Planning a mentorship initiative for foster parents: Does gender matter?

Accepted Manuscript Title: Planning A Mentorship Initiative for Foster Parents: Does Gender Matter? Authors: J. Jay Miller, Kalea Benner, Shawndaya Thrasher, Natalie Pope, Tamikia Dumas, Larry J. Damron, Melissa Segress, Chunling Niu PII: DOI: Reference:

S0149-7189(17)30021-6 http://dx.doi.org/doi:10.1016/j.evalprogplan.2017.05.009 EPP 1448

To appear in: Received date: Revised date: Accepted date:

27-1-2017 23-3-2017 6-5-2017

Please cite this article as: Jay Miller, J., Benner, Kalea., Thrasher, Shawndaya., Pope, Natalie., Dumas, Tamikia., Damron, Larry J., Segress, Melissa., & Niu, Chunling., Planning A Mentorship Initiative for Foster Parents: Does Gender Matter?.Evaluation and Program Planning http://dx.doi.org/10.1016/j.evalprogplan.2017.05.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Planning A Mentorship Initiative for Foster Parents: Does Gender Matter? J. Jay Miller*, Kalea Benner, Shawndaya Thrasher, Natalie Pope, Tamikia Dumas, Larry J. Damron, Melissa Segress, and Chunling Niu Planning A Mentorship Initiative for Foster Parents: Does Gender Matter? Training Resource Center, University of Kentucky College of Social Work *Corresponding Author: [email protected] Article Highlights    

Planning models for mentorship programs are few, particularly in the area of foster parenting. Existing literature suggest gender differences in the way individuals conceptualize and experience mentor programs. This study utilized multi-dimensional scaling and hierarchical cluster analysis with fpster parents to conceptualize planning an effective mentor program. Results yielded s seven-cluster planning framework; no significant gender differences were detected in priority ratings for the conceptualization.

Abstract Despite the use of mentoring programs in fields such as business, career training, and youth development, little is known about how mentoring can be used to train and support new foster parents. This paper describes how Concept Mapping was used with current foster parents to develop a conceptual framework suitable to plan a foster parent mentor program. A secondary aim of this study was to explore priority differences in the conceptualization by self-reported gender (foster mothers vs. foster fathers). Participant data was collected via three qualitative brainstorming sessions, and analyzed using non-metric multidimensional scaling and hierarchical cluster analysis. Findings indicate that foster parents participating in this study conceptualized effective mentor programs via a seven cluster solution. Study results also showed no significant differences in cluster ratings by gender. Implications for practice and program planning are identified, as well as areas for future research. KeyWords: Child Welfare; ; ; ; , Foster Parents, Mentor Programs, Gender, Planning Introduction Foster parents are tasked with caring for society’s most vulnerable children. In order to support foster parents in this endeavor, public (e.g., local and state governments) and private (e.g., private child welfare service providers) entities are looking for ways to support foster parents charged with caring for maltreated young people. One way this support has manifested

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itself is through the propagation of mentor initiatives that support both caregivers and the children in foster care (e.g., Cohen & Canan, 2006; Rhodes, Haight, & Briggs, 1999; Weinberger, 2014). Despite the acknowledgement that mentorship programs can support permanency and placement outcomes for children, the literature is devoid of research related to the use of mentoring for foster parents. Further, there is nominal research that examines differential planning processes for supporting foster parents through mentoring relationships. This paper seeks to uniquely address these limitations. The purpose of this exploratory research was to examine foster parent (N = 59) perceptions related to conceptualizing a framework necessary to plan a foster parent mentor program. Additionally, this study examined priority differences in the conceptualization, by selfreported gender (i.e., foster mothers vs foster fathers). To achieve these aims, researchers employed a mixed method approach that analyzes qualitative data via quantitative device, specifically non-metric multidimensional scaling and hierarchical cluster analyses. Through these analyses, illustrative visual depictions of participant data are computed. After a terse review of literature, this paper will outline methodological processes undertaken for this study, explicate results, and discuss lessons learned for future programmatic development and evaluation endeavors for mentorship programs. Background In general, mentorship programs are designed to support learning and development of skills (Breipohl & Hamburg, 2011) and seen as a way to improve quality and retention. Mentoring has been used in a variety of ways including helping youth transition to adolescence by pairing them with a nonparental adult (Spencer, 2007; Zimmerman, Bingenheimer, & Notaro, 2002) and supporting the career development of underrepresented minority groups in science and

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math through mentorship (San Miguel & Kim, 2015). In some of the earlier, and perhaps more influential, works around mentorship, Kram (1985; 1986) postulated that mentorship programs serve a variety of psychosocial functions. As Kram and Isabella (1985) explained, mentorship can offer “role modeling, acceptance, confirmation, counseling, and friendship” to those involved in the arrangement (p. 111). Child Welfare Mentor Programs In child welfare, mentor programs have been put forth to address a number of issues. For instance, Cohen and Canan (2006) discuss the use of mentorship programs to assist biological parents in navigating complex children welfare systems. Weinberger (2014) describes the implementation of a mentorship program to support young people in kinship arrangements; mentors matched with youth being raised by their grandparents can offer advice through sharing their own relevant experiences as well as advocate on behalf of their mentee. Mentoring programs are also a strategy to provide youth in foster care with healthy, stable relationships when frequent moves between biological families, foster parents, and group homes can interrupt healthy attachments (D’Andrade, 2005). A host of other authors have discussed the use of mentorship programs in other areas of child welfare (Yancey, Siegel, & McDaniel, 2002; Greeson, Usher, & Grinstein-Weiss, 2010). Based on these examples, some have argued that mentorship initiatives have become a seminal component of the child welfare service array (e.g., Avery, 2011). Much of the attention to mentorship programs in child welfare can be attributed to several pieces of federal legislation. Exemplars include the Foster Care Independence Act of 1999 (FICA; P.L. 106-169), which established the Chaffee Foster Care Independence Act, Promoting Safe and Stable Families Amendments of 2001 (P.L. 107-133), Child and Family Services

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Improvement Act (P.L. 109-288) of 2006, and the Child and Family Services Improvement and Innovation Act (P.L. 112-34) of 2011. All of these policies entail edicts that permit states to use resources to provide mentorship services to individuals involved in child welfare and other social services. Benefits There is consensus that mentor programs can prove beneficial in child welfare contexts (Eby, Allen, Evans, Ng, & Dubois, 2008; Moodie & Fisher, 2009; Weinberger, 2014.). Such benefits include improvements in self-esteem and prosocial behaviors among young people, as found in Rhodes, Haight, and Briggs’ (1999) study of mentoring for youth in out of home care. Others have expressed similar sentiments (e.g., Massinga & Pecora, 2004). For young people exiting foster care, nonkin, natural mentors provide not only social support (i.e., instrumental, informational, emotional), but these caring adults are people “to whom [youths feel] accountable to in a meaningful way” (Munson, Smalling, Spencer, Scott, & Tracy, 2010, p.532). Both Cohen and Canan (2006) and Marcenko, Brown, DeVoy, and Conway (2010) explained that mentorship can be useful in assisting biological parents to navigate complex public child welfare systems. Indeed, these examples, and others, point to the notion that the development and implementation of mentor programs in child welfare can be a worthwhile investment (Moodie & Fisher, 2009; Rhodes et al., 1999). Challenges Though mentorship programs can have positive outcomes on foster parents and the children they are caring for, the planning, implementation and evaluation of mentorship programming is not without challenges. One challenge is associated with the considerable variability in the way that mentorship programs are conceived and implemented. Divergent

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terminology such as protégé, mentor/mentee, role model, advisor, etc. can make clearly and broadly defining mentorship difficult (Rogers & Taylor, 1997; Miller et al., 2017). Additionally, structural variations, such as peer-to-peer/one-to-one mentoring (Yancey, 1998; Ring, 2015), integrational mentoring (Taylor & Dryfoos, 1999), and virtual mentoring (Fong, Wan Mansor, Zakaria, Sharif, & Nordin, 2012), among others, have indubitably presented challenges to building a broad-based understanding. Central to the challenges of implementing and evaluating mentoring are the lack of conceptual models associated with mentorship programs. In fact, the literature associated with mentorship has been criticized for the absence of “conceptual clarity” (Chao, 1998). Though early researchers and theorists identified these deficits in the mentorship literature (e.g., Kram, 1983), there remains a lack of conceptual models, specifically for implementation and planning of mentorship initiatives (e.g., Karcher, Kuperminc, Portwood, Sipe, & Taylor, 2006;). Mentorship and Gender Given the disparate models for mentorship programs, perhaps it is not surprising that individuals experience mentorship differently. One area that has been explored is the impact that gender has on mentorship experiences. Though dated, there is ample literature to suggest that men and women may perceive mentorship dynamics differently. For instance, Ezell and Odewahn (1981) found that female public social service managers perceived that ‘‘mentor systems work more effectively for males than for females’’ (p. 62). Research also suggests that women perceive less access to mentorship than men (Noe, 1988; Ragins & Cotton, 1991) and are less likely to initiate a mentorship relationship, when compared to men (Gaskill, 1991; Ragins & Cotton, 1993). Several other works have discussed differences in mentoring experiences by

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gender (e.g., Baugh, Lankau, & Scandura, 1996; Fitt & Newton, 1981; Morrison, White, & Van Velsor, 1987; Ragins, 1997). Though limited, more recent studies also suggest differential experiences to mentorship, by gender. One example is Hu (2008), who concluded that males and females may view functions of mentor support differently. In a study of mentorship in public and private organizations, Fowler, Gudmundsson, and O'Gorman (2007) concluded that female mentors provided personal and emotional guidance to a greater extent than did male mentors and that female mentors offered career development facilitation in greater doses than did male mentors. In a meta-analysis of gender differences in mentoring, O’Brien, Biga, Kessler, and Allen (2010) reported several differences in how males and females experience mentorship programs, including differences in psychosocial differences, and access to mentorship opportunities. Other authors have shared similar sentiments regarding gender differences in mentorship experiences (e.g., Rhodes, Lowe, Litchfield, & Walsh-Samp, 2008). Despite the current literature on gender differences in mentoring, as well as the host of researchers who have issued clarion calls for an increased understanding of gender and mentoring (Noe et al., 2002; O’Neill, 2002; Young et al., 2006), researchers, specifically in the areas of child welfare and foster care, have been somewhat slow to respond. Much of the existing literature about mentorship programs is concentrated in the field of business. Further, there are few conceptual frameworks for the planning, implementation, and evaluation of mentorship programs in child welfare (Spencer, Collins, Ward, & Smashnaya, 2010), and even fewer, if any, works that examine differences in conceptualizations, by gender. Indeed, these are areas that warrant further exploration (Hu, 2008). This paper seeks to contribute to addressing these limitations in the extant literature.

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Study Purpose and Research Questions Development The purposes of this study were twofold. First, this study sought to delineate a conceptual framework for planning foster parent mentorship programs, from the perspective of those most impacted by mentorship program implementation: the foster parents themselves. Second, this study examined priority differences in this conceptualization by gender. Priority differences were rooted in examining two variables: importance and feasibility. Specifically, this study pursued two research questions: Research Question 1 (RQ1): How do foster parents conceptualize mentorship programming? Research Question 2 (RQ2): Is there a difference in the way that females (e.g., foster mothers) prioritize elements of this conceptualization when compared to males (e.g., foster fathers)? Please note that for this study participants who identified as “female” also identified as “foster mothers” and participants who identified as “male” identified as “foster fathers.” As indicated, both of these research questions are rooted in addressing limitations in the current literature. Method To answer the research questions posited above, researchers employed Concept Mapping (CM) methodology. CM is an iterative, participatory, mixed-method research methodology that pairs non-metric multidimensional scaling (MDS) with hierarchical cluster analysis (HCA). CM is a research approach process often utilized to delineate conceptual structures around a focused area of study (Anderson, Day, & Vandenburg, 2011). Several researchers (e.g., Burke et al., 2005; Haque & Rosas, 2010; Rosas, 2005) have discussed the utility of this methodology in expanding existing theoretical approaches to programmatic planning endeavors, specifically in the area of child welfare (e.g., Brown, 2008; Miller & Owens, 2015). Sample Recruitment

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For this study, researchers utilized a non-random convenience sampling procedure. All participants were recruited from one southeastern state during Summer/Fall 2016. Researchers posted recruitment fliers at social service agencies throughout the state and potential participants contacted the researchers about being involved in the study. Participant inclusion criteria included being a foster parent and being 18 years of age, or older. Participants were offered a $75 cash card incentive for participating in the study. The sampling and protocol procedures associated with this study were approved by a University Institutional Review Board. Procedure and Protocol For this study, data was collected via three (3) brainstorming sessions performed at different places around the state. All qualitative data were collected via a focused prompt. Researchers piloted several brainstorming prompts with foster parents (n = 6). Using the pilot data as a guide, the researchers utilized a prompt form approach (e.g., Miller, 2016): Complete the following statement: An effective foster parent mentor program should…”. This prompt was used in all brainstorming sessions. During the brainstorming sessions, researchers collected the statements and projected them onto a white screen so that they could be viewed by the participants. This permitted the researchers to clarify statements with participants in real-time. As well, during the brainstorming session, each participant completed a brief demographic questionnaire. Once all three brainstorming sessions were completed, the statements from all sessions were collated. Then, researchers employed Kippendorf’s (2004) method to synthesize the statements. The primary purpose of this procedure is to eliminate redundant and/or unclear statements. After this process, a total of 68 unique statements entailed the final statement set. Table 1 includes statement examples, delineated by cluster groupings.

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Once all brainstorming sessions were completed, participants were invited to a second meeting to sort and rate each of the statements. The same participants took part in both the first and second meetings. The second meeting is often referred to as statement structuring. During this meeting, each participant was provided the entire statement set. First, participants were invited to sort the statements into piles that “make sense to them” (i.e., Kane & Trochim, 2007). Ideally, participants sorted statements into piles based on some perceived conceptual theme. During this process, each participant is asked to provide a pile “label” that captures the overall theme of the statements in the pile. After the statements were sorted, participants were invited to rate each of the statements in the final statement set on two variables: importance and feasibility. This allowed the researcher to examine priority areas among the conceptual themes in data. Both variables were rated via a Likert-type scale whereas importance was rated from 1 - “Not Important At All” to 5 “Very Important.” Feasibility was anchored at 1 - “Not Feasible At All” to 5 - “Very Feasible.” Please note that each participant individually sorted and rated the statement set. Statistical Data Analyses Once all of the data was collected, it was entered into a proprietary software for data management and analyses. First, an individual similarity matrix was computed for each participant. This matrix is binary and denotes statements that were sorted together into the same pile. In this binary matrix, “0” indicated that a pair of statements had not been sorted together into the same pile, whereas “1” indicated that the statements had been sorted together. Then, the individual participant similarity matrices were collated into an aggregate matrix. For the aggregated matrix, values ranged from 0 to 59, which is the total number of

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sorters (i.e., participants). Higher numbers for a pair of statements indicate that more participants sorted a particular pair of statements into the same pile. Next, MDS was performed using the aggregated similarity matrix as input. This analysis serves to place each statement as a represented point within a two-dimensional configuration (along x and y axes). These points are analyzed via HCA. During the HCA process, statements are grouped together through a hierarchical agglomerative procedure, which “clusters” statements into groupings. Results Participants Fifty-nine participants took part in brainstorming and statement structuring activities for this study. All participants were foster parents residing in one southeastern state. The typical participant identified as female (n = 35), Caucasian/White (n = 54), African-American/Black (n = 3), or Biracial/Multiracial (n = 2), was aged 39.53 (SD = 10.37) years, and had been a foster parent for approximately 4.4 months (SD= 2.4 months). In terms of educational background (highest obtained), 17 participants reported having a high school/general equivalency diploma, and 11, 20, and 11 participants reported having Associates, Bachelors, or Master’s degree, respectively. Nine of the participants reported having a current foster placement. Statement Set As discussed above, the final statement set contained a total of 68 unique ideas. Examples of these statements, by cluster, are contained in Table 1. INSERT TABLE 1 ABOUT HERE. Point Cluster Map The MDS analysis of the sort data merged after 20 iterations and yielded a stress value of 0.26. Typically, stress values range from .205 - .365 (Rosas & Kane, 2012). Thus, the value for

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this study was deemed to be within acceptable range. The HCA analysis, using the MDS output as input, produced a seven (7) cluster solution. The seven clusters are as follows: Program Evaluation, Matching Practices, Training, Foster Relationships, Program Structure, Mentor/Mentee Recruitment, and Ongoing Support. This seven cluster solution is illustrated via the Point Cluster Map in Figure 1. Please note that the labels ascribed to each of the clusters are derived from the labels participants gave to piles during the sorting exercises discussed above. Each point in this two dimensional space (along the x and y continuum), represent a statement collected during the brainstorming phase discussed above. INSERT FIGURE 1 ABOUT HERE. Bridging values, which are produced through the HCA analysis, ranged from 0.11 to 0.62. Bridging values associated with each cluster are delineated in Table 2. INSERT TABLE 2 ABOUT HERE. Pattern Matches and T-tests To examine differences in priority areas of the conceptualization, the researchers computed Pattern Matches based on participant cluster rating data. Pattern matches are pairwise comparisons of cluster ratings. As discussed above, for this study, participants provided rating data for two variables: importance and feasibility. Figure 2 illustrates the pattern match graph for cluster importance ratings, by participant group. INSERT FIGURE 2 ABOUT HERE. As Figure 2 illustrates, both participant groups, foster mothers and foster fathers, rated statements in the Recruitment cluster as most important. Additionally, both groups rated statements in the Matching Practices cluster as the least important. The correlation statistic for cluster importance ratings between the groups was 0.89.

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To further investigate differences in the cluster ratings of foster mothers and foster fathers, the researchers initiated Welsh’s t-tests, cluster. These analyses revealed no statistical differences for cluster ratings between the two groups. The cluster ratings and results of the ttests for each cluster are delineated in Table 3. INSERT TABLE 3 ABOUT HERE. Figure 3 is the pattern match for feasibility ratings, by participant group. INSERT FIGURE 3 ABOUT HERE. As Figure 3 illustrates, both participant groups, foster mothers and foster fathers, rated statements in the Recruitment cluster as most feasible. Foster fathers rated statements in the Program Evaluation cluster as least feasible, while foster mothers rated statements in the Matching Practices cluster as least feasible. The correlation statistic for cluster feasibility ratings between the groups was 0.83. Similarly to above, researchers initiated t-tests to investigate differences in the cluster feasibility ratings of foster mothers and foster fathers. These analyses revealed no statistical differences for cluster ratings between the two groups. The cluster ratings and results of the ttests for each cluster are delineated in Table 4. INSERT TABLE 4 ABOUT HERE. Discussion The purposes of this study were two-fold. First, this study was to explicate a conceptual framework for planning and developing foster parent mentor programs. Second, this work examined priority differences, in terms of importance and feasibility, of this conceptualization, by gender. Both of these purposes contribute to addressing limitations in the current literature. The following paragraphs outline prominent discussion points congruent with answering the research questions posited above.

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Foster parents who participated in this study conceptualized effective mentor programs via a seven cluster solution. These clusters included Fostering Relationships, Matching Practices, Program Structure, Program Evaluation, Recruitment, Training, and Ongoing Supports. The stress value resulting from the MDS analysis does indicate that the visual depictions of participant data (e.g., Figure 1) is a “good fit” to the actual participant sort data (e.g., Kane & Trochim, 2007; Rosas & Kane, 2012). Bridging values resulting from the HCA indicate that the Matching Practices cluster was the most cohesive, with a bridging value of 0.11. This indicates that participants were in most agreement about the conceptual relationship among statements sorted into this clusters. Conversely, based on the bridging values, the Program Structure cluster was the least cohesive, with a bridging value of 0.62. This statistic indicates that participants sorted statements into this cluster at a lower rate, when compared to other statements. Thus, participants were least agreeable about the conceptual relationship of statements sorted into this cluster. In many ways, aspects of this conceptualization are congruent with the existing mentorship literature. For instance, (Kram, 1985) articulated four phases of mentoring relationships: Initiation, Cultivation, Separation, and Redefinition and Kalbfleisch’s (2002) Theory of Enactment asserted that effective communication is central to health mentor/mentee relationships. The concept of phased relationships based on communication is captured by ideas in the Fostering Relationships, Matching Practices, and Recruitment clusters. Based on these data, participants recognized the need to be intentional about developing strong relationships between mentors and mentees, and being deliberate in matching mentors/mentees so as to encourage strong relationships.

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Though there is broad-based consensus regarding the positive benefit of mentorship programs, historically, authors have called for additional research related to these programs (e.g., Hu, 2008). This in mind, it makes pragmatic sense that participants viewed program evaluation as a pertinent aspect of conceptualizing mentor programs for foster parents. In terms of RQ2, data analyses revealed no statically significant differences, by gender, in priority areas of the conceptualization. Said another way, there were no significant differences in cluster ratings for either importance or feasibility, by gender. Overall, based on the correlation values, there was a high level of consensus between cluster ratings for males and females. Based on existing literature, one may have assumed that there would have been differences in priority areas of the conceptualization. However, there are several reasons that may impact why these differences were not evident in these data. One reason may be rooted in the origins of traditional mentorship theory. Though theory may suggest differences, it appears that most of the empirical base on which that literature was founded, was built on male dominated business fields (e.g., Scandura & Ragins, 1993, etc.). Thus, new theories, particularly related to mentorship in general, and in social services, specifically, may better explain mentorship priorities among foster parents. Implications: Lessons Learned A host of implications may be derived from findings associated with this study. The following paragraphs briefly outline several salient implications. First, mentoring is certainly an acceptable method to support individuals in developing skills, efficacy and quality related to a specific role or task. However, little is known about the role of mentoring with child welfare, specifically with foster parents. With mentoring in other disciplines demonstrating improved retention and quality of services (Foster et al., 2016),

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development of mentoring programs to provide social support, facilitation of skill development, and promotion of longevity for foster parents is certainly justified. Data from this study provides some insight into program structure. Participants in this study indicated that in addition to more traditional mentor structures (e.g., protégé), foster parents may benefit from peer-to-peer structures. Additionally, program structures should be conducive to building strong relationships among mentors/mentees. This point is certainly evident in the literature. Insights from study participants suggest that initial introductions between potential mentor/mentee matches should be made in a controlled environment and facilitated by program personnel. As well, data indicates that potential mentors and mentees should be able to interact, even if virtually, before being formally “matched.” Second, all participants rated recruitment as the most important and feasible components for effective mentorship programs. Thus, program managers and administrators should be mindful about recruitment of both mentors and mentees. Recruitment should include strategic marketing that targets seasoned foster parents interested in providing mentorship. Data from the current study indicates that programs may consider paying mentors and/or incentivizing participation in mentor programs. Another pertinent aspect related to recruitment is providing ample support for mentors and mentees, alike. Of course, support, or lack thereof, may negatively impact retention. As such, managers/administrators should be mindful of providing support to mentors. This may include the development of virtual support networks of foster parent mentors. Data suggest that participants are open to using virtual platforms in mentoring programs. Virtual networks may allow foster parents to connect in an efficient manner and assist in providing ongoing support for providing adept mentoring services. Moreover, programs should work to identify mentees who

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are open to being a mentor, and provide a training “track” for these individuals to seamlessly move into a mentor capacity. Third, there are implications associated with the rating data for the Program Evaluation cluster. This cluster was rated as one of the least feasible for both groups. As indicated in the literature (Spencer et al., 2010), program evaluation can be a difficult task associated with mentor programs and many programs may lack the capacity for evaluation. As such, administrators/managers should be mindful about building capacity for evaluation or work to establish relationships with entities (i.e., academic institutions) that may be able to assist in this area. When thinking about implications associated with the rating data posited above (see Figures 2 -3 and Tables 3 - 4) it is pertinent to note that the rating data is relative. Specifically, participants were asked to rate each statement vis a vis each other statement. Even the lowest rated clusters in terms of the rating variables of interest (importance and feasibility) could be considered pertinent and somewhat feasible. Fourth, although data from the current study suggest no differences in the way that males and females prioritize areas of effective foster parent mentor program, this study certainly has implications related to the need for theory development associated with foster parent mentor programs. As mentioned above, traditional mentorship theory appears to have originated in business literatures; these theories seem to be somewhat limited in taking into account complex relational dynamics between individuals (e.g., Bozeman & Feeney, 2007). Therefore, conceptual models, particularly in child welfare, can be helpful in developing theories that shed light on understanding mentorship among foster parents.

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Lastly, research implications associated with the current study abound. For instance, future studies should examine gender differences in the way that mentors/mentees perceive/experience mentorship relationships. This may include examining cross-gender relationships, and/or mentorship among same-sex couples. Additionally, research related to mentorship among foster parents should examine the impact that program participation has on permanency outcomes for youth and retention of foster parents, among others. All of these studies should take into account limitations in the current work, including the fact low racial/cultural variability, the fact that most participants were new foster parents, etc. Being mindful of incorporating different foster parent groups into future research may shed additional light on these findings. Conclusion While mentoring is an effective way to support new members and promote skill development and retention, little is known in the literature about the role of mentoring with foster parents. This research study sought to explore how foster parents conceptualized mentorship as well as if there were differences in perceptions by gender. Foster parents of both identified genders were fairly consistent in prioritizing areas of conceptualization and feasibility which deviates somewhat from literature in other disciplines that found gender differences. However, comparing mentoring in foster parenting to mentoring in fields like business, which can be largely patriarchal, may account for these differences. Overall, foster parents validated the need for mentoring programs as a means of support and development for their role in providing a stable home for foster youth. References Anderson, L., Day, K., & Vandenburg, A. (2011). Using a concept map as a tool for strategic planning: The Healthy Brain Initiative. Preventing Chronic Disease, 8(5), 1–7. Avery, R. (2011). The potential contribution of mentor programs to relational permanency for

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REVISED Figr-1Figure 1. Point Cluster Map

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REVISED Figr-2Figure 2. Cluster Importance Ratings, by group.

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Figure 3. Cluster Feasibility Ratings, by group.

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Table 1. Clusters and Statement Examples Table 1. Clusters1 and Statement Examples2

1

Cluster Name: Ongoing Supports

Cluster Name: Matching Practices

Cluster Name: Program Structure

Cluster Name: Foster Relationships

38. provide a consistent contact person that the mentors can reach out to should they need support

29. match mentors and mentees based on geographic proximity

50. require all new foster parents to have a mentor for a minimum of 12 months

55. allow for the interaction of foster youth of mentors/mentees

43. offer an online resource library for mentors

59. match new foster parents with a mentor immediately after the completion of training

36. offer aspects of peermentoring so that new foster parents can mentor other new foster parents

26. provide a "track" for mentees to eventually become mentors Cluster Name: Program Evaluation

2. match mentors and mentees based on similar family composition.

63. assess new foster parents to ensure that they are ready to be mentored

46. keep the ration of mentors to mentees 2:1 (e.g., no more than two families for every one mentor) 20. facilitate the first meeting of the mentor/mentee

Cluster Name: Mentor/Mentee Recruitment

Cluster Name: Training

16. track mentor/mentee contacts (frequency, format, etc.)

61. -make sure that program participants have clear expectations of what is expected of them

47. adequately train all mentors

13. use a standardized process to evaluate the mentor program 7. have a designated person to evaluate the program

27. recruit mentors who are experienced foster parents 14. hire professional, full-time mentors

45. train mentees on the correct way to be mentored 22. train mentors on behavior management/modification for foster youth

Cluster names are based on participant labels ascribed to piles during structuring exercises. Statement numbers are for reference only and are not related to any statistical computation.

2

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Table 2. Mean Bridging Values, by Cluster Cluster Matching Practices Training Mentor/Mentee Recruitment Ongoing Supports Program Evaluation Foster Relationships Program Structure

Mean Bridging Value 0.11 0.24 0.25 0.29 0.32 0.54 0.62

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Table 3. T-test results for statement importance ratings by cluster. Cluster

Mean Foster Father Ratings (SD)

Mean Foster Mother Ratings (SD)

Fostering Relationships

3.48(0.21)

3.53 (0.22)

(t(16) = -0.21, p > 0.05)

Matching Practices

3.20(0.57)

3.25(0.85)

(t(12) = -0.10, p > 0.05)

Program Structure

3.55(0.21)

3.60(0.24)

(t(18) = -0.23, p > 0.05)

Program Evaluation

3.62(0.21)

3.45(0.36)

(t(18) = 0.69, p > 0.05)

Recruitment

4.10(0.62)

4.09(0.64)

(t(24) = -0.04, p > 0.05)

Training

3.85(0.17)

3.61(0.42)

(t(10) = 0.76, p > 0.05)

Ongoing Supports

3.88(0.22)

3.65(0.33)

(t(24) = 1.09, p > 0.05)

T-test Results

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Table 4. T-test results for statement feasibility ratings by cluster. Cluster Fostering Relationships Matching Practices Program Structure Program Evaluation Recruitment Training Ongoing Supports

Mean Foster Father Ratings (SD) 3.49(0.16) 3.46(0.20) 3.57(0.11) 3.24(0.34) 3.83(0.41) 3.72(0.10) 3.81(0.08)

Mean Foster Mother Ratings (SD) 3.31 (0.22) 3.22(0.43) 3.26(0.15) 3.22(0.35) 3.73(0.55) 3.35(0.16) 3.55(0.17)

T-test Results (t(16) = 0.84, p > 0.05) (t(12) = 0.79, p > 0.05) (t(18) = 1.87, p > 0.05) (t(18) = 0.07, p > 0.05) (t(24) = 0.39, p > 0.05) (t(10) = 1.76, p > 0.05) (t(24) = 1.87, p > 0.05)