Volume XIII Article 4
October 2015
IJMC International Journal of Mentoring and Coaching
The International Journal of Mentoring and Coaching Volume XIII Article 4 October 2015
The Influence of Protégé Input to the Match on Mentoring Processes: An Experimental Investigation
Dana L. Kendall, Seattle Pacific University, Kimberly A. Smith-Jentsch, University of Central Florida
Abstract We employed a longitudinal, experimental approach to examine the effects of allowing protégés to choose their own mentor on the effectiveness of an online peer mentoring program at a four-year university in the United States. First-year students were randomly assigned to either select a mentor from a pool of volunteers or to be paired with a mentor by a program administrator. There were 65 dyads who met online for four chat sessions, and transcripts of their interactions were saved for analysis by independent coders. Protégés in the choice group reported greater feelings of similarity to their mentors than protégés who were assigned a mentor. Ordinary least-squares regression analysis showed that protégés who selected their mentors received greater mentor support. This effect was mediated by the extent to which protégés displayed proactive behaviors during the sessions. These findings suggest implications for designing and managing mentoring programs. Keywords:
Formal mentoring, input to match, e-mentoring, undergraduate peer mentoring
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Introduction Researchers and practitioners are working to understand how to structure mentoring programs for success, and one important element is how mentors and protégés are paired with one another. In this study, we add to the literature by addressing the efficacy of administrator-facilitated matching versus protégés selecting their own mentors in a college peer e-mentoring program. We believe this investigation contributes to the extant literature by highlighting the benefits of implementing protégé choice when designing peer mentoring programs.
Participant input to the match has been shown to facilitate successful mentoring relationships (e.g., Allen, Eby, O’Brien, & Lentz; 2008; Viator, 1999); however, the empirical evidence to date has been derived almost exclusively from cross-sectional, field studies. In this investigation, we explored the influence of protégé choice by taking a controlled, experimental approach in the context of a four-week-long undergraduate peer mentoring program.
Furthermore, in much of the existing mentoring research, researchers have relied solely upon dyad members’ personal assessments of the quality of the mentoring that was given/received over the course of their interactions. Allen et al. (2008) noted that this overreliance on self-report limits our understanding of the inner-workings of mentorships because dyad members are likely to view their interactions through their unique lenses. To address this gap, we assessed the mentoring processes from the perspectives of both protégés and neutral third-party observers who evaluated transcripts of e-mentoring sessions.
Literature and Theory In this section, we make the case that protégés’ comfort level with the match is critical for realizing desired outcomes in the mentorship. We first review the literature to present empirical evidence of links between protégés’ perceived similarity to their mentors and indicators of desired outcomes. We gleaned this information from both qualitative and quantitative investigations conducted across business, medical, and education contexts. Then, we describe two theories: (a) similarity attraction paradigm (Byrne, 1971) and (b) self-determination theory (Deci & Ryan, 2000) as justification for the research questions and study design.
Mentoring Programs and the Risk of Mismatch Formal mentoring occurs when an organization officially sponsors and facilitates mentoring relationships designed for the benefit of both participants and the organization as a whole (Laiho & Brandt, 2012; Thurston, D'Abate, & Eddy, 2012).
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These objectives may include socializing newcomers, increasing individuals’ efficacy and learning, and advancing women and minorities. In practice, programs can vary substantially in their structure and implementation features including: (a) mentor selection and vetting, (b) matching, (c) participant training, and (d) monitoring and assessment (Finkelstein & Poteet, 2010). Although each of these aspects warrant attention; in this investigation, we focus on the matching method because of its tremendous potential to impact the mentorship.
Across the literature, concerns expressed by program participants regarding the undesirable effects of mismatched dyads arose as a common theme. In organically- formed mentorships, mentors and protégés choose one another based on mutual chemistry and identification with one another. The mentor may choose to invest in someone who reminds them of their previous self; and likewise, a protégé chooses to pursue a mentor who exemplifies the qualities they wish to acquire (Ragins & Cotton, 1999). Conversely, in a situation in which the mentorships are initiated either partially or fully by an administrator, the results are often feelings of awkwardness and dissatisfaction among participants (Blake-Beard, O’Neill, & McGowen, 2007). Eby and Lockwood (2005) reported mismatch as one of the most frequently-cited issues by protégés in formal programs. In their extensive review of studies of formal programs in the education context, Ehrich, Hansford, and Tennett (2004) reported a similar result; and in a sample of junior physicians in the United Kingdom, Garr and Dewe (2013) found that some protégés had difficulty relating to their mentors due to divergent personality styles.
In a peer mentoring program for engineering students, also in the U.K. (Clark & Andrews, 2014), program administrators made a decision to shift the structure from one-on-one mentoring to group mentoring. With this change, they matched participants by academic discipline, rather than the prior method of allowing protégés to have input regarding their mentor’s demographic characteristics (e.g., gender, ethnicity). At the close of the program, only a little over half of the chemical engineering protégés indicated that they were satisfied with their match, causing program administrators to rethink their match strategy (Clark & Andrews).
Taken together, these findings suggest that a challenge in implementing formal mentoring programs is dealing with dyad mismatches. Moreover, mismatches may be more than simply a mild inconvenience for participants. Eby and Allen (2002) found that protégés who reported an incompatibility with their mentors’ values and personality were likely to experience high job stress, low job satisfaction, and desire to leave the
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organization. In summary, there is adequate reason to suspect that mismatched dyads are likely detrimental to program effectiveness.
Blake-Beard and colleagues (2007) provide a useful framework for understanding the various types of matching methods employed in formal programs. First, administrators may pair participants either by convenience criteria (e.g., physical co-location) or by a more rigorous method (e.g., similarity of personality types). Two other options include: (a) facilitating a mixer event in which participants may mingle and pair up on their own, or (b) utilize software algorithms that can match dyad members by any number of criteria. Currently, there is a dearth of empirical guidance available as to which of these matching methods (or combination thereof) produce the best outcomes.
Another layer of complexity is that there are many ways in which two individuals may be compatible with one another. Harrison, Price, and Bell (1998) proffered a taxonomy for classifying dimensions of diversity that distinguishes between surface-level, easily- recognizable characteristics (e.g., race, gender) and deep-level (e.g., values, attitudes, personality). Eby, Allen, Hoffman, Baranik, Sauer, Baldwin, Morrison, Kinkade, Maher, Curtis, and Evans (2013) proposed a third dimension of diversity, which is experiential—the extent to which dyad members share common experiences and bases of knowledge (e.g., education, work experience, geographical location, skills). In their extensive, interdisciplinary meta-analysis that included over 1,000 primary studies, they reported that deep-level and experiential similarity were positively correlated with the protégés’ perceptions relationship quality, including the amount of support they received from their mentors. In summary, the factors that contribute to chemistry and compatibility are varied, complex, and subjective in the sense that they are best-known by the participants themselves. Thus, providing protégés a choice in selection of a mentor may both lighten the burden on program administrators and improve the effectiveness of mentorships. In the following sections, we present reasons for why we expect that protégés who choose their own mentors will feel more similar to them, demonstrate initiative in the ensuing relationship, and report greater mentor support than those who are matched by an administrator.
Who Does the Choosing? There are a couple of reasons for leaving the choice of a mentor to the protégé. First, protégés are the ones who should drive the mentorship in ways that meet their developmental objectives (Allen, Finkelstein, & Poteet, 2009). Offering them the choice may empower them to make the most of the opportunity to interact with a mentor and build their confidence for initiating mentoring relationships in the future. Second, when mentors are the choosers, they tend to select individuals who demonstrate high initial
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potential (Allen, 2004; Singh, Ragins, & Tharenou, 2009), not necessarily those who would benefit most from a mentor. Thus, in this study we focus on developing a better understanding of the role of protégé choice in predicting the success of the mentorship.
Similarity-attraction Paradigm and Choice The similarity-attraction paradigm predicts that individuals will be drawn to similar others (Byrne, 1971); and by extension, protégés will be attracted to potential mentors with whom they identify and sense some commonality. The method of matching is an important aspect to consider when designing a program because structured mentorships differ in many respects from those that evolve organically, without external interposition (Chao, 2009). One critical aspect is that formal programs typically are six months to a year in duration and have official start/end dates (Chao, 2009; Finkelstein & Poteet, 2010), whereas informal mentoring relationships have no such restrictions. Consequently, dyad members’ initial comfort levels with one another are more salient in mentoring programs than in informal mentorships because there may be a limited time for trust and rapport to be built. This notion is consistent with studies revealing a positive association between protégé-perceived similarity to the mentor and the extent to which protégés report that they received support from their mentors (de Janasz, Ensher, & Heun, 2008; Murphy, 2011). Moreover, Turban, Dougherty, and Lee (2002) found that graduate students’ feelings of similarity to their major professors were more highly predictive of the mentoring they received in the early stages of mentorship than at the later stages. Thus, for short-term, structured mentoring programs, participants’ initial feelings of similarity to their mentors may be a signal forecasting the success of the subsequent mentorship
In summary, we contend that when protégés choose their mentors, the experience from their vantage points essentially maps onto the beginning stages of an informally- initiated mentorship. A mentor may be selected on criteria that are known only to the protégé, resulting in enhanced perceptions of compatibility with the mentor and smoothing the characteristically awkward early stages of the relationship (Blake-Beard et al., 2007). This line of reasoning is corroborated by the findings revealing higher participant levels of satisfaction and relationship quality when they are allowed input into the choice of a partner (Allen, Eby, & Lentz, 2006a; Allen, Eby, & Lentz, 2006b; Parise & Forret, 2008; Viator, 1999). Thus, we expect that, when given the choice, protégés will select a mentor that they will perceive to be similar to themselves. Consequently, protégés given this choice will report significantly greater feelings of similarity to their mentors than protégés who are assigned a mentor.
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Self Determination Theory and Choice One characteristic of successful protégés is that they proactively take ownership the mentoring process and assume responsibility for meeting their growth goals (Allen et al., 2009; Artis, 2013). Proactive behavior is conceptualized as an individual’s propensity to purposefully alter their circumstances in some manner (Bateman & Crant, 1993), and it is positively associated with various indicators of career success (see Fuller & Marler, 2009 for a comprehensive review).
According to self-determination theory (SDT), the opportunity for individuals to engage in goal-oriented, self-directed behavior results in increased motivation, satisfaction, and adaptive psychological functioning (see Deci & Ryan, 2000 for a full review of the supporting empirical evidence). Specifically, SDT recognizes autonomy as one of the primary antecedents for motivation and personal initiative, and this has been supported by empirical work (e.g., Parker, Williams, & Turner, 2006; Frese, Kring, Soose, & Zempel, 1996). Providing individuals the freedom to choose among various alternatives sends a signal that they are competent (Axtell & Parker, 2003). In turn, autonomy has been shown to boost efficacy beliefs, which drive the orchestration of desired outcomes (Grant & Ashford, 2008; Parker et al.; Speier & Frese, 1997).
Giving protégés the option to select a mentor may send a message that they are capable of taking control of their professional/personal development; which in turn, may lead to proactive behaviors in the mentorship. Furthermore, the process of selection necessarily involves careful thinking about the qualities they would value in a potential mentor and how that person could guide them in achieving developmental objectives. This intentionality can set the trajectory for enhanced personal investment in the relationship that is reflected in behaviors such as soliciting from their mentors the specific type of support they need (Wanberg, Kammeyer-Mueller, & Marchese, 2006). As the relationship unfolds; protégés may be rewarded for this level of proactivity, resulting in upward spirals of reinforcement. Thus, they receive information that is personally meaningful and relevant for their unique needs, as compared to protégés who assume a more passive role.
Based on this evidence, we posit that protégés who choose their own mentors will receive more relevant guidance from their mentors in the ensuing relationship because they will behave in ways that will elicit that support. They will ask more questions and dynamically direct the interactions with their mentors in ways that will meet their needs. Moreover, mentors are attracted to protégés who demonstrate proactivity (Hu, Thomas, & Lance, 2008) and may be more motivated to invest in them. Therefore, we propose that choosing a mentor will positively impact mentor support through the mediating
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mechanism of increased protégé proactivity. That is, the positive influence of protégé choice on mentor support will be at least partially explained by increased protégé initiative in the mentorship.
Rationale for a Mixed-Methods Approach In the majority of mentoring studies reviewed by Allen et al. (2008), protégés were the sole source of data on the quality of guidance provided by their mentors. This approach is potentially problematic because method (in this case the source of the reporting) is completely entangled with the essence of the construct itself. In contrast, measuring a phenomenon from two or more sources can provide evidence verifying its existence and nature. This mixed-method approach, known as “triangulation”, recognizes that the ubiquitous error inherent in any given measure cannot be estimated or parsed out in the absence of multiple operations for the same construct (Campbell & Fiske, 1959; Jick, 1979; Smith, 1975). For example, if protégés are the sole assessors of mentor support, their ratings will contain a combination of real, factual characteristics of dyad interactions and the protégés’ personalized, subjective construal of those exchanges. Following Campbell and Fiske’s reasoning, if a second, independent source is added (e.g., mentor, neutral third-party individual), then inaccuracies or biases that are intrinsic to any one source can be theoretically distinguished from the true extent of mentor support. The philosophy underlying this approach is a critical realism that recognizes the objective existence of a phenomenon without denying that constructivism plays an inevitable role in any attempt to capture its essence—even in part. Consequently, in this investigation, we employed a mixed-method strategy that included both protégé reports of the mentoring they received and an assessment made by trained, independent coders who reviewed transcripts of mentoring sessions. In this way, we used triangulation in an effort to piece together a more complete picture of the mentoring provided during e-mentoring sessions.
Method Recruitment of Participants One hundred seventy-six students from a large university located in the southern United States were recruited for a formal, online peer mentoring program. This program was offered annually by the psychology department with the stated goal of facilitating first year students’ adjustment to college (Smith-Jentsch, Scielzo, Yarbrough, & Rosopa (2008). First-year students were recruited as protégés, and third and fourth year students in good academic standing at the university were recruited as mentors. Recruitment methods included flyers on campus, email invitations, and classroom visits.
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Experimental Conditions Of the 80 recruited protégés, approximately half were assigned by a random number generator to the choice condition (n = 38) and the remainder (n = 42) to the convenience match condition. To ensure that protégés in the choice condition had a sufficient number of options to make a true selection, many more mentors were recruited for the pool than were actually needed. It was critical that protégés in the choice group could obtain a mentor who was their first choice and not be constrained by a either (a) a dearth of personally desirable mentors or (b) an abundance of appropriate mentors who did not share the protégé’s time availability. For this reason, rather than randomly assigning mentors to conditions, we intentionally assigned mentors to conditions such that the pools contained individuals with a variety of majors and a variety of days and times available to participate in mentoring sessions. A greater number of mentors (56) were assigned to the choice condition so that protégés who were among the last to choose had multiple mentors as options. The remaining 40 mentors were assigned to the administrator match group.
Eighty-eight percent of protégés in the choice condition indicated they were sufficiently satisfied with their choice and 82% indicated that the lack of coinciding availability times did not preclude them from obtaining their top-choice. Protégés in the administrator-match group were paired with mentors whose availability times to meet online coincided.
Procedure Protégés in the choice condition viewed online profiles of the volunteer mentors and made their selections. Profiles contained information collected from the mentors such as their sex, ethnicity, college major, career goals, and hobbies. Protégés in the administrator-match condition were presented with the profile of their administratively- assigned mentor prior to their first mentoring session. After the matching process, all protégés rated (a) their perceived similarity to their mentor, and (b) their expectations to receive support from him/her purely on the basis of that mentor’s profile. Before dyad members met for the first time, mentors were presented with a short profile of their protégé and asked to rate their intentions to provide support to him/her. Subsequently, participants met privately with their partners via an online chat site for a half-hour session, once per week, for four weeks. To ensure that frequency and duration of interactions were uniform across all dyads, participants were advised not to meet outside of their scheduled sessions or exchange contact information until the completion of the program. With participant permission, all session transcripts were saved for later coding; and at the conclusion of the program, protégés were asked to self-report the extent to which they received mentor support.
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Measures Pre-program similarity perceptions (protégé-reported). Before dyad members met, protégés were given their mentor’s profile and asked to rate on a Likert scale of (1 = strongly disagree) to (6 = strongly agree) the extent of perceived similarity. We used a modified, 3-item version of Ensher and Murphy’s (1997) similarity scale.1 An example item stated: “My mentor and I are alike in a number of areas.” We obtained an acceptable reliability estimate for the scale (α = .89).
Mentoring processes (rater-reported). To capture the inner workings of the mentoring interactions without relying solely on the protégés’ points of view, five senior psychology students were trained over three months to content-analyze the session transcripts for the frequency of instances in which (a) the mentor provided support and (b) the protégé engaged in proactive behavior in the sessions. The raters independently analyzed the session transcripts and they were blind to the experimental conditions to which the dyads belonged. Raters were trained using a schema that was fashioned from previous pilot testing in the same student population.
We operationalized support that protégé received as total number of mentor words across all sessions devoted to facilitating the protégé in his/her academic pursuit and adjustment to college life. For our measurement strategy, we borrowed from Kram’s (1998) framework of mentoring functions in developmental relationships. Kram posited that mentors provide protégés two primary types of support: instrumental and psychosocial.
Instrumental support was conceptualized as information provided by the mentor that pertained to the protégé’s academic progress and professional growth (e.g., guidance regarding school norms/policies, study skills, job-seeking tips).
Psychosocial support was conceptualized as the provision of personal, psychological support to protégés, which included statements of encouragement, inspiration or empathy as well as advice for interpersonal relationships.
For each dyad, raters analyzed the transcripts and counted all the mentor words— across the four sessions—that fell into psychosocial or instrumental support. Totals were computed for each dyad to represent the extent of support provided by the mentor.
Protégé proactivity was operationalized as the number of instances across all four sessions in which the protégé asked the mentor for informational or psychological
1 For full versions of the measures used in this study, please contact the first author.
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support related to the process of his/her adjustment to college. Examples of informational inquiries were questions such as: “Do you know if Professor Jones is any good?”, or “Do you know of any jobs near campus?” Examples of psychological support inquiries were: “My roommates are driving me crazy. Did you ever have roommate problems?” or “I broke up with my significant other, so it has been difficult for me to focus. Do you have any suggestions?” All session transcripts were carefully analyzed to identify and count all protégé elicitations of support. These were totalled across the four sessions to create proactivity indices for each protégé.
To assess inter-rater reliability, we took the generalizability theory approach (Cronbach, Gleser, Nanda, and Rajaratnam, 1972) in which estimates were derived from a previous sample (drawn from the same population) and applied to the current study’s sample. We used 30 transcripts, derived from the program implemented in the previous year at the same university, to train the five raters to share the same frame of reference when making assessments of interactions that constituted protégé proactivity and mentor support. Once the raters become competent and comfortable with this process, they coded 30 additional transcripts (also drawn from the previous year) independently. We computed two inter-rater reliability estimates on the same set of 30 transcripts. First, we calculated consistency estimates that treated the raters as items (analogous to Cronbach’s alpha)—one for mentor support (ICC[3] = .95), and the other for protégé proactivity (ICC[3] = .94). Second, because in the current study, each transcript was to be assessed by a single rater, rather than two; we calculated a second type of ICC that estimates the extent to which the raters were in absolute agreement with one another. This extra step allowed us to ascertain the extent to which the raters could be considered to be interchangeable, so their ratings could be generalized from the initial set of 30 independently-rated transcripts to the current study’s transcripts (Shrout & Fleiss, 1979). This type of inter-rater estimate is more stringent and therefore results in lower values than the consistency estimates above; however, they were still in the range of acceptability (ICC[2,1] = .80 for mentor support and ICC[2,1] = .86 for proactivity). Transcripts (i.e., 65 dyads, 4 sessions each) were randomly divided among the same five raters, such that one individual rated a given transcript for mentor support, and a second rater analyzed it for protégé proactivity.
Prior to collapsing mentoring support and protégé proactivity across the four sessions for each dyad, we examined the across-session consistency of these variables. For instance, we wanted to assess whether, on average, protégés who asked many questions in session one would be more likely to also ask several questions in subsequent sessions compared to protégés who asked relatively few questions in
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session one. Treating the four sessions as items, we obtained moderate estimates for proactivity (ICC[3] = .52) and mentor support (ICC[3] = .64); consequently, we felt justified in summing these variables across the sessions to create one composite score for proactivity and an accompanying composite score for mentor support for each dyad. These numerical values were used in all the subsequent statistical analyses.
Mentoring processes (protégé-reported). Based on content analyses of transcripts from prior pilot studies and feedback from program participants; we developed a 10- item protégé-reported assessment of mentor support adapted from the measure used in Allen, McManus, and Russell (1999). At the conclusion of the program, protégés rated the extent to which their mentor facilitated their adjustment to college and academic progress. Care was taken to ensure that the content of the measure closely mapped onto the same conceptual categories that the raters employed in their analyses of the transcripts (see above section). Some example items stated: (a) “My mentor taught me about school policies”, (b) “My mentor provided information regarding which courses to take”, and (c) “My mentor discussed my questions and concerns regarding relationships with peers.” Protégés responded to each question on a 6-point Likert scale of (1 = strongly disagree) to (6 = strongly agree), and the internal consistency index revealed adequate reliability (α = .92).
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Analyses We used several statistical techniques for analyzing the data, including calculating descriptives, bivariate correlations (Table 1) and an independent t-test was used to test the first hypothesis. To test the hypothesis that protégé choice would increase the support they received through and increase in protégé proactivity, we conducted a mediation analysis.
Table 1. Descriptives and Inter-Correlations among Study Variables
Note. N = 65 dyads. Coefficients ≥ |.21| are statistically significant at p < .05, 1-tailed. Coefficients ≥ |.26| are statistically significant at p < .05, 2-tailed. Reliabilities are on the diagonal. Protégé choice coded 0 = administrator-match; 1 = protégés chose their mentors. Rated protégé proactivity = total number of protégé-initiated, developmental-related inquiries across sessions. Rated mentor support = total number of support-related words communicated by the mentor across sessions.
For a graphical depiction of this hypothesis, see Figure 1 below). To test a mediation is to examine whether an independent variable (IV) influences a dependent variable (DV) through the operation of a variable in between them (i.e., mediator). Conceptually, a mediation analysis answers the question: Why does the independent variable affect the dependent variable?
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Indirect Effect: A path coefficient multiplied by the B path coefficient. Protégé Proactivity The indirect A path (mediator) B path effect represents the degree to which the influence of the IV on the DV is due to the mediator.
Select mentor versus matched Mentor support by administrator received (IV) (DV)
Direct Effect: Influence of the IV on the DV, controlling for the mediator.
Figure 1. Illustration of mediation hypothesis.
The “A” path depicted in Figure 1 above represents the relationship between the IV and the mediator. The “B” path represents the impact of the mediator on the DV controlling for the effects of the IV. The direct effect is the impact of the IV on the DV, controlling for the mediator’s influence. Finally, the indirect effect represents the effect of the IV on the DV that operates through the mediator. To calculate the indirect effect, the A and the B path coefficients are multiplied together; and to test its statistical significance, we used ordinary least-squares regression and the bootstrapping method available in the PROCESS Macro—an SPSS add-on (Hayes, 2013).
Data Preparation Before analyzing the data, we conducted a missing value analysis at the item level and discovered that 4 dyads had more than 15% of values missing. Three were originally assigned to the choice condition and the other to the convenience group. According to recommendations in Olinsky, Chen, and Harlow (2003), we eliminated those cases. Finally, the protégé proactivity variable appeared to have an obvious outlier that occurred in the choice group. For this dyad, the protégé asked a total of 36 questions
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across the mentoring sessions when the mean was 4.7 for the entire sample; therefore we decided to eliminate this case. This brought the final dyad count to 65 (33 choice and 32 convenience), and all cases had complete data.
Results Attrition Seventy mentor/protégé dyads completed the program. Three mentors and 8 protégés left the program early, reducing the dyad count to 37 in the choice condition and 33 in the administrator-match condition. All the mentors who left the program were originally assigned to the administrator-matched condition. Seven of the protégés who dropped out were originally from the administrator-match condition and one was from the choice condition, and we could not obtain data regarding their reasons for leaving. Seventy- four percent of the mentors who completed the program were female, and their ages ranged from 19-45 years old (M = 22 years). Seventy-six percent of the protégés who completed the program were female, and all were between the ages of 17-19 years (M = 18 years).
Pre-Program Comparison of Conditions Post-assignment analyses revealed that mentors in the two conditions were not significantly different in terms of gender (χ2 [1] = .13; p = .73) or class standing (χ2 [1] = .74; p = .39) or intentions to provide support (t = -1.21; p = .23). Moreover, protégés did not differ in their expectations to receive mentor support (t = -1.06; p = .29). Finally, groups were equivalent with respect to proportion of dyads’ gender compositions (i.e., MM, FF, FM, MF; χ2 [3] = 7.16; p = .13).
Descriptives and Bivariate Correlations Descriptives and bivariate correlations among the primary study variables are displayed in Table 1. The mean for protégé proactivity (indexed as the average number of protégé solicitations for support across the four sessions) was 4.22, with a standard deviation of 4.55, and a range of 0 –19.
For mentor support (indexed as the average number of mentor words devoted to protégé development across the four sessions), the mean was 446.46, standard deviation was 333.27, and the range was: 0 – 1379. For protégé-rated similarity to the mentor, the mean was 4.01, the standard deviation was .97, and the range was 1 – 5.67. The mean for protégé-rated mentor support was 3.64, the standard deviation was .90, and the range was 1.58 – 5.29. The association between raters’ and protégés’ assessment of mentor support was small but statistically significant (r = .23; p = .03, 1- tailed). Protégé-perceived similarity was significantly, positively associated with their reports of the extent of mentor support they received (r = .26; p = .02, 1-tailed).
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Testing the Hypotheses In the first hypothesis, we proposed that protégé choice would have a positive impact on the extent to which the protégés felt similar to their mentors. The results of an independent t-test supported this hypothesis (t = -3.76; p < 001). In fact, 18% of the variability in similarity was explained by choice.
For the second hypothesis, we predicted that choice would influence mentor support because protégés who chose their own mentors would be more proactive with their mentors than protégés who were assigned a mentor. To test this hypothesis, we ran two separate mediation analyses. The first analysis treated third-party-rated mentor support as the dependent variable, and second analysis treated protégé-reported mentor support as the dependent variable. We employed Hayes’ (2013) method which provides bootstrapped estimates of the indirect effect based on 1,000 resamples. This yields a test of significance for the indirect effect that is more reliable than the traditional Sobel Test method (Preacher, Rucker, & Hayes, 2007).
The results of the first mediation analysis revealed that the indirect effect was significant because the bootstrapped confidence interval did not contain zero (Bindirect = 80.73; bias-corrected 95% confidence interval = 19.62 to 202.99; see Table 2 for full results). Specifically, protégés in the choice condition made significantly more inquiries during the sessions, and the mentors responded with greater support. For the second analysis, we tested our hypothesis using protégé-reported mentor support as the dependent variable. Results did not indicate support for the hypothesis when this indicator of mentoring support was used because the confidence interval for the indirect effect contained zero (Bindirect = .02; bias-corrected 95% confidence interval = - .149 to .169). Thus, the second hypothesis was supported when third-party ratings of mentoring support served as the dependent measure, but not when protégé self- reported support was treated as the dependent variable.
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Table 2. Results for Mediation: Protégé ChoiceProtégé Proactivity Mentor Support
(rated) Note. N = 65. Choice coded 0 = match by program administrator; 1 = protégé chose mentor. All p values indicate non-directional tests. CI = confidence interval.
Discussion Summary and Contributions In the current investigation we have demonstrated that allowing protégés to choose their mentor can potentially influence the following outcomes: (a) the protégé’s feelings of similarity to his/her mentor, (b) mentor support provided, and (c) protégé proactivity in the mentoring sessions. Answering the call by Allen et al. (2008) to avoid relying solely on cross-sectional, self-report designs; we implemented a longitudinal design in a controlled setting while assessing mentor support from multiple sources. This research design enabled us to capture the exchanges that took place within the
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sessions and to draw causal inferences than would have been possible with a cross- sectional, observational study.
Implications In this section, we will discuss two recommendations for practitioners that stem from our findings: (a) provide protégés as much input as is feasible into the choice of their mentors, and (b) encourage protégés to take initiative in the mentorship. First, we highlight a novel finding that has not been previously reported in the literature. When given a choice, protégés are more likely to select mentors who they believe to be similar to themselves. This comports with the similarity-attraction theory (Byrne, 1971), and it is consistent with the available evidence that protégés in informal relationships tend to report their mentorships as having slightly higher quality than protégés in formal mentorships (Eby et al., 2013). Specifically, these results suggest the importance of making formal programs mirror informal relationships as much as possible to participants. Hegstad and Wentling (2004) and Blake-Beard et al. (2007) emphasize the criticality of the match in programs of relatively short duration. Given that procuring productive matches can be a time consuming, pressure-inducing endeavor for administrators; choice can alleviate some of those burdens and render the search for the “right” matching criteria irrelevant. Moreover, our results demonstrate that protégé choice has the added benefit of increasing proactivity, which would not be expected theoretically if the mentors had done the choosing. More research is needed to explore the joint effects of protégé and mentor choice in matching. Practically speaking, allowing mentors and protégés a choice (or veto power) adds greater complexity to the process, requiring an even larger pool of mentors. We recognize that not all mentoring programs may logistically allow for participant choice of a partner (e.g., limited supply of qualified mentors, and the potential detriments associated with participants being paired with individuals who were not their first choices are still unclear. Chao (2009) argues that to capitalize on the benefits of choice, organizations must be dedicated to recruiting, training, and supporting a large, assorted pool of competent mentors.
Second, our results indicate that choice had a positive influence on mentor support as viewed by third-party raters (who reviewed transcripts of mentoring sessions) and as viewed by the protégés themselves. The raters provided a glimpse into the inner workings of a dyad to which we would not have been privy otherwise. Interestingly, coded mentor support was only weakly related to protégé perceptions of the support they received. Moreover, choice was predictive of support as measured by raters, but the correlation between choice and protégé-reported mentor support narrowly missed significance (r = .19; p = .07, 1-tailed). It could be that with 65 dyads, we did not have sufficient power to detect this association. Another possibility is that the third-party
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observers were capturing the quantity of mentoring provided whereas the self-report measures were picking up on a relatively subjective, quality component. Outside sources such as a mentor’s supervisors (e.g., Gentry & Sosik, 2010) or program administrators may similarly provide a better picture of the quantity than the quality of mentoring provided, whereas only the protégé truly knows the extent to which the mentor’s support met his/her needs. Also, prior research has shown that protégés’ expectations moderated the relationship between the quantity of support provided (as coded from transcripts) and protégé-reported quality of support received (Fullick, Smith-Jentsch, & Kendall, 2013). These findings underscore the importance of protégé initiative in guiding the mentor toward topics of personal value and providing feedback to him or her on a regular basis as to how their needs are being met. In sum, we need more research on the merging and diverging of perspectives of mentors, protégés, and outside individuals to provide guidance when evaluating program effectiveness.
Limitations In this section, we address limitations and boundary conditions to consider when applying our study’s findings in various settings. First, our sample of undergraduates potentially places limits on extending the results to mentorships in other contexts and populations. We employed a student sample for the purpose of experimental control and the capacity to capture mentoring processes inside the sessions. Socialization in the workplaces and in academic contexts share similar elements, such as learning new skills and navigating the expectations of others. However, there are obvious dissimilarities, such as the stages of life and maturity level of undergraduates.
Another boundary condition involves the fact that the study was conducted in the highly individualistic context of the United States. There is evidence that individuals in Western cultures greatly value personal autonomy; therefore, there is a tighter association between choice and intrinsic motivation than is observed in collectivistic cultures (Kitayama & Uskul, 2011). Because individuals in collectivist cultures construe their identities in relation to the group rather regarding themselves primarily as autonomous individuals, offering them the opportunity to choose a mentor may not elicit the same feelings of ownership and incentive. For example in a lab study, Iyengar and Lepper (1999) found that when parents chose an activity for their children, the American children were less motivated to engage in the task than if they chose the activity for themselves. This pattern was reversed for Asian children, suggesting that choice can be a more powerful motivator for those in individualistic cultures than for those in collectivist cultures. Thus, in cultures that place a high value on interdependence; protégés may prefer to be assigned a mentor by a trusted authority figure. Although additional work in this area is needed, the available data suggest that
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we should exercise caution in presuming that protégé choice will have uniform effects across various cultural contexts.
Second, dyads met online only, which may pose some generalizability concerns if the results are used for face-to-face mentorships where participants have access to non- verbal cues in their interactions. Regardless, e-mentoring is gaining popularity in both academic and work contexts (e.g., deJanasz et al., 2008; DiRenzo, Linnehan, Shao, & Rosenberg, 2010; Murphy, 2011); therefore, additional research in this realm would be useful for understanding how to foster the effectiveness of online mentorships. Another potential concern is that participant knowledge that transcripts were being reviewed may have served to curtail their levels of self-disclosure. If this were the case, it should have affected participants in both conditions to the same extent and thus would not be an alternative explanation for the group differences. Moreover, we observed that many of the dyad members appeared to feel quite free with one another, often discussing extremely personal topics. Perhaps the sense of anonymity online provided an avenue for relational authenticity (Joinson, 2001).
Finally, mentors who were selected for the pool could not be assigned by a random process for logistical, programmatic reasons. We intentionally ensured that mentors within conditions had a sufficiently wide availability in terms of time blocks to meet online. Thus, there is the possibility that mentors differed systematically between the two conditions (e.g., commitment to the program). Nonetheless, as stated above, we did not find any a priori differences between conditions in mentor demographics or motivation to provide support to their protégés.
Conclusion In summary, these results broadly suggest that protégés may benefit from being given a choice in selecting their mentor, which corroborates previous findings (e.g., Allen et al., 2006a; 2006b). It may be beneficial for program administrators to reallocate the time and expense that would normally be devoted to matching participants to (a) recruiting and developing qualified mentors and (b) training protégés to assume a proactive role in the mentorship. It was our objective to illuminate new avenues for research and practice in the domain of participant input to the matching process as well as underscore the value of evaluating the quality of mentoring interactions from multiple perspectives. Consequently, we hope that the results may extend and enrich our knowledge of elements that contribute to the effectiveness of structured mentoring.
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References Allen, T. D. (2004). Protégé selection by mentors: Contributing individual and organizational factors. Journal of Vocational Behavior, 65, 469-483.
Allen, T. D., Eby, L. T., & Lentz, E. (2006a). Mentorship behaviors and mentorship quality associated with formal mentoring programs: Closing the gap between research and practice. Journal of Applied Psychology, 91, 567-578.
Allen, T. D., Eby, L. T., & Lentz, E. (2006b). The relationship between formal mentoring program characteristics and perceived program effectiveness. Personnel Psychology, 59, 125-153.
Allen, T. D., Eby, L. T., O’Brien, K. E., & Lentz, E. (2008). The state of mentoring research: A qualitative review of current research methods and future research implications. Journal of Vocational Behavior, 73, 343-357.
Allen, T. D., Finkelstein, L. M, & Poteet, M. L. (2009). Designing workplace mentoring programs: An evidence-based approach. Oxford: Blackwell-Wiley Publishing.
Allen, T. D., McManus, S. E., & RussellL, J. E. (1999). Newcomer socialization and stress: Formal peer relationships as a source of support. Journal of Vocational Behavior, 54, 453-470.
Artis, A. B. (2013). An alternative approach for MBA mentor programs: Empower the protégé. Journal of Education for Business, 88, 361-365.
Bateman, T. S., & Crant, J. M. (1993). The proactive component of organizational behavior: A measure and correlates. Journal of Organizational Behavior, 14, 103-118.
Blake-Beard, S. D., O’Neill, R. M., & McGowen, E. (2007). Blind dates? The importance of matching in successful formal mentoring relationships. In B. R. Ragins & K. E. Kram (Eds.), The handbook of mentoring at work: Theory, research, and practice (pp. 617–632). Thousand Oaks, CA: Sage.
Byrne, D. (1971). The attraction paradigm. New York: Academic Press.
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81-105
Chao, G. T. (2009). Formal mentoring: Lessons learned from past practice. Professional Psychology: Research and Practice, 40, 314-320.
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Clark, R., & Andrews, J. (2014). Tackling transition! Peer mentoring in engineering education: A UK Perspective. In SEFI conference proceedings. [125] SEFI.
De Janasz, S. C., Ensher, E. A., & Heun, C. 2008. Virtual relationships and real benefits: Using e-mentoring to connect business students with practicing managers. Mentoring and Tutoring: Partnership in Learning, 16, 394–411
Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227–268.
Direnzo, M., Linnehan, F., Shao, P., & Rosenberg, W. L. (2010). A moderated mediation model of e-mentoring. Journal of Vocational Behavior, 76, 292−305.
Eby, L. T., & Allen, T. D. (2002). Further investigation of protégés' negative mentoring experiences. Group & Organization Management, 27, 456-479.
Eby, L., Allen, T. D., Hoffman, B. J., Baranik, L. E., Sauer, J. B., Baldwin, S., Morrison, M.A., Kinkade, K. M., Maher, C. P., Curtis, S., and Evans, S.C. (2013). An interdisciplinary meta-analysis of the potential antecedents, correlates, and consequences of protégé perceptions of mentoring. Psychological Bulletin, 139, 441- 476.
Eby, L. T., & Lockwood, A. (2005). Protégé’s and mentors reactions to participating in formal mentoring programs: A qualitative investigation. Journal of Vocational Behavior, 67, 441-458.
Ensher, E. A., & Murphy, S. E. (1997). Effects of race, gender, and perceived similarity and contact on mentor relationships. Journal of Vocational Behavior, 50, 460-481.
Ehrich, L. C., Hansford, B., & Tennent, L. (2004). Formal mentoring programs in education and other professions: A review of the literature. Educational Administration Quarterly, 40, 518-540.
Finkelstein, L. M., & Poteet, M. L. (2007). Best practices in workplace formal mentoring programs. In T. D. Allen & L. T. Eby (Eds.), The Blackwell handbook of mentoring: A multiple perspectives approach (pp. 345–367). Malden, MA: Blackwell.
Frese, M., Kring, W., Soose, A., & Zempel, J. (1996). Personal initiative at work: Differences between East and West Germany. Academy of Management Journal, 39, 37-63.
Fuller, B. R., & Marler, L. E. (2009). Change driven by nature: A meta-analytic review of the proactive personality literature. Journal of Vocational Behavior, 75, 329-345.
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Fullick, J. M., Smith-Jentsch, K. A., & Kendall, D. L. (2013). Advisees' expectations for support as moderator between advisor behavior and advisee perceptions of advisor behavior. National Academic Advising Association Journal, 33, 55-64.
Garr, R. O., & Dewe, P. (2013). A qualitative study of mentoring and career progression among junior medical doctors. International Journal of Medical Education, 4, 247-252.
Gentry, W. A., & Sosik, J. J. (2010). Developmental relationships and managerial promotability in organizations: A multisource study. Journal of Vocational Behavior, 77, 266-278.
Grant, A. M., & Ashford, S. J. (2008). The dynamics of proactivity at work. Research in Organizational Behavior, 28, 3-34.
Harrison, D. A., Price, K. H., & Bell, M. P. (1998). Beyond relational demography: Time and the effects of surface-and deep-level diversity on work group cohesion. Academy of Management Journal, 41, 96-107.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis. New York: The Guilford Press.
Hegstad, C. D., & Wentling, R. M. (2004). The development and maintenance of exemplary formal mentoring programs in Fortune 500 companies. Human Resource Development Quarterly, 15, 421-448.
Hu, C., Thomas, K. M., & Lance, C. E. (2008). Intentions to initiate mentoring relationships: Understanding the impact of race, proactivity, feelings of deprivation, and relationship roles. The Journal of Social Psychology, 148, 727-744.
Iyengar, S. S., & Lepper, M. R. (1999). Rethinking the value of choice: a cultural perspective on intrinsic motivation. Journal of Personality and Social Psychology, 76, 349-366.
Jick, T. D. (1979). Mixing qualitative and quantitative methods: Triangulation in action. Administrative Science Quarterly, 24, 602–611.
Joinson, A. N. (2001). Self-disclosure in computer-mediated communication: The role of self-awareness and visual anonymity. European Journal of Social Psychology, 31, 177-192.
Kitayama, S., & Uskul, A. K. (2011). Culture, mind, and the brain: Current evidence and future directions. Annual Review of Psychology, 62, 419-449.
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Kram, K. E. (1988). Mentoring at work: Developmental relationships in organizational life. Lanham, MD: University Press of America.
Laiho, M., & Brandt, T. (2012). Views of HR specialists on formal mentoring: current situation and prospects for the future. Career Development International, 17, 435-457.
Murphy, W. (2011). From e-mentoring to blended mentoring: Increasing students' developmental initiation and mentors' satisfaction. Academy of Management Learning & Education, 10, 606-622.
Olinsky, A., Chen, S., & Harlow, L. (2003). The comparative efficacy of imputation methods for missing data in structural equation modeling. European Journal of Operational Research, 151, 53-79.
Parker, S. K., Williams, H. M., & Turner, N. (2006). Modeling the antecedents of proactive behavior at work. Journal of Applied Psychology, 91, 636-652.
Parise, M. R., & Forret, M. L. (2008). Formal mentoring programs: The relationship of program design and support to mentors' perceptions of benefits and costs. Journal of Vocational Behavior, 72, 225-240.
Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioural Research, 42, 185-227.
Ragins, B. R., & Cotton, J. L. (1999). Mentor functions and outcomes: a comparison of men and women in formal and informal mentoring relationships. Journal of Applied Psychology, 84, 529-550
Shrout, P. E. & Fleiss, J. L. (1979) Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 2, 420-428.
Singh, R., Ragins, B. R., & Tharenou, P. (2009). Who gets a mentor? A longitudinal assessment of the rising star hypothesis. Journal of Vocational Behavior, 74, 11-17.
Smith-Jentsch, K. A., Scielzo, S. A., Yarbrough, C. S., & Rosopa, P. J. (2008). A comparison of face-to-face and electronic peer-mentoring: Interactions with mentor gender. Journal of Vocational Behavior, 72, 193-206.
Smith, H. W. (1975). Strategies of Social Research: The Methodological Imagination. Englewood Cliffs, NJ: Prentice Hall.
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Speier, C., & Frese, M. (1997). Generalized self-efficacy as a mediator and moderator between control and complexity at work and personal initiative: A longitudinal field study in East Germany. Human Performance, 10, 171-192.
Thurston, P. W. Jr., D'Abate, C. P., & Eddy, E. R. (2012). Mentoring as an HRD Approach: Effects on employee attitudes and contributions independent of core self‐ evaluation. Human Resource Development Quarterly, 23, 139-165.
Turban, D. B., Dougherty, T. W., & Lee, F. K. 2002. Gender, race, and perceived similarity effects in developmental relationships: The moderating role of relationship duration. Journal of Vocational Behavior, 61, 240–262.
Viator, R. E. (1999). An analysis of formal mentoring programs and perceived barriers to obtaining a mentor at large accounting firms. Accounting Horizons, 13, 37-53.
Wanberg, C. R., Kammeyer-Mueller, J., & Marchese, M. (2006). Mentor and protégé predictors and outcomes of mentoring in a formal mentoring program. Journal of Vocational Behavior, 69, 410-423.