Variations in Benefits of Intergenerational Tutoring in the “New Normal”

Abstract

This study investigated the benefits and challenges of intergenerational tutoring in a post-pandemic context. We explored how the benefits of intergenerational tutoring vary among subgroups of volunteers—first-time tutors, male tutors, tutors who are caregivers, and tutors with moderate or severe loneliness. Older adult tutors (N = 319) were surveyed before and after the 2021–2022 school year, and the data were analyzed with structural equation multivariate regression and thematic analysis. Results indicated that while public health measures like mask-wearing posed challenges for some tutors, there were positive outcomes for tutors, especially first-time tutors, who experienced more health and well-being benefits, and tutors who are caregivers, who experienced improved civic attitudes towards public education. These results can help programs attract subgroups of volunteers who are likely to benefit the most, as well as attend to the unique challenges of pandemic-related policies.

Keywords

volunteerism civic engagement COVID-19

What this paper adds

• First-time tutors and tutors who are caregivers experienced greater health and well-being benefits and improved civic attitudes towards public education benefits, than their respective counterparts.

• Intergenerational tutoring following the pandemic was challenging because of public health measures, but tutors continued to find meaning and purpose through social connections.

Applications of study findings

• Targeting first-time tutors and tutors who are caregivers may maximize benefits of intergenerational engagement.

• Public health measures should be balanced with the social engagement needs of older adult volunteers.

Introduction

Volunteering played an important role in the lives of older adults during the COVID-19 pandemic. Despite overall decreases in the share of volunteering during the pandemic—43% of older adults aged 50 and over in England who volunteered prior to the outbreak stopped volunteering in June/July 2020 (Chatzi et al., 2020, p. 10)—older adults who volunteered during the pandemic saw increases in social relationships (Mak & Fancourt, 2022) and life satisfaction (Bu et al., 2021). Volunteering during the pandemic also buffered older adults against social isolation and loneliness (Bruce et al., 2021; Chatterjee & Yatnatti, 2020). Intergenerational exchange and solidarity have also emerged as a particularly crucial process for overcoming age-divided messaging, negative stereotypes about old age, and ageism during the COVID-19 outbreak (Ayalon et al., 2021). As pandemic restrictions such as social distancing are lifted and older adults return to volunteering (Dederichs, 2023), it is unclear if the benefits of volunteering both before and during the pandemic have continued. Therefore, focusing on intergenerational tutoring in the post-pandemic context, this paper asks if volunteering confers any benefits upon older adults and, if so, to whom those benefits are experienced among sub-groups of older adults.

Research on intergenerational tutoring has documented a variety of benefits for older adults both before and during the pandemic. A recent systematic review indicated that intergenerational programs consistently reduced anxiety, improved cross-age attitudes, and increased physical activity levels (Krzeczkowska et al., 2021). This is consistent with a prior systematic review that also found improved cross-age attitudes among multiple studies (Giraudeau & Bailly, 2019). Notably, results from randomized controlled trials of the Experience Corps program have shown that older participants increased their physical, cognitive, and social activity, as well as experienced generative fulfillment (Fried et al., 2004, 2013). Additionally, we found using a quasi-experimental design that volunteers from Experience Corps reported fewer depressive symptoms and functional limitations (Hong & Morrow-Howell, 2010). Interviews with Experience Corps participants also uncovered pathways from volunteering to civic engagement, such as advocating for public education policies (Morrow-Howell et al., 2014). While the pandemic disrupted the continuation of some intergenerational programs, other programs transitioned to online or hybrid formats. These programs continued to yield benefits for both children and older adults, such as purpose and meaning in participation and tutor retention (Hoffman et al., 2023).

In addition to the outcomes of intergenerational volunteering, research has also considered the outcomes among subgroups of volunteers. Overall, there are mixed results on who benefits the most from intergenerational programs. With respect to health and well-being, Teater (2016) found that there were no statistically significant relationships with older adults’ chronological age. Strand et al. (2014) also found that physical activity benefits from a 25-week intergenerational fitness program were unrelated to self-reported health, age, and attendance. Mahoney et al. (2020) found significant improvement in mental health among male intergenerational mentors, while Barbosa et al. (2021) found a significant reduction in depression, but no decreases in loneliness or increases in happiness, among female older adult volunteers. Young and Janke (2013) found that non-White older adults in intergenerational community service programs experienced greater increases in self-esteem, physical health, openness to new ideas, and involvement with the community. We found that aspects of the volunteer experience, such as training and stipends, were more important than individual characteristics in understanding who benefits from volunteering (Morrow-Howell et al., 2009). Generative concerns among older adults have previously been linked to civic engagement in later life (Serrat et al., 2017, 2023), though no research to our knowledge has explored sub-group differences in the effect of intergenerational tutoring on civic attitudes towards public education.

Given these inconsistent findings and gaps in knowledge, understanding how different subgroups benefit from intergenerational programming is an important empirical question. This paper focuses on the experiences of older adults who engaged in the Oasis Intergenerational Tutoring program in the 2021–2022 school year, which marked a return to in-person tutoring following a year of remote and online tutoring. Oasis is a national nonprofit organization that promotes healthy aging through lifelong learning, active lifestyles, and volunteer engagement. Its tutoring program matches older volunteers with elementary children in Grades K–3, is active in more than 84 school districts and nearly 441 schools, and engages over 2000 tutors in 15 states in 22 cities. Adults who have a desire to help children with reading and can commit to the Oasis program and ongoing training are eligible to become tutors. They are supported by a school district facilitator and do not receive stipends or incentives. The goal of this research is to document the opportunities and challenges of intergenerational tutoring in a post-pandemic context.

Guided by role theory and the expectation that well-defined social roles have a salutary effect on well-being (Biddle, 1986), we also explore sub-group variations in well-being and civic attitudes towards public education outcomes. Specifically, this research asks the following research questions: (a) Are there unique benefits of intergenerational tutoring among first-time tutors, male tutors, tutors who are caregivers, and tutors with moderate or severe loneliness? (b) What are the opportunities and challenges in the post-pandemic context of tutoring?

Methods

Design

To focus on within-group variations of intergenerational tutoring benefits, we adopted a fully mixed concurrent equal status design (Leech & Onwuegbuzie, 2009), using pretest and posttest quantitative data to answer the first research question and posttest-only qualitative data to answer the second research question. We integrated the data through a process of triangulation, considering areas of agreement (convergence), areas of contradiction (discrepancy/dissonance), and areas of reinforcement (complementarity) (O’Cathain et al., 2010). Mixed-methods is appropriate for this study because we wanted to expand the depth of our study and obtain “diversity of views” in our queries about the post-pandemic context of tutoring (Wisdom et al., 2012, p. 723). The Washington University in St Louis Institutional Review Board approved the study protocols (No. 202008102).

Survey Procedure

This pretest and posttest survey instruments were developed as part of a larger study on the effect of volunteering on older adults (Sun et al., 2023). Both surveys were tested for usability and comprehensibility. Using these two surveys, we surveyed Oasis tutors in four cities—Albuquerque, NM, Saint Louis, MO, Indianapolis, IN, and Pittsburgh, PA—before and after their tutoring programs in the 2021–2022 school year. For both the pretest and posttest surveys, Oasis staff sent an initial email with an informed consent form and provided options to complete the survey online using the Qualtrics survey platform or by phone. Up to six follow-up reminders to complete the survey were given to each participant via email, phone, and hard-copy letters. A total of 430 out of 530 tutors completed the pretest survey (81.1% response rate), and a total of 367 out of 530 tutors completed the posttest survey (69.2% response rate). The incentive to complete each survey was entering a random drawing for two $50 Amazon gift cards and a $5 credit for the tutor’s school district to purchase books.

Sample

This study’s sample is defined as the tutors who completed both the pretest and posttest surveys (N = 319). To assess the representativeness of our sample, we compared our sample’s demographic characteristics with a national sample of Oasis tutors in 2021 (Oasis Institute, 2021). Chi-square tests of independence revealed no significant differences by age, gender, race/ethnicity, or marital status. No complex sampling procedures were used. We excluded one tutor below age 50 to focus on older adults aged 50 and older.

Survey Measures

The posttest endogenous variables included two subjective measures: (1) total benefits (a sum score of six perceived benefits [range of 6–24] of being involved in the tutoring program, including increased social activities, use time more productively, feel better about self, better physical health, better cognitive health, and better emotional health) and (2) civic attitudes towards public education (a sum score [range of 4–12] of four changes in attitudes and actions regarding public education: understanding of teacher’s jobs, awareness of the needs of kids, knowledge of educational issues and policies, and likelihood of voting in favor of public support for schools and school programs). We created sum scores for each variable on the basis of an acceptable level of internal consistency among the items for total benefits (Cronbach’s α = 0.78) and civic attitudes towards public education (Cronbach’s α = 0.79) (Taber, 2018). The total benefits and civic attitudes towards public education scores were adapted from our previous work on intergenerational tutoring (Kinnevy & Morrow-Howell, 2000; Morrow-Howell et al., 2014).

The pretest exogenous variables for testing group differences included the following: (1) gender (1 = male; 2 = female), (2) first-time volunteer (1 = first volunteer work with a formal organization in the last 10 years; 2 = not first-time volunteer), (3) caregiver (1 = caregiver who spent 100 or more hours in the last two years helping someone who needed assistance; 2 = non-caregiver), and (4) loneliness (1 = a sum score of 1–4 on the Three-Item Loneliness Scale; 2 = a sum score of 5–9 on the Three-Item Loneliness Scale, which is considered “moderate” or “severe” loneliness) (Brunes et al., 2019). We chose these variables based on the role extension hypothesis, which predicts that multiple roles may be complementary and lead to increased productive engagement (Strauss, 2021). Consistent with the role accumulation theory, we also theorize that inaugurating a new social role (i.e., first-time volunteers) or volunteering with greater loneliness may accrue larger benefits (Sieber, 1974).

The pretest covariates used in this study included the following: (1) race (1 = White; 0 = Black or African American and Other Races), (2) education (1 = 4-year college degree or more; 0 = less than a 4-year college degree), (3) age, (4) marital status (1 = married; 0 = not married), (5) total household income in the past calendar year (0 = less than $25,000; 1 = $25,000–$50,000; 2 = $50,000–$75,000; 3 = $75,000–$100,000; 4 = $100,000–$125,000; 5 = $125,000 or greater), (6) Patient-Reported Outcomes Measurement Information System (PROMIS) Global Physical Health Score (converted to a T-score distribution where 50 represents the mean of the U.S. general population, and the standard deviation around that mean is 10 points), and (7) PROMIS Global Mental Health Score (T-score distribution). The PROMIS measures are from the PROMIS Scale v1.2 - Global Health, a health-related measurement system developed by the National Institutes of Health (Hays et al., 2009). Survey questions can be found in Table S1 of the Supplementary Material.

The open-ended questions included two questions on the posttest survey: (1) “Has your involvement with Oasis led to any negative effects?” and (2) “You have been volunteering during a pandemic. Please share your thoughts on how this year’s tutoring experience has affected you in light of these circumstances.”

Quantitative Analysis

Descriptive statistics (frequencies, means, and standard deviations) were used to examine the closed-ended survey responses. To study the effect of missing data on our analysis, we conducted Little’s (1988) test, χ²(251) = 279.80, p = .10, and assumed that the data were missing completely at random (MCAR). Despite meeting this assumption, missing data in the study variables would result in a loss of 31.0% of cases if listwise deletion were used. Therefore, to increase statistical power, we created 40 multiply imputed datasets via chained equations using the “mice” package in R (Buuren & Groothuis-Oudshoorn, 2011). We chose 40 imputations, based on the rule of thumb that the number of imputations should be equal or greater than the percentage of incomplete cases (White et al., 2011). As a sensitivity analysis, we also carried out the same analyses using 100 imputations, following the recommendation of Graham et al. (2007). Missing values were imputed using predictive mean modeling for continuous variables, proportional odds model for ordinal variables, and logistic regression for dichotomous variables. We inspected trace plots for each imputed variable to look for adequate mixing and convergence around a stable mean (Enders, 2022). Depending on the type of variable, Pearson’s, biserial, and tetrachoric correlations were estimated between all variables on the original sample to check for multicollinearity, using a threshold of greater than .85 as indicating harmful multicollinearity (Lei & Wu, 2007). Complete observations were used for the correlations when there were missing data.

To measure variations of benefits by different sub-groups, we adopted a structural equation multivariate regression modeling approach, regressing the posttest endogenous variables on the pretest exogenous variables, while controlling for the pretest demographic covariates. Due to the small sample size (N = 319), we were not able to model the endogenous variables as latent factors and used a multivariate regression approach with observed variables only. We fitted a separate regression model for each endogenous variable, without covarying the residual variances of the endogenous variables. The model was fitted on the imputed datasets, and the results were pooled using Rubin’s (1976) rule. Given the use of ordinal and nominal exogenous variables, we chose the weighted least square mean variance (WLSMV) estimator because it had superior performance than other diagonally weighted least square estimators in a simulation study (DiStefano & Morgan, 2014). The WLSMV estimator’s use of robust standard errors addressed the lack of multivariate normality in our data, which was verified by Mardia’s (1970) test and Zhou and Shao’s (2014) test. Due to the small sample size and model size (df = 1), we followed the recommendation of Shi et al. (2022) in pursuing a “two-index strategy,” using the standardized root mean square residual (SRMR) (≤.08 is a good fit) and the chi-square test of the overall model fit. We also conducted a power analysis to assess if the study had sufficient power (1-β > 0.8) to detect a small effect size (r = 0.06) that was found in a prior study investigating a similar phenomenon (Morrow-Howell et al., 2009, p. 98).

Qualitative Analysis

Thematic analysis was used to discover emergent themes in the posttest survey’s two open-ended questions (Braun & Clarke, 2006). Using Microsoft Excel, the data were coded independently by the first author and an undergraduate student, using an inductive, “bottom-up” approach to uncover the latent meanings from each manifest code (Weil, 2017, p. 63). First, the first author and the undergraduate student coded a random sample of the responses and met to discuss consistency of approach and any notable diversions. Second, coding continued for every open-ended response, until at least a 90% intercoder reliability was reached—defined as the quotient of the number of agreements and the quantity of the sum of the agreements and disagreements (Miles & Huberman, 1994, p. 65). Finally, the second author reviewed the codes for completeness and met with the first author and undergraduate student three times to search, sort, and name the final themes and subthemes. Divergent interpretations were continuously negotiated against each other to discover a good fit between the data and the themes.

Results

Quantitative Results

Table 1 shows the demographic characteristics of the participants (N = 319). Most of the tutors were White (94.1%), had a four-year college degree or higher education (81.9%), between the ages 70–79 (46.8%) and 60–69 (39.7%), and married (70.0%). More than half of the tutors had a total household income between $25,000 and $75,000 (55.9%). The PROMIS physical health (45.54) and PROMIS mental scores (47.99) were slightly below the mean of the general U.S. population (i.e., a score of 50), which is to be expected for older adults. With respect to the sub-groups of interest, 10.8% of the tutors were male volunteers, 11.9% were first-time volunteers in the last 10 years, 25.4% were caregivers in the last two years, and 23.1% of the tutors had a moderate or severe level of loneliness. At posttest, tutors had on average a total benefits score of 17.46 (on a six-item scale ranging from 6 to 24) and a civic attitudes towards public education score of 9.88 (on a four-item scale ranging from 4 to 12). Table 2 shows the correlation matrix of the study variables. None of the variables were likely to cause multicollinearity (i.e., all bivariate correlations <.85). Table 3 shows the multivariate regression results pooled from 40 imputed datasets. While the chi-square test indicated a poor fit (p < .01), the SRMR (.026) indicated a good fit. Furthermore, a power analysis for the general linear model indicated that the sample of 319 had enough power (1-β = 0.87) to detect a small effect size (r = .06). The sensitivity analysis using 100 imputations yielded the same conclusions and was therefore not reported. There were two significant sub-group differences: (1) the total benefits score at posttest was higher for first-time volunteers than non-first-time volunteers (β = 0.94, p < .05) and (2) the civic attitudes toward public education score at posttest was higher for caregivers than non-caregivers (β = 0.47, p < .05). There were no significant differences between the sociodemographic covariates (race, education, age, marital status, income, physical health, and mental health) and both outcomes.

Table 1.

Pretest Characteristics of Participants and Posttest Outcome Measures (N = 319).

Survey	Variable	N (%)
Pretest	Race = White (%) (ref: Black or African American and Other races)	289 (94.1)
	Education = 4-year college degree or more (ref: less than college)	244 (81.9)
	Age (%)
	50–59	20 (6.4)
	60–69	124 (39.7)
	70–79	146 (46.8)
	80–89	22 (7.1)
	Married (ref: not married)	219 (70.0)
	Total household income (ref: less than $25,000)
	Less than $25,000	8 (3.1)
	$25,000–$50,000	76 (29.1)
	$50,000–$75,000	70 (26.8)
	$75,000–$100,000	47 (18.0)
	$100,000–$125,000	33 (12.6)
	$125,000 or greater	27 (10.3)
	PROMIS Physical Health (mean [SD])	45.54 (6.80)
	PROMIS Mental Health (mean [SD])	47.99 (6.82)
	Male volunteer (ref: female volunteer)	34 (10.8)
	First-time volunteer in last 10 years (ref: not first-time volunteer)	38 (11.9)
	Caregiver in the last 2 years (ref: non-caregiver)	79 (25.4)
	Volunteers with moderate or severe loneliness (ref: volunteer without moderate or severe loneliness)	72 (23.1)
Posttest	Total benefits (mean [SD[)	17.46 (2.82)
	Increased social activities—agree/strongly agree (%)	119 (38.3)
	Use time more productively—agree/strongly agree (%)	143 (46.0)
	Feel better about self—agree/strongly agree (%)	264 (85.2)
	Physical health—better (%)	54 (17.4)
	Cognitive health—better (%)	62 (20.1)
	Emotional health—better (%)	89 (28.7)
	Civic attitudes towards public education (mean [SD[)	9.88 (1.84)
	Understanding of teacher’s jobs—increased (%)	166 (54.6)
	Awareness of the needs of kids—increased (%)	193 (63.5)
	Knowledge of educational issues and policies—increased (%)	150 (50.2)
	Likelihood of voting in favor of public support for schools and school programs—increased (%)	147 (49.5)

Note. Survey respondents had the option to not answer any question, therefore not all categories sum to 100%.

Table 2.

Correlation Matrix of Study Variables (N = 319).

Variable	1	2	3	4	5	6	7	8	9	10	11	12	13
1. Race	1.00
2. Education	−0.29	1.00
3. Age	−0.02	0.03	1.00
4. Married	0.31	−0.02	−0.37	1.00
5. Income	0.26	0.21	−0.10	0.53	1.00
6. PROMIS Physical	0.25	0.05	−0.01	0.07	−0.06	1.00
7. PROMIS Mental	0.24	0.05	0.08	0.15	−0.01	0.64	1.00
8. Male volunteer	0.16	0.22	0.18	0.22	−0.01	−0.03	0.02	1.00
9. First-time volunteer	−0.10	−0.20	−0.10	−0.13	0.00	0.05	0.13	−0.01	1.00
10. Caregiver volunteer	−0.11	−0.15	0.05	−0.09	0.07	−0.06	−0.01	−0.35	0.08	1.00
11. Loneliness	−0.17	−0.08	0.06	−0.40	−0.20	0.07	−0.08	−0.32	0.01	−0.01	1.00
12. Total benefits	0.09	0.00	−0.09	−0.08	−0.08	0.02	0.01	−0.04	0.17	0.10	0.03	1.00
13. Civic attitudes	0.03	0.10	0.05	0.03	0.08	0.03	0.04	0.01	0.03	0.12	−0.01	0.23	1.00
Mean	0.94	0.82	69.69	0.70	2.39	45.54	47.99	0.11	0.12	0.25	0.23	17.46	9.88
Standard deviation	-	-	6.75	-	-	6.80	6.82	-	-	-	-	2.82	1.84

Note. Correlations are Pearson’s correlation if continuous–continuous, biserial correlations if continuous–dichotomous, and tetrachoric correlations if dichotomous–dichotomous; complete observations were used when there were missing values; and standard deviations were omitted for dichotomous variables.

Table 3.

Multivariate Regression Results.

Covariates/Exogenous Variables	Endogenous Variables
Covariates/Exogenous Variables	Total Benefits	Civic Attitudes Towards Public Education
Covariates
Race	1.11 (0.94)	0.30 (0.44)
Education	0.36 (0.43)	0.40 (0.32)
Age	−0.039 (.025)	0.0070 (0.018)
Marital status	−0.35 (0.46)	−0.037 (0.26)
Income	−0.15 (0.15)	0.092 (0.088)
PROMIS Physical Health	0.012 (0.035)	0.0090 (0.022)
PROMIS Mental Health	−0.0090 (0.033)	0.00 (0.021)
Exogenous variables
Male volunteer	0.040 (0.51)	0.065 (0.36)
First-time volunteer	0.94 (0.46)*	0.28 (0.36)
Caregiver volunteer	0.65 (0.36)	0.47 (0.23)*
Volunteer with moderate or severe	0.14 (0.43)	0.076 (0.26)
Loneliness
(Intercept)	19.04 (1.93)*	7.99 (1.47)*
R²	0.045	0.029

Note. Model fit: χ²(1) = 12.33, p < .01; SRMR = .026. Rubin’s (1976) rules were used to pool the unstandardized regression estimates and robust standard errors (in parentheses) across 40 imputed datasets.

*p < .05, two-tailed test.

Qualitative Results

Pandemic Volunteering: Effects of Public Health Measures

Public health measures played a major role in the experience of tutors during the pandemic. Volunteers had polarizing views towards mask-wearing, which was mandated in most of the tutors’ school districts for the fall semester and lifted shortly before the end of the school year. On one hand, the volunteers appreciated masks for creating a safe environment for tutoring, even as there was anxiety about health and disease transmission:

It was a little scary at first but I wore a mask and felt better as the students wore them too and we all did a good job and no one complained about the mask (70–79-year-old female).

When the mask mandate was lifted, many volunteers felt ambivalent about whether to continue wearing masks, some having to weigh the risks of getting sick against the benefits of volunteering:

I had difficultly when the mask mandate was lifted. I continued to wear a mask, though removed it for the last session or two. I had very ambivalent feelings both wearing a mask and not wearing one (70–79-year-old female).

Tutoring has decreased my fearfulness about contracting COVID, even as I increased my possible exposure. I still mask up with KN95 (70–79-year-old female).

On the other hand, some volunteers were anxious to stop using masks, expressing skepticism about their usefulness. Mask-wearing impeded overall communication, made it difficult to see or show facial expressions, and made it harder for some tutors to bond with their students.

Masks are so not helpful for positive human relationships and interaction, so I am thankful those are gone! We won’t use them again in tutoring time! (50–59-year-old female).

Pandemic Volunteering: Benefits to Tutors

Despite the challenges of volunteering amid public health measures, the tutors also cited several benefits. First, the tutors expressed a sense of purpose and meaning, despite “COVID-19 still very much around”:

So tutoring this year kept me connected to people. It gave me a purpose and a reason to keep moving. I get more done on the days I tutor. I feel like I'm doing something very worthwhile. It gives me joy (60–69-year-old female).

This sentiment was echoed by tutors who appreciated socializing during the pandemic and having the chance to build a positive, meaningful relationship with children:

I would always look forward to the socializing aspect of meeting with my students. I really felt that I had a positive bond with my students. My tutoring hours were basically the only social contacts I had (outside of my family) during the pandemic (70–79-year-old female).

Second, many tutors increased their awareness and appreciation of the public school system, especially seeing how teachers and staff had to respond and adapt to the challenges of working during the ongoing pandemic:

It has shown me the resilience and dedication of the public school system teachers and staff (70–79-year-old male).

Third, the tutors expanded their pedagogical toolkit because of novel challenges brought by the pandemic. For example, many tutors adapted their lesson plans to accommodate student absences and shorter instructional time. Due to widespread report of student learning loss, the tutors also had to help their students catch up academically. Tutors also had to adapt to communicating and teaching while respecting the boundaries of social distancing:

I had to learn to respect the students' space and not to have any kind of contact. Also, had to listen closer and understand because of masking (70–79-year-old female).

Negative Effects of the Tutoring Experience

Only a small number of tutors reported negative effects because of the tutoring experience. However, there were three themes that emerged in the responses: Program Limitations, Student Challenges, and Competing Demands. First, some tutors were frustrated with the way the Oasis program and the school districts handled scheduling, student placement, and resource distribution, such as providing books for children to read. Some tutors were also disappointed with the school district not doing enough to help kids, such as addressing chronic student absences, or not caring enough about student progress, such as providing a competitive learning environment. Second, a few tutors were challenged by their students’ social and behavioral needs. Finally, there were tutors who struggled to tutor because of competing demands, such as their own health and mobility issues, family issues, or caregiving responsibilities.

Discussion

This study showed that there were challenges for older adult volunteers during the “New Normal,” such as the tutors' divergent responses to public health measures. It also highlighted the positive benefits of tutoring, especially among first-time volunteers and caregivers.

Our quantitative results are similar to our previous study on the Oasis Intergenerational Tutoring program, which found that benefits accrue equally with respective to age, gender, and marital status (Kinnevy & Morrow-Howell, 2000). That study also found that benefits increase with years of participation, which is related to our finding that there are differential benefits between first-time and non-first-time volunteers. Our finding that caregivers benefit more than non-caregivers is also consistent with our previous research on caregivers’ psychosocial benefits of engagement using a larger sample size of 5092 Oasis participants (Greenfield et al., 2012). While we do not know why changes in civic attitudes towards public education were more prominent among Oasis caregivers than noncaregivers, these unique benefits may derive from caregivers’ engagement in multiple forms of helping behaviors, both formal and informal, and their greater propensity to volunteer than noncaregivers (Burr et al., 2005). It is also unclear why tutors with moderate or severe loneliness in our study did not benefit more greatly than their counterparts. Gaggioli et al. (2014) noted in their evaluation of an intergenerational program that while emotional loneliness significantly decreased after the intervention, social loneliness did not. It is possible that our measure of general loneliness was not sensitive to these nuances, or any true program effects were masked by the pandemic’s lingering effects on loneliness (Ernst et al., 2022).

Our qualitative results highlight the intricate balance between ongoing safety concerns and the desire for socialization and productive engagement. First, consistent with both the real and socially constructed challenges that older adults faced during COVID-19 pandemic (Reynolds, 2020), the older adults in our sample cited continued impediments and strains associated with those challenges. For example, the tutors expressed a diminished appeal with volunteering while wearing masks, which likely inhibited volunteering behavior during the pandemic (Dederichs, 2023). Second, the polarizing views on mask-wearing reflected the heterogeneity of viewpoints toward pandemic policies and the importance of socio-demographics. Some older adults, especially marginalized groups, may be more susceptible to the effects of the pandemic than others, which explains why there were tutors in our study who felt ambivalent when mask mandates were lifted. Third, volunteering post-pandemic has been shown to have a positive impact on the tutors' sense of purpose and connection. This represents a continuation of similar outcomes reported by evaluations of intergenerational programs during the pandemic, particularly the finding that older adults established meaningful connections (Jarrott et al., 2022). Finally, some of the negative effects reported by tutors, including program limitations, student difficulties, and personal constraints, underscore the continued need for accountability of professionals and best practices that support both young children and older adults (DeVore et al., 2016).

Integrating both quantitative and qualitative data provides a more holistic view of the post-pandemic tutoring experience. Notably, the themes of sense of purpose and negative effects of tutoring were not captured by the closed-ended survey measures. While sense of purpose complements with the “total benefits” of tutoring, its relative importance compared to other forms of benefits remains unclear. Further, the theme of negative effects, if translated into a quantitative measure, may attenuate the overall reported benefits experienced by tutors. Future mixed-method research should explore these areas of complementarity and dissonance to arrive at a more nuanced view of health and well-being.

This study had several limitations. First, the within-group variations of benefits that we uncovered may be influenced by unobserved confounders. Second, our relatively small sample size is overwhelmingly White, female, and highly educated, limiting the generalizability of our study results. Future studies should use larger and more representative samples to deepen and replicate the analysis. Third, the discrepancy between the chi-square test and SRMR fit indices indicates the need for the results to be replicated in the future. Finally, there may be measurement error associated with our aggregated self-reported health and well-being outcomes. Objective measures of health, such as strength or walking speeds, should be considered alongside subjective self-report (Tan et al., 2006).

Despite these limitations, this study provides evidence that the Oasis Intergenerational Tutoring program may be viewed as an intervention for both health and well-being outcomes and improved civic attitudes towards public education, especially among first-time volunteers and caregivers. We also found that intergenerational programs continued to bestow social, physical, and psychological benefits upon older adult tutors situated in a challenging post-pandemic terrain.

Supplemental Material

Supplemental Material - Variations in Benefits of Intergenerational Tutoring in the “New Normal”

Supplemental Material for Variations in Benefits of Intergenerational Tutoring in the “New Normal” by Peter C. Sun, Nancy Morrow-Howell, and Mary V. Click in Journal of Applied Gerontology.

Footnotes

Acknowledgments

The authors thank Ran Huo for her assistance with coding.

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 RRF Foundation for Aging research (Grant No. 2020020).

IRB Protocol/Human Subjects Approval Number

The Washington University of St. Louis Institutional Review Board approved the study protocols (No. 202008102).

ORCID iD

Peter C. Sun

Supplemental Material

Supplemental material for this article is available online.

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