The perceptions of costs and benefits of high active versus low active groups in community...

The Perceptions of Costs and Benefits of High Active Versus Low Active Groups in Community Coalitions at Different

Stages in Coalition Development Matthew J. Chinman, Christopher M. Anderson, Pamela S. Imm, Abraham

Wandersman, and Robert M. Goodman University of South Carolina

Over 200 community volunteers who belong to different committees of an alcohol, tobacco, and other drug abuse prevention coalition completed a comprehensive survey designed to measure specific variables associated with coalition functioning including costs and benefits of participation. Community volunteers are one of the coalition’s greatest resources, and benefits and costs may mediate member participation throughout the different stages of coalition functioning. The survey was completed first at the formation stage (Time l), and then eight to ten months later at the implementation stage (Time 2) of the coalition’s development. Contrary to most previous research, a principal component analysis of the benefit and cost items yielded only one benefit component and one cost component. Also, the authors found that benefits and costs distinguished between the members of “High” and “Low” attendance groups only at Time 2. We consider the implications for coalition functioning, empowerment theory, and “incentive/cost management.” We also describe how we provided the partnerships with information in order to assist them to implement the incentivefcost management process.

Community coalitions are frequently being used to address serious public health concerns. For example, the Center for Substance Abuse Prevention (CSAP) currently funds 245 communities across the country to create community partnerships in order to mobilize individuals and organizations to address the alcohol, tobacco, and other drug abuse (ATODA) problems at a local level. CSAP partnerships form coalitions involving youth and parent volunteers, in addition to volunteers from business, the criminal justice system, the media, health services, the religious community, as well as community and school-based personnel to develop and implement a comprehensive plan for reducing ATODA within their community. The coalition studied in this research is one of the 245 CSAP partnerships. Maximizing volunteer participation is important because the coalition depends heavily on the efforts of these volunteers to do much of the coalition’s work. Gaining an understanding of the benefits and the costs that volunteer coalition members experience from their participation is the first step in this process.

Participation, benefit, and cost variables are related in various volunteer organizations (Prestby, Wandersman, Florin, Rich, & Chavis, 1990), political parties (Clarke, Price, Stew- art, & Krause, 1978), and business groups (Knoke & Adams, 1987). Since this relationship is robust and useful across several different types of organizations, this study will examine the relationship between participation, benefits, and costs in volunteer coalitions. Researchers have previously studied individuals’ perceptions of benefits and costs (Chavis, Florin, Rich, & Wandersman, 1987; Prestby & Wandersman, 1985; Wandersman & Alderman, 1993; Wan-

We would l i e to acknowledge Jim Roberts, Ph.D. for his help with the statistical analyses of this article. Journal of Community Psychology, Val. 24, No. 3, 263-274 (1996) 0 1996 John Wiley & Sons, Inc. CCC o090-4392/96/030263-12

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264 CHINMAN ET AL.

dersman, Florin, Friedmann, & Meier, 1987) in different organizations; however, coalitions differ because they are usually made of smaller groups or committees that represent other organizations, who are prone to being pulled away by other commitments (Butterfoss, Good- man, & Wandersman, 1993a). Investigating high active versus low active committees’ perceptions (as opposed to individuals’ perceptions) of the benefits and costs may offer social scientists a better understanding of people’s motivations as well as give practitioners the opportunity to improve coalition functioning. Also, benefits and costs experienced by volunteers can be systematically studied at various stages of coalition functioning to determine their relative importance over time.

Participation, benefits, and costs are also important because they have been linked to the construct of individual empowerment (Prestby et al., 1990). Recently, however, Israel, Checkoway, Schulz, and Zimmerman (1994) have begun to examine empowerment at the organizational level. Organizational empowerment is the result of democratic management, shared decision-making, and the pursuit of mutually defined goals. As a result, individuals are empowered as part of the organizational process. This type of empowerment enhances individuals’ control within the organization, and the organization’s ability to affect policy within the community. Coalitions may not only be agents of community change, they may foster empowerment within its membership as well. Gaining a better understanding of the relationship between benefits, costs, and participation at the group level may help to develop organizational empowerment theory. In order to place an analysis of benefits and costs in the proper context, a brief discussion of coalition research is warranted.

Coalitions and Stage Development

Although not all researchers and social scientists share the same definition of coalitions (Allensworth & Patton, 1990; Boissevain, 1974; Butterfoss et al., 1993a; Stevenson, Pearce, & Porter, 1985), most see coalitions as inter-organizational, cooperative affiliations that unite individuals and groups for a common purpose.

Recently, researchers have focused on stages of coalition development (Butterfoss et al., 1993a; Florin, Mitchell, & Stevenson, 1989). Butterfoss et al. discuss the stages of coalition development called formation, implementation, maintenance, and outcomes. For example, the formation stage of the CSAP coalition studied here began when the lead agency received funding from CSAP, hired project staff, formed committees, and began training volunteer members. This stage ended when the coalition structure was formed. The implementation stage involved committees forming more issue-specific subcommittees and conducting a needs assessment to better understand the problem of ATODA in their community and writing a comprehensive plan to help prevent ATODA based on that information. The maintenance stage involved sustaining the committee’s planned activities and ended when the coalition completed writing its prevention plans. The outcome stage will involve the effects of the coalition’s efforts on ATODA. The present study was conducted at the formation and implementation stages in order to shed light on the factors that are important at the different stages of coalition development. To date, there is little research about this topic (Butterfoss et al.).

Conceptualizing Benefits and Costs of Participation

Benefits are rewards that volunteers receive as a result of their participation. Providing these rewards serves as a type of social control mechanism that leads volunteers to give their own personal resources to the collective organization (Kanter, 1968; h o k e & Wood, 1981). Clark and Wilson (1961) believe the incentive system may be regarded as the main variable affecting organizational behavior. Costs can be viewed as the negative consequences associ-

BENEFITS AND COSTS 265

ated with participating in a group. Although there is less research on costs, minimizing a group member’s costs may be just as effective in enhancing that member’s participation as providing more benefits.

In order to conceptualize a framework for volunteer participation, Clark and Wilson (1961) created a topology that defines three general types of benefits from participation: 1) Material benefits are tangible rewards, 2) Solidary benefits refer to social aspects of the setting, 3) and Purposive benefits relate to personal-organizational goals. Kanter (1 968), Clark et al. (1978), and Knoke and Adams (1987) proposed similar types and numbers of categories but different names for those categories. While some of the earlier work points to three benefit and cost factors, other researchers have found that there are two factors for both the benefit and cost items (Friedmann, Florin, Wandersman, & Meier, 1988; Norton, Wan- dersman, & Goldman 1993; Prestby et al., 1990; Wandersman et al., 1987). The first benefit factor is called Personal (similar to Clark and Wilson’s Material factor), and the second is Social/Normative (a combination of Clark and Wilson’s Solidary and Purposive factors). The first cost factor is Personal costs, and involves what members personally give up as a result of their participation. The second, Social/Organizational costs, involve interpersonal conflicts with other members and conflict over organizational goals.

Similar to this study, Butterfoss (1993) also conducted a principal components analysis on the same data used in this study at two times (formation and implementation stages). She found that the benefit items all loaded on one component at both times. The cost items loaded on two components at the formation stage which corresponded to the two factor model (Friedmann et al., 1988; Norton, Wandersman, & Goldman 1993; Prestby et al., 1990; Wandersman et al., 1987), but loaded on three components at the implementation stage which corresponded to the three factor model (Clarke et al., 1978; Clark & Wilson, 1961; Kanter, 1968; Knoke & Adams, 1987).

However, most of these previous studies did not state how they generated their final number of factors or components (Butterfoss, 1993; Clarke et al., 1978; Friedmann et al., 1988; Knoke & Adams, 1987; Prestby et al., 1990; Wandersman et al., 1987). Instead, these studies discussed the factor loadings and how there was little overlap among the factors. The only study to mention any strategy was Norton et al. (1993), who examined one, two, three, and four component solutions and chose the two component solution because it had the lowest inter-factor correlations. We are unaware of this strategy as being a widely used method for component or factor retention. We used a scree plot of the eigenvalues (Catell, 1966) to determine the number of components to extract. Zwick and Velicer (1986) state that the scree method is better than simply retaining all the components or factors with eigenvalues greater than one.

Research on Benefits and Costs of Participation There is much research that shows that the perceived benefits and costs of participation

are important considerations for continued participation in volunteer neighborhood organizations (Chavis et al., 1987; Prestby et al., 1990; Prestby & Wandersman, 1985; Wandersman et al., 1987), in self-help groups (Norton et al., 1993), in volunteer agencies (Wandersman & Alderman, 1993), in political parties (Clarke et al., 1978), and in large voluntary associations (Knoke & Wood, 1981).

Although much of the empirical work on benefits and costs has been conducted using different groups, researchers have also attempted to assess benefits and costs using community coalitions (Adrian & Press, 1968; Bailey, 1986; Benard, 1989; Butterfoss, 1993; Hord, 1986; Roberts-DeGennaro, 1987). While this early coalition research simply catalogued the

266 CHINMAN ET AL.

benefits and costs members reported most, researchers recently studying coalition development have begun to investigate the potential association between member participation, benefits, and costs (Butterfoss, 1993; Butterfoss, Goodman, & Wandersman, 1993b; Rogers, Howard-Pitney, Feighery, Altman, Endres & Roeseler, 1993; ISA Associates, 1993).

ISA Associates (1993) reported that a high level of member participation in committees was associated with intermediate partnership achievements and tended to counter some of the common difficulties the partnerships experienced. Butterfoss (1993) found that the higher the perceived benefits, and the lower the costs, the more satisfied coalition members were with their committee work and the prevention plans they created. Rogers et al. (1993) also found that individual members reported feeling more satisfied with the coalition when they experienced lower costs. Benefits and costs also predicted the participatory roles assumed by committee members so that the higher the benefits and the lower the costs, the more participatory roles members assumed (Butterfoss, 1993).

The Present Study The benefit and cost approach has been useful in a variety of organizational settings.

While the research employing neighborhood organizations, political parties, and business groups offers a theoretical starting point, this study contributes to the literature on coalition functioning by assessing how participation is associated with benefits and costs within a coalition. Also, although the prior research has typically focused on assessing the benefits and costs of either high active or low active individuals, we chose to assess high and low participating groups since coalitions are usually comprised of smaller groups (i.e., committees). Contrary to previous studies, we examine the members’ perception of benefits and costs at two different points in the life cycle of the coalition. Since members engage in different activities at different stages of coalition development, it is likely that members experience benefits and costs differently at different stages of coalition development.

In this study, we examine three major issues. First, we assess whether or not the benefit and cost factor models from previous studies would be appropriate for coalitions. Although this analysis duplicates the Butterfoss (1993) PCA, that study did not report its strategy for determining the final number of components. Second, we investigate the differences between the high and low participation groups during the formation stage of coalition development (Time 1). Since all new members initially tend to be enthused about the coalition, both high- and low-active groups may view the benefits and costs of their early participation equally at the formation stage. Therefore, we hypothesize that members who belonged to committees with high- and low-attendance rates (“High” and “Low” attendance groups) should not experience benefits and costs differently at the formation stage of coalition development (Time 1). Third, we examine the differences between the high- and low- participation groups during the implementation stage of coalition development. It is possible that the “Low” attendance group begins to experience less benefits and more costs only after their initial enthusiasm begins to dissipate later in the implementation stage. Therefore, we hypothesize that members in the “High” attendance group should experience greater benefits and lesser costs than the “Low” attendance group at the implementation stage of coalition development (Time 2).

Method

Participants Participants in this study were members of a community coalition in one of three

adjacent counties in South Carolina. County A is a prosperous, urban, and rural community


with a population of approximately 175,000. County B is a poor, rural county with a population of 33,000. County C is also a poor, rural county with a population of approximately 22,000.

We conducted the first administration after a committee had met four times (Time 1). County A committee members completed 118 questionnaires (response rate of 8 l%), County B completed 44 questionnaires (89%), and County C completed 77 questionnaires (92%). Members were equally represented by gender (50% male in both Counties A and C, and 44% male in County B). The predominant age groupings were between 30 and 50 years (61%); and under twenty years of age (17.6%). The predominant races of the committee members were Caucasian (78%) and African American (21%) and the ratios of these racial groups reflect the general population trends in the three counties. Most respondents (94%) reported completing high school with 72% having a college degree. Over two-thirds of the committee members were employed full time. At the second administration conducted eight to ten months later (Time 2), County A committee members completed 101 surveys (response rate of 87%), County B completed 45 surveys (response rate of 87%), and County C completed 78 surveys (81%). Since there was very little turnover on these committees, most of the demographic information reported above for Time 1 remained the same.

Procedure Four of the authors, as program evaluators of the community coalition, helped develop a

comprehensive 127-item survey which was administered to a total of 15 committees in all three counties (Butterfoss et al., 1993b). There were 14 benefit items and 13 cost items (see Table 1). Committee members responded to the items by choosing one of the following for each item: (4) very much a benefit (or cost), (3) somewhat of a benefit (or cost), (2) a little of a benefit (or cost), and (1) not at all a benefit (or cost). We plotted the survey on committee members from a similar coalition in a neighboring county and revised the instrument accord- ingly.

Attendance rates. We created “High” and “Low” attendance groups in order to examine the relationship between benefits, costs, and group participation in the coalition. The 15 committees were ranked by attendance rates, and the “High” and “Low” groups were formed using a median split. Therefore, at Time 1, the “High” attendance group included the eight committees with the highest attendance (M = 64.25%) and the “Low” attendance group included the seven committees with the lowest attendance rates (M = 42.14%). At Time 2, there were seven “High” attendance groups (M = 46.14%) and eight “Low” attendance groups (M = 25.75%) when separated using a median split.

The use of the median split in creating the “High” and “Low” groups resulted in the groups differing somewhat between Time 1 and Time 2. However, the difference in attendance rates between the “High” and “Low” groups at Time 1 was about 22%, whereas the difference at Time 2 was about 30%. Although the difference between the groups was slightly greater at Time 2, it was out intention to study naturally occurring “High” and “Low” groups at two points in the development of a coalition. If the same split was used at both Times, the resulting groups would not have been “High” or “Low.”

Design The protocol called for each committee to complete the survey twice: once after the

fourth meeting of each committee to allow for a sense of “groupness” to develop (Time 1); and again about eight months later just prior to finishing their committee plans to prevent ATODA (Time 2). At Time 1, we asked each committee member to complete the survey

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Table 1 Benefit and Cost Items

CHINMAN ET AL.

Benefit Items

Learn new skills (public speaking, program planning, etc.) Receive information about community services, events, county government, etc. Learn more about AODA prevention Supports my decision to not abuse AOD Provides an opportunity to improve the way I do my job Provides a chance to explore new job opportunities Supports my agency or group’s concerns and missions Gain personal recognition and respect from others Increase cooperation with members of other community agenciedgroups Gain support by working with other members of the community Receive satisfaction by being involved in an important project Fulfill a sense of responsibility to contribute to the community Help people at risk for AODA Makes the community a safer place to live

Cost Items

Find caregivers for family members Demands too much of my personal time Have to give up activities with family or friends Adds unwanted job responsibilities Have to go to meetings/events at inconvenient times Have problems with transportation to meetings/events Takes too much time from agency or organizational commitments Feel unwelcome or not like a part of the committee Conflicts between the mission of my organization/agency and the committee’s

Conflicts between my professional practice/business and the committee’s work Disagree personally with the goals or activities of the committee Feel that the committee never gets anything accomplished Feel that the committee cannot really do much to solve the problems of AODA

work

during a regular committee meeting. If a committee member was absent or unable to complete the survey, we sent he or she a survey in the mail and asked them to return it. Coalition staff made follow-up phone calls and verbal reminders in order to increase response rates.

At Time 2, the coalition staff and the committee members felt that the committees were too involved in developing their committee plans to spend time during a committee meeting to complete the survey. Therefore, the committee members received and returned the surveys through the mail with the same follow-up procedures. We shared the results of the surveys with all county staff and committee chairpersons who then decided how the results would be communicated to the individual committee members.

Results

Time I Analyses First, we conducted a principal components analysis (PCA) on the benefit items and

another on the cost items to determine the number of underlying dimensions to use in the subsequent analyses. A scree plot of the eigenvalues (Catell, 1966; see Figure 1) shows the largest break between the first and second eigenvalue for both benefits and costs, suggesting one component for each. Thus, these results did not conform to either the two- or three-factor model for the benefit items nor to the two factor model for the cost items found in previous


7

6 *Time ICosts +Time 2-Benefits

5

u)

- 9 4 9 .% 3 w

2

1

0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4

FIGURE 1. Scree plot of eigenvalues for benefits and costs at Time 1 and Time 2.

research. The component loadings for benefit items at Time 1 ranged from .576 to .785, suggesting that all items contribute to a single underlying benefit construct. The component loadings for cost items at Time 1 ranged from .312 to .686, indicating that one dimension exists and that most items load on that dimension. We conducted reliability analyses (Cron- bach’s Alpha) on the resulting cost and benefit dimensions. The benefits at Time 1 had an Alpha of .88 and deletion of items did not improve reliability. The costs at time 1 had an Alpha of .78 with all items included and deletion of items did not greatly improve reliability.

Next, we conducted ANOVAs using a hierarchical nested design (Winer, 1971) to determine if members of “High” and “Low” participation groups differentially perceived benefit and cost dimensions that resulted from the PCA (see Table 2 for ANOVA results). This is a nested design because each committee is confined to only one level of the indepen- dent variable. For example, members in high participating committees can only appear in the

Table 2 Means, F-ratios, and p-values of the “High” and “Low” Participation Groups for Benefits and Costs

Participation Attendance Benefits/Costs Time Group Rates (%) Mean’ F-ratio P

Benefits Benefits costs costs Benefits Benefits costs costs

“High” “LOW” “High” “LOW”

“High” “Low” “High” “LOW”

64.25 42.14 64.25 42.14 56.14 25.15 56.14 25.75

~ ~~~

3.165 1.546 0.216 3.056 1.507 0.306 0.58 1 1.542 3.215 5.052 .026* 2.984 1.46 7.240 .008 * * 1.641

~~

‘Note. Benefitsponses Tanged from (4) very much a benefit, (3) somewhat of a benefit, (2) a little of a benefit, and (1) not at all a benefit. Cost responses ranged from (4) very much a difficulty, (3) somewhat of a difficulty, (2) a little of a difficulty, and (1) not at all a difficulty.

*p < .05. At Time 2, members in the “High” group experienced the benefits to a greater extent than the “Low” vrniin

--p c .WJ. AI lime L, memoers --LOW goup expenencea me costs to a grearer exrent Inan me nign group.

270 CHINMAN ET AL.

“High” participation group. This design is preferable here because it can assess the unique effects associated with each individual committee (i.e., group level effects) with a separate F-test.

As a result of PCA, we performed an ANOVA (using the hierarchical nested design) on the single benefit scale and on the single cost scale. The ANOVA at Time 1 yielded no significant differences between the “High” and “Low” participation groups on either benefits F(1,158) = 1 . 5 4 6 , ~ = .216 or costs F(1,158) = 0 . 3 0 6 , ~ = S81. The nested term was close to significance, F( 1,13) = 1.72 1, p = .06 1 . This result suggests that the lack of significant differences between “High” and “Low” groups may be attributed to variation among individual committees subsumed under the “High’ and “Low” groups.

Time 2 Analyses

In order to assess the consistency of the cost and benefit dimensions over time, we conducted another PCA at Time 2. Again, a scree plot of the eigenvalues (see Figure 1) identified one component for both benefits and costs. The component loadings for benefit items at Time 2 ranged from .609 to .794; therefore it seems all items contribute to a single underlying benefit construct. The component loadings for cost items at Time 2 ranged from .409 to .688 indicating that one dimension exists and that most items load on that dimension. Reliability analysis of the benefits at Time 2 yielded an Alpha coefficient of .91 and deletion of items did not improve reliability. The costs at Time 2 had an Alpha coefficient of .80 with all items included and deletion of items did not significantly improve reliability.

We wanted to compare the perceptions of costs and benefits from Time 1 to Time 2. Therefore, we conducted a similar ANOVA on the single benefit scale and on the single cost scale at Time 2. The ANOVA yielded a significant difference between the “High” and “Low” groups for benefits F(1,136) = 5.052, p = .026 and for costs F(1,136) = 7.240, p = .008. The “High” group perceived significantly more benefits (A4 = 3.215) than the “Low” group (M = 2.984), and the “Low” group perceived significantly more costs (A4 = 1.641) than the “High” group (M = 1.460). At this administration, there was little variation due to individual committees within the “High” and “Low” groups, therefore the nested term was not significant.

Discussion The major goal of community coalitions is to engage the community in large-scale

systems change (Smith, 1994). The coalitions discussed in this paper specifically target community residents who are interested in preventing ATODA in their counties. However, having committees of community volunteers that work effectively and efficiently is a major challenge. Therefore, understanding the relationship between volunteer participation and benefits and costs can reduce the problems of low member turnout and noncontributing members.

In this study, we first examined the dimensions of the benefit and cost items. Most research with various groups has proposed two and three motivational factors for benefits and costs that affect participation. In the present study, the PCA of the benefits and the costs failed to yield similar factor models found in most previous research at either the formation or implementation stages. However, using the scree plot method, the PCA results for the benefit items (one component) did replicate Butterfoss (1993). However, the PCA results of the costs (one component) differed from Butterfoss (1993), who found two and three components at the formation and implementation stages respectively.

Since the previous research did not specify the strategies used in determining the

BENEFITS AND COSTS 27 1

number of factors or components, it is difficult to know specifically why this study found one component for the benefit and the cost items. Perhaps the difference is a statistical issue: the other studies may have used the popular Kaiser’s eigenvalue greater than one rule, which tends to overestimate the number of components retained (Zwick & Velicer, 1986). On the other hand, the difference may be related to the type of organization studied in the previous literature: coalitions differ from block and neighborhood associations in that they are usually larger, involve a wider range of constituents, last longer, and focus on a more diverse set of issues. While the smaller associations may be consistent with regard to specific factors or components, the replication of Butterfoss (1 993) (despite possibly using different extraction methods) suggests that a more global assessment of benefits is more relevant for coalition members. The discrepancy among the cost items needs further study. In order to further clarify this issue in the future, it would be useful for researchers to include their procedures for determining the final number of factors or components.

Second, our hypothesis that the members of the “High” attendance group would experience benefits and costs the same as members of the “Low” attendance group at Time 1 (formation stage) was confirmed. Since members of both “High” and “Low” groups had not attended many meetings (ie., four), it is likely that their perceptions of benefits and costs were similar.

Third, members in the “High” attendance group experienced more benefits and less costs than members in the “Low” attendance group at Time 2 (the implementation stage), confirming our hypothesis. Possibly, after several meetings, the members of the “High” attendance group began to experience the benefits from their continuous attendance, whereas the members of the “Low” attendance group did not receive these benefits because they were not present at the meetings, or their group was not as functional.

In addition, the members of the “High” attendance group may be present more often when specific decisions were made concerning committee’s goals, objectives, and planned activities. The high group’s greater participation would have allowed them to have more of a significant impact on the coalition’s functioning. As a result, these members were more likely to agree with these goals and activities because they had an influence in the decision-making process. Members of the “Low” attendance group may have experienced the costs of goal conflict because they were not present often enough to have an impact, and may have been more likely to disagree with the goals and activities. This reasoning is consistent with results from ISA Associates (1993) indicating that members who did not actively participate in their committees were usually the most disillusioned about the partnership’s progress and less likely to be satisfied or optimistic. Also, the “LOW” attendance group may have experienced more costs because their committees had less accomplishments.

Strengths and Implications This study has a number of strengths. First, to our knowledge, this study is one of the

first to consider the impact of belonging to a high and low participating group on members’ perceptions of benefits and costs. Since many coalitions are comprised of smaller work groups or committees which do most of the work, studying these groups rather than the individuals who comprise the coalition as a whole, clarifies the issues involved that mediate participation. Therefore, while data is collected from individuals, only using data from this level is problematic because it does not take into account variance due to the group climate which may influence individuals’ perceptions (Shinn, 1990; Florin, Giamartino, Kenny, & Wandersman, 1990). However, the nested design employed in this study allowed us to assess the effects of belonging to both individual committees and high or low participation groups.

272 CHINMAN ET AL.

We found that membership in a “High” or “Low” attendance group had more of an impact on their perceptions of benefits and costs than their membership in individual committees.

Second, members of the “High” and “Low” attendance groups completed surveys at both the formation and implementation stages of coalition development. Since coalitions change as they mature, it is important to understand benefits and costs at each stage in order to maximize volunteer participation. Future studies should examine specific benefits and costs over the entire lifetime of a committee (i.e., throughout all the stages of coalition’s life- cycle).

Third, the group-level focus at two different points of coalition development adds to the understanding of benefits and costs as they relate to volunteer participation in coalitions. As community volunteers are recruited to participate in anti-drug community coalitions to help plan ATODA prevention strategies, enhancing participation becomes important for the suc- cess of these efforts. Coalition staff can use this greater understanding to improve coalition functioning through methods called “incentive/cost management” (Prestby et al., 1990) to create a benefit to cost ratio that members find favorable enough to continue their participation.

Fourth, the relationships between benefits, costs, and participation in groups has new implications for organizational empowerment theory. Participation, benefits, and costs among individuals has been found to be related to individual empowerment (Prestby et al., 1990). Therefore it is logical to propose based on the results found here that benefits, costs, and participation of groups will be related to organizational empowerment. Empowerment at the organizational level involves groups of individuals making decisions and having a significant effect on their surroundings as an organization (Israel et al., 1994). In Kieffer’s (1984) narrative description of how empowerment develops he discusses how it usually occurs in a group and how group members support each other in their growth. Therefore, the group process appears to be an important factor in the development of empowerment at the organizational level and must be taken into account in order to make conclusions about organizational empowerment. Although future research needs to assess these relationships directly, by examining the relationship between benefits and costs and participation of groups, we have taken the first steps to link the benefit and cost approach with organizational empowerment.

Feedback. Since benefits and costs discriminate between high and low participation groups, we recommend that professionals in this field use incentive/cost management to enhance participation of their volunteers. Every community is unique, therefore we advise practitioners to survey their members to find out what benefits and costs they are experiencing. From there, practitioners can provide more of the benefits their members desire and reduce the costs they do not want.

In order to facilitate the incentive/cost management process for the partnerships that we evaluated, we conducted a survey feedback process for the staff and the chairpersons of the committees. After we surveyed committee members, we arranged the data into tabular form for each committee, called Committee Profiles. These profiles contain various graphs and tables that cover a wide range of committee characteristics (i.e., linkages/resource exchange, team spirit, attendance, etc.), including benefits and costs. We then gave the staff The Committee Profiles Handbook, which contains explanations of the data and suggested activities the committees can implement to improve their functioning within each dimension, depending where they fell on that dimension. For example, if a committee profile showed that the members were not experiencing many benefits, the staff and the chairperson can then look


at the benefits section in the handbook and implement the suggested activities found there. Finally, we conducted a workshop for project staff to train them to feedback the committee profile information to their respective committees.

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