Introduction

Active ageing is currently a key policy goal in European countries, with their ageing populations (Foster & Walker, 2015). It refers to any socially valued – paid or unpaid – activity engaged in by older adults that produces goods or services (Bass & Caro, 2001; Burr et al., 2007). Although active ageing is often closely associated with participation in the labor market (e.g., van der Horst et al., 2017), the present study focuses on unpaid prosocial activities undertaken by older adults. We consider individuals who are engaged in providing several types of support across public and private domains, that is, ‘multi-helpers’; explore how common it is to engage in multiple help-giving activities; and identify the factors that predict being a multi-helper.

Public support includes volunteering and charitable giving. Volunteering is an unpaid activity directed toward parties with whom the provider does not have a personal relationship (i.e., support is targeted to strangers), while charitable giving refers to prosocial spending (i.e., donating money for the benefit of others with whom the donor does not have a personal relationship) (Musick & Wilson, 2008). Private support involves providing help to people with whom a helper has a personal relationship (i.e., relatives and friends). Financial support refers to giving money and/or gifts and/or covering costs, while instrumental support involves providing tangible or physical assistance with different tasks (i.e., practical help, personal care).

Who provides informal help?

As the provision of support requires resources, help-giving is always related to the resources of the potential helper in question. Studies have emphasised opportunity structures in examining the intergenerational exchange of support (e.g., Szydlik, 2016; Tanskanen & Danielsbacka, 2019). However, the preconditions for adequate resources and opportunities apply to other relations as well. For instance, to provide instrumental support or volunteer, one must have adequate time and physical resources. Providing informal financial aid or donating money to charity requires financial resources. Providing support also requires opportunities to actually share the resources, that is, having social contacts to whom one can offer help. From this perspective, the better the resources and the greater the opportunities available, the larger the number of activities potential helpers can engage in and vice versa. Opportunities (or the lack thereof) can be related to social expectations (Szydlik, 2016). For instance, gendered helping patterns can be reflected in opportunities, in that women are more likely to provide personal care, whereas men tend to provide more financial and practical help (e.g., Albertini et al., 2007; Heberkern et al., 2015; Kahn et al., 2011; Szydlik, 2016). Communities or peer-groups may affect helping behavior and encourage multiple engagements; religious communities, for instance, emphasise the importance of volunteering and charitable giving, thus offering religious individuals more opportunities to engage in such activities (Son & Wilson, 2012). Different environments can also provide different opportunities for helping (Amato, 1993; Paarlberg et al., 2021; Zwirner & Raihani, 2020); for instance, it has been found that individuals participate in help-giving activities, such as volunteering, more in rural than in urban areas (e.g., Balish et al., 2018; Paarlberg et al., 2021).

One type of prosocial engagement may promote other such activities. The role extension approach suggests that participation in different activities can complement each other and lead to greater overall productive engagement (Hank & Stuck, 2008). Engagement in one activity provides opportunities to participate in other productive tasks in part because people who engage in some prosocial activities are more likely to interact with others who participate in such activities, who may introduce them to new opportunities to support others (Burr et al., 2005; Choi et al., 2007). For example, individuals supporting family members outside their households are typically part of formal and informal social networks that may promote prosocial behavior, such as volunteering or charitable giving (Jacobs et al., 2016). As a result of the digital revolution, individuals can also multitask easily, and nowadays, it is possible, for example, to give money to a friend online while helping an older parent with household tasks offline. Thus, in particular when different forms of prosocial engagement are not too demanding, they may promote and complement each other.

Life course transitions may be reflected in the opportunity structure of help-giving; besides extending certain roles, individuals may seek to compensate for the loss of previous roles by engaging in new activities (Hank & Stuck, 2008; see also Atchley, 1971, 1989). Employment plays a key, determining role in Western lives and societies. Adults spend a great deal of their time on work or work-related tasks. Thus, retirement usually increases the amount of spare time they have, and may encourage older individuals to adopt compensatory productive roles in other fields of life. For example, the loss of the role of employee in the labor market following retirement may lead to increased frequency of volunteering (Eibich et al., 2022; Tanskanen et al., 2021a) and provision of intergenerational help (Tanskanen et al., 2021b). Moreover, spousal loss may also increase individuals’ social participation outside their own household, such as volunteering and interaction with friends and family (Bolano & Arpino, 2020; Lim-Soh, 2022).

What do we know about multi-helpers?

Empirical studies have shown that people tend to engage in more than one type of prosocial activity at a time. For example, the provision of informal practical help and/or care is positively associated with participation in voluntary work (e.g., Burr et al., 2005; Jegermalm & Grassman, 2013; Strauss, 2021), suggesting that providing one type of support increases the likelihood of providing another kind as well. A study of older Finns found that practical help and personal care channelled outside one’s household were associated with increased probability of volunteering, but not with likelihood of making charitable donations (Tanskanen et al., 2022).

Only a few studies have focused on individuals engaged in multiple types of help-giving toward different parties. Hank and Stuck (2008) investigated associations between volunteer work, informal help-giving, and caregiving among Europeans aged 50 years and older and found that all these activities complemented each other. Participation in all three types of activities varied across countries, although higher proportions of active older people were found in Northern Europe, whereas Southern Europe was characterised by lower rates of help-giving activity (Hank & Stuck, 2008).

Burr et al. (2007) investigated the structure of productive activities among middle-aged and older Americans. They analysed five activities (volunteering, domestic work, paid work, providing informal help to others, and caregiving) and detected four distinct clusters of commitments to productive activities, referring to these groups as home maintainers, workers/volunteers, helpers, and super-helpers. About 4% of the study population were identified as highly active helpers, labelled ‘super-helpers’, who were likely to engage in multiple types of prosocial activities. They were characterised by a low probability of engagement in paid work and a high or moderate likelihood of participating in informal help, caregiving, volunteering, and/or home-maintenance. The study examined individual characteristics by comparing super-helpers to home maintainers, and found that higher age and higher income were respectively negatively and positively associated with being a super-helper. The results did not show significant associations pertaining to the respondents’ gender, marital status, level of education, or functional status.

Overall, studies have shown that a large number of older adults are involved in several types of prosocial activities; however, individual studies have often considered only two types of help-giving, such as provision of personal care and volunteering, or instrumental support and volunteering (e.g., Strauss, 2021; Jegermalm & Jeppsson Grassman, 2009). In addition, research on engagement in multiple help-giving activities (i.e., on multi-helpers) has not considered prosocial spending (i.e., informal financial aid and charitable giving) as part of productive activity. Although studies have examined various explanatory factors pertaining to the provision of particular types of support, and have shown that help-giving is related to many individual characteristics and resources (e.g., Bertogg & Koos, 2021; van den Bogaard et al., 2014; Brandt & Deindl, 2013; Hank & Erlinghagen, 2010; Henretta et al., 2014; Musick & Wilson, 2008; Niebuur et al., 2018; Paarlberg et al., 2021; Szydlik, 2016; Tanskanen et al., 2022; Wiepking & Bekkers, 2012), investigations of characteristics of individuals engaged in multiple help-giving activities are scarce, and the few studies available have only considered a relatively limited number of possible explanatory factors at a time.

Research questions

We focused on older adults who provided unpaid support toward different parties in both public and private domains and investigated the provision of instrumental help and financial aid to friends and relatives as well as volunteering and charitable giving. We began by exploring the overall structure of help-giving among older Finns, that is, how the provisions of different types of support overlap. Respondents who provided both forms of support in public and private domains (i.e., all four types of help) were considered multi-helpers. To capture this research topic, we asked the following question (Q):

  • Q1: What proportion of the study population are multi-helpers?

After forming a picture of the prevalence of multi-helpers, we investigated the characteristics that predicted engagement in multiple types of help-giving. Based on extant research, we assumed that the tendency to engage in multiple prosocial activities could be associated with factors related to resources, opportunities, and social contexts. Thus, we considered a wide variety of possible explanatory variables and asked the following question:

  • Q2: What are the characteristics of multi-helpers?

Materials and methods

Sample

This study utilised population-based survey data from the Generational Transmissions in Finland (Gentrans) project, which gathered information on older Finnish adults born between 1945 and 1950. We used data from the second wave of data collection, as that survey included more questions that pertained to our examination (e.g., wider range of background variables and more specific information on the provision of informal support) when compared to the other rounds of data collection (waves 1 and 3) (see Danielsbacka et al., 2013; Haavio-Mannila et al., 2009; Hämäläinen et al., 2021). The survey data were collected by Statistics Finland in 2012 and included 2,278 participants, with a response rate of 65%. The present study’s sample comprised 2,174 older adults who were aged between 62 and 67 years at the time of data collection. We also utilised the Finnish administrative register data available on every participant who took the survey. With the permission of the respondents, the register information was merged with the survey data; this provided more background information on each individual.

Dependent variables

Our dependent variables were based on multiple questions measuring the provision of different types of support: personal care, practical help, financial aid, volunteering, and charitable giving. To gather data on practical help and financial support, the respondents were asked to report on the help they offered to their children, parents, siblings, parents’ siblings, cousins, and friends. To gather data on care, they were asked about caregiving for their parents, siblings, parents’ siblings, cousins, and friends; regarding friends, respondents were asked to consider one friend to whom they had provided the most help. Information on older parents caring for their adult children was not considered, as such care is extremely rare in contemporary Finland (Hämäläinen & Tanskanen, 2021).

The respondents were asked to report whether they had participated in voluntary work (0 = no, 1 = yes) or donated money to charity (0 = no, 1 = yes) in the preceding 12 months. They were also asked to report whether they had provided practical help, financial aid, or care to their relatives and/or friends, and were informed that financial aid referred to giving money and covering costs, practical help to support the performance of household tasks, paperwork, technology use, transportation, and so on, while care referred to personal care, such as helping with washing, eating, and dressing. To gather data on financial aid, the participants were asked if they had given financial aid in the preceding 12 months (0 = no, 1 = yes). To gather data on the provision of practical help and personal care, they were asked how often they had provided such support in the past 12 months on a 5-point scale (ranging from 0 = never to 4 = several times a week). Practical help and care variables were recoded into a single dummy variable: instrumental support (0 = no help, 1 = at least occasional help).

In the main analyses, we compared multi-helpers to those who were not multi-helpers and recoded this into a dummy variable (0 = no help or some help, 1 = all types of help). In addition, we constructed a multicategorical variable which allowed us to compare multi-helpers to those who did not provide any help (‘non-helpers’) and to those who had provided some help but not multi-help (‘basic helpers’) (0 = none, 1 = from one to three types of support, 2 = all four types of support).

Explanatory variables

Based on extant research, several factors were identified as related to providing financial aid, instrumental support, participating in voluntary work, and making donations to charity. We utilised the potential of our survey and register data to examine a wide variety of variables that could potentially be associated with the level of prosocial activity. These potential explanatory variables were gender, partnership and employment status, level of education, perceived financial condition, type of home municipality, religiousness, self-rated health, number of close relatives (0 to 20 or more), and number of friends (0 to 20 or more).

In order to conduct the analyses, several explanatory variables were recoded. The original marital status variable was recoded from six categories to four by combining ‘Married,’ ‘Registered partnership,’ and ‘Cohabitation with a partner’ into the category ‘Have a partner.’ Employment status was recoded to three categories: ‘Working’; ‘Retired’; ‘Other’; the average age for inception of old-age pension was 63.5 year (Finnish Centre for Pensions, 2022), and therefore most of the respondents were retired or about to retire, while the rest of them were dispersed among several smaller groups (e.g., permanently ill or disabled, taking care of a relative, unemployed), which were recoded into the category ‘Other’. Perceived financial condition was recoded from four categories to three by combining ‘comfortably off’ and ‘wealthy’ into the category ‘at least comfortably off’. We used perceived financial condition instead of monthly income because incomes may not accurately reflect respondents’ financial well-being, which also depends on other assets (e.g., housing, debts and savings). The descriptive statistics are shown in Table 1.

Table 1 Descriptive statistics (n = 2174)
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Analytical strategy

We began by investigating the structure of the respondents’ prosocial activity, and constructed a Venn diagram showing the different combinations of instrumental help, financial aid, volunteering and charity, using an R package ‘ggvenn’ with RStudio. The Venn diagram illustrated respondents’ frequency and proportion of engagement in multiple forms of support, which is the main target of interest in the following statistical analyses. We executed binomial logistic regression analyses to examine predictors of multi-helping, and interpreted the results as odds ratios (ORs). The findings were illustrated by calculating predicted probabilities with 95% confidence intervals. The predicted probabilities represented the likelihood of being a multi-helper according to different individual characteristics when other factors are held constant. Next, we utilised multinomial logistic regression, for which we interpret the results as relative risk ratios (RRRs). Multinomial logistic regression allowed us to analyse each category of our dependent multicategorical variable relative to the reference category. In the analyses, we used multi-helpers as the reference category, meaning that the results are presented (i) for non-helpers relative to multi-helpers and (ii) for basic helpers relative to multi-helpers. Besides the abovementioned Venn diagram, analyses were conducted using statistical software Stata, version 17.

Results

First, we present descriptive results for the structure of support provided by the respondents. Overall, 75% of the participants provided instrumental support, 44% provided financial aid, 58% gave to charity, 21% participated in volunteering, and 9% did not provide any of these forms of support. Figure 1 highlights all possible combinations of the different types of support examined.

Fig. 1
figure 1

Structure of the provision of support (N = 2174)

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In Fig. 1, every ellipse represents one type of support (e.g., the left-most comprises all respondents who had provided instrumental support to friends or family members). The intersections of the ellipses illustrate the overlap in provision of types of support. About 24% of the respondents had provided only one, 35% two, and 25% three types of support. The intersection of all circles showed that 7% of the respondents were multi-helpers, that is, they had been involved in providing all four types of support.

Next, we examine the predictors of multi-helping. Table 2 shows the results of the logistic regression analysis, which are illustrated by calculating predicted probabilities with 95% confidence intervals, as shown in Table 3; Fig. 2. Respondents with partners as well as widowed respondents were more likely to be multi-helpers than those without partners (no partner = 3.2%; with partner = 7.5%; widowed = 9.0%). Level of education predicted being a multi-helper: respondents with higher levels of education were more likely to be multi-helpers than were those with lower levels of education (low = 3.4%; middle = 6.9%; high = 15.2%). Rural dwellers had higher probability of being multi-helpers than did individuals living in urban areas (urban = 6.5%; rural = 9.7%). Those who considered religion very or somewhat important were more likely to be multi-helpers than were those to whom religion was not important (not important = 3.8%; somewhat important = 8.0%; very important = 13.6%). The results also showed that one’s number of friends was positively associated with the likelihood of being a multi-helper, that is, individuals who had a larger number of friends were more likely multi-helpers when compared to individuals with fewer friends (lowest decile: 2 friends = 6.2%; highest decile: 10 friends = 8.3%). We detected a few marginally significant associations (p < .1). Females (8.0%) were more likely to be multi-helpers than males 6.0%. Employed respondents (5.0%) were less likely to be multi-helpers than those who were retired (7.7%). In addition, middle-income respondents were more likely to be multi-helpers as opposed to those who had a poorer perceived financial condition (low-income = 5.7%; middle-income = 8.1%).

Table 2 Predictors of multi-helping: Logistic regression
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Table 3 Predicted probabilities of multi-helping
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Fig. 2
figure 2

Predicted probabilities (with 95% CIs) of being a multi-helper by respondents’ characteristics (N = 2174)

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Then, we examined the predictors of multi-helpers by utilising multinomial logistic regression analysis with multi-helpers as the reference group (i.e., the results were presented for non-helpers in relation to multi-helpers and for basic helpers in relation to multi-helpers). The results from multionomial regression are similar to those from binomial regression presented above (Appendix Table 4). According to the results for non-helpers relative to multi-helpers, respondents with a partner as well as widowed respondents were more likely to be multi-helpers than unmarried respondents were. Moreover, those with middle and high levels of education had higher probability than the low educated of being multi-helpers. Respondents who described their financial condition as middle-income or better also had a higher chance of being multi-helpers than low-income people, as did respondents who considered religion somewhat or very important to them compared to those who did not perceive religion as important. Finally, respondents with a larger number of close relatives were more likely to be multi-helpers than those who had fewer relatives.

Respectively, results for basic helpers relative to multi-helpers show that respondents with middle or high education were more likely to be multi-helpers than those with low education, retirees were more likely to be multi-helpers than employed individuals, rural residents were more likely to be multi-helpers than urban dwellers, individuals who considered religion to be very or somewhat important were more likely to be multi-helpers compared to those who did not perceive religion to be important, and finally, respondents with more close friends had a higher probability of being multi-helpers than those with fewer friends.

Discussion

How to foster active ageing after retirement is a burning question in rapidly ageing societies. However, studies on the topic have been scarce and have mostly considered only a few prosocial activities at a time, such as volunteering or some form of instrumental help (e.g., practical help, personal care). Here, we investigated profiles of older adults engaged in multiple unpaid help-giving activities, in both private and public domains. We examined the acts of providing (1) instrumental help and (2) financial aid to friends and relatives; (3) volunteering; and (4) charitable giving. Those who had provided both types of help across private and public realms (i.e., a total of four types of support) were considered multi-helpers.

First, we considered the structures of help-giving and detected that the vast majority of older Finns had provided others with some type of support. Of the total, 75% had provided instrumental help, 44% had provided financial aid, 58% had given to charity, and 21% had participated in volunteering. Further, 7% were identified as multi-helpers, in that they had provided all types of support examined. These results are in line with previous studies that examined multiple engagements in unpaid help-giving outside one’s household, although the previous studies examined fewer types of support (Burr et al., 2007; Hank & Stuck, 2008; Jegermalm & Jeppsson Grassman, 2009; Jegermalm & Grassman, 2013). Our results suggest that different types of help provided by the same individual may complement rather than displace each other to some extent, in line with Hank and Stuck (2008), although our results also indicate a ∩-shaped trend in engagement in prosocial activities. Respondents most commonly provided two types of support, indicating that most individuals may be reluctant or unable to take on new prosocial activities after a certain point or that engaging in additional activities may lead to the abandonment of previous ones.

We examined characteristics of multi-helpers, and found that having a partner, having a higher level of education, living in a rural area, being religious, and having a larger number of friends increased the probability of being a multi-helper. Separate comparison of multi-helpers to non-helpers and basic helpers provided additional information about the predictors. Better perceived financial situation and larger number of close relatives were predictors of multi-helping compared to non-helping but not in comparison to basic helping, whereas in comparison to basic helpers, being retired increased the likelihood of being a multi-helper. Our findings align with studies that have provided evidence of factors related to participants’ resources and opportunities being associated with the increased provision of support (e.g., Niebuur et al., 2018; Tanskanen et al., 2022). In line with other prior studies (Bolano & Arpino, 2020; Lim-Soh, 2022) we also detected that widow(er)hood was associated with increased probability of being a multi-helper, indicating that individuals may attempt to compensate for the loss of previous social roles by engaging in other activities.

Previous studies have detected gender differences in the provision of different types of support. For instance, men are more likely to provide practical help, such as help with repairs, whereas women are more likely to provide personal care (e.g., Haberkern et al., 2015; Kahn et al., 2011). Our results provide only limited evidence for gender differences—that females were more likely multi-helpers than males (see also Burr et al., 2007). Interestingly, we did not detect any significant association between self-rated health and engagement in help-giving, although previous studies have shown that health is positively associated with provision of help among older adults (e.g., Hank & Stuck, 2008; Strauss, 2021). One explanation could be that our study focused on ‘younger’ older adults (62–67 years old), whereas previous investigations have usually considered the older population as whole (e.g., individuals over 50). When individuals age, the decline of health is inevitable and limits their possibility of providing help to others. According to our main results, one’s number of close relatives was not associated with the likelihood of being a multi-helper; however, compared to non-helpers, individuals with a larger number of close relatives had a higher probability of being multi-helpers. Studies have shown that individuals have a strong tendency to help their kin, and typically more support is provided to relatives than friends (e.g., Burnstein, 2005; Madsen et al., 2007), and therefore, having more close relatives may decrease one’s likelihood of not providing any support. In contrast, compared to all individuals who provided some types of help, our results showed that having a larger number of friends increases the likelihood of being a multi-helper. This suggests that engaging in multiple help-giving activities, instead of a few, is associated with having more social contacts to whom help can be provided or through whom opportunities to give help can be secured.

A major strength of our study was that the data helped us examine a wide variety of explanatory factors while investigating multiple forms of support. The few studies that have investigated older adults providing multiple types of support toward different parties (Burr et al., 2007; Hank & Stuck, 2008) have examined only a limited number of explanatory factors and have not considered the provision of financial aid or charity donations. Thus, our results offer more comprehensive insight on the characteristics of individuals engaged in multiple forms of help-giving. One downside is the cross-sectional nature of the data, meaning that while the results are informative on the proportion and predictors of multi-helpers, they do not provide evidence for causal associations or shed light on the dynamics of multiple engagement over time. Thus, future studies should investigate whether changes in an individual’s resources and opportunities affect their likelihood of being a multi-helper. Studies should also examine whether the composition of prosocial activities remains stable or changes over time, for instance because of engagements in new tasks—that is, whether additional activities displace or complement previous ones. Another limitation is that we could not measure the intensity of support provided or whether one type of support was given to multiple recipients; further investigations should consider support frequency among multi-helpers and whether, for instance, the frequency of one type of support affects the composition of help-giving. Finally, our results concerned only one country, and future research should explore whether the prevalence of multi-helpers and predictors differs across countries and welfare state regimes.

Active ageing is a key policy goal in countries with rapidly ageing populations (Foster & Walker, 2015), as noted. However, the value of unpaid prosocial activities engaged in by older adults may nevertheless not always be adequately recognised, as policymakers often consider active ageing only from the perspective of the labor market. Our results show that a vast majority of older adults are providing several types of support to different parties. While engagement in help-giving can be beneficial for older adults themselves, for example by strengthening their social networks and improving their health and wellbeing (e.g., Burr et al., 2021; Musick & Wilson, 2008), by providing support older adults also become an important asset for their social networks and society at large. Thus, promoting older adults’ resources and opportunities to participate in prosocial activities should be incorporated as an integral part of active ageing policies.