The Role of Faculty Mentors in the Research Training of CounselingPsychology Doctoral StudentsMerris A. Hollingsworth and Ruth E. FassingerUniversity of MarylandThis study investigated research mentoring experiences of counseling psychology doctoral students aspredictors of students’ research productivity. The authors also assessed the research training environmentand research self-efficacy as influences on research productivity. Participants were 194 third- andfourth-year counseling psychology doctoral students. Results indicated that the research training environment predicted students’ research mentoring experiences and their research self-efficacy. Bothresearch mentoring experiences and research self-efficacy mediated the effect of the research trainingenvironment on research productivity. Analyses showed no significant differences in these relationshipsby student gender or scientific stature of training programs.Research training of counseling psychology doctoral studentshas received increased scrutiny in the last 2 decades. This scrutinystems, in part, from the observation that few counseling psychologists conduct research after completing their doctoral requirements despite training in a scientist–practitioner model (Brems,Johnson, & Gallucci, 1996). Although research suggests that individual factors, such as personality and interests, play a major rolein research attitudes and productivity (e.g., Kahn & Scott, 1997;Krebs, Smither, & Hurley, 1991; Mallinckrodt, Gelso, & Royalty,1990), theorists have also proposed that the research trainingenvironment plays an influential role in shaping counseling psychologists’ perceptions of research (Gelso, 1997).To describe the role of the research training environment, Gelso(1997) has proposed and empirically tested a model. The researchtraining environment model hypothesizes nine themes central toresearch training, which include (a) teaching students that allresearch is flawed, (b) teaching students to look inward for research ideas, (c) helping students understand the connection between science and practice, (d) teaching varied methodologies, (e)teaching statistics in ways that are relevant to research applications, (f) faculty modeling of appropriate scientific behavior andattitudes, (g) providing positive reinforcement of scientific activity, (h) involving students in research activities early in graduatetraining, and (i) viewing participation in science as a partiallysocial activity. A number of empirical studies have indicated thatthe research training environment model describes critical elements that differentiate between research training programs(Gelso, Mallinckrodt, & Judge, 1996; Kahn & Scott, 1997; Royalty, Gelso, Mallinckrodt, & Garrett, 1986).Studies also consistently show positive relationships betweenthe research training environment, students’ research self-efficacy,and students’ research productivity. For example, Krebs et al.(1991) found a positive relationship between students’ perceptionsof the research training environment and subsequent researchproductivity. Investigations also supported positive relationshipsbetween the research training environment and students’ researchself-efficacy (Bishop & Bieschke, 1998; Phillips & Russell, 1994).Further analyses suggested that research self-efficacy mediates therelationship between the research training environment and students’ research productivity; that is, the training environmentaffects productivity indirectly, through the influence of the trainingenvironment on students’ research self-efficacy (Brown, Lent,Ryan, & McPartland, 1996; Kahn & Scott, 1997).In addition, previous research suggests that student gender moderates the research training environment, self-efficacy, and productivity relationship, with significantly different relationshipsexisting between these variables for men and for women. Specifically, Brown et al. (1996) found that research self-efficacy had asignificantly stronger effect on research productivity for malestudents than for female students; in contrast, the research trainingenvironment had a greater direct effect on productivity for femalethan for male students. Evidence from Kahn and Scott (1997) alsosupports student gender as a possible moderator, with males reporting higher research self-efficacy than females.The literature also supports expressed interest in research as apredictor of research productivity (Kahn & Scott, 1997; Parker &Detterman, 1988; Royalty & Magoon, 1985). Although the research training environment and research self-efficacy appear toinfluence students’ interest in research (Bishop & Bieschke, 1998;Kahn & Scott, 1997), students also have had interest and experiences with scientific inquiry that they developed prior to theirdoctoral program training (Gelso, 1997). Varied levels of priorresearch interest reflect individual differences that students bringto their doctoral programs. Although data have supported theeffects of the research training environment in changing students’level of research interest (Mallinckrodt et al., 1990; Royalty et al.,1986), the extent to which prior levels of research interest mayinfluence students’ later research productivity is unclear.Although mentoring is not a specific focus of the researchtraining environment literature, faculty mentoring emerges as aconsistently important undercurrent in the research training enviMerris A. Hollingsworth and Ruth E. Fassinger, Counseling and Personnel Services, University of Maryland.The data were collected by Merris A. Hollingsworth as part of herdoctoral dissertation.Correspondence concerning this article should be addressed to MerrisHollingsworth, who is now at the Center for Counseling and StudentDevelopment, 261 Perkins Student Center, University of Delaware, Newark, Delaware 19716. E-mail: [email protected] of Counseling Psychology Copyright 2002 by the American Psychological Association, Inc.2002, Vol. 49, No. 3, 324–330 0022-0167/02/$5.00 DOI: 10.1037//0022-0167.49.3.330324ronment. For example, Gelso (1993) outlined specific facultybehaviors associated with good research-related mentoring. In thisdescription, faculty offer interpersonal reinforcement for researchactivity, express enthusiasm for science and research, acknowledge the inevitability of flaws in research, expose students to avariety of research methods, model a balance of science andpractice, and use relationship skills that communicate empathy,positive regard, and genuineness to students.However, some researchers have critiqued research trainingenvironment theory in regard to mentoring, suggesting that facultymentoring should be a more explicit element of the researchtraining environment. For example, Hill (1997) compared the roleof the faculty–student mentoring relationship in research trainingto that of the working alliance between the counselor and theclient, which prompted her suggestion that the faculty–studentmentoring relationship itself may be an essential ingredient in theresearch training environment. Similarly, Mallinckrodt (1997) recommended a systemic perspective, in which each advisor–studentrelationship is considered as a “micro-environment” that existswithin the larger contexts of a department and institution.Other researchers have voiced similar support for the importantrole of mentors in research training, although not within thespecific context of the research training environment. For example,Royalty and Reising’s (1986) data indicated that research activitiesinvolving interaction with role models or an advisor were amongthe strongest positive influences on interest in research. O’Brien(1995) and Gelso (1997) both noted that student responses toopen-ended questions about critical incidents in their researchtraining often focused on their relationships with faculty members.Several studies suggest that faculty modeling or mentoring inresearch activities corresponds with higher rates of research involvement and productivity among psychology students and recentgraduates (Cronan-Hillix, Gensheimer, Cronan-Hillix, & Davidson, 1986; Galassi, Brooks, Stoltz, & Trexler, 1986; Krebs et al.,1991).Despite these associations, no studies could be identified thatfocused specifically on research-related mentoring in counselingpsychology. The literature suggests that graduate students believethat having a mentor is a critical component of graduate training(Atkinson, Neville, & Casas, 1991; Lark & Croteau, 1998; Luna &Cullen, 1998). Many psychology graduate students also appear tohave mentors during their training; two studies among this population found that more than half of respondents reported having amentor during their graduate work (Cronan-Hillix et al., 1986;Mintz, Bartels, & Rideout, 1995). Furthermore, Atkinson et al.(1991) surveyed ethnic minority psychologists and found thatrespondents recalled their faculty mentors’ encouragement relatedto research involvement as important and useful.A few studies have investigated outcomes associated withresearch-related mentoring in other academic disciplines. Greenand Bauer’s (1995) study of doctoral students in the physicalsciences showed little relationship between research mentoringand students’ research productivity after controlling for participants’ research interest prior to graduate school. In contrast,Cronan-Hillix et al. (1986) found a significant relationship between receipt of mentoring and several measures of researchproductivity. The lack of additional studies in academic settingsthat explore outcomes associated with mentoring contrasts sharplywith studies of mentoring in business settings, where measuressuch as rate of promotion, salary increases, and job satisfaction areconsistently correlated with receipt of mentoring (e.g., Bahniuk,Dobos, & Kogler Hill, 1990; Bowen, 1985; Turban & Dougherty,1994; for a more complete review of this literature, see Noe,1988a).The current study extended the investigation of research trainingin counseling psychology by exploring the role that faculty research mentoring plays in predicting student research productivity,above and beyond the contributions of the research training environment, students’ research self-efficacy, and students’ past research attitudes. Five research questions guided our work:
Does the research training environment predict students’research mentoring experiences, their research self-efficacy, ortheir research productivity?
Do students’ research mentoring experiences mediate therelationship between the research training environment andproductivity?
Do students’ self-efficacy beliefs mediate the influence of theresearch training environment on research productivity?
Does controlling for students’ past attitudes toward researchsignificantly change the relationships between research trainingenvironment, self-efficacy, research mentoring, and researchproductivity?
Are relationships between these variables moderated by students’ gender or by the scientific stature of their training program?MethodParticipantsParticipants were 194 (135 women and 59 men) third- or fourth-yearstudents enrolled in 25 APA-approved counseling psychology programs.Only students working toward a PhD participated in the study, and theresponse rate was 70%. The majority of the participants identified themselves as European American (71%), and 12% identified as African American/Black, 5% as Hispanic/Latino/Latina, 4% biracial, 3.5% Asian American, 2% international students, and 1.5% unspecified. Ninety-five percentof the respondents categorized themselves as third- or fourth-year doctoralstudents, whereas the remaining 5% included second-, fifth-, and sixth-yearstudents. The ages of the participants ranged from 23 to 58 years(M 31.08 years, SD 6.36 years). Participants from high and mediumresearch productivity programs comprised the majority of the sample (38%and 36%, respectively), with 26% coming from low research productivityprograms. More than half of the respondents (57.5%) indicated that theycurrently participated in an active research team, and 72% consideredthemselves as currently having a research mentor. Students who did nothave a research mentor were instructed to “consider the faculty relationshipthat has been most important in your research training while in yourcurrent doctoral program” when answering questions.InstrumentsIndependent variables. The research training environment was assessed by a modified version of the Research Training EnvironmentScale—Revised (RTES–R; Gelso et al., 1996). The original instrumentcontains nine subscales measuring the following: teaching relevant statistics, facilitating students “looking inward” for research ideas, teaching thatall experiments are flawed and limited, focusing on varied investigativestyles, wedding science and clinical practice, faculty modeling of appropriate scientific behavior, faculty reinforcement of student research, students’ early involvement in research, and science as a partly social experience. Items ask students to rate their doctoral program in each of theseareas. Test–retest reliabilities for each subscale range from .74 to .94, andthe subscales consistently correlate with changes in research attitudesRESEARCH MENTORS 325during graduate training and with research self-efficacy (Gelso et al.,1996). The current study used a modified 16-item version of the RTES–R.First, the three items with the highest factor loading on each subscale wereselected for this study on the basis of factor analyses conducted by Kahnand Gelso (1997), in which all items were forced to load on one of the ninesubscales. This step yielded an abbreviated version with 27 items. To avoida potential problem of item overlap between this instrument and theResearch Mentoring scale (described below), we omitted 11 additionalitems from the RTE measure because they addressed the role of the facultyadvisor (e.g., “I feel that my faculty advisor expects too much from myresearch projects”). Participants responded on a 5-point Likert scale ranging from 1 to 5, with higher numbers indicating a greater level of agreement with each statement. Responses were added to yield a total score,with potential scores ranging from 16 to 80. Cronbach’s alpha for the RTEmeasure was .87 in the current study.We measured research mentoring experiences with the Research Mentoring Experiences Scale (RMES), a measure created for this study that isbased on comparable instruments developed for business settings (e.g.,Noe, 1988b; Ragins & McFarlin, 1990). The RME included two subscales.The first subscale, Psychosocial Mentoring, includes 13 items that exploredthe affective aspects of research training, focusing on the personal elementsof the relationship between faculty member and student. Participants indicated the extent to which a specific faculty member expressed emotionalsupport, communicated respect and personal regard, and modeled positiveattitudes toward research. The second subscale, Career Mentoring, investigated faculty members’ efforts to help students acquire specific information necessary to complete research tasks successfully. The 16 items on thissubscale explored faculty members’ teaching of research skills, givingadvice, and providing research opportunities. For both psychosocial andcareer mentoring, instructions asked respondents to rate their relationshipwith the faculty member whom they considered most important in theircurrent doctoral research training. Possible responses ranged from 1 (faculty member pays very little attention to . . . ) to 5 (faculty member pays agreat deal of attention to . . . ). Responses to items were added and dividedby the number of items to generate a total score. Possible scores rangedfrom 1 to 5. The RMES was initially tested and revised in a pilot study (n 25); Cronbach’s alpha in the current study was .74.Research self-efficacy, hypothesized as a second mediating variable, wasmeasured by a shortened version of the Self-Efficacy in Research Measure(SERM; Phillips & Russell, 1994). As previously adapted by Kahn andScott (1997), the shortened version of Phillips and Russell’s measureincludes 12 items asking doctoral students to describe their confidence inapplying four types of research-related skills: research design, practicalresearch skills, quantitative and computer skills, and writing skills. In thisstudy, participants indicated their responses on a 5-point Likert scale,ranging from 1 (no confidence) to 5 (total confidence). Each response wasadded to yield a total score, with potential scores ranging from 12 to 60.This instrument yielded high internal consistency (.90) in previous research(Kahn & Scott, 1997) and in the current study ( .87).Past attitudes toward research was measured by the four items constructed by Royalty et al. (1986). These items measured counseling psychology students’ recalled interest in conducting research prior to theirenrollment in the doctoral program. The items included the following: (a)“I would have preferred to have the option of completing my doctoraltraining without being required to complete research projects” (Preference), (b) “I had a strong interest in doing research” (Interest), (c) “I placeda high value on the place of research in my future career” (Value), and (d)“Participating in research activities after graduation was not a majorpriority for me” (Priority). Participants rated their level of agreement witheach item, using a 5-point Likert scale, which ranged from 1 (stronglydisagree) to 5 (strongly agree), and the first and last items were reversescored. Responses were added, then divided by the number of items toproduce a final score, with a potential range from 1 to 5. Previous researchshows good internal consistency for the scale, with alpha ranging from .87to .90 (Gelso et al., 1996; Kahn & Scott, 1997; Royalty et al., 1986), andthe test–retest correlation for this measure was .93 (Royalty et al., 1986).Cronbach’s alpha in the current study was .89.Dependent variable. The dependent variable, research productivity,was assessed using Kahn and Scott’s (1997) 8-item measure. These itemsprovided a broad measure of students’ involvement in research-relatedactivities, including collection and analysis of data, development of manuscripts, participation in public presentations, and attendance at researchconventions (Kahn & Scott, 1997). Students responded to each item byproviding a number indicating the number of projects for which they arecurrently collecting or analyzing data, the number of manuscripts they havecompleted or are now working on, and so forth. Responses were summedto obtain a total number, with potential scores ranging from zero to infinity.The current study yielded responses ranging from zero to 40, with a modalscore of 6. Internal consistency coefficients (K-R 20) for this scale rangedfrom .59 to .72 (Kahn & Scott, 1997), and in the current study Cronbach’salpha was .75 for this measure.A demographic data form requested information about participants’gender, race, year in doctoral program, and age. Additional items asked ifstudents were currently part of an active research team and if they currentlyhad a research mentor.ProcedureThe instruments for this study included a demographic form and asurvey booklet with the scales administered in the following sequence:Attitudes Toward Research, Research Productivity, Research TrainingEnvironment, Research Self-Efficacy, and Research Mentoring Experiences. To incorporate participants from training programs with varyinglevels of emphasis on research, the 63 currently active, APA-accreditedcounseling psychology programs were stratified into three groups on thebasis of their scientific stature: high, medium, or low. An evaluation ofcounseling psychology doctoral programs based on faculty research production (Hanish, et al., 1995) served as a guideline for each trainingprogram’s designation within a category. Nine programs were selectedfrom each category (high, medium, or low scientific stature), with attentionto geographical and institutional diversity. The researchers’ home university was omitted from the participant pool to avoid potential bias. Threeprogram directors declined to participate, and only one replacement program could be identified on short notice, resulting in a sample representing25 programs: 9 high, 9 medium, and 7 low scientific stature trainingprograms.To identify participants, counseling psychology program directors wereasked to provide names and mailing addresses of third- and fourth-yeardoctoral students in the spring of 1998. Potential participants (N 278)received an advance postcard inviting their participation, followed by amailed survey packet and personalized cover letter 1 week later, accompanied by a stamped return envelope. Each survey packet was numericallycoded to permit accurate follow-up. As an incentive to participate, weincluded a pencil with each test packet. To maximize the return rate,potential participants who had not yet returned their survey received areminder postcard 10 days after the mailing of the original survey, and afollow-up letter and additional survey packet 2 weeks after the mailing ofthe reminder postcard. Nonrespondents received one final request forparticipation by mail 2 weeks after the mailing of the second survey packet.In addition, survey packets were distributed anonymously by two programdirectors who were unable to release student names. No follow-up mailingswere sent to these two sites. Overall, 200 students responded. Data from 6surveys were incomplete and could not be used; thus, the final number ofparticipants was 194.ResultsIn preliminary analyses, we noticed strong positive skew on theResearch Productivity scale. To manage this difficulty, we used alogarithmic transformation to adjust each score, which yielded a326 HOLLINGSWORTH AND FASSINGERmore normal distribution. The data in Table 1 and all subsequentanalyses used the transformed productivity scores. Means, standard deviations, and zero-order correlations for the five variablesare indicated in Table 1.Multiple regression analyses were used to investigate the research questions. We used hierarchical regression to investigateresearch mentoring experiences as a mediator of the researchtraining environment’s influence on students’ research productivity. According to Baron and Kenny (1986), several conditions areneeded to support mediation: (a) the independent variable (trainingenvironment) must be related to the mediator (mentoring), and (b)the independent variable (training environment) must be related tothe dependent variable (productivity). In addition, when the mediator (mentoring) and the independent variable (training environment) are added, in subsequent steps, to a regression equationpredicting the dependent variable (research productivity), the regression coefficient for the independent variable (training environment) should decrease when the effects of the mediator (mentoring) are partialed out. Research mentoring would be considered a“perfect” mediator if the training environment had no effect onproductivity when mentoring is controlled (Baron & Kenny,1986). The first two conditions were supported by correlationcoefficients (see Table 1), so we proceeded with a regressionequation in which research mentoring experiences was added inthe first step, followed by research training environment in thesecond step. This analysis supported research mentoring experiences as a mediator ( .45, p .001) because the researchtraining environment became a nonsignificant predictor of research productivity ( .03, p .60).Similarly, hierarchical regression was used to analyze researchself-efficacy for a mediating effect between the research trainingenvironment and research productivity. As above, the two preliminary conditions were satisfied by correlation coefficients (i.e.,training environment and self-efficacy were related, and trainingenvironment and productivity were related). Regression supportedthe mediational hypothesis: Research self-efficacy predicted research productivity ( .36, p .001), whereas the researchtraining environment coefficient decreased ( .07, p .30) afterself-efficacy was partialed out.In a third analysis, we explored the role of research mentoringexperiences and research self-efficacy when we controlled forstudents’ past attitudes toward research. Past research attitudes wasentered in the first step of the hierarchical regression. Past researchattitudes emerged and remained a significant predictor of researchproductivity ( .38, p .001) despite the addition of researchtraining environment, research mentoring experiences, and research self-efficacy to the regression equation. Although pastresearch attitudes explained an additional 10% of students’ research productivity, research mentoring experiences and researchself-efficacy remained significant predictors ( .38, p .001,and .28, p .001, respectively) of research productivity.We tested student gender as a potential moderating variable ofthe relationships noted earlier with additional regression equations.In the first hierarchical regression, we entered gender as a dummyvariable, followed by entry of the research training environmentand research mentoring experiences in subsequent steps. We thenanalyzed the two- and three-way interactions among these variables. A significant interaction term would suggest that studentgender acts as a moderator, affecting the strength and/or directionof the relationship between the independent variables (Baron &Kenny, 1986). As Table 2 indicates, student gender was not asignificant predictor of research productivity, and the two- andthree-way interaction terms with mentoring and the training environment also were not significant. We completed a similar regression analysis with student gender, research self-efficacy, and theresearch training environment and found no significant interactioneffects. Similar analyses showed no significant differences basedon scientific stature of students’ programs (high, medium, or low)in the relationships among research training environment, researchmentoring, and research self-efficacy. Results are reported inTable 2.DiscussionThis study built on previous research describing the researchtraining environment and its effects on counseling psychologydoctoral students by addressing fundamental questions about students’ research mentoring experiences as a potentially importantaddition to the research training environment. Previous researchsupports the research training environment, research self-efficacy,and students’ past research attitudes as predictors of students’research productivity. The current study incorporated these established variables and investigated research mentoring experiencesas an additional influence on productivity. Consistent with previous research, analyses supported the role of the research trainingenvironment, research self-efficacy, and past research attitudes asdirect predictors of productivity.The data also suggested that students’ mentoring experiencesserve as an important predictor of research productivity, mediatingthe relationship between the research training environment andresearch productivity. This finding supports recent assertions thatfaculty mentoring is a critical component within the researchtraining environment as a whole (e.g., Gelso & Lent, 2000; Hill,1997) and provides additional evidence that students’ experienceswith faculty research mentors are important to students’ development as researchers. The strong correlation between the researchtraining environment and research mentoring experiences supportsthe logical proposition that a strong research training environmentis most likely to promote strong research mentoring relationships.However, the mediating role of research mentoring in the prediction of research productivity suggests that a research mentoringrelationship is the vehicle through which the training environmenthas greatest impact on individual students’ research production. Ifthis is the case, then working to improve student–faculty researchTable 1Zero-Order Correlations, Means, and Standard Deviationsof VariablesVariable 1 2 3 4 5
Research training environment —
Research monitoring experience .46** —
Research self-efficacy .34** .22** —
Attitudes toward research .04 .15* .31** —
Research productivity .19** .45** .36** .37** —M 56.27 3.18 45.85 3.28 2.20SD 11.94 0.82 7.46 1.17 0.76Note. N 194.
p .05. ** p .01.RESEARCH MENTORS 327mentoring may be an important step toward promoting greaterresearch productivity among counseling psychology doctoralstudents.Students’ research self-efficacy served as another mediator between the research training environment and research productivity.This result supports earlier findings by Brown et al. (1996) that thetraining environment influences productivity indirectly through itseffects on students’ self-efficacy.When we controlled for students’ past attitudes toward research,students’ mentoring experiences and research self-efficacy remained as influential predictors of research productivity. Althoughthis finding supports the importance of individual differences thatstudents bring to their doctoral programs, it also underscores theeffects of environmental and interpersonal factors, such as mentoring relationships and research self-efficacy, during doctoraltraining. Although one may argue that students who enter a training program with high research interest are more likely to seekresearch mentoring and to develop research self-efficacy, thesedata suggest that environmental interventions to support researchmentoring and development of students’ research self-efficacyhave effects exceeding those associated solely with students’ pastlevel of interest. This result supports earlier suggestions (e.g.,Gelso, 1997) that environmental interventions may play a decisivepart in promoting student research activity.Participants’ gender did not significantly influence these relationships among the variables of interest. This outcome divergesfrom results of previous research, which showed male studentsexperiencing research self-efficacy as a greater influence on research productivity than their female peers (e.g., Brown et al.,1996). The absence of significant findings by gender for researchself-efficacy in the current study may reflect restricted range inparticipants’ responses because we used a 5-point scale for research self-efficacy responses, compared with the 10-point scaleused in the earlier studies (Brown et al., 1996; Kahn & Scott,1997). Our results also showed no difference by gender in theeffects of the research training environment on productivity, contrasting with a previous study (Brown et al., 1996). Although theabbreviated version of the research training environment measureused in our study was based on earlier work (Gelso et al., 1996;Kahn & Gelso, 1997) and showed internal consistency comparableto the full scale, perhaps the smaller number of items limited therange of participant responses, leading to no effects by gender.However, the lack of significant effects by gender in our study alsomay reflect changes that have occurred in many counseling psychology training programs because the data for Brown et al.’sanalyses were collected in the early 1990s. As many trainingprograms have experienced an influx of female students, perhapsthe research training environments have shifted, leading to fewerdifferences in the research training experiences of men andwomen. Because not many published studies have analyzed participant gender and our findings conflict with earlier work, theseresults highlight the critical need for investigation of potentialdifferences and similarities by gender in future research.Our analyses also showed no differences between male andfemale students in the effects of research mentoring on productivity. This result suggests that mentoring plays an equally importantrole for students, regardless of gender; however, this findingshould be interpreted cautiously given the absence of prior work inthis area. As above, we note the importance of further research,with attention to possible differences in the relationships betweenvariables as a function of student gender.We also investigated potential differences in the effects of thetraining environment, mentoring, and research self-efficacy onresearch productivity by the scientific stature of participants’ training programs. The absence of significant differences suggests thatthese variables function similarly to support research productivityin all counseling psychology doctoral programs, regardless of thescientific stature of the program. This result should be consideredpreliminary because other studies have not used a comparablestratification system in selecting programs to sample. However, ifsupported by further study, this finding lends support to the universality of the research training environment, research mentoring,and research self-efficacy as constructs that are fundamental components of the research training process.Strengths and LimitationsThis study has several strengths that underscore its value tocounseling psychology. This work provides a conceptual bridgelinking two areas—the research training environment and mentoring relationships—that had not yet been combined empirically.The research demonstrates that linking these two areas is criticallyimportant in understanding the research training process. Theextent of the sampling and the high return rate support the generalizability of these findings to upper level doctoral students incounseling psychology. Our study also generates numerous questions for further research.Table 2Summary of Hierarchical Regression Analyses PredictingResearch ProductivityVariable F pFirst equationGender 0.10 .75Research mentoring experience (RME) 9.66 .00**Research training environment (RTE) 3.14 .08Gender RME 0.00 .95Gender RTE 0.06 .81Gender RTE RME 2.18 .12Second equationGender 0.27 .60Research self-efficacy (RSE) 4.75 .03*RTE 2.46 .12Gender RSE 0.09 .76Gender RTE 0.15 .70Gender RSE RTE 1.13 .33Third equationScientific stature 2.08 .13RME 8.29 .00**RTE 1.72 .19Scientific Stature RME 1.98 .14Scientific Stature RTE 1.77 .17Scientific Stature RTE RME 1.72 .17Fourth equationScientific stature 2.27 .11RSE 2.82 .10RTE 1.03 .31Scientific Stature RSE 1.92 .15Scientific Stature RTE 2.46 .09Scientific Stature RTE RSE 1.77 .15Note. N 194.
p .05. ** p .01.328 HOLLINGSWORTH AND FASSINGERSeveral limitations also must be considered in interpreting theseresults. First, the data collected were cross-sectional and correlational. Thus, perceptions of past research interest were based onparticipants’ recollections, which easily may be blurred by currentexperiences. In addition, mentoring relationships, like most relationships, are likely to change over time. For example, a student inthe early stages of developing a mentoring relationship is likely tohave a different perspective than when the relationship is wellestablished. Similarly, a student who has a long history with aspecific mentor may find their relationship becoming more collegial as the student approaches the status of a professional peer.Relying on cross-sectional data provides only a brief snapshot ofstudents’ experiences, which may result in omission of importantinformation. A future study that incorporated a longitudinal designcould address some of these concerns.Second, the measures relied solely on self-report by studentparticipants. The data did not corroborate students’ perceptions oftheir research training environment, research productivity, or theirmentoring relationships from additional sources. Additional research would greatly benefit from study of paired observationsregarding these variables, for example, comparisons of student andfaculty mentor responses. Furthermore, the study design and accompanying analyses assume independence among respondents.Despite random sampling of training programs, clusters of respondents were enrolled in the same doctoral program and shared thesame research training environment. Consequently, one might findsome homogeneity within clusters, based on students having metsimilar admission criteria and selecting the same research trainingprogram environment (Kish, 1965). Lack of independence maymagnify the relationships between variables. This problem couldbe corrected by conducting analyses at the program level; however, the sample size in this study was insufficient to support thislevel of analysis.Finally, the absence of established measures to explore mentoring relationships prompted use of a new, unproven instrument toassess psychosocial mentoring in this study. Although the measurewas revised on the basis of pilot study data and achieved anadequate measure of reliability in this study, the data should beregarded with some caution given the lack of established reliabilityand validity evidence for this instrument. This limitation pointsclearly to the need for more instrument development in the studyof academic mentoring relationships. In addition, the researchtraining environment measure was greatly abbreviated from Gelsoet al.’s (1996) original version. Although an adequate reliabilitycoefficient was obtained for the measure used in this study, resultsshould be interpreted with the awareness that this abbreviatedversion is not an established use of this scale.Implications for Research and PracticeThis study suggests a number of avenues for further research.Additional research is warranted to explore the role of facultymentoring within the research training environment and as a contributor to students’ research productivity. Consistent with thissuggestion, further efforts to develop and refine instruments toassess faculty mentoring are particularly needed. Several wellestablished instruments to describe mentoring exist in businesssettings, but few attempts have been made to create comparablemeasures for academic settings. This study focused exclusively ondyadic mentoring relationships between faculty and students. Additional research could investigate the effects of group mentoring,such as that received through research team experiences or peermentoring by research-oriented classmates. In addition, specificmodels of mentoring, such as feminist mentoring (Fassinger,1997), could be explored to investigate aspects of mentoringapproaches, such as traditional, hierarchical approaches versusmore collaborative styles. It is also important to note that methodological diversity is needed in both the research training environment and mentoring literatures, incorporating methods thatpermit longitudinal assessment of change. Methodological diversity should include a wider range of perspectives than self-reportby students and use both quantitative and qualitative approaches.Further exploration of potential similarities and differences in theresearch training environment and students’ research self-efficacyby gender are also needed, particularly as training programs beginto reflect greater numbers of female faculty and female students.Because this study applies specifically to the interactions ofdoctoral students and faculty, the implications for practical application are tailored to those who learn and teach in doctoral trainingprograms. For prospective doctoral students, the results suggestthat students who value research training should explore the research training environment of programs they are consideringbecause the overall research training environment influences individual research mentoring relationships and development of research self-efficacy beliefs. At the same time, students also need toconsider the person variables (e.g., past level of research interest)that they bring to their research training as a way to dispel possibleexpectations that the “right” mentor can create high levels ofresearch interest, self-efficacy, or productivity. For faculty, theresults offer some encouragement that efforts to mentor students’research development are associated with greater research productivity among students. At a more systemic level, the data inviteconsideration of the research training environment and mentoringactivities at the program and departmental level. Training programs that value research may benefit from discussion about theextent to which faculty feel supported in their efforts to be researchmentors. Faculty discussions of mentoring may also encouragesharing of strategies or collaborative efforts, which may decreasethe likelihood that some faculty will bear a disproportionate burden for research mentoring of students. This type of discussionmay also encourage faculty to explore ways that they can manageelements of the mentoring relationships that seem particularlyburdensome. Because the research training environment contributes to students’ research self-efficacy, faculty in training programs may also wish to consider specific ways in which they,individually and collectively, nurture research self-efficacy amongtheir students. Faculty also may wish to help their own studentswho plan on careers in academe develop their own skills asresearch mentors. For example, helping advanced doctoral students organize and direct their own research team, composed ofundergraduate students and graduate peers, provides an opportunity to develop research self-efficacy, receive research mentoring,and begin developing skills as a future research mentor.In summary, this study suggests that research mentoring experiences make a notable contribution to students’ research productivity. We encourage further innovation, collaboration, and evaluation in this area to promote continued development of scientist–practitioners in counseling psychology.RESEARCH MENTORS 329ReferencesAtkinson, D. R., Neville, H., & Casas, A. (1991). The mentorship of ethnicminorities in professional psychology. Professional Psychology: Research and Practice, 22, 336–338.Bahniuk, M. H., Dobos, J., & Kogler Hill, S. E. (1990). The impact ofmentoring, collegial support, and information adequacy on career success: A replication. Journal of Social Behavior and Personality, 5,431–451.Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variabledistinction in social psychological research: Conceptual, strategic, andstatistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182.Bishop, R. M., & Bieschke, K. J. (1998). Applying social cognitive theoryto interest in research among counseling psychology doctoral students:A path analysis. 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Researchtraining environments and student productivity: An exploratory study.Counseling Psychologist, 14, 31–36.Gelso, C. J. (1993). On the making of a scientist–practitioner: A theory ofresearch training in professional psychology. Professional Psychology:Research and Practice, 24, 468–476.Gelso, C. J. (1997). The making of a scientist in applied psychology: Anattribute by treatment conception. Counseling Psychologist, 25, 307–320.Gelso, C. J., & Lent, R. W. (2000). Scientific training and scholarlyproductivity: The person, the training environment, and their interaction.In S. D Brown & R. W. Lent (Eds.), Handbook of counseling psychology(3rd ed., pp. 109–139). New York: Wiley.Gelso, C. J., Mallinckrodt, B., & Judge, A. B. (1996). Research trainingenvironment, attitudes towards research, and research self-efficacy: TheRevised Research Training Environment Scale. Counseling Psychologist, 24, 304–322.Green, S. G., & Bauer, T. N. (1995). 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