisfactory internal consistencies, which were deemed acceptable given that each subscale contains only 3 to 5 items (EMO-REP: α = .69; CONTR-POS: α = .74; CONS-POS: .64; CONSCON-NEG: .58; TL-CHR: α = .62; overall α = .67). A series of exploratory tests showed that the mean item-total correlations for each of the five subscales were satisfactory, with rs ranging from .35 to .57.

Work engagement (UWES-9)

We used the validated 9-item version of the original 17-item Utrecht Work Engagement Scale (Schaufeli et al., 2006). UWES-9 measures work engagement as a combination of positive work-related fulfillment characterized by the three factors of vigor, dedication, and absorption. All items (e.g., “At my work, I feel bursting with energy”) are rated on a Likert scale ranging from 0 (never) to 6 (always). The scale score was calculated as the mean of the individual item scores. The Cronbach’s α for UWES-9 was .94.

Turnover Intention (TIS-6)

Turnover intention was measured with the 6-item version of the Turnover Intention Scale (TIS-6), validated by Bothma and Roodt (2013). TIS-6 is a shortened version of the original 15-item scale developed by Roodt (2004) and has proven as a reliable and valid tool for assessing turnover intention and predict actual turnover (Bothma & Roodt, 2013). An illustrative item is: “How often have you considered leaving your job?” All items are rated on a Likert scale ranging from 1 (never) to 6 (always). The total score is calculated as a sum of the individual items, with scale scores ranging from 6 to 30 and higher scores indicating a higher turnover intention. The Cronbach’s α for TIS-6 was .81.

Background Variables

These include self-reported age (specific age between 18–74 years), gender (woman, man), education (low, high), sector (public, private), occupational sector (13 types), leadership role (leader, not leader), and geographical region (the five Danish regions).

Data Analyses

We first conducted a series of zero-order, parametric correlations between background variables (age, gender, education, sector, leadership status) and scores on WICS, B-APQ, UWES-9, and TIS-6. We then conducted a two-step hierarchical regression analysis for each outcome (i.e., B-APQ-subscales, UWES-9, and TIS-6). In Step 1, we entered age (in years), gender, and education as covariates since they were significantly related to all scales (uncorrected zero-order correlations p < .5). Note that, for this analysis, we collapsed education into fewer groups, that is elementary school, high school, vocational, and short-term higher education (50% of the sample) and medium- or long-term higher education (50%). In Step 1, we also entered leadership status and sector when the correlations indicated them as potentially relevant confounders (p < .1). In Step 2, we then entered WICS as independent variable to examine if intergenerational workplace climate was associated with the dependent variables over and above the confounders. To explore age-related differences in the examined relationships, we performed the same hierarchical regression analyses within each age group separately (18–39 years; 40–54 years; 55–64 years; 65–74 years). To exclude a potential effect of outliers on the regression models, we excluded 43 participants scoring >3 SD from the mean on any of the WICS, B-APQ, UWES, and TIS scales, applying common outlier detection criteria (Zimek & Filzmoser, 2018).

We considered p-values <.05 (two-tailed) as statistically significant and used Bonferroni–Holm-correction to correct for multiple tests. Regression coefficients are reported both as unstandardized beta values (B) and standardized beta values (β), while the explained variance for each step of the regression models is shown as both unadjusted and adjusted R-squared (R², R²_adj). All statistical analyses were performed by means of SPSS (IBM; version 28.0.0.0).

Results

As Table 2 shows, the intergenerational workplace climate (WICS) scores were significantly related to all self-perceived aging (B-APQ) subscales (ps <.001). Specifically, higher WICS-scores were related to lower levels of emotional response (EMO-REP: r = −.34), timeline-chronic (TL-CHR: r = −.22), and consequences and control-negative (CONSCON-NEG: r = –.29). Conversely, higher WICS-scores were related to higher levels of B-APQ-consequences-positive (CONS-POS: r = .23) and higher levels of control-positive (CONTR-POS: r = .31).

Table 2.

Correlations between Intergenerational Working Climate Scores, Age Perception Scores and Work-Related Scores in a Large, Danish Sample Across the Public and Private Sector.

	N	Pearson r	p	95% Confidence Interval
	N	Pearson r	p	Lower	Upper
WICS - TL_CHR	1555	−.215	<.0001	−.262	−.167
WICS - EMO_REP	1551	−.338	<.0001	−.382	−.293
WICS - CONSCON_NEG	1551	−.292	<.0001	−.337	−.246
WICS - CONS_POS	1555	.230	<.0001	.182	.276
WICS - CONTR_POS	1551	.309	<.0001	.263	.353
WICS - TIS	1556	−.326	<.0001	−.370	−.281
WICS - UWES	1550	.382	<.0001	.339	.424

Notes. p-values were two-tailed and Bonferroni–Holm-corrected. B-APQ = Brief Ageing Perceptions Questionnaire: CONTR-POS = Control-positive. CONS-POS = Consequences-positive. CONSCON-NEG = Consequences and control-negative. EMO-REP = Emotional representations. TL-CHR = Timeline-chronic. UWES = Utrecht Work Engagement Scale. WICS = Workplace Intergenerational Climate Scale. TIS = Turnover Intension Scale.

As shown in Table 3, the hierarchical regression models indicated that WICS was significantly related to all B-APQ-subscales (consequences and control-negative: β = −.279; Emotional representations: β = −.340; Timeline-chronic: β = −.217; Control-positive: β = .304; Consequences-positive: β = .231; all ps <.001) even after controlling for age, gender, education, leadership status and occupational sector (all ps < 0.001). WICS contributed to the explained variance to a larger extent than the confounders, as shown by the R²-values. Similarly, higher scores on WICS were related to higher levels of work engagement (UWES: β = .369) and to lower levels of intention to leave (TIS: β = −.32; both ps < .001). In sum, the present findings lent support to all three hypotheses (H1, H2, and H3).

Table 3.

Intergenerational Workplace Climate as Predictor of Self-Perceived Aging and Work Outcomes.

	Model 1				Model 2
	B (SE)	β	ΔR ²	ΔF	B (SE)	β	ΔR ²	ΔF
B-APQ (CONT-POS)
Gender	0.041 (0.030)	.035			0.004 (0.029)	.003
Age	0.003 (0.001)**	.067			0.002 (0.001)	.042
Education	0.098 (0.033)**	.078			0.062 (0.031)*	.049
Sector	0.071 (0.031)*	.058			0.080 (0.030)**	.065
			.012	4.793***
WISC					0.09 (0.008)***	.304
							.090	155.029***
B-APQ (CONS-POS)
Gender	−0.110 (0.027)***	−.078			−0.084 (0.027)**	−.078
Age	−0.003 (0.001)***	−.084			−0.004 (0.001)***	−.103
Education	−0.015 (0.030)	−.013			−0.042 (0.029)	−.036
			.018	9.628***
WISC					0.066 (0.007)***	.231
							.052	86.915***
B-APQ (CONSCON-NEG)
Gender	−0.104 (0.027)***	−.095			−0.072 (0.026)**	−.066
Age	0.001 (0.001)	.037			0.002 (0.001)*	.060
Education	−0.150 (0.030)***	−.129			−0.129 (0.028)***	−.111
			.031	16.478***
WISC					−0.080 (0.007)***	−.279
							.076	131.313***
B-APQ (EMO-REP)
Gender	−0.024 (0.038)	−.017			0.028 (0.036)	.019
Age	−0.002 (0.001)	−.039			−0.001 (0.001)	−.011
Education	−0.045 (0.041)	−.029			−0.008 (0.039)	.005
			.002	1.167
WISC					−0.132 (−0.009)***	−.340
							.113	196.774***
B-APQ (TL-CHR)
Gender	−0.176 (0.034)***	−.128			−0.145 (0.033)***	−.105
Age	0.010 (0.001)***	.217			0.011 (0.001)***	.235
Education	−0.040 (0.037)	−.027			−0.009 (0.036)	−.006
			.070	39.103
WISC					−0.079 (0.009)***	−.217
							.046	80.742***
UWES
Gender	0.258 (0.050)***	.127			0.182 (0.047)***	.089
Age	0.016 (0.002)***	.222			0.014 (0.002)***	.191
Education	−0.050 (0.054)	−.023			−0.130 (0.051)**	−.060
Leadership	−0.241 (0.064)***	−.093			−0.259 (0.059)***	−.100
			.071	29.447***
WISC					0.198 (0.012)***	.369
							.133	256.838***
TIS
Gender	−0.558 (0.250)*	−.054			−0.219 (0.237)	−.021
Age	−0.112 (0.009)***	−.308			−0.102 (0.008)***	−.282
Education	0.675 (0.270)**	.061			1.020 (0.257)***	.092
			.104	60.269***
WISC					−0.863 (0.063)***	−.316
							.097	188.544***

Notes. N = 1549–1555. B-APQ = Brief Ageing Perceptions Questionnaire: CONTR-POS = Control-positive. CONS-POS = Consequences-positive. CONSCON-NEG = Consequences and control-negative. EMO-REP = Emotional representations. TL-CHR = Timeline-chronic. UWES = Utrecht Work Engagement Scale. WICS = Workplace Intergenerational Climate Scale. TIS = Turnover Intension Scale.

*.p < .05.**.p < .01.***.p < .001 (two-tailed, Bonferroni–Holm-corrected).

Further exploratory analyses (Supplementary Table 1) indicated that WICS-scores were significantly related to the three dependent variables considered within all four age groups. The standardized regression coefficients were similar across age groups when it comes to UWES (β = .352–.420), TIS (β = .341–.384), and B-APQ-emotional representations (β = .295–.371), all at ps<.001. WICS was also significantly related to B-APQ-Control-positive (β = .248–.347) and B-APQ-Consequences and control-negative (β = .187–.340) in all age groups, all at ps<.001, although the sizes of the coefficients were more varied. For B-APQ-Consequences-positive, we obtained weaker regression coefficients with increasing age (β = .128–.286). For B-APQ-Timeline-chronic, the coefficients were similar in the three younger groups (β = −.236−.312, ps<.001), while the association was not significant in the older age group (β = −.053, p > .3). Thus, the exploratory analyses indicated that WICS was related to all dependent variables in nearly all age groups, with more variation in terms of the strength of the associations for B-APQ than for UWES and TIS.

Discussion

In this study, we set out to examine the association between intergenerational workplace climate and self-perceived aging, work engagement and intention to leave the workplace in a representative sample of the Danish working population. We also explored if such associations differ according to age. Our findings supported the study hypotheses, by indicating that a positive intergenerational workplace climate was associated with better self-perceived aging (H1), higher work engagement (H2), and lower levels of turnover intention (H3). In addition, our findings suggest that these associations are similar for workers of all ages.

A closer inspection of the findings about the self-perceived aging subscales reveals that a better intergenerational workplace climate was related to more positive attitudes towards the positive impact of aging (consequences-positive subscale), with indications of decreasing effect sizes among the older groups. A more positive intergenerational workplace climate was also related to more positive feelings of control over the positive experiences of aging (control-positive subscale) in all age groups. These two facets of self-perceived aging have both been linked to higher subjective well-being (Barker et al., 2007; Lang & Heckhausen, 2001; Steverink et al., 2001).

A better intergenerational workplace climate was also associated with less negative emotional reactions to aging (emotional representation subscale) and more control of the negative experience of aging and of one’s own negative attitudes towards the consequences of aging (consequences and control-negative subscale). The perception of negative aging consequences has previously been linked to lower subjective well-being and depression (Gattuso, 2003), while negative emotional responses to aging has been found in association with negative changes in physical and functional health (Smith & Freund, 2002) and to unhealthy coping strategies (Gomez & Madey, 2001).

The findings also showed that a more positive intergenerational workplace climate was associated with a less constant awareness of one’s own aging (timeline-chronic subscale), except for the oldest age group (64–74 years). A chronic awareness of one’s own aging is closely connected to the concept of age identification (i.e., the extent to which people identify with an age category) (Barak & Stern, 1986). A possible explanation for this finding could be related to the increasing awareness of one’s own age that typically occurs when one gets older, which may not be compensated by a positive intergenerational workplace climate. Another explanation might be that many individuals belonging to the older age group might have stopped working full time, with cross-age relationships having lost significance for them as a result.

In light of the aforementioned severe consequences of negative self-perceived aging on both physical and mental health (Levy, 2002; Levy et al., 2009; Marchiondo et al., 2019; Weber et al., 2019) and the limited knowledge of the factors impacting self-directed ageism, the present findings provide an important contribution to the understanding of this form of ageism not only among older workers, but among workers of all ages. Previous studies proved the adverse consequences of negative self-perceived aging in younger people on their late-life health (Levy et al., 2009; Levy et al., 2002a), thus pointing to the importance of early interventions to prevent later detrimental effects of negative self-perceived aging. Improving a workplace’s intergenerational climate can be regarded as a useful intervention tool for supporting the health and well-being of employees of all ages and reduce the adverse consequences of ageism.

The finding that a more positive intergenerational workplace climate is linked to more work engagement and less intention to leave is in line with previous studies among younger and older workers (Bilinska et al., 2016; Iweins et al., 2013; Rožman et al., 2020). Given that an increased focus on intergenerational policies has been suggested as a possible solution to the so-called labor and welfare crisis resulting from the increasing longevity in Europe (Barabaschi, 2015), our findings confirm the potential benefits that initiatives aimed at strengthening the intergenerational climate in workplaces may have for all age groups.

Limitations and Suggestions for Future Research

The cross-sectional nature of our study prevents us from drawing causal conclusions about the examined relationships. For instance, the lack of temporal separation between measurement points does not enable us to rule out reverse causation, that is, the possibility that those participants with more positive self-perceptions of aging appraise the intergenerational climate more positively, which might at least partially explain the observed associations. Future research employing a longitudinal design is thus needed to prove intergenerational workplace climate as a predictor of self-perceived aging, work engagement and turnover intention.

An alternative interpretation of our findings, which we could not examine empirically, is that intergenerational climate is the result of an overall positive workplace climate; owing to this, one might conclude that the associations between intergenerational workplace climate and self-perceived aging, work engagement and turnover intention are in fact due, at least partially, to the role of said overall workplace climate. Yet, previous research found that a positive organizational age climate increases the job satisfaction of older workers and their motivation to stay in the organization, over and above the impact of overall social climate in the organization (Bilinska et al., 2016). Future studies should rely on a broader perspective of the psychosocial work environment to isolate the unique impact of intergenerational workplace climate on core individual and organizational outcomes.

Future studies may also advance the field by looking into cultural attitudes towards aging and definitions of the term “generation” when studying the impact of the intergenerational workplace climate. In this study, we have defined generation in a way that is relevant to the Danish workplace context, but this might differ from the understanding in other cultural contexts. In Europe, an increasing number of people continue to work after the official retirement age (Lassen & Vrangbæk, 2021) resulting in a broader age span within the overall workforce. Still, the degree of age diversity in organizations varies and factors like, for example, the size of the organization can influence the number of older employees (Jensen et al., 2020) leaving certain workplaces with a more narrow age span within the group of employees. Hence, future studies might benefit from applying an understanding to the term “generation” as cross-aged relations (relations between age groups) as opposed to focusing on the more traditional understanding of generations when examining the effects of the intergenerational workplace climate. Applying this view, every workplace could be a potential incubator for cross-aged relationships.

Further research should also invest in the design, implementation and evaluation of interventions aimed to improve the intergenerational workplace climate and its positive impact on self-perceived aging and work attitudes.

Conclusion

To the best of our knowledge, this study is the first to examine associations between intergenerational workplace climate and self-perceived aging. We were able to support our hypothesis of a significant association of intergenerational workplace climate and self-perceived aging. In addition, we were able to confirm previous research finding associations between intergenerational workplace climate and core attitudinal outcomes such as work enjoyment and intention to leave. These findings justify future studies aimed at confirming these relationships using stronger research designs.

Supplemental Material

Supplemental Material - Is a Positive Intergenerational Workplace Climate Associated with Better Self-Perceived Aging and Workplace Outcomes? A Cross-Sectional Study of a Representative Sample of the Danish Working Population

Supplemental Material for Is a Positive Intergenerational Workplace Climate Associated with Better Self-Perceived Aging and Workplace Outcomes? A Cross-Sectional Study of a Representative Sample of the Danish Working Population by Anette Tybjerg-Jeppesen, Paul Maurice Conway, Yun Ladegaard and Christian Gaden Jensen in Journal of Applied Gerontology

Footnotes

Authors’ Contributions

Anette Tybjerg-Jeppesen drafted the conceptual ideas, the design of the study and the manuscript and was responsible for the data collection. Anette Tybjerg-Jeppesen participated in the interpretation of the findings. Paul Maurice Conway participated in the design of the statistical analyses, the interpretation of the findings and reviewed the manuscript. Yun Ladegaard participated in the design of the study, the interpretation of the findings and reviewed the manuscript. Christian Gaden Jensen participated in the design of the statistical analyses, participated in the statistical analyses and the interpretation of the findings.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Nordea-Fonden, Denmark (grant number 02-2017-1749).

Author’s Note

The data collection was conducted by Epinion A/S, Ryesgade 3F, 2200 København N

Ethical Approval

The Faculty Secretariat at the Faculty of Social Sciences at Copenhagen University approved the study (j. nr. 514-0250-22-2000).

Informed Consent

All participants submitted informed, written consent prior to participating.

ORCID iDs

Anette Tybjerg-Jeppesen

Paul Maurice Conway

Yun Ladegaard

Christian Gaden Jensen

Supplemental Material

Supplemental material for this article is available online.

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