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Psychological and social-structural influences on commitment to volunteering
Journal of Research in Personality 41 (2007) 889–907 www.elsevier.com/locate/jrp
Psychological and social-structural inXuences on commitment to volunteering 夽 M. Kyle Matsuba a,¤, Daniel Hart b,¤, Robert Atkins b a
Psychology Department, University of Northern British Columbia, 3333 University Way, Prince George, BC, Canada V2N 4Z9 b Center for Children and Childhood Studies, Rutgers University, 405/407 Cooper Street, Camden, NJ 08102, USA Available online 4 January 2007
Abstract A model is described in which commitment to volunteering is hypothesized to be the result of demographic qualities, personality, identity, values, and social relationships. The model is tested and cross-validated using data from a nationally representative sample of American adults. The results from structural equation modeling analyses suggest that the hypothetical model provides a good Wt to the data. Moreover, the Wndings suggest that the relations of personality and demographic characteristics to hours devoted to volunteering are largely mediated by latent constructs capturing helping identity and community participation. The implications of the model and the Wndings for our understanding of volunteering are discussed. © 2007 Published by Elsevier Inc. Keywords: Volunteering; Personality type; Identity; Altruism
1. Introduction Volunteers make a substantial contribution to the health and functioning of many societies. Recent surveys indicate that large fractions of adults in the United States volunteer (estimates range between 28%, Bureau of Labor Statistics, 2005; and 44%, Independent Sector, 2005). The annual monetary value of this donated labor is calculated to be more 夽 *
The support of the W. T. Grant Foundation is gratefully acknowledged. Corresponding authors. E-mail addresses: [email protected] (M.K. Matsuba), [email protected] (D. Hart).
0092-6566/$ - see front matter © 2007 Published by Elsevier Inc. doi:10.1016/j.jrp.2006.11.001
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than 280 billion dollars (Independent Sector, 2005). Interest in volunteering is triggered not only by its importance to the civic well-being of our society but by its unique psychological qualities—volunteering is planned, generally sustained over time, multiply motivated and voluntary (Omoto & Snyder, 1995; Penner, 2002)—that distinguish it from the reactive and automatic prosocial behaviors most familiar to researchers (e.g., helping; for a review, see Penner, Dovidio, Piliavin, & Schroeder, 2005). The combination of civic importance and distinctive characteristics makes volunteering an important topic for study. 1.1. Three research traditions Our goal in this paper is to test a model of the psychological and social inXuences on the number of hours volunteered per month, the latter indexing involvement in volunteering. The model tested in this study derives from the social-structural, personality, and identity research traditions. The social-structural approach aims to specify the combination of social roles and social class attributes that are associated with volunteering. Wilson (2000) concluded that there is considerable evidence showing that age, gender, educational attainment, household income, and the breadth of an individual’s social network are predictors of volunteering. Thus, the model tested in this study includes these social-structural factors. Personality research, broadly deWned, has focused on the motives and traits that lead individuals to volunteer, and to persist in their volunteering. Based on the past work, suYcient evidence has emerged for researchers to reach three conclusions regarding the link between personality and volunteering. First, people are motivated to volunteer for diVerent reasons, and these motives inXuence the longevity of service (Clary et al., 1998; Omoto & Snyder, 1995). For instance, Omoto and Snyder (1995) identiWed Wve motives associated with AIDS volunteering including values, understanding, personal development, community concern, and esteem enhancement. Second, research indicates that personality traits related to positive emotions, social skillfulness, sympathy, and emotion regulation are more prominent in volunteers than in non-volunteers (e.g., Davis et al., 1999; Omoto & Snyder, 1995; Penner, Fritzsche, Craiger, & Freifeld, 1995; Unger & Thumuluri, 1997). Third, the available research indicates that there is a broad proWle of personality dispositions related to volunteering, and that volunteers cannot be distinguished from non-volunteers by the presence of a single discrete, narrow trait. As Penner (2002, p. 450) concluded, “one relatively speciWc personality trait is unlikely to be related to a wide range of helping behaviors.” In one of the strongest demonstrations of the eVects of personality on volunteering, Atkins, Hart, and Donnelly (2005) found that school-age children characterized by a trait proWle suggesting resilience—compliant, socially skillful, and with positive emotional tone—were more likely to be volunteers as adolescents than were children whose trait proWles suggested either an over-controlled or an under-controlled personality type. The fact that personality was measured years before most children engage in volunteering suggests that the resilient personality proWle leads to volunteering, rather than being shaped by it. Atkins and colleagues also found that adding speciWc childhood personality trait dimensions did not improve the link between personality types and volunteering. In the third tradition, researchers of identity (e.g., Grube & Piliavin, 2000; Piliavin & Callero, 1991) have focused on the transformation of the sense of self that is aVected by, and that in turn sustains, volunteering. For example, Piliavin and Callero (1991) studied the emergence of the role identity of blood donor among those who regularly volunteered to
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give blood. They found that those volunteers for whom the identity was elaborated and salient were more likely to persist over time in blood donation. Lee, Piliavin, and Call (1999), using a nationally representative survey, found that those who reported thinking a lot about their identities as donors judged the likelihood of future donations to be higher than those for whom donor identities were less salient in consciousness. Finally, Hart and Fegley (1995) found that adolescents deeply engaged in volunteer community service viewed their activities as integral components of themselves in the future and of their ideal selves, a constellation of self-representations suggesting that the volunteer activities had been synthesized into their identities. There are points of consensus and disagreement across the three traditions. First, there is consensus among the three traditions that volunteering is partly motivated by ethical and civic values (e.g., Janoski, Musick, & Wilson, 1995; Omoto & Snyder, 1995), although there is disagreement about whether such values constitute a separate construct (e.g., Janoski et al., 1995) or are facets of other constructs such as personality (e.g. Omoto & Snyder, 1995). Moreover, studies within all three traditions (e.g., Grube & Piliavin, 2000; Penner, 2002) regularly report that demographic factors such as educational attainment distinguish between volunteers and non-volunteers. The three traditions oVer substantially divergent views on the relative importance of various factors that inXuence volunteering, and how these factors might interact. For example, Wilson (2000) reported that most researchers in the social-structural tradition— generally sociologists—are skeptical that personality plays a signiWcant role in determining whether an individual volunteers. In contrast, personality researchers, at times, have concluded that the demographic variables central to social-structural explanations are empirically unimportant in the prediction of volunteering (Omoto & Snyder, 1995), a Wnding that may reXect as much the samples of convenience often studied by psychologists as it does the genuine signiWcance of social-structural variables in the prediction of volunteering. Further, there is little consensus among researchers concerning the organization of constructs in their process models of volunteering. For instance, although some have suggested that the personality trait of extraversion might lead individuals to develop large social networks that, in turn, increase the likelihood of recruitment into volunteer roles (e.g., Wilson, 2000), others posit that both personality and social networks have direct, unmediated inXuences on volunteering (e.g., Omoto & Snyder, 1995). Finally, some have argued that organizational contexts inXuence role identity that in turn predicts volunteering (Grube & Piliavin, 2000), while others conceptualize organizational context as inXuencing identity and volunteering independently (Omoto & Snyder, 2002). Our goal was to test an integrative model of volunteering that incorporates many of the factors believed to inXuence volunteering as identiWed by the three traditions. Moreover, unlike previous investigations that used small samples of volunteers (e.g., AIDS volunteers and blood donors), we tested our model using a large, representative sample of American adults. 1.2. An integrative model of factors inXuencing volunteering 1.2.1. Enduring inXuences Our model is depicted in Fig. 1. Like the model of Omoto and Snyder (1995), our model captures developmental processes associated with volunteering. For example, Omoto and Snyder (1995) studied AIDS volunteers and described the Wrst stage in the volunteering
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M.K. Matsuba et al. / Journal of Research in Personality 41 (2007) 889–907 Enduring Influences
Personality Sympathy Empathy
Mediating Influences
Moral Cognition Judgment Moral/Civic Attitudes
Self & Identity Exploration Moral evaluation Salient ideals Commitment to ideals
Social Structure Family Culture Class
Volunteering
Opportunity Institutions Relationships
Fig. 1. Model of inXuences on volunteering.
process as the antecedents stage. Similarly, our model posits Enduring inXuences that represent those relatively stable characteristics of individuals, and are apparent early in life. Two classes of enduring inXuences are proposed. Personality, the Wrst of the two enduring inXuences, is positioned at the top left edge of the model. Personality traits are very stable characteristics of individuals (Costa & McCrae, 1994; Roberts & Del Vecchio, 2000). One way to imagine the constellation of traits associated with volunteering is as a personality type. Personality types are conWgurations of personality traits (see Hart, Atkins, & Fegley, 2003 for a discussion). The underlying assumption of personality type research is that there are relatively few combinations of traits that allow stable adjustment to life (Block, 1971). Recent research suggests that three personality types are regularly identiWed in children (e.g., Caspi, 1998) and adults (e.g., Asendorpf, Borkenau, Ostendorf, & van Aken, 2001). These types are usually labeled resilient, over-controlled, and under-controlled. Adults who exhibit the resilient type are sympathetic, extraverted, and positive in emotion (see Asendorpf et al., 2001). As suggested earlier, this proWle of characteristics is associated with prosocially motivated volunteering. Moreover, resilient adults are high in conscientiousness (Asendorpf et al., 2001), a trait that should be associated with the pursuit of activities that improve skills and increase knowledge. Consequently, the resilient personality type is characterized by traits that ought to be associated with forms of volunteering that have diVerent underlying motivations. The over-controlled personality type is characterized by high levels of generally negative aVect and by social withdrawal (Asendorpf et al., 2001), traits that our review earlier suggested are inconsistent with participation in volunteer activities. Finally, individuals of the under-controlled personality type are generally unsympathetic, aggressive, lack emotional control, and are low in conscientiousness (Asendorpf et al., 2001), all characteristics that ought to inhibit entry into volunteering. The other class of enduring inXuences includes the socio-economic, cultural, and demographic factors that inXuence volunteering (Hart, Atkins, Markey, & Youniss, 2004). A wealth of evidence exists showing that the more human capital an individual has the more
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likely that individual is to volunteer (Rosenthal, Feiring, & Lewis, 1998). For instance, numerous studies have found that volunteering increases with education and income (Smith, 1994). Further, highest rates of volunteering have been found to occur during middle age when most adults have completed their formal education and are approaching their income apexes (Wilson, 2000). So far we have discussed the enduring factors of the model that include personality and social factors associated with volunteering. These factors do not by themselves determine whether an individual will volunteer. As Clary et al. (1998) discussed, the motivations for volunteering and the psychological functions satisWed by volunteering vary across individuals. For example, for some the motivation to volunteer may be rooted in an interest in expressing an altruistic value while others may volunteer because it provides the opportunity to form or maintain social relationships. The proximal paths to volunteering are represented in the middle layer of our model. 1.2.2. Mediating inXuences The middle column in Fig. 1 captures the mediating inXuences in our model, and includes moral cognition, moral identity, and social opportunity. The broad construct of moral cognition includes more speciWc constructs such as moral reasoning and civic and moral obligations. Previous research suggests that individuals with higher levels of moral reasoning are more likely to act prosocially than individuals with lower levels of moral reasoning (Lapsley, 1996). Moreover, a number of studies have found that individuals with a greater sense of moral and civic obligations are more likely to volunteer than individuals who feel less obligated to take moral or civic action (Smith, 1994). Such a relationship Wnds support in Omoto and Snyder’s (2002) study of AIDS volunteers. The volunteers frequently referred to humanitarian obligations to explain the impetus for their work. Similar Wndings have emerged in other studies on volunteers (Hodgkinson & Weitzman, 1992; Wilson & Musick, 1997). Volunteering may also be motivated by moral identity. Several studies have explored self-identity and prosocial behavior show that an individual’s commitment to volunteering (Lydon & Zanna, 1990; Reich, 2000) and voluntary actions (Piliavin & Callero, 1991) are predicted by the degree to which one’s commitment is related to one’s identity. Central to moral identity is the salience of one’s prosocial traits and actions in awareness (Aquino & Reed, 2002; Lee et al., 1999), the belief that the self is committed to prosocial action into the future (Hart & Fegley, 1995), and the sense of personal eYcacy (Yates & Youniss, 1995). In our model, moral identity is the center block of the middle column and is designed to reXect these experiences and their combined relationship to volunteering. Finally, at the bottom of the middle column of Fig. 1 is a block corresponding to opportunities for entry into volunteer activities. Social networks generate opportunities for volunteering (Wilson, 2000). In contrast to caring, which is done privately, volunteering is typically a public form of altruism and much volunteering is done within the context of social organizations (Musick, Wilson, & Bynum, 2000). Not surprisingly, individuals who belong to clubs and religious organizations are more likely to volunteer than individuals without these social aYliations (Hart, Atkins, & Ford, 1998; Wilson, 2000). In addition, volunteers frequently report being recruited into their roles by friends and family (e.g., Independent Sector, 2001), which suggests that informal social relationships also increase opportunities for involvement in volunteer activities.
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1.3. Study overview We used Midlife in the United States (MIDUS) survey data to test the model depicted in Fig. 1. The sample of the MIDUS survey was representative in 1995 of American adults between the ages of 25 and 74. The representative nature of the sample allows accurate estimation of the relation of demographic factors to volunteering. The MIDUS survey included self-report measures of personality traits. We used these measures to identify personality types. Our prediction was that adults of the resilient personality type would be more likely to volunteer than would adults of the other two types. Second, we expected that personality’s inXuence on volunteering would be partially mediated through moral cognition, identity and opportunity. For example, as Wilson (2000) suggested, an extraverted personality may lead individuals to join groups where there are opportunities to volunteer. Indices of age, educational attainment, and income were included in our study to represent social structure. We predicted that these social-structural variables would predict volunteer work. Furthermore, we predicted that the impact of these social structure factors on volunteering would be partially mediated through moral opportunity, identity, and cognition. For example, with increased income comes more opportunities to volunteer (Wilson, 2000). Based on our review of the literature, we chose questions about civic obligation to represent one facet of the moral cognition construct. Our prediction was that individuals reporting high degrees of civic obligation would be more likely to volunteer than those reporting low levels of civic obligation (Omoto & Snyder, 1995). The construct of moral identity was tapped using questions assessing the extent to which participants judged that they control their contributions to the welfare of others, extend eVort to help others, and believe they would be helping others in the future. Our hypothesis was that those high on this measure of helping identity would be more likely to volunteer than those low on this measure (Grube & Piliavin, 2000). Opportunities were measured through questions tapping the frequency of attendance at religious or spiritual services, and the frequency of participants’ involvement in a variety of community meetings. We expected that individuals with frequent interactions with others in the community would be more likely to volunteer than those who have fewer interactions (Omoto & Snyder, 2002). Lastly, commitment to volunteering was indexed by the number of hours volunteered per month. Because we were interested in testing the factors that inXuence the level of commitment to volunteering, we initially excluded from the analyses those individuals who reported that they did no volunteering. In post hoc, exploratory analyses, non-volunteers were included, approximately doubling the size of our original sample, and contrasted volunteers to non-volunteers. To test our predictions, structural equation modeling was used. In the Wrst step of model testing, we constructed a measurement model corresponding to the center column in Fig. 1. In the second step, we tested a version of the model in Fig. 1 in which the eVects of the enduring inXuences (the left-hand column) on volunteering were fully mediated by the mediating inXuences. In the third step, we compared the model in Step 2 to a model in which the enduring inXuences were allowed to have direct as well as mediated eVects on volunteering. Based on the literature reviewed, we expected that the full (mediated and direct eVects) model would be a signiWcantly better Wtting model compared to the mediated-only model. In the fourth
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step involving post hoc analyses, we tested our model on the full set of data, which includes people who have reported no volunteer experiences, to determine whether the pattern of results were diVerent when we included these “no volunteer” participants. 2. Method 2.1. Participants The sampling strategy for the MIDUS was intended to obtain a representative sample of English-speaking American adults between the ages of 25 and 74 residing in households with telephones in the 48 contiguous states. Participants were contacted by phone, and those agreeing to participate in a study of health and well-being in mid-life completed both phone and mail-in surveys. Approximately 60% of those contacted by phone agreed to participate (for sampling details, see MacArthur Foundation Research Network on Successful Midlife Development, 1999). Out of the 4242 participants who completed the measures, 1454 (48% female) reported spending some time doing volunteer work in the past month. 2.2. Measures 2.2.1. Personality type Personality type was captured through the use of 30 items intended to reXect the trait domains of the Wve-factor model of personality. Participants judged the self-descriptiveness of each adjective using a four-point scale ranging from “not at all” to “a lot” (see Johnson & Krueger, 2003; for detailed analysis of these items). Examples of adjectives include “outgoing” (extraversion), “helpful” (agreeableness), “moody” (neuroticism), “organized” (conscientiousness), and “creative” (openness to experience). Scores on the 30 items were combined to form indices of the factors (Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness) in the Wve-factor model of personality (Costa & McCrae, 1992). Reliability for these scale scores ranged from .58 to .80 (Lachman & Weaver, 1997). Personality types were identiWed through k-means cluster analysis of these 30 items. K-means cluster analysis has been shown to be eVective in identifying taxa or classes, deWned as groups sharing multiple indicators, with the pattern of shared indicators diVerentiating groups from each other (Beauchaine & Beauchaine, 2002). K-means cluster analysis sorts cases into groups, or clusters, that minimize diVerences among members of each cluster. Drawing upon previous research within personality development, a three-cluster solution was speciWed to capture the personality types resilient, over-controlled and under-controlled that have been regularly identiWed in many types of data (see Hart et al., 2003). Fig. 2 depicts the mean scores for each of the traits in the Wve-factor model of personality for reach of the personality types. As in other studies (e.g., Asendorpf et al., 2001), the resilient cluster is characterized by traits suggesting extraversion (outgoing and lively), agreeableness (caring and warm), and openness (imaginative and curious). The over-controlled type is high in neuroticism (worrying, nervous, and low in self-conWdence). The under-controlled type is deWned by dominance and restlessness (dominant, forceful, and low score for calm) and a lack of concern for others (low scores for helpful, friendly, caring, and sympathetic). Dummy variables were created to code for personality types, with the resilient type as the comparison group (following the precedent in Hart et al., 2003).
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Fig. 2. Three major personality types by their Big Five Factor patterns.
2.2.2. Education Participants reported their educational attainment using a 12-point scale (ranging from no school/some grade school to a professional degree). 2.2.3. Household income Using a 12-point scale, participants reported their annual income from wages and investments, their spouses’/partners’ annual income from wages and investments, household social security income, household income from government assistance programs, and household income from all other sources. Total household income was estimated by summing income from all Wve types of income. The average household income was estimated at $52,205 (SD D $36,273). Because the distribution of income is positively skewed (few participants with very high family incomes), we used the log of family income in our analyses. 2.2.4. Demographics Participants reported their gender and age (in years). 2.2.5. Civic obligation This latent variable was constructed with three items tapping participants’ sense of obligation regarding civic issues. Using an 11-point scale (ranging from “none” to “very great”), participants were asked to report their feelings of obligation to (a) “serve on a jury if called,” (b) “keep fully informed about national news and public issues,” and (c)“vote in local and national elections.” 2.2.6. Helping identity This latent variable was captured using three items. Using an 11-point scale (ranging from “worst”/“no thought or eVort” to “best”/“very much thought or eVort”), participants responded to the following questions: “Looking ahead 10 years into the future, what do
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you expect your contribution to the welfare and well-being of other people will be like at that time?”; “How would you rate the amount of control you have over your contribution to the welfare and well-being of other people these days?”; and “How much thought and eVort do you put into your contribution to the welfare and well-being of other people these days?” 2.2.7. Opportunity Two indicators made up this latent construct. The Wrst indicator was a single item reXecting religious or spiritual community: On a Wve-point scale (ranging from “never” to “more than once a week”), participants were asked how often they “usually attend religious or spiritual services?” The second indicator reXected opportunities through group participation. Participants were asked “in a typical month, about how many times do you attend” group meetings involving sports, social, and other non-work-related activities? The number of times was summed, and then the log of that sum was computed to diminish the positive skew to this indicator. The two indicators were standardized. 2.2.8. Commitment to volunteering Hours per month spent volunteering reXected commitment to volunteering. Participants were asked “how many hours per month do you spend doing formal volunteer work of any of the following types?” The four types of volunteer work included “health-care-oriented,” “school or other youth-related,” “political organizations or causes,” and “any other organization, cause or charity.” Hours volunteered across the four types were summed. Because the distribution of hours volunteered per month was positively skewed, we transformed the data by taking the log of the sum. 3. Results 3.1. Analytic strategy In our primary analyses we focus on those participants (n D 1209) who reported one or more hours of volunteering, and who had a complete set of data on those variables of interest. In the Wrst step in model testing (using the AMOS 5 program, Arbuckle, 2003), the measurement model of our latent constructs was tested. In the second step, a hybrid model (including measures observed and mediating latent variables) was tested, demonstrating the indirect paths between enduring variables and volunteering. In the third step, this hybrid model was compared to a model in which the direct and indirect paths between enduring variables and volunteering were included. In the fourth step, we conducted post hoc analyses to determine model Wt when the full set of data (volunteers and non-volunteers) (n D 2953) was used. For the analyses in Steps 1–3, the sample was split in half for cross-validation purposes. To test and revise our models we used the data from one randomly selected sub-sample (n D 602). The Wnal model was then cross-validated on the second sub-sample (n D 607). Moreover, because our data were not multivariate normal, a bootstrapping approach was employed in our analyses. Bootstrapping involves drawing multiple sub-samples (with replacement) of the original sample, thus creating a bootstrapping sampling distribution for each parameter that is free from the assumptions of normality associated with the original sampling distribution (see Byrnes, 2001). Bootstrapping has been shown to be an
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Table 1 Cross-validation of models Model 1
Model 2
2
df
2
df
.987 .983 .984
11.71 16.96
5 13
5.25
8
.955 .956 .957
14.3 16.59
18 24
2.29
6
(c) Cross-validation of the full model (Volunteers and Non-volunteers) 1. Measurement intercepts 711.89 (125) .000 .040 .931 2. Structural weights 740.98 (149) .000 .037 .931 3. Structural means 745.20 (155) .000 .033 .931
29.09 33.31
24 30
4.22
6
2 (df)
p
(a) Cross-validation of the measurement model 1. Freely estimated 57.26 (34) .008 2. Measurement weights 68.97 (39) .002 3. Measurement intercepts 74.25 (47) .007
RMSEA
.026 .024 .022
(b) Cross-validation of the mediating model (Volunteers Only) 1. Measurement intercepts 258.45 (131) .000 .028 2. Structural weights 272.75 (149) .000 .026 3. Structural means 275.04 (155) .000 .025
CFI
eVective method of dealing with non-normal distributions (Baer, 2006; Nevitt & Hancock, 2001). 3.2. Step 1: Measurement model Civic obligation and helping identity each had three indicators, while opportunity had two indicators. Each of the indicators loaded moderately or highly on their latent construct. The measurement model was a very good Wt to the data from the Wrst sub-sample (n D 602), 2(34 df) D 57.26, p D .008; CFI D .987; RMSEA D .024. To determine measurement equivalence between the two sub-samples, we tested the eVects of constraining the loadings and intercepts on Wt. When invariance of the loadings and intercepts were forced, the model Wt was good in both cases (see Table 1a). This pattern of Wndings indicates that our constructs had equivalent measurement properties in the two independent subsamples. 3.3. Step 2: Mediating (indirect) eVects model The next step was to test the paths depicted in Fig. 3. The measurement model, with latent variables for civic obligation, helping identity, and opportunity, corresponds to the mediators depicted in Fig. 1. The measured variables of personality types, gender, age, income, and education reXect the enduring inXuences at the left edge of Fig. 1. The personality typology of resilient, over-controlled, and under-controlled was represented by two variables, over-controlled and under-controlled, which are dummy codes (the over-controlled variable is coded as 1 for those assigned to the over-controlled type and 0 for the other two types; the under-controlled variable is coded as 1 for those of the under-controlled type and as 0 for those of the other two types). Using half the data (n D 602), we tested a model positing that the eVects of the enduring inXuences on volunteering are indirect, and are fully mediated by civic obligation, helping identity, and opportunity. The model Wt was adequate, 2(116) D 385.70, p < .001; CFI D .904; RMSEA D .044.
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Over-controlled -.20** -.15**
Civic Obligation
.00
-.22**
Under-controlled
-.30** -.06
-.01
.05
Gender
.21** .06
Identity
.20**
Volunteering
.37**
Age
.12** .16** .18** .09** .15**
Education
.03
.06 .00
Income
Opportunity
-.01
Fig. 3. Mediating eVects model without paths of direct inXuences from personality and demographic factors to volunteer hours (Volunteers Only).
To potentially improve model Wt, we investigated the modiWcation indices and found that allowing age and the helping identity contribution indicator to covary would lead to a better Wtting model. This Wnding makes theoretical sense. Recall that this helping identity indicator asks participants to consider whether they expect to contribute to the welfare of others 10 years into the future. As people get older, they are less likely to be expecting themselves to be helping others 10 years into the future. When we allowed these parameters to covary, this new model was found to be a good Wt, 2(114) D 230.62, p < .001; CFI D .958; RMSEA D .029, and an improvement over the previous model, 2 D 155.08, df D 2, p < .001. To test our revised model, we cross-validated it using the second sub-sample (n D 607) by placing cross-group equality constraints on both measurement weights, intercepts and residuals, and on structural weights, intercepts and residuals, which is considered a conservative, “overly restrictive” test (Byrnes, 2001). Placing equality constraints did not diminish Wt; indeed, these constraints still resulted in good Wtting models. Table 1b presents only the measurement intercepts, structural weights and means constraint models,
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Table 2 Standardized indirect eVects between the enduring variables and volunteering Enduring variables
Indirect eVect (Volunteers Only)
Indirect eVects (Volunteers & Non-volunteers)
Over-controlled Under-controlled Gender Age Education Income
¡.030¤ ¡.070¤ .052¤ .051¤ .034¤ ¡.004
¡.053¤ ¡.079¤ .066¤¤ .089¤ .067¤ .018¤
¤ ¤¤
p < .05. p < .01.
because in cross-validating patterns of causal structure these parameters are most important (Byrnes, 2001). 3.4. Step 3: Full model (direct and indirect eVects) In the third step of model testing, we compared the mediating model described in the previous paragraph to a full, saturated model that allowed for the enduring inXuences to have both direct and mediated eVects on volunteering. Using half the data (n D 602), this full model also showed a good Wt to the data, 2(102 df) D 212.57, p < .001; CFI D .961; RMSEA D .030. This model did not produce a signiWcant improvement in Wt over the mediating eVects model (2 D 18.05, df D 12, p > .05). Consequently, the mediating eVects model, because it is more parsimonious, is preferred over the full model. 3.5. Mediated model: Direct and indirect eVects Because the mediating model could be cross-validated with the two samples, we collapsed the data together and ran the model using the full set of data (n D 1209). Not surprisingly this model also Wt the data well, 2(57 df) D 181.28, p < .001; CFI D .956; RMSEA D .042. Consistent with our hypotheses, the latent variables helping identity and opportunity all positively, and statistically signiWcantly (p < .01) predicted volunteer hours (see Fig. 3). However, civic obligation did not. In addition, personality, gender, age and education variables were found to have signiWcant indirect eVects (see Table 2).1 1 At the recommendation of one reviewer, we tested the mediating model substituting Big-5 dimension scores (agreeableness, neuroticism, openness to experience, extraversion and conscientiousness) for personality types: (1) with half the data randomly selected (n D 556), we found model Wt to be adequate, 2(152) D 443.94, p < .001; CFI D .925; RMSEA D .041; (2) to improve Wt, we investigated the modiWcation indices and found that allowing age and the helping identity contribution indicator to covary would lead to a better Wtting model, 2(150) D 309.99, p < .001; CFI D .959; RMSEA D .031 (2 D 133.95, df D 2, p < .001); (3) this Wnal model was cross-validated with the second sub-sample (n D 589) by placing cross-group equality constraints on both measurement weights, intercepts and residuals, and on structural weights, intercepts and residuals: (4) the two subsamples were collapsed to determine model Wt using the entire sample. Results indicated the data were a good Wt, 2(75 df) D 229.98, p < .001; CFI D .960; RMSEA D .043. Agreeableness and neuroticism were the only dimensions to have a signiWcant indirect eVect on volunteering. These Wndings show that the use of dimension scores do not improve the Wt of our model. The various Wt measures (CFI, RMSEA) show no improvement over those for the models using the personality type scores.
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3.6. Step 4: Mediating eVects model and full model with volunteers and non-volunteers In the fourth step, we explored model Wt when participants reporting no volunteering were added to our sample (n D 2953). This data set was randomly split in half, and parallel analyses were performed as done previously in Steps 1–3 on the halved data set (n D 1485). In the Wrst analysis, our mediating model was a good Wt to the data, 2(114 df) D 490.15, p < .001; CFI D .956; RMSEA D .033. In the second analysis, the full model also produced a good Wt to the data, 2(102 df) D 440.85, p < .001; CFI D .960; RMSEA D .034. In fact, the full model produced a signiWcant improvement in Wt over the mediating eVects model, 2 D 49.3, df D 12, p < .05. Further, we cross-validated our full model by placing cross-group equality constraints on both measurement weights, intercepts and residuals, and on structural weights, intercepts and residuals between the Wrst halved sample and the second halved sample (n D 1485). Again, these analyses demonstrated that the models with the equality constraints did not diVer from the unconstrained model (see Table 1c), thereby showing that the full model could be cross-validated. Because the full model could be cross-validated with the two samples, we collapsed the data together and ran the model using the full set of data (n D 2953). The model was a good Wt to the data, 2(51 df) D 401.60, p < .001; CFI D .959; RMSEA D .048. In terms of signiWcant direct pathways leading to volunteer hours, opportunity and identity were signiWcant as were under-controlled personality and education (see Fig. 4).2 As for indirect eVects, all the enduring variables were found to be signiWcant predictors of volunteer hours (see Table 2). 4. Discussion To reiterate, our goal in this research was to test a model of psychological and social inXuences on commitment to volunteering. The model posits that commitment to volunteering is a product of enduring, stable qualities of persons and their location in social structures and of more malleable features such as moral cognition, identity, and social opportunities. Moreover, our model predicted that the inXuences of the enduring stable qualities on commitment to volunteering are mediated in part by moral cognition, identity, and opportunity. Using structural equation modeling, we found support for a model in which the enduring qualities aVected volunteering through our set of mediating constructs when tested on volunteers from a large, nationally representative, cross-sectional sample of American adults. And when data from volunteers and non-volunteers were merged, our full model of direct and mediating eVects emerged as a better Wt than the mediating model. When volunteers were studied separately, our results show that both helping identity and social opportunities contributed to volunteering. Individuals who think about their contributions to others, feel that they control their contributions to the welfare of others, and feel that they will make important contributions to the welfare of others, are more committed to volunteering than are those who do not share these characteristics. These Wndings are consistent with theories that emphasize the centrality of identity for understanding sustained prosocial behavior (Hart, 2005; Lee et al., 1999).
2
To simplify the Wgure, only signiWcant paths are reported—¤p < .05; ¤¤p < .01.
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-.17**
Over-controlled
-.16** -.05*
Civic Obligation
-.19**
Under-controlled
.04* -.25**
-.08**
.05*
Gender
.19** .09**
Identity
.18**
Volunteering
.36** .09**
Age
.17**
.14**
Education
.34** .09** .08** .13**
.08** .06**
Opportunity
Income Fig. 4. Full eVects model with paths of direct and indirect inXuences from personality and demographic factors to volunteer hours (Volunteers and Non-volunteers).
Second, participation in the community was also predictive of involvement in hours of volunteering, suggesting that increased community activity creates more opportunities for people to increase their hours of volunteering. Although we found positive associations between our mediating factors of identity and opportunity with hours volunteered, the parameter estimate for the path from civic obligation to hours volunteered was near zero and non-signiWcant. Perhaps our measure of civic obligation, which includes items concerning voting in elections, serving on a jury, and being informed about public issues, is too narrowly focused on governmental aVairs to capture a sense of obligation to the broader community that might culminate in volunteering. Interestingly, however, longitudinal research (Hart, Donnelly, Youniss, & Atkins, in press) has similarly found only the weakest of evidence for the eVects of adolescent civic attitudes on volunteering in early adulthood, controlling for the eVects of a variety of background factors. The possibility exists that civic concerns play less of a role in the motivation of volunteering than previously believed. Another possible explanation relates to an historical trend on the motivation to volunteer: perhaps in the past, volunteering reXected civic motivation more so than
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in the present epoch, in which volunteering may be motivated by individual-oriented rather than civic-oriented goals (see Hart et al., in press for a discussion). Future research might beneWt from a consideration of a more diVerentiated, broader notion of civic obligation, as well as to consider distinguish among types of volunteering. Our results also showed all of the enduring factors had an indirect eVect on volunteering with the exception of income. For example, the tendency for women to volunteer more hours than men is accounted for by diVerences between the genders in the salience of a helping identity. Similarly, our results help explain the relation of personality to volunteering that, although robust, has been poorly understood (e.g., Atkins et al., 2005). In this study, compared to resilient individuals, both overcontrolled and under-controlled adults judged themselves to have less salient helping identities which are associated with a reduction in volunteering. An issue for future research is the nature of the relation of personality types to identity. Although theorists believe that the theoretical personality processes corresponding to our identity latent variable—identity, self, and self-eYcacy—are more malleable and less temporally stable than personality dispositions, traits, and types (Mischel & Shoda, 1998), empirical research suggests that the distinction is less clear than often assumed (Judge, Erez, Bono, & Thoresen, 2002). Consequently, a more accurate representation of the processes involved in volunteering may demand Venn diagrams in which constructs partially subsume each other instead of Fig. 1’s depiction of independent, separable processes. Alternatively, diVerentiation of identity and personality may be clearest for identities articulated within contexts, such as blood donor (Piliavin & Callero, 1991). Our measure of identity, which reXected indicators of commitment to help in the future, the experience of oneself as prosocially eYcacious, and the salience of helping in awareness—all key qualities of identity—did not capture the intertwining of identity and social context that is necessary for full accounts of identity development (for a discussion, see Hart & Yates, 1997). Context-speciWc identities are clearly distinct from personality traits and types, and are more likely to change than personality. Finally, like others (e.g., Wilson, 2000), we found evidence for the relations of age and education commitment to volunteer. People who are older and more educated devote more hours to volunteering, with these associations being mediated by helping identity and opportunities through community participation. When data from non-volunteers were added, the patterns of results did not change drastically. Yet a few Wndings are worth mentioning: First, the link between opportunity to volunteering increased in strength with the addition of non-volunteers suggesting that getting people involved in their community may be an important initial step in them making a commitment towards volunteering. This Wnding is consistent with research suggesting that people volunteer because they are in the contexts in which they are asked to do so (Independent Sector, 2001; Wilson, 2000). Moreover, with the addition of non-volunteers, personality types, gender, and education became signiWcant predictors of opportunity, along with age. Together, these results suggest that among volunteers, being resilient, female, and more educated make no diVerence in the number of hours of volunteering via their inXuence on community involvement. However, these enduring variables may be important in the decision to volunteer by inXuencing the initial step of getting them involved in their community.
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Finally, with non-volunteers added to our analyses, a few direct eVects emerged. Curiously, the under-controlled personality type had a small positive but signiWcant direct eVect on volunteering. A possible explanation is that under-controlled individuals are impulsive and physically active (Hart et al., 2003), and so volunteering could be one of many avenues they use to direct their energies. However, given the small eVect, further research is needed to test the robustness of this Wnding. A second direct eVect emerged between education and volunteering, and is consistent with past research (Wilson, 2000). Our results suggest that education’s eVect on volunteering follows many paths, both direct and indirect depending on the research context. That is, for volunteers, education seems to have an indirect eVect on the amount they will volunteer. However, when non-volunteers are added, the paths of inXuence change, suggesting that education’s eVect is greater on the decision to volunteer rather than on the number of hours volunteered. In fact, this may be true of all enduring variables given that their indirect eVects were greater when non-volunteers were added to the volunteers sample than when volunteers were considered alone. Together, our results and model integrate lines of work from other research traditions on volunteering, although a number of issues remain unresolved. For example, at a conceptual level, our measures may not fully capture the richness of the theoretical constructs articulated in each research tradition. Some personality psychologists might suggest that the measurement of very speciWc traits would result in better prediction of volunteering than the broad personality types used in this study (though our analyses demonstrate that the types predict volunteering as well as the Wve dimensions of the five factor model); similarly, those who situate volunteering within the social niches deWned by income, neighborhood, age, and race/ethnicity are likely to be dissatisWed by our global measures of social structure. These are questions that are best addressed by those working within each tradition. Our goal in proposing an integrative model was not to displace the theories oVered by personality, identity, and social-structural researchers, but instead to suggest that the theories can complement each other in understanding commitment to volunteering. We believe that the Wndings in this study—even though they do not measure every quality of interest to researchers in the three traditions—do advance this more modest goal. Another limitation of this study is the fact that causal connections among the various constructs cannot be determined. Although we have modeled the paths from enduring variables such as personality through mediating factors such as identity to volunteering behavior, it is likely that the inXuences between some of these factors are more transactional in nature with volunteering impacting the mediating variables such as identity and opportunities. Stronger inferences about causal pathways await studies employing longitudinal data rather than the cross-sectional data used in this study.3 An experimental study, in which some of these factors were manipulated, would be the ideal design; however, many of the variables in this model probably cannot be controlled through experimental intervention. It should also be noted that although most of our constructs have statistically signiWcant associations with volunteering, none of them is strongly predictive. One possible rea-
3
The sample in this study was assessed a second time, and these data may become available to the public in 2007. A second wave of data would permit longitudinal assessments of the model.
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son for the weak eVects is that volunteering is multidimensional, having multiple motivations, and occurs in many diVerent contexts. These diVerent motivations and contexts aVect involvement in volunteering in diverse ways that cannot be parsimoniously incorporated into a single model. However, the complexity of volunteering, and the shortcomings of the model proposed in this paper, should encourage—rather than discourage— research into a topic that is both theoretically rich and socially important. Further research that illustrates such complexity awaits. References Aquino, K., & Reed, A. (2002). The self-importance of moral identity. Journal of Personality and Social Psychology, 83, 1423–1440. Arbuckle, J. L. (2003). Amos 5.0 update to the Amos user’s guide. Chicago, IL: SPSS. Asendorpf, J. B., Borkenau, P., Ostendorf, F., & van Aken, M. A. G. (2001). Carving personality description at its joints: conWrmation of three replicable personality prototypes for both children and adults. European Journal of Personality, 15, 169–198. Atkins, R., Hart, D., & Donnelly, T. M. (2005). The inXuence of childhood personality on volunteering during adolescence. Merrill-Palmer Quarterly, 51, 145–162. Baer, D. (2006). Latent variable structural equation models. Unpublished manuscript. Beauchaine, T. P., & Beauchaine, R. J. (2002). A comparison of maximum covariance and K-means cluster analysis in classifying cases into known taxon groups. Psychological Methods, 7, 245–261. Block, J. (1971). Lives through time. Berkeley: Bancroft. Bureau of Labor Statistics. (2005). Volunteering in the United States, 2005. Retrieved April 28, 2006 from
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Hart, D., & Yates, M. (1997). Identity and self in adolescence. In R. Vasta (Ed.), Annals of child development, 1996 (pp. 207–242). London: Jessica Kingsley. Hodgkinson, V., & Weitzman, M. (1992). Giving and volunteering in the United States. Washington, DC: Independent Sector. Independent Sector (2001, November). Giving and volunteering in the United States. Retrieved October 17, 2003 from
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Unger, L. S., & Thumuluri, L. K. (1997). Trait empathy and continuous helping: the case of voluntarism. Journal of Social Behavior and Personality, 12, 785–800. Wilson, J. (2000). Volunteering. Annual Review of Sociology, 26, 215–240. Wilson, J., & Musick, M. (1997). Who cares? Toward an integrated theory of volunteer work. American Sociological Review, 62, 694–713. Yates, M., & Youniss, J. (1995). A developmental perspective on community service in adolescence. Social Development, 5, 85–111.
Psychological and social-structural inXuences on commitment to volunteering 夽 M. Kyle Matsuba a,¤, Daniel Hart b,¤, Robert Atkins b a
Psychology Department, University of Northern British Columbia, 3333 University Way, Prince George, BC, Canada V2N 4Z9 b Center for Children and Childhood Studies, Rutgers University, 405/407 Cooper Street, Camden, NJ 08102, USA Available online 4 January 2007
Abstract A model is described in which commitment to volunteering is hypothesized to be the result of demographic qualities, personality, identity, values, and social relationships. The model is tested and cross-validated using data from a nationally representative sample of American adults. The results from structural equation modeling analyses suggest that the hypothetical model provides a good Wt to the data. Moreover, the Wndings suggest that the relations of personality and demographic characteristics to hours devoted to volunteering are largely mediated by latent constructs capturing helping identity and community participation. The implications of the model and the Wndings for our understanding of volunteering are discussed. © 2007 Published by Elsevier Inc. Keywords: Volunteering; Personality type; Identity; Altruism
1. Introduction Volunteers make a substantial contribution to the health and functioning of many societies. Recent surveys indicate that large fractions of adults in the United States volunteer (estimates range between 28%, Bureau of Labor Statistics, 2005; and 44%, Independent Sector, 2005). The annual monetary value of this donated labor is calculated to be more 夽 *
The support of the W. T. Grant Foundation is gratefully acknowledged. Corresponding authors. E-mail addresses: [email protected] (M.K. Matsuba), [email protected] (D. Hart).
0092-6566/$ - see front matter © 2007 Published by Elsevier Inc. doi:10.1016/j.jrp.2006.11.001
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than 280 billion dollars (Independent Sector, 2005). Interest in volunteering is triggered not only by its importance to the civic well-being of our society but by its unique psychological qualities—volunteering is planned, generally sustained over time, multiply motivated and voluntary (Omoto & Snyder, 1995; Penner, 2002)—that distinguish it from the reactive and automatic prosocial behaviors most familiar to researchers (e.g., helping; for a review, see Penner, Dovidio, Piliavin, & Schroeder, 2005). The combination of civic importance and distinctive characteristics makes volunteering an important topic for study. 1.1. Three research traditions Our goal in this paper is to test a model of the psychological and social inXuences on the number of hours volunteered per month, the latter indexing involvement in volunteering. The model tested in this study derives from the social-structural, personality, and identity research traditions. The social-structural approach aims to specify the combination of social roles and social class attributes that are associated with volunteering. Wilson (2000) concluded that there is considerable evidence showing that age, gender, educational attainment, household income, and the breadth of an individual’s social network are predictors of volunteering. Thus, the model tested in this study includes these social-structural factors. Personality research, broadly deWned, has focused on the motives and traits that lead individuals to volunteer, and to persist in their volunteering. Based on the past work, suYcient evidence has emerged for researchers to reach three conclusions regarding the link between personality and volunteering. First, people are motivated to volunteer for diVerent reasons, and these motives inXuence the longevity of service (Clary et al., 1998; Omoto & Snyder, 1995). For instance, Omoto and Snyder (1995) identiWed Wve motives associated with AIDS volunteering including values, understanding, personal development, community concern, and esteem enhancement. Second, research indicates that personality traits related to positive emotions, social skillfulness, sympathy, and emotion regulation are more prominent in volunteers than in non-volunteers (e.g., Davis et al., 1999; Omoto & Snyder, 1995; Penner, Fritzsche, Craiger, & Freifeld, 1995; Unger & Thumuluri, 1997). Third, the available research indicates that there is a broad proWle of personality dispositions related to volunteering, and that volunteers cannot be distinguished from non-volunteers by the presence of a single discrete, narrow trait. As Penner (2002, p. 450) concluded, “one relatively speciWc personality trait is unlikely to be related to a wide range of helping behaviors.” In one of the strongest demonstrations of the eVects of personality on volunteering, Atkins, Hart, and Donnelly (2005) found that school-age children characterized by a trait proWle suggesting resilience—compliant, socially skillful, and with positive emotional tone—were more likely to be volunteers as adolescents than were children whose trait proWles suggested either an over-controlled or an under-controlled personality type. The fact that personality was measured years before most children engage in volunteering suggests that the resilient personality proWle leads to volunteering, rather than being shaped by it. Atkins and colleagues also found that adding speciWc childhood personality trait dimensions did not improve the link between personality types and volunteering. In the third tradition, researchers of identity (e.g., Grube & Piliavin, 2000; Piliavin & Callero, 1991) have focused on the transformation of the sense of self that is aVected by, and that in turn sustains, volunteering. For example, Piliavin and Callero (1991) studied the emergence of the role identity of blood donor among those who regularly volunteered to
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give blood. They found that those volunteers for whom the identity was elaborated and salient were more likely to persist over time in blood donation. Lee, Piliavin, and Call (1999), using a nationally representative survey, found that those who reported thinking a lot about their identities as donors judged the likelihood of future donations to be higher than those for whom donor identities were less salient in consciousness. Finally, Hart and Fegley (1995) found that adolescents deeply engaged in volunteer community service viewed their activities as integral components of themselves in the future and of their ideal selves, a constellation of self-representations suggesting that the volunteer activities had been synthesized into their identities. There are points of consensus and disagreement across the three traditions. First, there is consensus among the three traditions that volunteering is partly motivated by ethical and civic values (e.g., Janoski, Musick, & Wilson, 1995; Omoto & Snyder, 1995), although there is disagreement about whether such values constitute a separate construct (e.g., Janoski et al., 1995) or are facets of other constructs such as personality (e.g. Omoto & Snyder, 1995). Moreover, studies within all three traditions (e.g., Grube & Piliavin, 2000; Penner, 2002) regularly report that demographic factors such as educational attainment distinguish between volunteers and non-volunteers. The three traditions oVer substantially divergent views on the relative importance of various factors that inXuence volunteering, and how these factors might interact. For example, Wilson (2000) reported that most researchers in the social-structural tradition— generally sociologists—are skeptical that personality plays a signiWcant role in determining whether an individual volunteers. In contrast, personality researchers, at times, have concluded that the demographic variables central to social-structural explanations are empirically unimportant in the prediction of volunteering (Omoto & Snyder, 1995), a Wnding that may reXect as much the samples of convenience often studied by psychologists as it does the genuine signiWcance of social-structural variables in the prediction of volunteering. Further, there is little consensus among researchers concerning the organization of constructs in their process models of volunteering. For instance, although some have suggested that the personality trait of extraversion might lead individuals to develop large social networks that, in turn, increase the likelihood of recruitment into volunteer roles (e.g., Wilson, 2000), others posit that both personality and social networks have direct, unmediated inXuences on volunteering (e.g., Omoto & Snyder, 1995). Finally, some have argued that organizational contexts inXuence role identity that in turn predicts volunteering (Grube & Piliavin, 2000), while others conceptualize organizational context as inXuencing identity and volunteering independently (Omoto & Snyder, 2002). Our goal was to test an integrative model of volunteering that incorporates many of the factors believed to inXuence volunteering as identiWed by the three traditions. Moreover, unlike previous investigations that used small samples of volunteers (e.g., AIDS volunteers and blood donors), we tested our model using a large, representative sample of American adults. 1.2. An integrative model of factors inXuencing volunteering 1.2.1. Enduring inXuences Our model is depicted in Fig. 1. Like the model of Omoto and Snyder (1995), our model captures developmental processes associated with volunteering. For example, Omoto and Snyder (1995) studied AIDS volunteers and described the Wrst stage in the volunteering
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Personality Sympathy Empathy
Mediating Influences
Moral Cognition Judgment Moral/Civic Attitudes
Self & Identity Exploration Moral evaluation Salient ideals Commitment to ideals
Social Structure Family Culture Class
Volunteering
Opportunity Institutions Relationships
Fig. 1. Model of inXuences on volunteering.
process as the antecedents stage. Similarly, our model posits Enduring inXuences that represent those relatively stable characteristics of individuals, and are apparent early in life. Two classes of enduring inXuences are proposed. Personality, the Wrst of the two enduring inXuences, is positioned at the top left edge of the model. Personality traits are very stable characteristics of individuals (Costa & McCrae, 1994; Roberts & Del Vecchio, 2000). One way to imagine the constellation of traits associated with volunteering is as a personality type. Personality types are conWgurations of personality traits (see Hart, Atkins, & Fegley, 2003 for a discussion). The underlying assumption of personality type research is that there are relatively few combinations of traits that allow stable adjustment to life (Block, 1971). Recent research suggests that three personality types are regularly identiWed in children (e.g., Caspi, 1998) and adults (e.g., Asendorpf, Borkenau, Ostendorf, & van Aken, 2001). These types are usually labeled resilient, over-controlled, and under-controlled. Adults who exhibit the resilient type are sympathetic, extraverted, and positive in emotion (see Asendorpf et al., 2001). As suggested earlier, this proWle of characteristics is associated with prosocially motivated volunteering. Moreover, resilient adults are high in conscientiousness (Asendorpf et al., 2001), a trait that should be associated with the pursuit of activities that improve skills and increase knowledge. Consequently, the resilient personality type is characterized by traits that ought to be associated with forms of volunteering that have diVerent underlying motivations. The over-controlled personality type is characterized by high levels of generally negative aVect and by social withdrawal (Asendorpf et al., 2001), traits that our review earlier suggested are inconsistent with participation in volunteer activities. Finally, individuals of the under-controlled personality type are generally unsympathetic, aggressive, lack emotional control, and are low in conscientiousness (Asendorpf et al., 2001), all characteristics that ought to inhibit entry into volunteering. The other class of enduring inXuences includes the socio-economic, cultural, and demographic factors that inXuence volunteering (Hart, Atkins, Markey, & Youniss, 2004). A wealth of evidence exists showing that the more human capital an individual has the more
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likely that individual is to volunteer (Rosenthal, Feiring, & Lewis, 1998). For instance, numerous studies have found that volunteering increases with education and income (Smith, 1994). Further, highest rates of volunteering have been found to occur during middle age when most adults have completed their formal education and are approaching their income apexes (Wilson, 2000). So far we have discussed the enduring factors of the model that include personality and social factors associated with volunteering. These factors do not by themselves determine whether an individual will volunteer. As Clary et al. (1998) discussed, the motivations for volunteering and the psychological functions satisWed by volunteering vary across individuals. For example, for some the motivation to volunteer may be rooted in an interest in expressing an altruistic value while others may volunteer because it provides the opportunity to form or maintain social relationships. The proximal paths to volunteering are represented in the middle layer of our model. 1.2.2. Mediating inXuences The middle column in Fig. 1 captures the mediating inXuences in our model, and includes moral cognition, moral identity, and social opportunity. The broad construct of moral cognition includes more speciWc constructs such as moral reasoning and civic and moral obligations. Previous research suggests that individuals with higher levels of moral reasoning are more likely to act prosocially than individuals with lower levels of moral reasoning (Lapsley, 1996). Moreover, a number of studies have found that individuals with a greater sense of moral and civic obligations are more likely to volunteer than individuals who feel less obligated to take moral or civic action (Smith, 1994). Such a relationship Wnds support in Omoto and Snyder’s (2002) study of AIDS volunteers. The volunteers frequently referred to humanitarian obligations to explain the impetus for their work. Similar Wndings have emerged in other studies on volunteers (Hodgkinson & Weitzman, 1992; Wilson & Musick, 1997). Volunteering may also be motivated by moral identity. Several studies have explored self-identity and prosocial behavior show that an individual’s commitment to volunteering (Lydon & Zanna, 1990; Reich, 2000) and voluntary actions (Piliavin & Callero, 1991) are predicted by the degree to which one’s commitment is related to one’s identity. Central to moral identity is the salience of one’s prosocial traits and actions in awareness (Aquino & Reed, 2002; Lee et al., 1999), the belief that the self is committed to prosocial action into the future (Hart & Fegley, 1995), and the sense of personal eYcacy (Yates & Youniss, 1995). In our model, moral identity is the center block of the middle column and is designed to reXect these experiences and their combined relationship to volunteering. Finally, at the bottom of the middle column of Fig. 1 is a block corresponding to opportunities for entry into volunteer activities. Social networks generate opportunities for volunteering (Wilson, 2000). In contrast to caring, which is done privately, volunteering is typically a public form of altruism and much volunteering is done within the context of social organizations (Musick, Wilson, & Bynum, 2000). Not surprisingly, individuals who belong to clubs and religious organizations are more likely to volunteer than individuals without these social aYliations (Hart, Atkins, & Ford, 1998; Wilson, 2000). In addition, volunteers frequently report being recruited into their roles by friends and family (e.g., Independent Sector, 2001), which suggests that informal social relationships also increase opportunities for involvement in volunteer activities.
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1.3. Study overview We used Midlife in the United States (MIDUS) survey data to test the model depicted in Fig. 1. The sample of the MIDUS survey was representative in 1995 of American adults between the ages of 25 and 74. The representative nature of the sample allows accurate estimation of the relation of demographic factors to volunteering. The MIDUS survey included self-report measures of personality traits. We used these measures to identify personality types. Our prediction was that adults of the resilient personality type would be more likely to volunteer than would adults of the other two types. Second, we expected that personality’s inXuence on volunteering would be partially mediated through moral cognition, identity and opportunity. For example, as Wilson (2000) suggested, an extraverted personality may lead individuals to join groups where there are opportunities to volunteer. Indices of age, educational attainment, and income were included in our study to represent social structure. We predicted that these social-structural variables would predict volunteer work. Furthermore, we predicted that the impact of these social structure factors on volunteering would be partially mediated through moral opportunity, identity, and cognition. For example, with increased income comes more opportunities to volunteer (Wilson, 2000). Based on our review of the literature, we chose questions about civic obligation to represent one facet of the moral cognition construct. Our prediction was that individuals reporting high degrees of civic obligation would be more likely to volunteer than those reporting low levels of civic obligation (Omoto & Snyder, 1995). The construct of moral identity was tapped using questions assessing the extent to which participants judged that they control their contributions to the welfare of others, extend eVort to help others, and believe they would be helping others in the future. Our hypothesis was that those high on this measure of helping identity would be more likely to volunteer than those low on this measure (Grube & Piliavin, 2000). Opportunities were measured through questions tapping the frequency of attendance at religious or spiritual services, and the frequency of participants’ involvement in a variety of community meetings. We expected that individuals with frequent interactions with others in the community would be more likely to volunteer than those who have fewer interactions (Omoto & Snyder, 2002). Lastly, commitment to volunteering was indexed by the number of hours volunteered per month. Because we were interested in testing the factors that inXuence the level of commitment to volunteering, we initially excluded from the analyses those individuals who reported that they did no volunteering. In post hoc, exploratory analyses, non-volunteers were included, approximately doubling the size of our original sample, and contrasted volunteers to non-volunteers. To test our predictions, structural equation modeling was used. In the Wrst step of model testing, we constructed a measurement model corresponding to the center column in Fig. 1. In the second step, we tested a version of the model in Fig. 1 in which the eVects of the enduring inXuences (the left-hand column) on volunteering were fully mediated by the mediating inXuences. In the third step, we compared the model in Step 2 to a model in which the enduring inXuences were allowed to have direct as well as mediated eVects on volunteering. Based on the literature reviewed, we expected that the full (mediated and direct eVects) model would be a signiWcantly better Wtting model compared to the mediated-only model. In the fourth
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step involving post hoc analyses, we tested our model on the full set of data, which includes people who have reported no volunteer experiences, to determine whether the pattern of results were diVerent when we included these “no volunteer” participants. 2. Method 2.1. Participants The sampling strategy for the MIDUS was intended to obtain a representative sample of English-speaking American adults between the ages of 25 and 74 residing in households with telephones in the 48 contiguous states. Participants were contacted by phone, and those agreeing to participate in a study of health and well-being in mid-life completed both phone and mail-in surveys. Approximately 60% of those contacted by phone agreed to participate (for sampling details, see MacArthur Foundation Research Network on Successful Midlife Development, 1999). Out of the 4242 participants who completed the measures, 1454 (48% female) reported spending some time doing volunteer work in the past month. 2.2. Measures 2.2.1. Personality type Personality type was captured through the use of 30 items intended to reXect the trait domains of the Wve-factor model of personality. Participants judged the self-descriptiveness of each adjective using a four-point scale ranging from “not at all” to “a lot” (see Johnson & Krueger, 2003; for detailed analysis of these items). Examples of adjectives include “outgoing” (extraversion), “helpful” (agreeableness), “moody” (neuroticism), “organized” (conscientiousness), and “creative” (openness to experience). Scores on the 30 items were combined to form indices of the factors (Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness) in the Wve-factor model of personality (Costa & McCrae, 1992). Reliability for these scale scores ranged from .58 to .80 (Lachman & Weaver, 1997). Personality types were identiWed through k-means cluster analysis of these 30 items. K-means cluster analysis has been shown to be eVective in identifying taxa or classes, deWned as groups sharing multiple indicators, with the pattern of shared indicators diVerentiating groups from each other (Beauchaine & Beauchaine, 2002). K-means cluster analysis sorts cases into groups, or clusters, that minimize diVerences among members of each cluster. Drawing upon previous research within personality development, a three-cluster solution was speciWed to capture the personality types resilient, over-controlled and under-controlled that have been regularly identiWed in many types of data (see Hart et al., 2003). Fig. 2 depicts the mean scores for each of the traits in the Wve-factor model of personality for reach of the personality types. As in other studies (e.g., Asendorpf et al., 2001), the resilient cluster is characterized by traits suggesting extraversion (outgoing and lively), agreeableness (caring and warm), and openness (imaginative and curious). The over-controlled type is high in neuroticism (worrying, nervous, and low in self-conWdence). The under-controlled type is deWned by dominance and restlessness (dominant, forceful, and low score for calm) and a lack of concern for others (low scores for helpful, friendly, caring, and sympathetic). Dummy variables were created to code for personality types, with the resilient type as the comparison group (following the precedent in Hart et al., 2003).
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Fig. 2. Three major personality types by their Big Five Factor patterns.
2.2.2. Education Participants reported their educational attainment using a 12-point scale (ranging from no school/some grade school to a professional degree). 2.2.3. Household income Using a 12-point scale, participants reported their annual income from wages and investments, their spouses’/partners’ annual income from wages and investments, household social security income, household income from government assistance programs, and household income from all other sources. Total household income was estimated by summing income from all Wve types of income. The average household income was estimated at $52,205 (SD D $36,273). Because the distribution of income is positively skewed (few participants with very high family incomes), we used the log of family income in our analyses. 2.2.4. Demographics Participants reported their gender and age (in years). 2.2.5. Civic obligation This latent variable was constructed with three items tapping participants’ sense of obligation regarding civic issues. Using an 11-point scale (ranging from “none” to “very great”), participants were asked to report their feelings of obligation to (a) “serve on a jury if called,” (b) “keep fully informed about national news and public issues,” and (c)“vote in local and national elections.” 2.2.6. Helping identity This latent variable was captured using three items. Using an 11-point scale (ranging from “worst”/“no thought or eVort” to “best”/“very much thought or eVort”), participants responded to the following questions: “Looking ahead 10 years into the future, what do
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you expect your contribution to the welfare and well-being of other people will be like at that time?”; “How would you rate the amount of control you have over your contribution to the welfare and well-being of other people these days?”; and “How much thought and eVort do you put into your contribution to the welfare and well-being of other people these days?” 2.2.7. Opportunity Two indicators made up this latent construct. The Wrst indicator was a single item reXecting religious or spiritual community: On a Wve-point scale (ranging from “never” to “more than once a week”), participants were asked how often they “usually attend religious or spiritual services?” The second indicator reXected opportunities through group participation. Participants were asked “in a typical month, about how many times do you attend” group meetings involving sports, social, and other non-work-related activities? The number of times was summed, and then the log of that sum was computed to diminish the positive skew to this indicator. The two indicators were standardized. 2.2.8. Commitment to volunteering Hours per month spent volunteering reXected commitment to volunteering. Participants were asked “how many hours per month do you spend doing formal volunteer work of any of the following types?” The four types of volunteer work included “health-care-oriented,” “school or other youth-related,” “political organizations or causes,” and “any other organization, cause or charity.” Hours volunteered across the four types were summed. Because the distribution of hours volunteered per month was positively skewed, we transformed the data by taking the log of the sum. 3. Results 3.1. Analytic strategy In our primary analyses we focus on those participants (n D 1209) who reported one or more hours of volunteering, and who had a complete set of data on those variables of interest. In the Wrst step in model testing (using the AMOS 5 program, Arbuckle, 2003), the measurement model of our latent constructs was tested. In the second step, a hybrid model (including measures observed and mediating latent variables) was tested, demonstrating the indirect paths between enduring variables and volunteering. In the third step, this hybrid model was compared to a model in which the direct and indirect paths between enduring variables and volunteering were included. In the fourth step, we conducted post hoc analyses to determine model Wt when the full set of data (volunteers and non-volunteers) (n D 2953) was used. For the analyses in Steps 1–3, the sample was split in half for cross-validation purposes. To test and revise our models we used the data from one randomly selected sub-sample (n D 602). The Wnal model was then cross-validated on the second sub-sample (n D 607). Moreover, because our data were not multivariate normal, a bootstrapping approach was employed in our analyses. Bootstrapping involves drawing multiple sub-samples (with replacement) of the original sample, thus creating a bootstrapping sampling distribution for each parameter that is free from the assumptions of normality associated with the original sampling distribution (see Byrnes, 2001). Bootstrapping has been shown to be an
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Table 1 Cross-validation of models Model 1
Model 2
2
df
2
df
.987 .983 .984
11.71 16.96
5 13
5.25
8
.955 .956 .957
14.3 16.59
18 24
2.29
6
(c) Cross-validation of the full model (Volunteers and Non-volunteers) 1. Measurement intercepts 711.89 (125) .000 .040 .931 2. Structural weights 740.98 (149) .000 .037 .931 3. Structural means 745.20 (155) .000 .033 .931
29.09 33.31
24 30
4.22
6
2 (df)
p
(a) Cross-validation of the measurement model 1. Freely estimated 57.26 (34) .008 2. Measurement weights 68.97 (39) .002 3. Measurement intercepts 74.25 (47) .007
RMSEA
.026 .024 .022
(b) Cross-validation of the mediating model (Volunteers Only) 1. Measurement intercepts 258.45 (131) .000 .028 2. Structural weights 272.75 (149) .000 .026 3. Structural means 275.04 (155) .000 .025
CFI
eVective method of dealing with non-normal distributions (Baer, 2006; Nevitt & Hancock, 2001). 3.2. Step 1: Measurement model Civic obligation and helping identity each had three indicators, while opportunity had two indicators. Each of the indicators loaded moderately or highly on their latent construct. The measurement model was a very good Wt to the data from the Wrst sub-sample (n D 602), 2(34 df) D 57.26, p D .008; CFI D .987; RMSEA D .024. To determine measurement equivalence between the two sub-samples, we tested the eVects of constraining the loadings and intercepts on Wt. When invariance of the loadings and intercepts were forced, the model Wt was good in both cases (see Table 1a). This pattern of Wndings indicates that our constructs had equivalent measurement properties in the two independent subsamples. 3.3. Step 2: Mediating (indirect) eVects model The next step was to test the paths depicted in Fig. 3. The measurement model, with latent variables for civic obligation, helping identity, and opportunity, corresponds to the mediators depicted in Fig. 1. The measured variables of personality types, gender, age, income, and education reXect the enduring inXuences at the left edge of Fig. 1. The personality typology of resilient, over-controlled, and under-controlled was represented by two variables, over-controlled and under-controlled, which are dummy codes (the over-controlled variable is coded as 1 for those assigned to the over-controlled type and 0 for the other two types; the under-controlled variable is coded as 1 for those of the under-controlled type and as 0 for those of the other two types). Using half the data (n D 602), we tested a model positing that the eVects of the enduring inXuences on volunteering are indirect, and are fully mediated by civic obligation, helping identity, and opportunity. The model Wt was adequate, 2(116) D 385.70, p < .001; CFI D .904; RMSEA D .044.
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Over-controlled -.20** -.15**
Civic Obligation
.00
-.22**
Under-controlled
-.30** -.06
-.01
.05
Gender
.21** .06
Identity
.20**
Volunteering
.37**
Age
.12** .16** .18** .09** .15**
Education
.03
.06 .00
Income
Opportunity
-.01
Fig. 3. Mediating eVects model without paths of direct inXuences from personality and demographic factors to volunteer hours (Volunteers Only).
To potentially improve model Wt, we investigated the modiWcation indices and found that allowing age and the helping identity contribution indicator to covary would lead to a better Wtting model. This Wnding makes theoretical sense. Recall that this helping identity indicator asks participants to consider whether they expect to contribute to the welfare of others 10 years into the future. As people get older, they are less likely to be expecting themselves to be helping others 10 years into the future. When we allowed these parameters to covary, this new model was found to be a good Wt, 2(114) D 230.62, p < .001; CFI D .958; RMSEA D .029, and an improvement over the previous model, 2 D 155.08, df D 2, p < .001. To test our revised model, we cross-validated it using the second sub-sample (n D 607) by placing cross-group equality constraints on both measurement weights, intercepts and residuals, and on structural weights, intercepts and residuals, which is considered a conservative, “overly restrictive” test (Byrnes, 2001). Placing equality constraints did not diminish Wt; indeed, these constraints still resulted in good Wtting models. Table 1b presents only the measurement intercepts, structural weights and means constraint models,
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Table 2 Standardized indirect eVects between the enduring variables and volunteering Enduring variables
Indirect eVect (Volunteers Only)
Indirect eVects (Volunteers & Non-volunteers)
Over-controlled Under-controlled Gender Age Education Income
¡.030¤ ¡.070¤ .052¤ .051¤ .034¤ ¡.004
¡.053¤ ¡.079¤ .066¤¤ .089¤ .067¤ .018¤
¤ ¤¤
p < .05. p < .01.
because in cross-validating patterns of causal structure these parameters are most important (Byrnes, 2001). 3.4. Step 3: Full model (direct and indirect eVects) In the third step of model testing, we compared the mediating model described in the previous paragraph to a full, saturated model that allowed for the enduring inXuences to have both direct and mediated eVects on volunteering. Using half the data (n D 602), this full model also showed a good Wt to the data, 2(102 df) D 212.57, p < .001; CFI D .961; RMSEA D .030. This model did not produce a signiWcant improvement in Wt over the mediating eVects model (2 D 18.05, df D 12, p > .05). Consequently, the mediating eVects model, because it is more parsimonious, is preferred over the full model. 3.5. Mediated model: Direct and indirect eVects Because the mediating model could be cross-validated with the two samples, we collapsed the data together and ran the model using the full set of data (n D 1209). Not surprisingly this model also Wt the data well, 2(57 df) D 181.28, p < .001; CFI D .956; RMSEA D .042. Consistent with our hypotheses, the latent variables helping identity and opportunity all positively, and statistically signiWcantly (p < .01) predicted volunteer hours (see Fig. 3). However, civic obligation did not. In addition, personality, gender, age and education variables were found to have signiWcant indirect eVects (see Table 2).1 1 At the recommendation of one reviewer, we tested the mediating model substituting Big-5 dimension scores (agreeableness, neuroticism, openness to experience, extraversion and conscientiousness) for personality types: (1) with half the data randomly selected (n D 556), we found model Wt to be adequate, 2(152) D 443.94, p < .001; CFI D .925; RMSEA D .041; (2) to improve Wt, we investigated the modiWcation indices and found that allowing age and the helping identity contribution indicator to covary would lead to a better Wtting model, 2(150) D 309.99, p < .001; CFI D .959; RMSEA D .031 (2 D 133.95, df D 2, p < .001); (3) this Wnal model was cross-validated with the second sub-sample (n D 589) by placing cross-group equality constraints on both measurement weights, intercepts and residuals, and on structural weights, intercepts and residuals: (4) the two subsamples were collapsed to determine model Wt using the entire sample. Results indicated the data were a good Wt, 2(75 df) D 229.98, p < .001; CFI D .960; RMSEA D .043. Agreeableness and neuroticism were the only dimensions to have a signiWcant indirect eVect on volunteering. These Wndings show that the use of dimension scores do not improve the Wt of our model. The various Wt measures (CFI, RMSEA) show no improvement over those for the models using the personality type scores.
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3.6. Step 4: Mediating eVects model and full model with volunteers and non-volunteers In the fourth step, we explored model Wt when participants reporting no volunteering were added to our sample (n D 2953). This data set was randomly split in half, and parallel analyses were performed as done previously in Steps 1–3 on the halved data set (n D 1485). In the Wrst analysis, our mediating model was a good Wt to the data, 2(114 df) D 490.15, p < .001; CFI D .956; RMSEA D .033. In the second analysis, the full model also produced a good Wt to the data, 2(102 df) D 440.85, p < .001; CFI D .960; RMSEA D .034. In fact, the full model produced a signiWcant improvement in Wt over the mediating eVects model, 2 D 49.3, df D 12, p < .05. Further, we cross-validated our full model by placing cross-group equality constraints on both measurement weights, intercepts and residuals, and on structural weights, intercepts and residuals between the Wrst halved sample and the second halved sample (n D 1485). Again, these analyses demonstrated that the models with the equality constraints did not diVer from the unconstrained model (see Table 1c), thereby showing that the full model could be cross-validated. Because the full model could be cross-validated with the two samples, we collapsed the data together and ran the model using the full set of data (n D 2953). The model was a good Wt to the data, 2(51 df) D 401.60, p < .001; CFI D .959; RMSEA D .048. In terms of signiWcant direct pathways leading to volunteer hours, opportunity and identity were signiWcant as were under-controlled personality and education (see Fig. 4).2 As for indirect eVects, all the enduring variables were found to be signiWcant predictors of volunteer hours (see Table 2). 4. Discussion To reiterate, our goal in this research was to test a model of psychological and social inXuences on commitment to volunteering. The model posits that commitment to volunteering is a product of enduring, stable qualities of persons and their location in social structures and of more malleable features such as moral cognition, identity, and social opportunities. Moreover, our model predicted that the inXuences of the enduring stable qualities on commitment to volunteering are mediated in part by moral cognition, identity, and opportunity. Using structural equation modeling, we found support for a model in which the enduring qualities aVected volunteering through our set of mediating constructs when tested on volunteers from a large, nationally representative, cross-sectional sample of American adults. And when data from volunteers and non-volunteers were merged, our full model of direct and mediating eVects emerged as a better Wt than the mediating model. When volunteers were studied separately, our results show that both helping identity and social opportunities contributed to volunteering. Individuals who think about their contributions to others, feel that they control their contributions to the welfare of others, and feel that they will make important contributions to the welfare of others, are more committed to volunteering than are those who do not share these characteristics. These Wndings are consistent with theories that emphasize the centrality of identity for understanding sustained prosocial behavior (Hart, 2005; Lee et al., 1999).
2
To simplify the Wgure, only signiWcant paths are reported—¤p < .05; ¤¤p < .01.
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-.17**
Over-controlled
-.16** -.05*
Civic Obligation
-.19**
Under-controlled
.04* -.25**
-.08**
.05*
Gender
.19** .09**
Identity
.18**
Volunteering
.36** .09**
Age
.17**
.14**
Education
.34** .09** .08** .13**
.08** .06**
Opportunity
Income Fig. 4. Full eVects model with paths of direct and indirect inXuences from personality and demographic factors to volunteer hours (Volunteers and Non-volunteers).
Second, participation in the community was also predictive of involvement in hours of volunteering, suggesting that increased community activity creates more opportunities for people to increase their hours of volunteering. Although we found positive associations between our mediating factors of identity and opportunity with hours volunteered, the parameter estimate for the path from civic obligation to hours volunteered was near zero and non-signiWcant. Perhaps our measure of civic obligation, which includes items concerning voting in elections, serving on a jury, and being informed about public issues, is too narrowly focused on governmental aVairs to capture a sense of obligation to the broader community that might culminate in volunteering. Interestingly, however, longitudinal research (Hart, Donnelly, Youniss, & Atkins, in press) has similarly found only the weakest of evidence for the eVects of adolescent civic attitudes on volunteering in early adulthood, controlling for the eVects of a variety of background factors. The possibility exists that civic concerns play less of a role in the motivation of volunteering than previously believed. Another possible explanation relates to an historical trend on the motivation to volunteer: perhaps in the past, volunteering reXected civic motivation more so than
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in the present epoch, in which volunteering may be motivated by individual-oriented rather than civic-oriented goals (see Hart et al., in press for a discussion). Future research might beneWt from a consideration of a more diVerentiated, broader notion of civic obligation, as well as to consider distinguish among types of volunteering. Our results also showed all of the enduring factors had an indirect eVect on volunteering with the exception of income. For example, the tendency for women to volunteer more hours than men is accounted for by diVerences between the genders in the salience of a helping identity. Similarly, our results help explain the relation of personality to volunteering that, although robust, has been poorly understood (e.g., Atkins et al., 2005). In this study, compared to resilient individuals, both overcontrolled and under-controlled adults judged themselves to have less salient helping identities which are associated with a reduction in volunteering. An issue for future research is the nature of the relation of personality types to identity. Although theorists believe that the theoretical personality processes corresponding to our identity latent variable—identity, self, and self-eYcacy—are more malleable and less temporally stable than personality dispositions, traits, and types (Mischel & Shoda, 1998), empirical research suggests that the distinction is less clear than often assumed (Judge, Erez, Bono, & Thoresen, 2002). Consequently, a more accurate representation of the processes involved in volunteering may demand Venn diagrams in which constructs partially subsume each other instead of Fig. 1’s depiction of independent, separable processes. Alternatively, diVerentiation of identity and personality may be clearest for identities articulated within contexts, such as blood donor (Piliavin & Callero, 1991). Our measure of identity, which reXected indicators of commitment to help in the future, the experience of oneself as prosocially eYcacious, and the salience of helping in awareness—all key qualities of identity—did not capture the intertwining of identity and social context that is necessary for full accounts of identity development (for a discussion, see Hart & Yates, 1997). Context-speciWc identities are clearly distinct from personality traits and types, and are more likely to change than personality. Finally, like others (e.g., Wilson, 2000), we found evidence for the relations of age and education commitment to volunteer. People who are older and more educated devote more hours to volunteering, with these associations being mediated by helping identity and opportunities through community participation. When data from non-volunteers were added, the patterns of results did not change drastically. Yet a few Wndings are worth mentioning: First, the link between opportunity to volunteering increased in strength with the addition of non-volunteers suggesting that getting people involved in their community may be an important initial step in them making a commitment towards volunteering. This Wnding is consistent with research suggesting that people volunteer because they are in the contexts in which they are asked to do so (Independent Sector, 2001; Wilson, 2000). Moreover, with the addition of non-volunteers, personality types, gender, and education became signiWcant predictors of opportunity, along with age. Together, these results suggest that among volunteers, being resilient, female, and more educated make no diVerence in the number of hours of volunteering via their inXuence on community involvement. However, these enduring variables may be important in the decision to volunteer by inXuencing the initial step of getting them involved in their community.
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Finally, with non-volunteers added to our analyses, a few direct eVects emerged. Curiously, the under-controlled personality type had a small positive but signiWcant direct eVect on volunteering. A possible explanation is that under-controlled individuals are impulsive and physically active (Hart et al., 2003), and so volunteering could be one of many avenues they use to direct their energies. However, given the small eVect, further research is needed to test the robustness of this Wnding. A second direct eVect emerged between education and volunteering, and is consistent with past research (Wilson, 2000). Our results suggest that education’s eVect on volunteering follows many paths, both direct and indirect depending on the research context. That is, for volunteers, education seems to have an indirect eVect on the amount they will volunteer. However, when non-volunteers are added, the paths of inXuence change, suggesting that education’s eVect is greater on the decision to volunteer rather than on the number of hours volunteered. In fact, this may be true of all enduring variables given that their indirect eVects were greater when non-volunteers were added to the volunteers sample than when volunteers were considered alone. Together, our results and model integrate lines of work from other research traditions on volunteering, although a number of issues remain unresolved. For example, at a conceptual level, our measures may not fully capture the richness of the theoretical constructs articulated in each research tradition. Some personality psychologists might suggest that the measurement of very speciWc traits would result in better prediction of volunteering than the broad personality types used in this study (though our analyses demonstrate that the types predict volunteering as well as the Wve dimensions of the five factor model); similarly, those who situate volunteering within the social niches deWned by income, neighborhood, age, and race/ethnicity are likely to be dissatisWed by our global measures of social structure. These are questions that are best addressed by those working within each tradition. Our goal in proposing an integrative model was not to displace the theories oVered by personality, identity, and social-structural researchers, but instead to suggest that the theories can complement each other in understanding commitment to volunteering. We believe that the Wndings in this study—even though they do not measure every quality of interest to researchers in the three traditions—do advance this more modest goal. Another limitation of this study is the fact that causal connections among the various constructs cannot be determined. Although we have modeled the paths from enduring variables such as personality through mediating factors such as identity to volunteering behavior, it is likely that the inXuences between some of these factors are more transactional in nature with volunteering impacting the mediating variables such as identity and opportunities. Stronger inferences about causal pathways await studies employing longitudinal data rather than the cross-sectional data used in this study.3 An experimental study, in which some of these factors were manipulated, would be the ideal design; however, many of the variables in this model probably cannot be controlled through experimental intervention. It should also be noted that although most of our constructs have statistically signiWcant associations with volunteering, none of them is strongly predictive. One possible rea-
3
The sample in this study was assessed a second time, and these data may become available to the public in 2007. A second wave of data would permit longitudinal assessments of the model.
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son for the weak eVects is that volunteering is multidimensional, having multiple motivations, and occurs in many diVerent contexts. These diVerent motivations and contexts aVect involvement in volunteering in diverse ways that cannot be parsimoniously incorporated into a single model. However, the complexity of volunteering, and the shortcomings of the model proposed in this paper, should encourage—rather than discourage— research into a topic that is both theoretically rich and socially important. Further research that illustrates such complexity awaits. References Aquino, K., & Reed, A. (2002). The self-importance of moral identity. Journal of Personality and Social Psychology, 83, 1423–1440. Arbuckle, J. L. (2003). Amos 5.0 update to the Amos user’s guide. Chicago, IL: SPSS. Asendorpf, J. B., Borkenau, P., Ostendorf, F., & van Aken, M. A. G. (2001). Carving personality description at its joints: conWrmation of three replicable personality prototypes for both children and adults. European Journal of Personality, 15, 169–198. Atkins, R., Hart, D., & Donnelly, T. M. (2005). The inXuence of childhood personality on volunteering during adolescence. Merrill-Palmer Quarterly, 51, 145–162. Baer, D. (2006). Latent variable structural equation models. Unpublished manuscript. Beauchaine, T. P., & Beauchaine, R. J. (2002). A comparison of maximum covariance and K-means cluster analysis in classifying cases into known taxon groups. Psychological Methods, 7, 245–261. Block, J. (1971). Lives through time. Berkeley: Bancroft. Bureau of Labor Statistics. (2005). Volunteering in the United States, 2005. Retrieved April 28, 2006 from
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Hart, D., & Yates, M. (1997). Identity and self in adolescence. In R. Vasta (Ed.), Annals of child development, 1996 (pp. 207–242). London: Jessica Kingsley. Hodgkinson, V., & Weitzman, M. (1992). Giving and volunteering in the United States. Washington, DC: Independent Sector. Independent Sector (2001, November). Giving and volunteering in the United States. Retrieved October 17, 2003 from
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