Untangling Protégé Self-Reports of Mentoring Functions

Abstract

In the current study, we sought to further our understanding of the relations between various types of protégé-reported mentoring functions (psychosocial and career support and role modeling [RM]) by conducting a meta-analysis. We examined the relationships among these functions and investigated their relationships with expected mentorship outcomes. There is still a great deal left for us to understand regarding how these functions relate to outcomes and what these relationships mean. We expanded upon previous meta-analyses in the following ways: We included RM functions in addition to psychosocial and career support functions, corrected for unreliability of the function scales in addition to sampling error, and examined the relations of these functions with one another. Results show that all the mentoring functions were related to outcomes, with RM being the strongest predictor. Finally, we identified and conceptually analyzed numerous moderators of these relations.

Keywords

mentor protégé psychosocial support career development role modeling

Mentoring has rapidly developed over the past few decades as a means of training and developing individuals within organizations as well as youth educational programs. Although the term mentor is an ancient word derived from Greek mythology, the concept of a mentor has expanded over time to include a variety of relationships and encompass an array of occupations. The dynamic role that mentors play in the lives of their protégés is important and has been shown to have a number of positive effects (see Allen, Eby, Poteet, Lentz, & Lima, 2004, for a review). Some aspects of mentoring, including sponsorship, coaching, role modeling (RM), counseling, and friendship, have been found to be directly associated with enhanced work performance and job satisfaction (Allen et al., 2004).

The primary goal of this meta-analysis is to uncover the relationships between the type of mentoring provided, specifically looking at different mentoring functions, and various protégé outcomes, including promotions, turnover, salary, job and mentorship satisfaction, and others. Further, we wanted to check for potential moderators of these relationships to determine the factors that strengthen or weaken the relationship between mentoring provided and outcomes.

What is Mentoring?

One of the first comprehensive classifications of the mentoring and protégé relationship defined it as an interpersonal relationship between an older individual and a younger individual with the goal of guiding, supporting, and counseling the younger person (Kram, 1985). Although the early definitions of the mentor–protégé relationship used the words “older” and “younger” to designate the mentor and the protégé, newer conceptualizations depict an interpersonal relationship in which a relatively experienced/skilled individual (mentor) puts forth intentional effort to guide, support, and counsel a less experienced/skilled individual (protégé; Eby, Rhodes, & Allen, 2007; Haggard, Dougherty, Turban, & Wilbanks, 2011). For the current investigation, we used this broad conceptualization of mentoring and selected studies that assessed both informal and formal mentorships. Informal mentorships are those that emerge naturally between the mentor and protégé, while formal mentoring relationships are usually formed in the context of an organizationally sponsored mentoring program (Kram, 1985).

Assessing Mentoring Quality

Kram (1985) identified two key categories of mentor functions that are often seen in workplace mentoring relationships. These main mentoring functions included career development (CD) and psychosocial support (PS). Kram (1985) defined CD as the function of mentoring that can enhance a protégé’s advancement in the organization, including sponsorship, exposure and visibility, coaching, protection, and challenging assignments. Furthermore, she defined PS as the aspect of the relationship that can boost a sense of competency, identity, and effectiveness through RM, acceptance, confirmation, counseling, and friendship (Kram, 1985). Subsequent studies supported these functions and demonstrated that PS and CD are indeed distinct aspects of mentoring (e.g., Noe, 1988; Ragins & Cotton, 1999). Scandura (1992) later identified RM to be an additional facet of mentoring that is separate and distinct from the rest of the PS functions. RM was first defined by Kram (1985) as a younger person identifying with an older person who models a career that the younger person would like to follow, for example, when a person begins a new job they may seek out someone already working at that job for advice and help when needed. Not only has the definition of RM remained unchanged since that time, but recently, Haggard, Dougherty, Turban, and Wilbanks (2011) noted that overall, there is relatively little attention paid to the RM aspect of mentoring in the current literature when compared to the PS and CD dimensions. However, the authors contended that RM is a foundational element of mentoring and should not be omitted when conceptualizing the mentoring construct (Haggard et al., 2011). Thus, in the current endeavor, we will examine all three components separately, although we realize that some primary study authors have treated RM as a separate dimension from PS and others have collapsed them. In the latter case, we will only be able to examine the effect of PS, as there is no way to disentangle them.

Overview of the Benefits of Mentorships

Mentoring has the potential to increase benefits for protégés, mentors, and the organization. In their meta-analysis, Allen et al., (2004) reported that PS and CD were positively associated with important benefits for protégés, such as compensation, promotions, and career satisfaction; protégés tended to have higher salaries and receive more promotions than nonmentored individuals. Other researchers have found that mentoring is associated with increased protégé motivation and positive attitudes (Eby, Allen, Evans, Ng, & DuBois, 2008). Moreover, Kraimer, Seibert, Wayne, Liden, and Bravo (2011) argued that individuals might have higher job performance if they perceived that their organization supported their development and if they had the opportunity to advance in their organization. Fostering mentorships is one way for organizations to provide this type of support to employees. Career development mentoring functions have been found to be positively associated with increased protégé compensation and promotions (Allen et al., 2004). Career support may also aid the protégé in setting performance goals early on in the mentorship and is related to an increase in job performance ratings (Ragins & Cotton, 1999).

In addition to aiding protégés, mentoring relationships may also provide benefits to the mentor. For example, mentors who provided exposure (help the protégé meet others and be more visible) to their protégés tended to feel rejuvenated in their jobs and have higher job satisfaction (Pullins & Fine, 2002). Additionally, the amount of mentoring functions that the mentor provided to protégés was associated with more personal learning for the mentor, which in turn increased the mentor’s job performance (Liu, Liu, Kwan, & Mao, 2009). Furthermore, mentoring can also provide benefits at the organizational level. For example, engaging in mentorship (as either a mentor or a protégé) may decrease turnover rates by 38% (Payne & Huffman, 2005), which could save financial resources associated with hiring and training new employees.

Mentoring programs may also provide benefits specific to female protégés. Theoretically, organizationally sponsored formal mentoring programs have been shown to assist female protégés by expanding their professional networks, giving them advancement opportunities (O’Neil, Hopkins, & Bilimoria, 2008). Additionally, female leaders who had mentors reported higher career planning, increased job satisfaction, and they perceived themselves to be more effective in their leadership roles (Høigaard & Mathisen, 2009). Formal mentoring programs can be crucial in helping women find mentors because women have reported more barriers to forming informal mentorships than men (Ragins & Cotton, 1991). Additionally, even if women are in mentoring relationships, they may be less likely than men to receive mentorship benefits (i.e., sponsorship) that lead to promotions (Ibarra, Carter, & Silva, 2010). Therefore, it is important to examine the possibility that the gender of the protégé and/or mentor serves as a moderator of the relationship between mentoring functions received and outcomes.

The Current Investigation

Over the past decade, there have been a few other meta-analyses (e.g., Allen et al., 2004; Eby et al., 2008; Kammeyer-Mueller & Judge, 2008; O’Brien, Biga, Kessler, & Allen, 2010) that have assessed the effectiveness of mentoring relationships in the workplace. Each of these meta-analyses addressed very specific research questions around the effectiveness of mentoring. For example, Eby, Allen, Evans, Ng, and DuBois (2008) analyzed differences between mentored versus nonmentored individuals across the workplace, academic, and youth mentoring settings. O’Brien, Biga, Kessler, and Allen (2010) analyzed gender differences in mentoring given and received, whereas Allen et al. (2004) and Kammeyer-Mueller and Judge (2008) both assessed the relationships between mentoring functions and various protégé outcomes. Allen et al. (2004) compared mentored individuals to nonmentored individuals and assessed the relationships between mentoring functions (PS and CD) and outcomes like compensation and job satisfaction. They found overall support for mentoring functions, but these results had small effect sizes. Later, Kammeyer-Mueller and Judge (2008) tested a model of projected career outcomes based on mentoring and found that mentoring functions (PS and CD) were related to satisfaction with job or career.

Our current investigation builds and expands upon these past meta-analyses in the following ways. First, we seek to confirm the positive relationships they reported between mentoring functions and desired outcomes. Second, we include the often neglected mentoring function, RM, and analyze it separately rather than combining it with PS. We believe that it is essential to understand how this function relates both to protégé outcomes and to the other two functions, PS and CD. Finally, we explore the following possible moderators of the relationship between mentoring functions and outcomes: (a) mentor and protégé gender, (b) protégé race, and (c) aspects about the relationship, including formality (formal vs. informal), setting (workplace vs. academic), and duration of the relationship. The choice of these moderators was based partly on evidence from past research and partly on the fact that they were repeatedly reported across multiple primary studies in our sample. We know that the type of mentoring relationship, either formal or informal, makes a difference in the amount of mentoring received, and Sosik, Lee, and Bouquillon (2005) suggested that mentoring type can influence protégé perceptions of mentor functions. Because many primary studies evaluate either formal or informal relationships, the best way to compare the two is through a meta-analysis. Additionally, the duration of the relationship has been found to have moderating effects on the amount of mentoring received (Turban, Dougherty, & Lee, 2002). Finally, protégé race was included as a potential moderator based on previous research that suggests that race might influence mentoring relationships (Ensher & Murphy, 1997). Mentor race was not examined due to the lack of studies that reported it.

In summary, the primary goal of this meta-analysis is to further specify relationships between mentoring functions provided (i.e., PS, CD, and RM) and various protégé-related outcomes, including promotions, turnover, salary, job and mentorship satisfaction, and others. The second goal is to assess potential moderators of these relationships to determine the factors that may strengthen or weaken the relationship between mentoring provided and outcomes.

Method

Literature Search

We employed several search methods in order to identify relevant articles for the meta-analysis. First, we performed a computerized search of the PsycINFO, PsychARTICLES, and ABI/INFORM databases using the key words psychosocial support, career development, academic career support, protégé, mentor, social support, and career counseling. Our search intent was to encompass any article about mentoring that investigated the mentoring functions of CD and PS as well as other related antecedent and outcome variables. As our next method, we conducted a manual search for mentoring articles, using sources such as Google Scholar. For our last method of search, we reviewed the reference list of each article we had identified in order to discover additional articles not previously revealed in our other search methods. These articles were subsequently included in the meta-analysis.

Criteria for Inclusion

Studies had to meet established criteria in order to be included in the meta-analysis. First, the study’s authors had to employ a multi-item measure assessing perceived mentoring functions received. Thus, our aim was not to compare mentored versus nonmentored individuals, as this has already been reported in excellent depth elsewhere (see Eby et al., 2008). Second, the authors had to present data; either in the form of a correlation matrix or reported within the text of the document. Third, the data had to be reported in the form of effect sizes for the mentoring functions psychosocial support and career development. Finally, the study needed to yield a usable effect size (i.e., a correlation or other effect from which a correlation could be computed). From our thorough search, we initially identified 280 articles. Sixty-one articles met these criteria and were ultimately included in the meta-analysis.

Coding

After the list of useable articles was compiled, the following information was collected from each study: (1) correlations of mentoring functions with protégé-reported outcomes, (2) correlations between CD, PS, and RM (3) whether mentorships were formal versus informal, (4) whether the sample was from an academic or workplace context, (5) average duration of the mentorships, (6) mentoring scale reliabilities, (7) the race of the protégé, and (8) percentages of males and females. In order to ensure coding consistency, two authors independently coded each article. A third coder resolved the few discrepancies that arose during the process. Although there are studies that report on mentoring from a mentor’s point of view, all of the articles that met the criteria for inclusion were from the protégé’s perspective only.

Statistical Analyses

The current meta-analysis used the Hunter and Schmidt (1990) methodology. Specifically, we not only examined the uncorrected weighted mean effect sizes but also corrected partially for unreliability (based on the α coefficients of the reports of the mentoring functions, individually for each study when available). Thus, the relationship of three types of mentoring functions typically recognized in the literature (PS, CD, and RM functions) with various outcomes (e.g., mentorship and job satisfaction, promotions, job performance) was examined. Several steps were taken to prepare the data for analysis. First, undesirable outcomes (e.g., turnover, depression) were recoded to ensure that high values corresponded to less of those constructs. Second, if one study reported two or more outcomes, they were collapsed to provide one outcome indicator. We did this in order to simplify our analyses because of the relatively small number of primary studies in our sample. Finally, all the correlations culled from the articles were translated into effect sizes.

The first step of data analysis was to assign weights based on sample sizes, correcting for sampling error. Moreover, each correlation was corrected for attenuation, due to the unreliability in the mentoring functions’ scales. Hunter and Schmidt (1990) recommended this correction in order to obtain the best possible indicator of the strength of the relationship. For studies that did not report a reliability coefficient, taking a conservative approach, as suggested by Hunter and Schmidt, the reliability was assumed to be perfect and no correction applied. Furthermore, 95% confidence intervals (around the uncorrected values) and 80% credibility intervals (around the corrected values) were constructed. Confidence intervals provide an estimate of the variability around the mean corrected correlation, allowing for inferences regarding the likelihood that the true effect differs from zero. All of the average uncorrected correlations were deemed to be significant at α = .05. Examining variation across true effects in the studies, credibility intervals were also calculated to assess possible moderators. Although the credibility intervals did not include zero, the lower bounds were close to enough in all instances to warrant further investigation.

Moderator Analyses

One of the major contributions of a meta-analytic study is to examine the effects of possible moderator variables that were not necessarily examined at the level of the primary studies. Steel and Kammeyer-Mueller (2002) define a moderator in the meta-analysis context as “a systematic difference among studies under review that might explain differences in the strength or direction of observed relationships between the primary variables of interest” (p. 96). Many methods have been offered in the literature to determine the presence of moderators in a meta-analysis. For example, the span of a credibility interval is a useful indicator of the likelihood of the existence of moderators, with larger spans indicating a greater probability (Whitener, 1990). In the current study, several possible moderator variables were of interest, including (1) race (i.e., percentage of Caucasians), (2) gender (defined as the percentage of females in the sample), (3) relationship context (i.e., academic or workplace), (4) relationship formality (i.e., informal, formal), and (5) relationship duration (measured in years). These moderators were chosen based on variables that were codeable across multiple studies. Using the approach advocated by Steel and Kammeyer-Mueller (2002), weighted least squares (WLS) regression was used as the preferred method to determine the effect of each moderator. This method was chosen due to its robustness and superiority in accuracy over other methods (Steel & Kammeyer-Mueller, 2002). Finally, file drawer analyses were conducted to determine the number of studies with null results that would be required to overturn our findings.

Results

The results of the direct effects examined in this analysis are presented in Table 1. Specifically, the table shows the relationship of the three typically recognized types of mentoring functions with mentoring relationship outcomes (coded such that higher values represent more positive outcomes), and the relations of these functions with themselves. The weighted mean uncorrected (bare bones) r, SD, the 95% confidence interval, ρ, σ, and the credibility intervals are reported. Corrected values for functions predicting outcomes range from .26 to .33, and relations between functions range from .57 to .60. The credibility intervals however did not include zero, indicating that the presence of moderators was unlikely. However, given the small number of studies, coupled with the proximity of the lower bound of the credibility interval to including zero, further analyses were conducted.

Table 1.

Meta-Analytic Results for Relationships of Mentoring Functions With Outcomes.

Relationship	k	n	r	SD	95% CI	ρ	σ	CV	Fail-Safe n
PS to outcomes	39	7,500	.25	0.17	[.20, .30]	.26	0.17	.05−.47	265
CD to outcomes	42	8,968	.27	0.16	[.23, .32]	.29	0.15	.10−.49	266
RM to outcomes	11	2,899	.30	0.16	[.21, .40]	.33	0.15	.14−.52	82
PS to CD	42	7,892	.51	0.15	[.47, .56]	.60	0.17	.38−.82	360
PS to RM	13	3,012	.46	0.12	[.40, .53]	.57	0.14	.39−.75	80
CD to RM	13	3,012	.47	0.14	[.39, .55]	.59	0.14	.41−.77	83

Note. k = number of correlations; n = total sample size for studies combined; r = uncorrected correlations; SD = standard deviation for uncorrected correlations; CI = confidence interval; ρ = corrected correlations; σ = standard deviation for corrected correlations; CV = credibility value; fail-safe n = the number of participants averaging null results that would be needed to reduce the sample-weighted mean r to .01; CD = career development; RM = role modeling; PS = psychosocial support.

Moderator Analyses

Table 2 presents the results of the moderator analyses conducted. Specifically, we examined the effects of protégé race, protégé gender, mentor gender, setting, formality (formal or informal), and duration on the relationships for which we had a large enough number of studies. Based on the guideline of approximately 20 studies needed for these types of analyses inferred from Rhoades and Eisenberger (2002), the lowest number of studies utilized was 42, for the relationship between PS and CD. Furthermore, due to low sample sizes, no moderator analyses were conducted for RM. As previously discussed, WLS regression was used to examine interactions. In order to do this, the effects and inverse variance were corrected for unreliability. Then, each of the continuous moderator variables were entered into the regression model, thus predicting the corrected effect size, weighted with the corrected inverse variance. Due to incorrect weightings being utilized in SPSS, the correction suggested by Hedges and Olkin (1985) was applied.

Table 2.

Moderator Analyses and Intercorrelations.

Moderators	b value	SE	Mean Square Residual			SE Corrected		Z	p Value
PS to outcomes
Protégé race	−0.10	0.23	6.80			0.09		−1.63	.24
Protégé gender	−0.19	0.16	6.23			0.06		−3.01	<.00
Mentor gender	−0.62	0.29	3.56			0.15		−4.07	<.00
Setting	0.03	0.07	6.05			0.03		0.96	.34
Formality	0.06	0.11	5.59			0.05		1.27	.20
Duration	0.00	0.03	3.20			0.02		0.21	.83
CD to outcomes
Protégé race	−0.16	0.22	7.24			0.08		−1.96	.05
Protégé gender	0.01	0.13	5.64			0.06		0.23	.82
Mentor gender	−0.21	0.15	3.64			0.08		−2.63	<.00
Setting	0.00	0.06	5.52			0.03		0.22	.83
Formality	0.06	0.10	6.07			0.04		1.53	.13
Duration	0.02	0.06	4.55			0.03		1.85	.39
PS to CD
Protégé race	0.02	0.14	3.98			0.07		0.21	.84
Protégé gender	0.02	0.17	4.99			0.08		0.20	.84
Mentor gender	−0.23	0.34	5.11			0.15		−1.50	.13
Setting	−0.04	0.06	4.50			0.03		−1.28	.20
Formality	0.14	0.12	4.64			0.05		2.58	.01
Duration	−0.14	0.04	7.98			0.02		−0.90	.37
Intercorrelations between variables			1	2	3		4	5	6
1. Protégé race (percentage Caucasian)			1.00	−.05	.06		−.14	.32	.16
2. Protégé gender (percentage female)			−.09	1.00	.94		.08	.30	−.20
3. Mentor gender (percentage female)			.01	.89	1.00		.15	.33	−.62
4. Context (academic 1, workplace 0)			−.10	−.11	−.20		1.00	−.30	.31
5. Formality (formal 1, informal 0)			.42	.20	.31		−.33	1.00	.09
6. Duration (in years)			−.15	−.09	−.43		.28	−.12	1.00

Note. Moderator analyses: b value = beta value; SE = standard error; SE corrected = corrected standard error; Z = z-score critical value. PS = psychosocial and CD = career development mentoring functions. Role modeling mentoring functions were not included due to the low number of studies measuring this separately. Intercorrelations: Nonweighted correlations are presented in the bottom diagonal, and sample size weighted correlations are presented on the top. Ks range from 11 to 42, whereas ns range from 3,012 to 8,968.

As indicated in Table 2, both protégé and mentor genders were moderators of the PS to outcomes relationship. Specifically, the positive relationship between PS and outcomes was stronger when both the protégé and the mentor were male than when they were female. Mentor gender was also found to be a moderator of the career development to outcomes relationship, and protégé race was approaching significance at p = .05. Specifically, the positive relationship between CD and outcomes was stronger when the mentor was male and when the protégé was an ethnic minority, or non-Caucasian. Only formality of the mentoring relationship was found to be a moderator of the relationship between self-reported PS and CD. More specifically, the positive relationship between PS and CD was stronger when the relationship was formal versus informal. The setting of the mentoring relationship and the duration of the relationship did not emerge as significant moderators in any of the analyses.

Supplementary Analyses

A regression analysis was conducted in AMOS (version 18) to examine the independent effects of the three types of mentoring relationships predicting outcomes simultaneously. The true corrected values were used as inputs. After parsing out shared effects, resultant standardized effects were .06 for PS, .12 for CD, and .22 for RM.

Furthermore, intercorrelations of the moderator variables were examined, unweighted and weighted based on sample size, to further understand possible mechanisms for some of the moderator effects. As demonstrated in Table 2, many of these indicators were highly related.

Discussion

Overall, our results indicate that CD and PS account for approximately 8.4% and 6.8% of the variance in outcomes, respectively. These results are comparable to the previous meta-analyses (i.e., Allen et al., 2004; Eby et al., 2008) and demonstrate the value of mentoring under the larger umbrella of employee development. Furthermore, RM was found to be the strongest predictor, accounting for approximately 10.9% of the variance in outcomes. However, when all three mentoring functions were entered simultaneously, each one by itself explained only a small portion of unique variance in the outcomes: PS dropped to less than 1%, CD to 1.4%, and RM remained the strongest but only accounted for 4.8%. Thus, due to high intercorrelations among mentoring functions, assessing all three may provide no more additional information than what one alone might provide—unless specific types of outcomes are targeted.

Theoretical Implications

Theoretical implications of these results center on the inherent challenges associated with conceptualizing and capturing the mentoring functions’ constructs. Most importantly, this is the first meta-analytic study to date examining RM separately from the other mentoring functions, and this function was the strongest predictor of outcomes of the three functions. This finding substantiates the suggestions of Scandura (1992) and Haggard et al. (2011) that RM is a mentor function in itself, and it should be treated as conceptually distinct from the others. In our examination of the relationships among the three mentoring functions, it is noteworthy that RM shared approximately 32.5% of the variance with PS and approximately 34.8% with CD. This suggests there is no justification to fold RM in with PS, rather than CD, since it shares comparable variance with both of these functions. More broadly, regarding the overall effect size of the relationship between mentoring and outcomes, Scandura and Pellegrini (2007) discussed at some length the variability of methods that are employed for capturing protégé perceptions of their mentors’ behavior. For example, in some studies, protégés are asked to rate their most recent mentor while they respond to the scales, whereas others are asked to evaluate their most influential mentor. This introduces the possibility that studies in which protégés report on an influential mentor will yield stronger mentoring–outcome relationships than studies with protégés reporting on their current mentor. In summary, as mentoring research evolves and moves forward, investigators need to continue to strive for construct clarity and consistency.

Furthermore, although they must be interpreted with caution due to the small number of primary studies included, the moderator analyses present some starting points for further research as well as some interesting implications for practitioners. First, we found that gender moderated the relationship between the two primary mentoring functions, PS and CD. Specifically, these two facets shared approximately 36% of the variance with one another and demonstrated an even higher positive correlation in studies with high proportions of both male mentors and protégés in the samples. A couple of possible explanations for this finding include (a) PS and CD actually occur together more often in mentorships with male participants or (b) the relationship between PS and CD is spuriously inflated as a result of measurement invariance in how men and women respond to the mentoring function scales. We hope future research will shed light on the relationship between the gender composition of the dyad and the degree of intercorrelation between PS and CD.

Practical Implications

We believe our results can be used to inform leaders and human resource professionals on ways in which to foster mentoring relationships in their organizations. First, we wish to highlight the findings regarding the importance of mentors providing RM to their protégés. Protégés who regarded their mentors as someone to emulate realized more benefits from the mentorship than those who failed to regard their mentors in this way. This corroborates with leadership theories, which predict that the most effective leaders are those who inspire and influence subordinates by providing their own behavior as an example to follow (Bass, Waldman, Avolio, & Bebb, 1987). Bandura (1997) posited that this kind of RM boosts subordinates’ inner confidence that they can complete a given task successfully. Furthermore, Walumbwa and Hartnell (2011) empirically demonstrated that subordinates’ identification with a leader was positively associated with both their self-efficacy levels and job performance.

In summary, we wish to suggest some basic principles to provide guidance for how to prepare individuals for their role as mentors. First, organizational professionals can design training programs in such a way as to intentionally teach mentors how to be aware that their protégés are watching how they handle various situations and challenges. Mentors need to be cognizant of how they are influencing their protégés, even when they do not think that their protégé is directly observing them. Additionally, teaching mentors to discuss how they dealt with personal challenges and difficult situations may increase protégés’ self-efficacy and identification with the mentor (Ensher & Murphy, 2005). Finally, research on authentic leadership can provide an additional framework for developing successful mentors who are appropriate role models to their protégés. Authentic leaders are aware of the ways in which both their strengths and their weaknesses impact others, and they are guided by deeply held values and sense of responsibility to the individuals over whom they have influence (Gardner, Cogliser, Davis, & Dickens, 2011). Because authentic leaders possess these qualities, Avolio, Gardner, Walumbwa, Luthans, and May (2004) have proposed that they will be regarded as inspiring role models to those they lead. We expect the same would hold true for mentoring relationships. We hope that these suggestions will provide starting points for the purposes of (a) self-reflection for mentors who desire to intentionally grow and develop in their roles and (b) providing direction for organizational support and training of mentors.

Future Research and Additional Limitations

The goal of the current study was to gain a basic understanding of the impact of various mentoring functions on outcomes. One of the major limitations was the relative lack of primary studies available to assess some of the relations of interest. In turn, some relations based on smaller sample sizes should be interpreted with caution. Future research should further evaluate these relations as more studies become available. Finally, as with all meta-analyses, the current inferences are based on the information available in the primary studies; therefore, the findings may not be generalizable to other areas of mentoring research.

Conclusion

Similar to other mentoring meta-analyses, this study contained a relatively small number of primary studies. Furthermore, our moderator analyses incorporated an even smaller number of studies, so conclusions stemming from those analyses must remain tentative. Nevertheless, our study builds on previous meta-analyses and represents a starting point for assessing the conditions under which protégés are most likely to realize desired benefits of mentoring. In summary, we anticipate future mentoring research endeavors to build our knowledge of the various benefits protégés can expect to derive from the mentoring process. More studies with a longitudinal design will advance our understanding of how and when protégés can expect to experience desired outcomes. Taken together, our findings reiterate the value of mentoring to protégé development and provide evidence of trends that may serve to better inform both research and practice.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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