Abstract

When predicting volunteer intention, much attention is paid to the volunteer organization environment (VOE). Given that self-efficacy and motivation have emerged as important predictors of volunteer intention, we adopted a combination of ideas of Bandura's social cognitive theory and Ajzen's theory of planned behavior integrating VOE, self-efficacy and motivation to examine their effects on volunteer intention and to determine whether self-efficacy and motivation mediate the relationship between VOE and volunteer intention. The subjects of this study consisted of 198 community health volunteers in Shanghai city, China. Exploratory factor analysis was performed to identify the factor structure using standard principal component analysis. Six new factors were revealed, including two VOE factors, relation with organization and support from government; two motivation factors, personal attitude and social recognition; self-efficacy and volunteer intention. The results of a hierarchical regression analysis indicated that relation with organization accounted for 14.8% of the variance in volunteer intention, and support from government failed to add significantly to variance in volunteer intention; self-efficacy and personal attitude motivation partially mediated the effects of relation with organization on volunteer intention; social recognition motivation did not mediate the relationship between relation with organization and volunteer intention; and relation with organization, self-efficacy and personal attitude motivation accounted for 33.7% of the variance in volunteer intention. These results provide support for self-efficacy and personal attitude motivation as mediators and provide preliminary insight into the potential mechanisms for predicting volunteer intention and improving volunteering by integrating VOE, self-efficacy and motivation factors.

INTRODUCTION

The World Health Organization (WHO, 1986, 1998) called for volunteering to promote health at the local level. A volunteer has been defined as ‘someone who contributes services without financial gain to a functional sub-community or cause’ [(Henderson, 1985), p. 31]. Community health volunteers (CHVs) have played important and sustainable roles in a variety of community health promotion projects and CHV organizations (CHVOs), which has also been observed in China (Fu et al., 2003).

A substantial share of volunteer work happens in and through organizations. Sills [(Sills, 1972), p. 363] defined a volunteer organization as ‘an organized group of persons (1) that is formed in order to further some common interest of its members; (2) in which membership is voluntary in the sense that it is neither mandatory nor acquired through birth; and (3) that exists independently of the state’. It is important to know more about why people volunteer and ‘why people join organizations and what encourages them to devote time and energy to those organizations' aims’ [(Gittell, 1980), p. 263]. Chelladurai (Chelladurai, 2006) pointed out that people volunteer based on whether one outlines and clarifies the possible benefits that can accrue through participation in a voluntary organization. Prestby (Prestby, 1984) stated that a social exchange takes place in organizations in which participants invest their energy only if they expect to receive some benefits. Therefore, the interplay between a volunteer and a volunteer organization environment (VOE) that produces and sustains volunteering should be considered when seeking to understanding why people volunteer and/or join volunteer organizations.

A VOE refers to the forces that can make an impact on volunteering. Such forces may serve as facilitators or barriers. A VOE includes external forces, such as broader social, economic, political, legal and cultural environments, and internal forces, including both organizational elements (e.g. organizational structures, administration, leadership, incentives, communication systems, and continuous learning and evaluation) and relational elements (e.g. shared vision, a cohesive and trusting working climate, and a culture that promotes internal power-sharing, inclusiveness and regular interactions among diverse stakeholders of the collaboration) (Foster-Fishman et al., 2001; Rama et al., 2009). Earp et al. (Earp et al., 1997) also indicated volunteer program challenges related to some organizational elements, such as resource needs, volunteer monitoring and support. Identifying the possible mechanisms underlying relevant VOE variables that influence CHVs and their volunteering is clearly needed.

When attempting to understand volunteering, it is important to do so within a theoretical framework that takes into account the relationship between the VOE and volunteering. Bandura's social cognitive theory (SCT) (Bandura, 1986) fulfills this role and may be the most comprehensive model of human behavior yet proposed. Indeed, one central theme of this social cognitive perspective is that of triadic reciprocity between three key concepts—the individual, the environment and behavior—which operate as determinants of each other. Key concepts associated with the individual include personal characteristics, behavioral capacity, self-efficacy, motivation, expectation etc. The environment can be physical, social, cultural, economical, political in nature and situational in nature, which can facilitate or inhibit behavior (Baranowski et al., 1997). The SCT differs from behaviorist learning theories, in that it includes a cognitive component—i.e. individuals can do more than react to an environmental stimulus; they can form mental representations and think about the stimulus and their behavior. Social cognitive factors such as self-efficacy and motivation are theorized to have strong effects on behavior and behavior intention under challenging environments (Gargano et al., 2004; Morris et al., 2008).

Behavior intentions from the theory of planned behavior (TPB) are indicators of how hard people are willing to try and how much effort they are willing to put forth to perform a behavior (Ajzen, 1991). The TPB is an extension of the theory of reasoned action (Ajzen and Fishbein, 1980) by including the perceived behavioral control (PBC) (perception about being able to perform a specific behavior). The TPB model suggests that intention is directly driven by three major constructs: attitude, subjective norm and PBC, and the stronger the intention, the more likely an individual will perform the behavior (Ajzen, 1991). Large amounts of research have focused on the prediction of behavioral intention rather than on the behavior itself.

Ajzen (Ajzen, 1991) considers the PBC construct of TPB identical to self-efficacy. However, Giles and Cairns (Giles and Cairns, 1995) suggested that self-efficacy is more precisely related to one's competence and to future behavior and the predictive utility of the TPB may be enhanced by replacing PBC with self-efficacy. Conner and Armitage (Conner and Armitage, 1998) suggested a dimensionalization of single PBC construct into dichotomized components, internal and external controls, for addressing weaknesses in the operationalization of PBC. The internal control based on factors that come from within the individual (such as ability and motivation) and external control based on factors that come from outside the individual (such as task difficulty, cooperation of others, access to necessary resources etc.) (Ajzen, 1991; Manstead and Van Eekelen, 1998; Armitage and Conner, 1999). This concept of external control is similar to Bandura's concept of environment; and the concept of internal control is similar to Bandura's concept of individual (Bandura, 1986). External control is an antecedent and internal control is the more proximate determinant of behavior intention (Kidwell and Jewell, 2003).

According to Bandura (Bandura, 1977), self-efficacy in this study refers to a volunteer's confidence in his or her ability to do volunteering in various situations. Self-efficacy influences the volunteering courses, how much effort they are likely to put forth and how long they will persevere in the face of adversity. High levels of self-efficacy will bring stronger intentions to complete a behavior. Bandura (Bandura, 1977) also stated that motivation is primarily concerned with how behavior is activated and maintained. Motivation in this study is a system of self-regulatory processes that involves selection, activation and sustained volunteering toward goals. People who are strong in motivation also have a strong behavior intention.

Given Bandura's (Bandura, 1986) suggestion that self-efficacy and motivation are not context-free disposition-like measures but are highly dependent on situational environments, a VOE may include important antecedents of self-efficacy and motivation. Combining this idea with the concept that self-efficacy and motivation may predict volunteer intention lends substantial support to using self-efficacy and motivation as mediator variables for volunteer intention. Further, in our study, the selection and examination of mediators (i.e. self-efficacy and motivation) was consistent with two criteria proposed by Frazier et al. (Frazier et al., 2004) when examining mediation: first, the selection of a mediator was based on previous research where relationships between the predictor and the outcome, and the mediator and the outcome, have been established, and second, the selection of a mediator was grounded in a theoretical framework.

This study combining ideas of the SCT and TPB is to determine whether perceptions of VOE are associated with volunteer intention and whether this relationship is mediated by self-efficacy and motivation. Additionally, a great deal of previous research indicated that past behaviors affect motivation, self-efficacy and behavior intention; thus, past behavior was also considered as an independent variable in our study.

METHODS

Research site

The study is located in Shanghai, China. Shanghai, the biggest city and the economic center of China, had a population of 17.78 million in 2005 (Shanghai Statistical Bureau, 2005). Economic development brought with it a remarkable improvement in the lives of the people in Shanghai. Nevertheless, Shanghai residents continue to face challenges to their health, such as communicable and non-communicable diseases, environmental hazards and unhealthy behaviors; moreover, generally, the health literacy of people in Shanghai is moderate or low (Gu et al., 2004). To meet these challenges and to practice and promote healthier behaviors and environments as well as to improve health (especially in underserved populations), more CHVs need to be recruited, developed and retained.

Participants and procedures

Thirteen CHVOs from a district of Shanghai city were identified from a list provided by a local health agency that maintains records on CHVOs. The local government recruits CHVs and builds CHVOs. Local centers for disease prevention and control, centers for community health service and other health institutions undertake the training of these CHVs. Each CHVO has 40–60 CHVs who are total volunteers. These CHVOs aim to help others in their community to improve their health. The CHVs take the blood pressure of individuals in a community, educate and motivate others to live healthier, advocate for positive health issues in the community, provide health information for community bulletin boards, offer social support (i.e. advice, referrals, emotional support) to community residents in need, participate in health promotion specialist collaborative meetings and so on. Volunteer times and opportunities are varied, and the CHVs usually are asked to commit one to two times during a typical week from 2 to 5h. During the spring of 2008, the research staff informed all directors of 13 CHVOs about the interest of this study by telephone and/or email. As a result, five CHVOs agreed to participate in this study.

Data were collected using questionnaires with a cover letter that explained the confidential and voluntary nature of the survey. The questionnaires were distributed to and retrieved from all the CHVs of five CHVOs (n = 257) by hand through the CHVO directors in June and July 2008. The study complied with appropriate ethical standards in the treatment of participants and was approved by a health agency research ethics committee in Shanghai city, China. Completed returns were received from 216 CHVs, with full data on volunteering available for 198 CHVs (77.0%); these were used for this analysis. We did not have detailed sociodemographic data on the CHVs of the other eight CHVOs as they chose not to participate in this study.

Measures

All of the measures were created based on our previous qualitative study and other existing literature pertinent to motivation (Omoto and Snyder, 1995; McCurley and Lynch, 1996; Esmond and Dunlop, 2004) and self-efficacy (Bandura, 1986; Maibach and Murphy, 1995; Schwarzer and Jerusalem, 1995). The previous qualitative study included four focus groups and seven individual interviews and was carried out with a total of 32 CHVs in Shanghai city from June 2006 to February 2007; it aimed to capture and understand the experiences and perceptions of the CHVs' participation in community health promotion projects in Shanghai city. The findings of the qualitative study contributed to create the questionnaire items, particularly in the section on VOE. To increase the validity of the items, a pilot survey was carried out in June 2008 using a small group of CHVs in Shanghai city. The pilot survey was meant to identify questionnaire item ambiguities and to verify the clarity of the questions as well as to reflect the thinking characteristics of local volunteers. The CHVs in the pilot survey came from one of the five CHVOs mentioned above; they also participated in the main survey. The final questionnaire contained a sociodemographic form and a volunteering module of 49 items designed to measure five relevant volunteering factors: VOE (16 items), self-efficacy (4 items), motivation (22 items), volunteer intention (3 items) and past behavior (4 items). All volunteering items utilized Likert scale response options.

Data analysis

Data were analyzed with SPSS version 15.0. Descriptive statistics were used to summarize the sociodemographic of the sample. To assess the underlying factor structure of the entire volunteering module of items and thus determine how well the constructs being measured retain their unique identity when examined in a multivariate context, an explore factor analysis (EFA) of the principal components with varimax rotation was carried out on the volunteering module of 49 items. The following criteria were used in analyzing and interpreting the results. An eigenvalue >1 was used as a cut-off point to determine the applicability of the original five-factor module to volunteering. A factor loading of 0.5 and conceptual relevance were used as criteria for retaining an item in a factor. Items with loadings >0.4 on two or more factors were excluded.

The presence of mediation effects was tested using hierarchical linear regression according to the guidelines recommended by Baron and Kenny (Baron and Kenny, 1986) as follows: (i) the independent variables should be significantly associated with the dependent variable, (ii) the independent variables should be significantly associated with the mediator, (iii) the mediator should be associated with the dependent variable and (iv) the addition of the mediator to the full model should significantly reduce the relationship between the independent variable and the dependent variable. Moreover, when controlling for the mediator, if the relationship between the independent variable and the dependent variable is reduced in size but still differs from zero, partial mediation is said to have occurred (Frazier et al., 2004). Standardized coefficients were calculated to examine changes in path coefficients with the addition of the mediator to the regression model. Sobel's z-scores (Sobel, 1988) were calculated to assess the significance of changes in the path coefficients. All regression analyses were assessed for collinearity by calculating tolerance and variance inflation factors (VIFs).

RESULTS

Preliminary analyses

Of the 198 CHVs, the mean age was 54.3 years [standard deviation (SD) = 10.1] and 68.2% were female. A majority (87.9%) of respondents were married and half of the participants were retired. The percentage of college level educational attainment or above was 34.3% (Table 1).

Table 1:

Sociodemographic data of CHVs (N = 198)

Characteristic Summary statistics 
Gender, n (%) 
 Male 63 (31.8) 
 Female 135 (68.2) 
Age (years) 
 Mean ± SD 54.3 ± 10.1 
 Range 25–76 
Marital status, n (%) 
 Single/divorced/windowed/separated 24 (12.1) 
 Married 174 (87.9) 
Highest education level completed, n (%) 
 Junior high school or less 31 (15.7) 
 Senior high school 99 (50.0) 
 Some college or technical school and above 68 (34.3) 
Employment, n (%) 
 Employed for wages 81 (40.9) 
 Retired 103 (52.0) 
 Self-employed/out of work/student 14 (7.1) 
Characteristic Summary statistics 
Gender, n (%) 
 Male 63 (31.8) 
 Female 135 (68.2) 
Age (years) 
 Mean ± SD 54.3 ± 10.1 
 Range 25–76 
Marital status, n (%) 
 Single/divorced/windowed/separated 24 (12.1) 
 Married 174 (87.9) 
Highest education level completed, n (%) 
 Junior high school or less 31 (15.7) 
 Senior high school 99 (50.0) 
 Some college or technical school and above 68 (34.3) 
Employment, n (%) 
 Employed for wages 81 (40.9) 
 Retired 103 (52.0) 
 Self-employed/out of work/student 14 (7.1) 

EFA yielded seven factors with eigenvalues >1 that accounted for 68.9% of total variance. Twelve items were deleted in light of the criteria mentioned above. One aim of this study was to examine the relationship between volunteer past behavior and volunteer intention, motivation and self-efficacy; however, analysis indicated that volunteer past behavior (four items) and volunteer intention (three items) were one factor. Therefore, the four items on past behavior were also deleted, and the variable of past behavior was not included in subsequent analyses. Factor analysis of the new scales, employing 33 of 49 items, revealed six factors with eigenvalues >1 that accounted for 71.1% of the total variance. The six factors were two VOE factors, relation with organization and support from government; two motivation factors, personal attitude motivation and social recognition motivation; self-efficacy and volunteer intention. The factor loadings based on EFA, coefficient α, score mean and SD for these scales are presented in Table 2. (The original item set is available by request from the first author.)

Table 2:

Factor loading, reliability coefficient, mean and SD

Item Item factor loading Reliability coefficient (α) Mean (SD) 
Volunteer organization environment (VOE) scale (How satisfied are you with …?a   
Relation with organization (VOE subscale)  0.92 3.45 (0.50) 
 How much you are allowed to decide how volunteering goals are achieved? 0.60  3.40 (0.59) 
 Your responsibility for the results of volunteering? 0.56  3.40 (0.61) 
 The training for volunteer activities? 0.61  3.48 (0.69) 
 Your role in volunteer activities? 0.64  3.52 (0.64) 
 The supply of information and tools for volunteer activities? 0.73  3.38 (0.620 
 The relationship between you and other volunteers? 0.78  3.54 (0.63) 
 The communication with health professionals? 0.83  3.47 (0.61) 
 The communication with government staff? 0.69  3.36 (0.61) 
Support from government (VOE subscale)  0.90 3.34 (0.54) 
 The government financial support for your volunteering? 0.84  3.30 (0.64) 
 The government material support for your volunteering? 0.88  3.27 (0.62) 
 The moral encouragement by the government? 0.66  3.51 (0.63) 
 The material encouragement by the government? 0.81  3.35 (0.63) 
 Paying our-of-pocket money in your volunteering activities? 0.71  3.28 (0.65) 
Motivation scale (Participating in volunteering is to …, that is/are important to you.b   
 Personal attitude motivation (motivation subscale)  0.95 3.35 (0.64) 
 Gain skills and experience 0.65  3.30 (0.84) 
 Make new friends 0.73  3.45 (0.77) 
 Be part of the community 0.70  3.45 (0.76) 
 Have fun 0.79  3.49 (0.77) 
 Gain qualifications/accreditation 0.75  3.28 (0.80) 
 Work with a particular group of people 0.79  3.34 (0.72) 
 Get away from problems 0.62  3.14 (0.81) 
 Meet new people 0.74  3.26 (0.81) 
 Provide a service 0.75  3.49 (0.75) 
 Put existing skill to good use 0.78  3.37 (0.79) 
 Fill time 0.75  3.30 (0.81) 
Social recognition motivation (motivation subscale)  0.81 2.92 (0.73) 
 Get out of the house 0.72  2.85 (0.93) 
 Gain status 0.83  2.84 (0.82) 
 Work in the community 0.76  3.10 (0.82) 
Self-efficacy scalec  0.82 3.57 (0.53) 
 How much confidence do you have in your ability to participate in volunteer activities? 0.79  3.55 (0.65) 
 How much confidence do you have to overcome obstacles and challenges in volunteer activities? 0.74  3.57 (0.58) 
 How much do you believe that you can participate in volunteer activities? 0.54  3.59 (0.62) 
Volunteer intention scale  0.84 3.40 (0.64) 
 Do you intend to volunteer in the future?c 0.72  3.43 (0.70) 
 How often will you participate in future volunteering?d 0.82  3.08 (0.74) 
 Do you agree that you have decided to participate in future volunteering?e 0.84  3.68 (0.78) 
Item Item factor loading Reliability coefficient (α) Mean (SD) 
Volunteer organization environment (VOE) scale (How satisfied are you with …?a   
Relation with organization (VOE subscale)  0.92 3.45 (0.50) 
 How much you are allowed to decide how volunteering goals are achieved? 0.60  3.40 (0.59) 
 Your responsibility for the results of volunteering? 0.56  3.40 (0.61) 
 The training for volunteer activities? 0.61  3.48 (0.69) 
 Your role in volunteer activities? 0.64  3.52 (0.64) 
 The supply of information and tools for volunteer activities? 0.73  3.38 (0.620 
 The relationship between you and other volunteers? 0.78  3.54 (0.63) 
 The communication with health professionals? 0.83  3.47 (0.61) 
 The communication with government staff? 0.69  3.36 (0.61) 
Support from government (VOE subscale)  0.90 3.34 (0.54) 
 The government financial support for your volunteering? 0.84  3.30 (0.64) 
 The government material support for your volunteering? 0.88  3.27 (0.62) 
 The moral encouragement by the government? 0.66  3.51 (0.63) 
 The material encouragement by the government? 0.81  3.35 (0.63) 
 Paying our-of-pocket money in your volunteering activities? 0.71  3.28 (0.65) 
Motivation scale (Participating in volunteering is to …, that is/are important to you.b   
 Personal attitude motivation (motivation subscale)  0.95 3.35 (0.64) 
 Gain skills and experience 0.65  3.30 (0.84) 
 Make new friends 0.73  3.45 (0.77) 
 Be part of the community 0.70  3.45 (0.76) 
 Have fun 0.79  3.49 (0.77) 
 Gain qualifications/accreditation 0.75  3.28 (0.80) 
 Work with a particular group of people 0.79  3.34 (0.72) 
 Get away from problems 0.62  3.14 (0.81) 
 Meet new people 0.74  3.26 (0.81) 
 Provide a service 0.75  3.49 (0.75) 
 Put existing skill to good use 0.78  3.37 (0.79) 
 Fill time 0.75  3.30 (0.81) 
Social recognition motivation (motivation subscale)  0.81 2.92 (0.73) 
 Get out of the house 0.72  2.85 (0.93) 
 Gain status 0.83  2.84 (0.82) 
 Work in the community 0.76  3.10 (0.82) 
Self-efficacy scalec  0.82 3.57 (0.53) 
 How much confidence do you have in your ability to participate in volunteer activities? 0.79  3.55 (0.65) 
 How much confidence do you have to overcome obstacles and challenges in volunteer activities? 0.74  3.57 (0.58) 
 How much do you believe that you can participate in volunteer activities? 0.54  3.59 (0.62) 
Volunteer intention scale  0.84 3.40 (0.64) 
 Do you intend to volunteer in the future?c 0.72  3.43 (0.70) 
 How often will you participate in future volunteering?d 0.82  3.08 (0.74) 
 Do you agree that you have decided to participate in future volunteering?e 0.84  3.68 (0.78) 

aResponse options ranged from ‘very dissatisfied’ (1) to ‘very satisfied’ (5).

bResponse options ranged from ‘not at all important’ (1) to ‘extreme important’ (5).

cResponse options ranged from ‘not at all’ (1) to ‘an extreme amount’ (5).

dResponse options ranged from ‘almost never or never’ (1) to ‘almost always or always’ (5).

eResponse options ranged from ‘strongly disagree’ (1) to ‘strongly agree’ (5).

Table 3 presents bivariate correlations for the study variables. All correlations were significant in a positive direction.

Table 3:

Correlations of study variables

Variable 
1. Volunteer intention      
2. Self-efficacy 0.563     
3. Personal attitude motivation 0.367 0.533    
4. Social recognition motivation 0.191 0.195 0.542   
5. Relation with organization 0.385 0.464 0.642 0.314  
6. Support from government 0.245 0.327 0.471 0.199 0.616 
Variable 
1. Volunteer intention      
2. Self-efficacy 0.563     
3. Personal attitude motivation 0.367 0.533    
4. Social recognition motivation 0.191 0.195 0.542   
5. Relation with organization 0.385 0.464 0.642 0.314  
6. Support from government 0.245 0.327 0.471 0.199 0.616 

All correlations are significant at the 0.01 level.

Since the sample was derived from five different organizations, a series of univariate one-way ANOVAs were conducted to assess subsample compatibility across the different study scales. The ANOVAs indicated non-significant differences across all scales except self-efficacy.

Diagnostic tests showed no problems with multicollinearity in all subsequent regression analyses in the data. The VIF was well below 5, whereas the tolerance was well above the guideline of 0.2.

Mediation analyses

Regression of volunteer intention on relation with organization and support from government

Relation with organization accounted for 14.8% of the variance in volunteer intention, whereas support from government failed to add significantly to the model (Table 4). Therefore, the variable of support from government was not included in subsequent analyses.

Table 4:

Volunteer intention predicted by relation with organization and support from government

Step Variables R2 ΔR2 F β 
Relation with organization 0.148 0.148 34.086*** 0.385*** 
Support from government 0.148 0.000 0.026 0.013 
Step Variables R2 ΔR2 F β 
Relation with organization 0.148 0.148 34.086*** 0.385*** 
Support from government 0.148 0.000 0.026 0.013 

***p < 0.001.

Self-efficacy mediating relation with organization and volunteer intention

Relation with organization was associated significantly with volunteer intention and self-efficacy. In addition, when controlling for self-efficacy as a mediator, the previously significant relationship between relation with organization and volunteer intention remained (ΔR2 = 0. 019, p= 0.018). However, it decreased in magnitude, indicating partial mediation (Table 5, Analysis 1). A follow-up Sobel test of the magnitude of change on path coefficients further supported the significant mediating effect of self-efficacy on relationship with organization when predicting volunteer intention (z = 5.246, p= 0.000).

Table 5:

Hierarchical multiple regression results for the mediating effects of self-efficacy and motivation in the relationship between relation with organization and volunteer intention

Step Variables R2 ΔR2 F β 
Analysis 1 
Self-efficacy 0.318 0.318 91.182*** 0.563*** 
Relation with organization 0.337 0.019 5.714* 0.157* 
Analysis 2 
Personal attitude motivation 0.135 0.135 30.593*** 0.367*** 
Relation with organization 0.173 0.038 8.907** 0.253** 
Analysis 3 
Social recognition motivation 0.036 0.036 7.410** 0.191** 
Relation with organization 0.154 0.117 26.994*** 0.360*** 
Analysis 4 
Self-efficacy 0.324 0.324 46.696*** 0.513*** 
 Personal attitude motivation    0.094 
Relation with organization 0.337 0.013 3.849 0.152 
Step Variables R2 ΔR2 F β 
Analysis 1 
Self-efficacy 0.318 0.318 91.182*** 0.563*** 
Relation with organization 0.337 0.019 5.714* 0.157* 
Analysis 2 
Personal attitude motivation 0.135 0.135 30.593*** 0.367*** 
Relation with organization 0.173 0.038 8.907** 0.253** 
Analysis 3 
Social recognition motivation 0.036 0.036 7.410** 0.191** 
Relation with organization 0.154 0.117 26.994*** 0.360*** 
Analysis 4 
Self-efficacy 0.324 0.324 46.696*** 0.513*** 
 Personal attitude motivation    0.094 
Relation with organization 0.337 0.013 3.849 0.152 

Step 1 is the analysis of the relationship between the potential mediator(s) and outcome; and step 2 is the analysis of the relationship between relation with organization and the outcome, controlling for the mediator(s).

*p < 0.05, **p < 0.01 and ***p < 0.001.

Personal attitude motivation mediating relation with organization and volunteer intention

Relation with organization was associated significantly with volunteer intention and personal attitude motivation. In addition, when controlling for personal attitude motivation as a mediator, the previously significant relationship between relation with organization and volunteer intention remained (ΔR2 = 0.038, p= 0.003). However, it decreased in magnitude, indicating partial mediation (Table 5, Analysis 2). A follow-up Sobel test of the magnitude of change on path coefficients further supported the significant mediating effect of personal attitude motivation on relationship with organization when predicting volunteer intention (z = 2.373, p= 0.018).

Social recognition motivation mediating relation with organization and volunteer intention

Relation with organization was associated significantly with volunteer intention and social recognition motivation. In addition, when controlling for social recognition motivation as a mediator, the previously significant relationship between relation with organization and volunteer intention remained (ΔR2 = 0.117, p= 0.000). It did not decrease in magnitude, suggesting that social recognition motivation did not mediate the relationship between relation with organization and volunteer intention (Table 5, Analysis 3). A follow-up Sobel test of the magnitude of change on path coefficients further supported that social recognition motivation had no significant mediating effect on relationship with organization when predicting volunteer intention (z = 1.095, p = 0.274).

Full meditational model

The two statistically significant mediating variables, self-efficacy and personal attitude motivation, were tested simultaneously in one model (Figure 1). When controlling for self-efficacy and relation with organization as mediators, the previously significant relationship between relation with organization and volunteer intention did not remain, indicating full mediation. The full model accounted for 33.7% of the variance in volunteer intention (Table 5, Analysis 4). A follow-up Sobel test of the magnitude of change on path coefficients further supported the significant mediating effect of self-efficacy and personal attitude motivation on relation with organization when predicting volunteer intention (z = 3.917, p= 0.000).

Fig. 1:

The full model of the mediating effects of self-efficacy and personal attitude motivation in the relation between relation with organization and volunteer intention.

Fig. 1:

The full model of the mediating effects of self-efficacy and personal attitude motivation in the relation between relation with organization and volunteer intention.

DISCUSSION

The effects of the VOE factor relation with organization on volunteer intention was significantly mediated by self-efficacy and personal attitude motivation. The results provide support for use of a combination of ideas of the SCT and the TPB in predicting volunteer intention from the cross-sectional survey of CHVs in Shanghai, China. Selecting and testing self-efficacy and motivation as mediators through which correlates may operate on volunteer intention has been identified in our volunteering model as critical in furthering our understanding of the mechanisms to target in improving volunteering and community health promotion projects.

In our study, the VOE included the two subscales of relation with organization and support from government. The effect of support from government on volunteer intention was non-significant, which suggests that it may be more effective to improve volunteering through better internal environmental elements (e.g. relation with organization) rather than through external environmental elements (e.g. support from government).

In addition to improving the internal environmental elements, the CHVOs should also strengthen individual capacity to react to these organizational forces. Studies have shown that organizational training and mentoring programs can improve volunteering by providing CHVs with the support or the confidence necessary to work within the constraints placed upon them (McCurley and Lynch, 1996). Sufficient organizational support and appropriate relations with an organization could motivate CHVs to fulfill volunteer roles such as (i) assisting individuals in their social networks with needs that are difficult for professionals to address, (ii) negotiating with professionals for support from the health system and (iii) mobilizing the resources of associations in their community to sustain support from the health system (Eng and Smith, 1995). Foster-Fishman et al. (Foster-Fishman et al., 2007) indicated that residents typically engage in comprehensive community-building initiatives on three levels: (i) involvement in governance, planning, decision-making or design entities; (ii) participation in designing and implementing neighborhood improvement projects or activities; and (iii) involvement in collective action or mobilization efforts. These are consistent with volunteer opportunities in China (Li, 2002; Fu et al., 2003). Strengthening the CHVs' self-efficacy through the efforts of CHVOs may be useful to CHVs' participation at all levels.

The findings supported that self-efficacy and personal attitude motivation functioned as mediators in this volunteering model through which relation with organization exerted a significant positive effect on volunteer intention. CHVOs should target self-efficacy beliefs and personal attitude motivation and attempt to enhance them by, for example, improving the VOE—especially the relation with the organization—to strengthen CHVs' volunteer confidence and attitude. Such findings support the inclusion of not only VOE but also self-efficacy and motivation should not be examined in isolation when assessing VOE association with volunteer intention. An understanding of the sustainability of volunteer motivation should include the interaction of organizational characteristics with processes of individual motivation (Karr and Meijs, 2006). We should remove barriers to motivation by designing satisfying work experiences, and we should create systems that allow volunteers to meet their own needs. A satisfying VOE can insure that sufficient and appropriate volunteering is harnessed (McCurley and Lynch, 1996). The core construct of our model, self-efficacy, was measured in volunteering specifically, rather than via a generalized self-efficacy measurement instrument. Bandura [(Bandura, 1986), p. 396)] has argued, ‘measures of self-percept must be tailored to the domain of psychological functioning being explored’. Maibach and Murphy (Maibach and Murphy, 1995) pointed out that the measures of generalized self-efficacy have little explanatory and predictive value, whereas domain-related measures have proven to have considerable predictive value. Our study also indicates that self-efficacy could be measured using generic scales developed for the volunteering domain.

On the basis of volunteer organizations of sample in our study and the knowledge that most CHVOs in China are based on broad partnerships among local government, health agencies and community residents, the relational elements (e.g. shared vision, a cohesive and trusting working climate, and a culture that promotes internal power-sharing, inclusiveness and regular interactions among diverse stakeholders of the collaboration) must be considered to improve the volunteering. When CHVs' self-efficacy and motivation increase and VOE is improved, greater partnerships and negotiations between CHVs and organizations as well as with other stakeholders will emerge. These partnerships and negotiations are assumed, in turn, to promote volunteer participation and will eventually lead to sustainment and improvement of community health promotion projects. Also, the external environmental elements (such as the broader social, economic, political, legal and cultural environments in Shanghai) that affect volunteer organizations and support or constrain the individual volunteer should not be ignored.

The findings reported in this study have certain limitations. First, these data are cross-sectional. The interactions proposed by the SCT suggest that the variables will interact in a reciprocal manner, but the model tested focused on a unidirectional causation in order to study the mediation effects of self-efficacy and motivation. Although the literature and theory support the causal assumptions found, the design does not allow for a causal determination between the variables. While future research should continue to investigate the relationships among the variables to verify the causal relationships, the reciprocal nature of the SCT suggests that the causal directions are unimportant, as a change in one variable can affect all the variables; this means that there is some difficulty in showing causality between related factors and volunteering. Nevertheless, this study effectively uses the volunteering model to understand volunteering tendencies. Future work should also utilize longitudinal designs to determine whether the relationships found here are predictive or simply associative. Second, although a self-administered format was used to minimize response bias, these results remain based on self-reported data with their potential limitations (Gonyea, 2005). Third, this study was conducted only with CHVs in Shanghai city and with only organizations that we could recruit. Therefore, consistency and generalizability observed by different persons in different places with different samples could strengthen the likelihood of an effect as mentioned above.

CONCLUSION

This study advances the understanding of volunteering by using a well-established theoretical framework provided by SCT and TPB to examine how the VOE might influence volunteer intention. Self-efficacy and personal attitude motivation each both partially and fully mediated the effects of relation with organization on volunteer intention. An integrated understanding of VOE, self-efficacy and motivation, therefore, is essential to any effort to improve volunteering.

FUNDING

This research was funded by the Graduate Student Development Project of Kumamoto University in 2008, Japan.

ACKNOWLEDGEMENTS

We would like to thank the study participants and their respective organizations for their cooperation and participation.

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