ABSTRACT Title of Dissertation: COUNSELING SELF-EFFICACY AND THE RELATIONAL EFFICACY MODEL Marylee Ashley Morrison, Doctor of Philosophy, 2016 Dissertation directed by: Robert W. Lent Department of Counseling, Higher Education, and Special Education Relation-inferred self-efficacy (RISE), a relatively new concept, is defined as a target individual’s beliefs about how an observer, often a relationship partner, perceives the target’s ability to perform certain actions successfully. Along with self-efficacy (i.e., one’s beliefs about his or her own ability) and other-efficacy (i.e., one’s beliefs about his or her partner’s ability), RISE makes up a three part system of interrelated efficacy beliefs known as the relational efficacy model (Lent & Lopez, 2002). Previous research has shown this model to be helpful in understanding how relational dyads, including coach-athlete, advisor-advisee, and romantic partners, contribute to the development of self-efficacy beliefs. The clinical supervision dyad (i.e., supervisor-supervisee), is another context in which relational efficacy beliefs may play an important role. This study investigated the relationship between counseling self-efficacy, RISE, and other-efficacy within the context of clinical supervision. Specifically, it examined whether supervisee perceptions about how their supervisor sees their counseling ability (RISE) related to how supervisees see their own counseling ability (counseling self-efficacy), and what moderates this relationship. The study also sought to discover the degree to which RISE mediated the relationship between supervisor working alliance and counseling self-efficacy. Data were collected from 240 graduate students who were currently enrolled in counseling related fields, working with at least one client, and receiving regular supervision. Results demonstrated that years of experience and RISE predicted counseling self- efficacy and that the relationship between RISE and counseling self-efficacy was, as expected, moderated by other-efficacy. Contrary to expectations, however, counseling experience and level of client difficulty did not moderate the relationship between RISE and counseling self-efficacy. These findings suggest that the relationship between RISE and counseling self-efficacy was stronger when supervisees saw their supervisors as capable therapists. Furthermore, RISE was found to fully mediate the relationship between supervisor working alliance and counseling self-efficacy. Future research directions and implications for training and supervision are discussed. COUNSELING SELF-EFFICACY AND THE RELATIONAL EFFICACY MODEL by Marylee Ashley Morrison Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2016 Advisory Committee: Professor Robert W. Lent, Chair Professor Clara E. Hill Professor Mary Ann Hoffman Professor Dennis M. Kivlighan, Jr. Professor Richard Q. Shin © Copyright by Marylee Ashley Morrison 2016 ii Acknowledgements I do not think I could have completed this undertaking without the help of so many wonderful, supportive people. Thank you to my advisor, Robert W. Lent, for embodying the very model we study. Your belief in my ability has indeed helped me believe in myself and it has been an honor to be your advisee. Thank you to my committee members Clara Hill, Mary Ann Hoffman, Dennis Kivlighan, and Richard Shin, not just for your role in helping me create a solid study, but also for your contributions to my growth as both a scientist and a practitioner. I am so grateful to have gotten to know and learn from you all in so many different contexts. Thank you to my accountabili-buddies Matt and Ijeoma. Your combination of humor, authenticity, and hard work inspired me and kept me going. The dissertation process can be a very lonely undertaking, but I always felt we were in it together. The time we spent working together will always be some of my favorite memories of graduate school. Most of all, thank you to my family and my partner. Your unconditional love, encouragement, and support and your unwavering confidence have meant the world to me, and I am so grateful for your presence in my life. iii Table of Contents Acknowledgements ....................................................................................................... ii Table of Contents ......................................................................................................... iii List of Tables ............................................................................................................... iv List of Figures ............................................................................................................... v Introduction ................................................................................................................... 1 Counseling Self-Efficacy and Counselor Training ................................................... 2 Sources of Self-Efficacy ........................................................................................... 4 The Tripartite Model of Relational Efficacy Beliefs ................................................ 5 RISE and the Working Alliance in Supervision ....................................................... 9 Counseling Experience ........................................................................................... 10 Statement of the Problem ........................................................................................ 11 Hypotheses .............................................................................................................. 12 Method ........................................................................................................................ 14 Participants .............................................................................................................. 14 Measures ................................................................................................................. 15 Procedure ................................................................................................................ 19 Results ......................................................................................................................... 21 Preliminary Analyses .............................................................................................. 21 Testing for Main Effects and Moderation ............................................................... 29 Testing for Mediation ............................................................................................. 33 Discussion ................................................................................................................... 35 Implications and Future Research ........................................................................... 38 Limitations .............................................................................................................. 44 Conclusion .............................................................................................................. 47 Appendices .................................................................................................................. 48 References ................................................................................................................... 74 iv List of Tables Table 1: Analysis of Variance (ANOVA) Between Counseling Self-Efficacy and Categorical Variables of Interest -------------------------------------22 Table 2: Means, Standard Deviations, Correlations, and Internal Consistency Reliabilities -------------------------------------------------------------------24 Table 3: Variable Items and Pattern Matrix Factor Loadings---------------------25 Table 4: Hierarchical Multiple Regression Analysis Testing the Moderating Effect of Years of Experience on the Relationship between RISE and Counseling Self-Efficacy ---------------------------------------------------30 Table 5: Hierarchical Multiple Regression Analysis Testing the Moderating Effect of Other-Efficacy on the Relationship between RISE and Counseling Self-Efficacy ---------------------------------------------------31 Table 6: Hierarchical Multiple Regression Analysis Testing the Moderating Effect of Client Difficulty on the Relationship between RISE and Counseling Self-Efficacy----------------------------------------------------33 v List of Figures Figure 1: Model with other-efficacy moderating the relationship between RISE and counseling self-efficacy -------------------------------------------------8 Figure 2: Model with supervisee experience moderating the relationship between RISE and counseling self-efficacy -------------------------------9 Figure 3: Model with client difficulty moderating the relationship between RISE and counseling self-efficacy -------------------------------------------------9 Figure 4: Model with supervisory working alliance mediating the relation of RISE to counseling self-efficacy ------------------------------------------10 Figure 5: Relationships between RISE and Self-Efficacy at Low, Medium, and High Levels of Other-Efficacy ---------------------------------------------32 Figure 6: Hypothesized path model of counseling efficacy beliefs --------------40 vi List of Appendices Appendix A: Extended Literature Review -----------------------------------------------48 Appendix B: Letter to Directors and Participants ---------------------------------------62 Appendix C: Informed Consent Form-----------------------------------------------------64 Appendix D: Counseling Self-Efficacy (CLIENT-SPECIFIC) ------------------------67 Appendix E: Supervisory Working Alliance --------------------------------------------68 Appendix F: Relation-Inferred Counseling Self-Efficacy (CLIENT-SPECIFIC) --69 Appendix G: Other Counseling Self-Efficacy (CLIENT SPECIFIC) ----------------70 Appendix H: Client Difficulty -------------------------------------------------------------71 Appendix I: Demographic Questions ----------------------------------------------------72 1 Counseling Self-Efficacy and the Relational Efficacy Model Introduction Becoming a mental health practitioner requires extensive clinical training. In counseling psychology and other related professions, facilitating trainee development is a primary concern, although it has proven somewhat difficult to study (Hill & Knox, 2012). Counseling is a complex undertaking that involves a diverse set of tasks that include using a variety of helping skills, preparing for and managing sessions, and navigating any clinical situation that may arise (Lent, Hill, & Hoffman, 2003). One important component of trainee development is the trainees’ sense of competence at performing these counseling behaviors. This sense of competence, termed counseling self-efficacy, has been found to relate to a number of trainee outcomes, such as more positive outcome expectations, more positive self-evaluations, and less distress (for a review, see Larson & Daniels, 1998). While previous research has focused largely on outcomes and correlates of counseling self-efficacy, we know relatively little about how such self-efficacy develops. I aim to address this by looking at a relationship-specific source of counseling self- efficacy and how it may relate to client-specific counseling self-efficacy (i.e., a counselor’s self- efficacy beliefs about working with a particular client). Relationship-specific sources of self- efficacy are experiences that occur within particular relationships. How individuals believe their relationship partner views their ability to perform particular behaviors, termed relation-inferred self-efficacy beliefs (RISE), is a relationship-specific source of self-efficacy (Lent & Lopez, 2002). Because RISE is a fairly new, unstudied concept in the training and supervision literature, I would like to investigate its relationship to counseling self-efficacy by examining whether RISE offers utility in predicting counseling self-efficacy. I would also like to see whether the 2 relationship of RISE to counseling self-efficacy is moderated by other variables, such as supervisee experience, client difficulty, and supervisee perceptions about supervisor ability (i.e., other-efficacy). Finally, I plan to explore the relationship between the supervisory working alliance, RISE, and self-efficacy and determine if RISE mediates the relationship between working alliance and self-efficacy, as has been found in the academic advising relationship (Morrison & Lent, 2014). Counseling Self-Efficacy and Counselor Training Self-efficacy beliefs are “people’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performances” (Bandura, 1986, p. 391). These beliefs are hypothesized to influence people’s thoughts, feelings, and behaviors, including the activities in which people choose to participate (Bandura, 1997). According to Bandura (1997), Efficacy beliefs operate as a key factor in a generative system of human competence. Hence, different people with similar skills, or the same person under different circumstances, may perform poorly, adequately, or extraordinarily, depending on fluctuations in their beliefs of personal efficacy. (p. 37) Self-efficacy is viewed as context and behavior specific, rather than a global trait. Counseling self-efficacy, for example, involves individual’s confidence in their ability to perform behaviors and navigate situations specifically related to counseling (Larson & Daniels, 1998). Self-efficacy is also a key variable in social cognitive career theory (SCCT), which posits that efficacy beliefs help to determine interest, choice, satisfaction, and performance in academic and career contexts (Lent, Brown, & Hackett, 1994; Lent & Brown, 2006). According to SCCT, counseling self-efficacy should impact trainees’ interest in and whether they actually pursue counseling as a career choice. While only three studies have looked at counseling self-efficacy 3 related to counseling interest and choice (Lent et al., 2003; Heppner, O’Brien, Hinkelman, & Flores, 1996; Sheu, Rigali-Olier, & Lent), there is a wealth of research supporting the relationship between self-efficacy, interest, and choice in other areas. Research self-efficacy, for instance, has been found to predict interest and engagement in research behaviors in counseling psychology graduate students (Kahn, 2001; Kahn & Schlosser, 2010; Kahn & Scott, 1997) and in graduate students in other fields (Morrison & Lent, 2014). Examining counseling self-efficacy specifically, Lent and colleagues (2003) found that trainees who were more confident in their counseling ability reported greater interest in therapy activities and a greater intention to pursue counseling-related career options. Similarly, Heppner et al. (1996) found that trainees who were more confident in their ability to provide career counseling were more likely to report being interested in working with individuals who had career-related concerns. Sheu and colleagues (2012) found that trainees who reported feeling more confident in their ability to counsel racially diverse clients reported more interest in engaging in activities related to multicultural counseling. According to SCCT, counseling self-efficacy is also likely to impact how well trainees are able to perform counseling-related behaviors. There have been several studies of how counseling self-efficacy relates to trainee performance. Findings suggest that counseling self- efficacy may be related to trainee performance as rated by trained raters (Larsen et al., 1992; Munson, Stadulis, & Munson, 1986; White, 1996) and supervisors (Beverage, 1989; Hanson, 2007), though not all findings support this conclusion (Johnson, Baker, Kopala, Kiselica, & Thompson, 1989; Larson & Daniels, 1998). Based on their own findings, Heppner et al. (1998) suggested that the relationship between self-efficacy and outcomes may be more complex than originally thought. 4 Sources of Self-Efficacy While self-efficacy has received a great deal of attention across a number of disciplines, sources of self-efficacy have received less attention. Bandura (1997) hypothesized that four types of experience serve as the primary sources of self-efficacy beliefs and that these sources varied in the strength of their influence. Enactive mastery experience, later termed performance accomplishments, was argued to be the most influential source under most conditions. Vicarious experience, also termed vicarious learning, was the second most influential, followed by verbal persuasion (also known as social persuasion) and physiological and affective states (Bandura, 1997). These sources can be considered cross-relational sources because they occur outside the context of a specific relationship, or more accurately, they are present across relationships. More recently, Lent and Lopez (2002) argued that there is also an interpersonal component to the acquisition of self-efficacy. “The manner in which efficacy information is processed and integrated may also depend on a variety of cognitive, affective, and contextual considerations (e.g., attributions of success/failure to internal vs. situational factors; negative mood states)” (Lent & Lopez, 2002, p. 259). This efficacy information is often processed in a social context in which self-evaluations are influenced by the reactions of others (Bandura, 1986), especially in interpersonal performance domains. As Lent and Lopez (2002) point out, “how a child interprets his or her efforts at drawing or math will likely depend on the comments and non-verbal reactions of family members or other significant persons” (p. 260). Similarly, how a trainee interprets his or her efforts at performing counseling behaviors will likely depend on the comments and non-verbal reactions of important others, especially supervisors. There has been surprisingly little research examining supervision in relation to counseling self-efficacy, and the few existing studies have produced inconsistent findings. In a 5 study of professional counselors and doctoral students, Cashwell and Dooley (2001) found that receiving continuous clinical supervision predicted levels of counseling self-efficacy. Fernando and Hulse-Killacky (2005) found that counseling students who perceived their supervisor’s style to be more task oriented were more likely to report increased counseling self-efficacy, but this finding was not supported in subsequent research (Hanson, 2007). Hanson (2007) found supervisory working alliance to be the strongest predictor of counseling self-efficacy in supervisees, over and above other elements of supervision, such as the evaluation process (i.e., goal setting and feedback) and role clarification (i.e., role conflict and ambiguity). By contrast, Ladany, Ellis, and Friedlander (1999) found that changes in supervisor working alliance were not predictive of changes in supervisees’ self-efficacy. Marmarosh et al. (2013) found that the working alliance predicted counseling self-efficacy over and above avoidant and anxious adult attachment, but in a subsequent path analysis the path from working alliance to counseling self- efficacy was not significant. Such mixed findings suggest that the relationship between the supervision relationship and counseling self-efficacy is more complex than originally envisioned. The Tripartite Model of Relational Efficacy Beliefs One model that may address this complexity is Lent and Lopez’s (2002) tripartite model of efficacy beliefs in close relationships. In this model, self-efficacy exists within a network of other relational beliefs that interact and complement one another. This network of beliefs is theorized to be particularly applicable to growth-promoting interpersonal relationships, such as the one between a clinical supervisor and a supervisee. Included in this network are self- efficacy, other-efficacy, and relation-inferred self-efficacy (RISE) beliefs. Self-efficacy is each member’s beliefs about their own ability. Other-efficacy is each member’s beliefs about their partner’s ability. RISE is each member’s beliefs about how the other member views his or her 6 ability. In the context of supervision, RISE would be supervisee perceptions about how the supervisor sees the supervisee’s abilities or the supervisor’s perceptions about how the supervisee sees the supervisor’s abilities. Thus far, the relational efficacy model has generated a good deal of research in the context of sports relationships, such as those involving athletes and coaches (e.g., Jackson & Beauchamp, 2010a), athlete pairs (e.g., Jackson, Beauchamp, & Knapp, 2007), and physical education instructors and students (e.g., Jackson, Whipp, Chua, Dimmock, & Hagger, 2013). It has also been applied to romantic (Lopez & Lent, 1991; Gere, Martire, Keefe, Stephens, & Schulz, 2014), physical therapy (Jackson, Dimmock, Taylor, & Hagger, 2012c), financial advising (Yim, Chan, & Lam, 2012), and academic advising relationships (Morrison & Lent, 2014). The proposed study would be the first one to examine relational efficacy beliefs in the context of a supervision relationship. One thing to note is that self-efficacy beliefs, RISE beliefs, and other efficacy beliefs all represent perceptions that individuals have about themselves and others, not objective truths. In fact, social cognitive theory assumes that the optimal level of self-efficacy perceptions slightly overestimate one’s actual skill level because modest overconfidence encourages individuals to persist in the face of challenges and to develop more skill (Bandura, 1986). On the other hand, significantly over- or underestimating ability would have the opposite impact. Overestimating one’s ability may set that individual up for failure, while underestimating may lead to avoiding the task because of the perceived likelihood of failure (Lent et al., 1994). Currently, there is no research looking at optimal levels of RISE beliefs. How accurate or distorted these perceptions are, is likely complexly determined and beyond the scope of this study. Self-efficacy beliefs have been found to predict a variety of outcomes in other domains (e.g., interests, goals, and 7 performance; Lent et al., 1994) independent of their accuracy and the same may be true of RISE beliefs. Lent and Lopez (2002) suggest that this tripartite set of beliefs have important implications for both the relationship and for self-efficacy formation and maintenance processes. RISE, in particular, is thought to function as a relationship-specific source of self-efficacy (Lent & Lopez, 2002). If a supervisee believes that his or her supervisor sees the supervisee as capable of performing particular counseling tasks or effectively managing particular counseling situations, the supervisee may be more likely to come to see her- or himself as competent at conducting counseling. Furthermore, it also seems likely that other-efficacy, or how one partner views the other’s ability, impacts the relationship between RISE and self-efficacy (Morrison & Lent, 2014). Supervisees’ beliefs about how their supervisor views their counseling ability may affect their own sense of counseling self-efficacy to the extent that the supervisor is viewed as adept at counseling in their own right. For example, if a supervisee views the supervisor as lacking in counseling ability (low other-efficacy), how the supervisee thinks the supervisor views the supervisee’s counseling ability is unlikely to affect the supervisee’s efficacy because the supervisor may lack credibility as an efficacy source. Thus, the supervisee’s other-efficacy perceptions regarding the supervisor may moderate the relationship between RISE and counseling self-efficacy beliefs (see Figure 1). 8 Figure 1. Model with other-efficacy moderating the relationship between RISE and counseling self-efficacy. Two other variables that may influence the relationship between RISE and counseling self-efficacy are supervisee experience and client difficulty. Lent and Lopez (2002) argue that, because of its bolstering effect, RISE may be especially important in situations that involve (a) developing new skills, (b) using existing skills in a new context, and (c) reevaluating existing skills during a crisis or transition. Because supervisees with less experience are working on developing their basic skills, they may rely more heavily on RISE in determining their self- efficacy compared to supervisees who are more advanced. Similarly, dealing with a particularly difficult client may trigger a sort of “crisis” whereby supervisees re-evaluate their counseling efficacy. In these instances, they may also rely more heavily on RISE when determining their own level of ability than they would when working with a less challenging client. Figures 2 and 3, respectively, illustrate the moderating roles that supervisee experience and client difficulty may play relative to the relationship between RISE and counseling self-efficacy. Counseling self-efficacy RISE Other-efficacy 9 Figure 2. Model with supervisee experience moderating the relationship between RISE and counseling self-efficacy. Figure 3. Model with client difficulty moderating the relationship between RISE and counseling self-efficacy. RISE and the Working Alliance in Supervision RISE is assumed to relate to the quality of close relationships (Lent & Lopez, 2002). One way to conceptualize the quality of supervisory relationships is with respect to the working alliance that develops between the supervisor and supervisee. This working alliance consists of a mutual understanding of the goals and tasks of supervision as well the presence of an emotional Counseling self-efficacy RISE Client difficulty Counseling self-efficacy RISE Supervisee experience 10 bond between supervisor and supervisee (Bordin, 1983). Previous research on the relational efficacy model in the context of research advising found that advisees’ RISE beliefs regarding advisor perceptions of their research ability fully mediated the relationship between the advisory working alliance and students’ research self-efficacy (Morrison & Lent, 2014). Similar to the advisory working alliance, a good supervisory working alliance may be seen by the supervisee as reflecting favorably on the supervisor’s beliefs about the supervisee’s counseling abilities which, in turn, may promote a sense of counseling self-efficacy in the supervisee. Figure 4 shows RISE as a mediator of the relationship between the supervisory working alliance and counselor self- efficacy; the dashed path allows for the possibility of a direct (i.e., unmediated) path between the working alliance and counselor self-efficacy as well. Figure 4. Model with supervisory working alliance mediating the relation of RISE to counseling self-efficacy. Counseling Experience As trainees progress through their program and accrue clinical hours, they gain more exposure not only to relationship-specific sources of self-efficacy information, but also to the Counseling self-efficacy RISE Supervisory working alliance 11 four cross-relational sources. Both relationship-specific and cross-relational sources may then contribute to level of counseling self-efficacy. In fact, counseling experience, although operationalized in a number of different ways (e.g., year in program, years of counseling experience, number of client hours), has been found to consistently relate to counseling self- efficacy (Heppner et al., 1998; Larson, Suzuki, Gillespie, Potenza, Bechtel, & Toulouse, 1992; Lent et al., 2003; Melchert, Hays, Wiljanen, &Kolocek, 1996; O’Brien et al., 1997; Potenza, 1990). Theoretically, the increase in counseling self-efficacy may be due to trainees’ increasing exposure to favorable levels of all sources of self-efficacy over the course of training. For this reason, I expect that supervisees with more counseling experience will report higher levels of client-specific counseling self-efficacy. The study’s design will take years of counseling experience and hours of supervised counseling experience into account as control variables, in addition to their role as moderator variables. Statement of the Problem While researchers have started trying to understand the role of counseling self-efficacy in trainee development, very little of this attention has been aimed at understanding how counseling self-efficacy develops. This is problematic in that we have, to some degree, established the importance self-efficacy generally and counseling self-efficacy specifically, but we have very little empirical information about how to foster it. Because of the relational nature of self- efficacy development in the context of counseling, it is possible that conventional notions about the cross-relational sources of efficacy may need to be augmented by sources of efficacy that are forged in the context of specific counseling and supervisory relationships. In other words, how efficacious counselors believe they can be with a particular client (i.e., client-specific counseling 12 self-efficacy) may depend partly on sources of efficacy information that are relatively unique to that relational context. This study has several purposes. First, I will examine the predictive utility of the relationship specific source of self-efficacy, RISE, in regard to client-specific self-efficacy, while controlling for counseling experience. Next, I will examine the moderating role of other- efficacy, supervisee counseling experience, and client difficulty on the relationship between RISE and client-specific self-efficacy. Finally, I will investigate whether RISE mediates the relationship between the supervisory working alliance and counseling self-efficacy. Specific hypotheses follow. Hypotheses Hypothesis 1. Supervisee’s amount of counseling experience will predict supervisee counseling self-efficacy, such that supervisees who report more experience will report higher client specific counseling self-efficacy. Hypothesis 2. Supervisee’s client-specific relation-inferred self-efficacy (RISE) beliefs will positively predict supervisee client-specific counseling self-efficacy, over and above amount of counseling experience. Hypothesis 3. Supervisee’s amount of counseling experience will moderate the relationship between RISE and client-specific counseling self-efficacy such that the relationship will be stronger when supervisees have less counseling experience and weaker when they have more counseling experience. Hypothesis 4. Other-efficacy will moderate the relationship between RISE and client- specific counseling self-efficacy such that the relationship will be stronger when supervisees 13 believe their supervisors are more skilled as counselors and weaker when they believe their supervisor are less skilled as counselors. Hypothesis 5. Client difficulty will moderate the relationship between RISE and client- specific counseling self-efficacy such that the relationship will be stronger when supervisees believe their client is more challenging to work with and weaker when they believe their client is easier to work with. Hypothesis 6. RISE will fully mediate the relationship between the supervisory working alliance and client-specific counseling self-efficacy. 14 Method Participants Using G*Power (Faul, Erdfelder, Buchner, & Lang, 2009), a power analysis was conducted to determine that a sample size of at least 190 would be needed to detect medium effect sizes (f² = .15) at the level of α = .05 based on the hierarchical regression strategy. Data were collected online from a sample of 240 graduate-level students. Supervisees in accredited counseling or clinical psychology programs were eligible if they were currently engaged in providing counseling (practicums, externships, or internships) and receiving regular supervision. Of those who reported gender, one hundred and eighty seven students self-identified as female (82 %), 40 as male (17%), and 2 as other (>1%). Twelve participants did not report their gender. In terms of race/ethnicity, 77% participants identified as White, 8% as Asian, 4% as Hispanic or Latino/-a, 4% Multi-Ethnic or Multi-racial, 3% as Black or African American, and < 1% American Indian, Alaskan Native, Native Hawaiian, or Pacific Islander. Three percent identified with another ethnic group and 13 participants did not report their race/ethnicity. Compared to demographics reported by APA accredited combined clinical, counseling, and school psychology programs from the 2014 report cycle (APA, 2014), this sample was fairly representative except for Hispanic/Latino/a and Black/African American student groups, both of which were underrepresented. APA reported that 82% of students in these programs were identified as female, 18% as male, and .4% as other. Eighty percent were identified as White, 10% as Hispanic or Latino/a, 7% as Black or African American, 5% as Asian, 3% as multi-ethnic, and .8% as American Indian, Alaskan Native, Native Hawaiian, or Pacific Islander. The average age of this sample was 28.11 years (SD = 4.31), which is similar to what has been reported in other studies involving this population (e.g. Larson et al., 1992; O’Brien et al., 1997). 15 Students represented all levels of academic training with 37 (15%) in their first year, 60 (25%) in their second year, 40 (16%) in their third year, 46 (19%) in their fourth year, 30 (12%) in their fifth year, 13 (5%) in their sixth year, and 3 (1%) in their seventh year or beyond; 6% did not report this information. In terms of academic program, 49% reported being enrolled in a counseling psychology program, 39% reported being enrolled in a clinical psychology program, 6% reported other, and 6% did not indicate which program they were enrolled in. Fifty four percent of participants reported that they were working on a PhD, 25% were working on a PsyD, 12% were working on a terminal masters, 3% were working on another degree, and 6% did not respond. Parenthetically, the 6% incidence of missing demographic data may have been partly due to the fact that the demographic questions were placed at the end of the survey; it is also possible that some participants did not want to share this information so as to ensure that their survey responses would remain anonymous from their supervisors, given that the survey involved rating of the supervisor and the supervision relationship. Measures Counseling Self-Efficacy. The client specific version of the Counselor Activity Self- Efficacy Scales (CASES-S), developed by Lent et al. (2006), was used to assess supervisees’ client-specific perceptions of their ability to perform counseling-related behaviors. The CASES- S contains six scales organized under three larger domains. The Helping Skill Self-Efficacy scale consists of three subscales containing a total of 15 items measuring self-efficacy related to exploration skills, insight skills, and action skills. The Session Management Self-Efficacy scale contains 10 items measuring supervisees’ perceptions around their ability to facilitate the flow of the counseling session. The Counseling Challenges Self-Efficacy scale contains two subscales and 16 items measuring perceived capacity to handle relationship conflict and difficult client 16 presenting problems. Because participants ranged from novice to advanced supervisees, only the Session Management Self-Efficacy scale was used. This is because the Helping Skill scale focuses on micro-skills that are less relevant to experienced supervisees and the Counseling Challenges scale focuses on advanced skills that are less relevant to novice supervisees. Supervisees rated their confidence in their ability to perform each skill on a 10 point scale ranging from 0 (no confidence) to 9 (complete confidence). Because the study was concerned with client-specific counseling self-efficacy, participants were asked to indicate how confident they were in their ability to use the set of helping skills effectively, in the session with the most difficult client on their caseload. Supervisees then rated their ability to perform each counseling task. A sample item is “keeping sessions on track and focused”. Scale scores were computed by summing over the item responses and then dividing by the number of items on the scale, with higher scores indicating higher confidence in one’s counseling capabilities. Lent et al. (2003) reported adequate internal consistency reliability coefficients on the general version of the CASES (CASES-G), with the Session Management subscale alpha of .94 and a total scale reliability of .97. Scores on the Session Management subscale of CASES-G related strongly to a previously validated measure of counseling self-efficacy, thereby supporting the convergent validity of the measure. Scores also related weakly to a social desirability measure, supporting divergent validity. Furthermore, the CASES, including the Session Management subscale, was found to change significantly over the course of a semester practicum, and to differentiate between students with differing levels of counseling experience (Lent et al., 2003). See Appendix D. Working Alliance. Supervisee perceptions of the supervisory working alliance were measured using the Supervisory Working Alliance Inventory (SWAI; Efstation et al., 1990). The 17 19-item form includes two subscales. The Rapport subscale consists of 12 items and measures supervisees’ perceptions of support received from the supervisor (e.g., my supervisor makes the effort to understand me). The Client Focus subscale consists of 7 items and measures supervisee perceptions of the emphasis their supervisor places on promoting the supervisee’s understanding of the client (e.g., my supervisor helps me work within a specific treatment plan with my clients). Participants were instructed to respond to the SWAI based on their relationship with their current supervisor (i.e., the person supervising their work with the particular client whom they had in mind when completing the CASES-S). Participants were asked to indicate the frequency of each supervisor behavior on a 7-point rating scale ranging from 1 (almost never) to 7 (almost always). An example item is, “My supervisor welcomes my explanations about the client’s behavior.” A total scale score was calculated by summing the item responses and then dividing by the total number of items. Higher scores indicated a stronger working alliance. Efstation et al. (1990) reported a total score internal consistency reliability of .90. In terms of validity, the SWAI total scale score was found to correlate moderately and positively with measures of supervisory style and supervisee counseling self-efficacy (Efstation et al., 1990). See Appendix E. Relation-Inferred Self-Efficacy. Using a method similar to that employed by Morrison and Lent (2014), an altered version of the Counselor Activity Self-Efficacy Scale – Client- specific form (CASES-S; Lent, Hoffman, Hill, Treistman, Mount, & Singley, 2006) was used to measure supervisees’ perceptions of their supervisors’ beliefs about the supervisees’ ability to perform counseling-related skills with a particular client. The CASES-S was adapted to assess client-specific RISE beliefs to ensure that a similar set of counselor activities was being evaluated while varying the perspective of the rating. The RISE version employed the same 0-9 18 confidence scale as the CASES, but asked supervisees to indicate how much confidence they believed their supervisors had in their (the supervisees’) ability. Specifically, the instructions stated, “In answering the following questions please think about the most difficult client on your caseload and the supervisor who supervises your work with that particular client”. Supervisees were then asked to rate their ability to perform each counseling task on the CASES-S from the imagined perspective of their supervisor. See Appendix F. Other-Efficacy. Also using a method similar to that of Morrison and Lent (2014), an altered version of the Counselor Activity Self-Efficacy Scale – Client-specific form (CASES-S; Lent et al., 2006) was used to measure supervisees’ perceptions of their supervisors’ ability to perform particular counseling activities with the same client that the supervisee rated their own ability to work with, that is, the supervisee’s most difficult client. Adapting the CASES-S to assess client-specific other-efficacy beliefs ensured that a similar set of counselor activities was being evaluated while varying the perspective of the rating. The other-efficacy version employed the same 0-9 confidence scale as the CASES, but asked supervisees to indicate how much confidence they had in their supervisor’s ability to work with a particular client (i.e., the client with whom they were feeling most challenged at the present time). See Appendix G. Client Difficulty. Client difficulty was assessed using the Global Assessment of Functioning (GAF; American Psychiatric Association, 1987). The GAF examines three areas of functioning: psychological, social and interpersonal, and occupational. The GAF consists of 11 behavioral descriptors ranging from “No symptoms. Superior functioning in a wide range of activities…” (100-91) to “persistent danger of severely hurting self or others…or persistent inability to maintain minimal personal hygiene or serious suicidal act with clear expectation of death” (10-1). Clients were rated between 0 (most severe) and 100 (least severe), with each 19 descriptor having a 9 point range. Jones, Thornicroft, Coffey, and Dunn (1995) found that the GAF showed a satisfactory inter-rater reliability coefficient of .70. The GAF was positively related to changes in antipsychotic medications and increased provision of support (Jones et al., 1995). Participants were instructed to rate their most difficult client on this scale. The scores were then reversed so that higher scores indicated lower functioning or more difficult clients. See Appendix H. Supervisee Counseling Experience. Supervisee counseling experience was assessed in two ways. The first way used a single item: “Please estimate how many total years of experience you have counseling clients.” Similar measures of experience have been used in other research on counseling self-efficacy (Heppner et al., 1998; Larson et al., 1992; Lent et al., 2003; Melchert et al., 1996; O’Brien et al., 1997). In support of the construct validity of the years of experience measure, Orlinsky et al. (1999) found that years of experience correlated with perceived therapeutic mastery. In addition, Goldberg and colleagues (2016) found that therapists varied significantly in skill level over years of experience and that years of experience was related to early rates of termination. Another single item was also used to measure counseling experience: “How many hours of supervised counseling experience do you have?” This measure was added because it could offer more precision as an indicator of experience (e.g., 4th year graduate students in different programs may accrue substantially different numbers of clinical hours). Procedure Supervisees were invited to participate in a confidential study investigating how they “use supervision and efficacy beliefs when working with difficult clients.” They were also informed that once they completed the survey they would be eligible to enroll in a drawing that would provide them with a one in twenty chance of winning a $20 gift certificate to 20 Amazon.com. Two hundred twenty seven training directors and 15 UMD alumnae working at counseling and clinical psychology programs listed in the APA program directory received a personalized request to share a survey link with trainees in their programs. Upon entering the web-based survey page, housed on Qualtrics, participants first read and endorsed the online consent form before being directed to the actual survey. Participants completed the survey through an encrypted Internet server. The survey itself was structured in the following order: self-efficacy items, first half of the working alliance items, RISE items, second half of the working alliance items, other-efficacy items, and demographic items. Working alliance items were used to create space between each efficacy measure to help ensure that participants did not get confused about the rating perspective for each set of items. Participants who declined to participate were directed to a page thanking them for their time. No participants declined to take the survey, but twenty six agreed to participate and then did not respond to any items. After participants completed the survey they were provided with a link that redirected them to a separate survey where they were asked to provide their email address if they wanted to enter the drawing. 21 Results Preliminary Analyses I observed that 3% of the data (apart from the demographic questions) were missing and the results of the MCAR test (Little, 1988) indicated that these data were missing completely at random (χ²=173.29, df =172, p = .46). In order to retain the most data, missing scores were replaced using the estimation maximization algorithm in SPSS 22. All values were z- transformed. Analyses of variance (ANOVAs) were conducted for the dependent variable of counseling self-efficacy to examine whether it varied as a function of the categorical demographic variables. These variables included type of program (i.e., counseling, clinical, or other), type of degree (i.e., PhD, PsyD, or other), whether the supervisee was from the US or an international student, whether or not the supervisee worked with more than one supervisor, supervisor gender and race, supervisee gender and race, and frequency of supervision (i.e., never, less than once a month, once a month, 2-3 times a month, once a week, 2-3 times a week, and daily). The impact of whether the supervisor and supervisee identified as the same ethnicity or gender was also assessed by creating dichotomous yes/no variables. There were no significant findings (see Table 1). 22 Table 1. Analysis of Variance (ANOVA) Between Counseling Self-Efficacy and Categorical Variables of Interest Variable SS Df MS F p η² Supervisee gender 1.371 2 .685 .400 .671 .004 Supervisee race 10.520 7 1.503 .888 .517 .028 Supervisor gender .285 2 .142 .082 .921 .000 Supervisor race 11.452 6 1.909 1.124 .349 .030 Supervisee-supervisor gender match (i.e., same gender or different gender) .549 1 .594 .346 .557 .002 Supervisee-supervisor race match (i.e., same race or different race) .754 1 .754 .446 .505 .002 Type of program 6.817 2 3.408 2.014 .136 .018 Type of degree 3.783 3 1.261 .736 .532 .010 U.S. or international student .656 1 .656 .384 .536 .002 More than one supervisor (i.e., yes or no) .042 1 .042 .025 .875 .000 Frequency of supervision 5.223 5 1.045 .608 .694 .014 Note. N = 226-228 *p < .05. Means, standard deviations, intercorrelations, and reliability estimates were calculated for all of the measured variables. In Table 2 it can be seen that the variables were significantly correlated with one another in the expected direction, with some exceptions. Surprisingly, client difficulty correlated positively with RISE, years of experience, and hours of supervised experience and did not correlate with counseling self-efficacy or other-efficacy. This means that participants who reported working with a more difficult, lower functioning client also reported having more experience and more positive RISE beliefs. Client difficulty did not appear to relate 23 to how capable supervisees saw themselves or their supervisors in working with the client. Years of experience also correlated significantly and positively with counseling self-efficacy and RISE but did not correlate with other-efficacy or supervisory working alliance. This suggests that years of experience does not necessarily relate to how supervisees perceive the ability of, or their relationship with, their supervisors. Hours of supervised counseling experience correlated positively with client difficulty and years of experience, but did not correlate with any of the efficacy variables and was dropped from further analysis. There were also some significant correlations that were not expected. For instance, RISE was not expected to correlate significantly positively with client difficulty. Supervisees who reported working with more difficult clients also reported more positive RISE beliefs. One possible explanation for this finding is that when supervisees find a client challenging to work with, they may be more likely to talk about that client in supervision (Hill, Lent, Morrison, Pinto- Coelho, Jackson, & Kivlighan, in press). The supervisor may normalize reactions to that client (validate how difficult the client is to work with), which may then help the supervisee to believe that the supervisor thinks they are doing a good job. Previous research has suggested that trainees respond positively to supervisors’ normalizing difficult reactions to clients (Ladany, O’Brien, Hill, Melincoff, Knox, & Petersen, 1997). Another unexpected significant correlation was between other-efficacy and self-efficacy. Supervisees who reported having more confidence in their supervisors’ counseling ability also reported having more confidence in their own counseling ability. This may reflect some level of identification with the supervisor (e.g., “if my supervisor is good then, as their supervisee, I must be good, too”) or the effects of modeling or instruction (i.e., the supervisor modeling or explaining counseling behaviors that may be helpful to use with the client). 24 Table 2. Means, Standard Deviations, Correlations, and Internal Consistency Reliabilities Counseling Self-Efficacy RISE Other- efficacy Supervisory Working Alliance Client Difficulty Years of Experience Supervised Hours Counseling Self-Efficacy (.92) RISE .57* (.96) Other- Efficacy .29* .55* (.97) Supervisory Working Alliance .31* .58* .70* (.94) Client Difficulty .08 .15* -.06 .08 -- Years of Experience .25* .20* -.03 .09 .17* -- Supervised Hours .11 .12 -.08 .06 .16* .43* -- Mean 5.50 6.76 7.56 5.66 49.05 3.26 506.87 SD 1.30 1.23 1.36 .91 15.31 2.17 591.18 Note. N = 240. RISE = Relation-Inferred Self-Efficacy. Reliabilities are on the diagonal. *p < .05. Because some of the correlations were large (e.g., for other-efficacy and working alliance, r = .70) and because the other-efficacy and RISE measures were created by altering the self-efficacy measure, an exploratory factor analysis with principal axis factoring was conducted to determine the underlying factor structure. In the factor analysis, I retained items that loaded at .40 or above on their primary factor and that did not cross-load greatly on two or more factors (difference of > .10 in loadings between primary and secondary factors). The Kaiser-Meyer- Olkin (KMO) index of .95 and Bartlett’s test (χ² [1176] = 10617.85, p <.05]) provided support for the factorability of the data. Initial eigenvalues indicated that the first two factors explained 41% and 12% of the variance respectively. The third factor explained 6% of the variance and 25 fourth factor explained 5%. The fifth and six factors had eigenvalues just over one and explained 3% and 2% of the variance, respectively. Solutions for three, four, five, and six factors were examined using principal axis factoring and oblimin rotation. The four factor solution, which explained 64% of the variance, was deemed most plausible because the more complex solutions did not produce primary loadings above .40 on the fifth or sixth factors. Furthermore, under the four-factor structure no items exceeded the cross-loading criterion and all items had a factor loading of .40 or greater, so all items were retained. In Table 3 it can be seen that items loaded on their expected factors. This suggests that counseling self-efficacy, RISE, other-efficacy, and working alliance represent distinct though related factors. Table 3. Variable Items and Pattern Matrix Factor Loadings Factor Scale M SD 1 2 3 4 Counseling Self-Efficacy How confident are you in your ability to help your most difficult client to understand his or her thoughts, feelings, and actions? 5.29 1.72 .85 .10 .10 -.05 How confident are you in your ability to know what to do or say next after your most difficult client talks? 5.39 1.73 .72 -.09 -.10 .05 How confident are you in your ability to help your most difficult client to talk about his or her concerns at a deep level? 5.26 1.94 .75 -.04 .08 -.03 How confident are you in your ability to build a clear conceptualization of your most difficult client and his or her counseling issues? 6.15 1.68 .54 -.13 -.05 .04 How confident are you in your ability to help your most difficult client to explore his or her thoughts, feelings, and actions? 5.70 1.72 .78 .02 .11 -.02 How confident are you in your ability to respond with the best helping skill, depending on what your most difficult client needs at a given moment? 5.43 1.55 .71 -.14 -.10 .07 How confident are you in your ability to help your 5.42 1.73 .70 .08 .07 .10 26 most difficult client to set realistic counseling goals? How confident are you in your ability to keep sessions on track and focused with your most difficult client? 5.15 1.76 .61 -.10 .03 -.09 How confident are you in your ability to remain aware of your intentions (i.e., the purposes of your interventions) during sessions with your most difficult client? 6.00 1.63 .46 -.26 -.13 .11 How confident are you in your ability to help your most difficult client to decide what actions to take regarding his or her problems? 5.15 1.74 .81 .00 -.05 .00 Relation-Inferred Self-Efficacy How confident is your supervisor in your ability to help your most difficult client to understand his or her thoughts, feelings, and actions? 6.78 1.38 .18 -.68 .24 -.01 How confident is your supervisor in your ability to know what to do or say next after your most difficult client talks? 6.78 1.41 .00 -.81 .07 .09 How confident is your supervisor in your ability to help your most difficult client to talk about his or her concerns at a deep level? 6.72 1.48 .11 -.77 .03 .05 How confident is your supervisor in your ability to build a clear conceptualization of your most difficult client and his or her counseling issues? 6.93 1.48 .08 -.69 .01 0 .13 How confident is your supervisor in your ability to help your most difficult client to explore his or her thoughts, feelings, and actions? 6.86 1.43 .06 -.79 .19 -.01 How confident is your supervisor in your ability to respond with the best helping skill, depending on what your most difficult client needs at a given moment? 6.75 1.40 .00 -.84 .04 .04 How confident is your supervisor in your ability to help your most difficult client to set realistic counseling goals? 6.83 1.35 .06 -.73 .15 .04 27 How confident is your supervisor in your ability to keep sessions on track and focused with your most difficult client? 6.53 1.42 .10 -.64 .14 .09 How confident is your supervisor in your ability to remain aware of your intentions (i.e., the purposes of your interventions) during sessions with your most difficult client? 6.77 1.42 .09 -.75 .02 .12 -How confident is your supervisor in your ability to help your most difficult client to decide what actions to take regarding his or her problems? 6.69 1.37 .01 -.77 .12 -.09 Other-Efficacy How confident are you in your supervisor’s ability to help your most difficult client to understand his or her thoughts, feelings, and actions? 7.44 1.63 .05 -.07 .86 .05 How confident are you in your supervisor’s ability to know what to do or say next after your most difficult client talks? 7.70 1.43 -.02 -.11 .83 .02 How confident are you in your supervisor’s ability to help your most difficult client to talk about his or her concerns at a deep level? 7.42 1.63 .02 -.14 .84 -.04 How confident are you in your supervisor’s ability to build a clear conceptualization of your most difficult client and his or her counseling issues? 7.77 1.42 -.04 -.05 .71 .15 How confident are you in your supervisor’s ability to help your most difficult client to explore his or her thoughts, feelings, and actions? 7.56 1.51 .04 -.01 .82 .09 How confident are you in your supervisor’s ability to respond with the best helping skill, depending on what your most difficult client needs at a given moment? 7.62 1.48 -.01 -.15 .82 .06 How confident are you in your supervisor’s ability to help your most difficult client to set realistic counseling goals? 7.55 1.62 .10 -.03 .78 .08 How confident are you in your supervisor’s ability to keep sessions on track and focused with your most 7.42 1.58 -.04 -.12 .73 .02 28 difficult client? How confident are you in your supervisor’s ability to remain aware of their intentions (i.e., the purposes of their interventions) during sessions with your most difficult client? 7.72 1.52 .00 -.01 .59 .33 How confident are you in your supervisor’s ability to help your most difficult client to decide what actions to take regarding his or her problems? 7.37 1.64 .08 -.05 .77 .10 Working Alliance I feel comfortable working with my supervisor. 6.20 1.10 -.06 -.08 .02 .80 My supervisor welcomes my explanations about the client’s behavior. 6.33 .98 .02 -.14 -.06 .73 My supervisor makes the effort to understand me. 6.03 1.24 -.17 -.16 .06 .79 My supervisor encourages me to talk about my work with clients in ways that are comfortable to me. 6.00 1.19 -.08 -.19 .02 .71 My supervisor is tactful when commenting about my performance. 6.03 1.26 .00 .03 .09 .69 My supervisor encourages me to formulate my own interventions with the client. 5.80 1.14 .15 -.02 -.13 .69 My supervisor helps me talk freely in our sessions. 6.08 1.13 .02 -.10 -.05 .82 My supervisor stays in tune with me during supervision. 5.85 1.31 -.03 -.01 .09 .75 I understand client behavior and treatment technique similarly to the way my supervisor does. 5.30 1.15 .13 .09 .03 .67 I feel free to mention to my supervisor any troublesome feelings I might have about him/her. 4.87 1.83 .08 .01 -.03 .65 My supervisor treats me like a colleague in our supervisory sessions. 5.86 1.28 -.11 -.26 .00 .55 In supervision, I am more curious than anxious when discussing my difficulties with clients. 5.72 1.48 -.02 -.19 -.15 .52 29 In supervision, my supervisor places a high priority on our understanding the client’s perspective. 5.55 1.33 .06 -.04 .12 .56 My supervisor encourages me to take time to understand what the client is saying and doing. 5.85 1.19 -.02 .02 .19 .57 My supervisor’s style is to carefully and systematically consider the material I bring to supervision. 4.99 1.54 .00 .12 .14 .60 When correcting my errors with a client, my supervisor offers alternative ways of intervening with the client. 6.00 1.18 .02 .11 .17 .56 My supervisor helps me to work within a specific treatment plan with my clients. 5.11 1.45 .04 .05 .17 .41 My supervisor helps me stay on track during our meetings. 5.13 1.47 .07 .13 .15 .49 I work with my supervisor on specific goals in the supervisory session. 4.90 1.55 -.02 -.01 .10 .51 Testing for Main Effects and Moderation Hierarchical regression analyses were conducted using SPSS 22 to test hypotheses 1 through 5. All variables were standardized to control for possible multicollinearity (Aiken & West, 1991). In order to test hypotheses one through 3, years of experience was entered as the first step in the regression. Results, summarized in Table 4, show that years of experience significantly predicted self-efficacy (β= .25, p<.05) and accounted for 6% of the variance, providing support for hypothesis 1. In Step 2, RISE was entered into the regression equation and also significantly predicted self-efficacy, accounting for an additional 28% of the variance in self-efficacy (β= .54, p <. 05), providing support for hypothesis 2. Together years of experience and RISE accounted for 35% of the variance in self-efficacy. In Step 3, the interaction term of RISE x Years of experience was entered but was not a significant predictor, β= -.02, p>.05; ΔR² 30 = .00, ΔF (1, 236) = .09, p>.05, failing to support the hypothesis that the relationship between RISE and counseling self-efficacy would be moderated by years of counseling experience (Hypothesis 3). Table 4. Hierarchical Multiple Regression Analysis Testing the Moderating Effect of Years of Experience on the Relationship between RISE and Counseling Self-Efficacy Step/ variable entered R² Adjusted R² ΔR² ΔF B SE β t p VIF Step1 .064 .060 .064* 16.270* Years .253 .063 .253* 4.034 .000 1.00 Step 2 .345 .339 .281* 101.456* Years .146 .054 .146* 2.730 .007 1.040 RISE .054 .054 .540* 10.730 .000 1.040 Step 3 .345 .336 .000 .090 Years .151 .056 .151* 2.696 .007 1.135 RISE .540 .054 .540* 10.035 .000 1.042 RISE x Years -.018 .061 -.016 -.300 .765 1.091 Note. N = 240. RISE = Relation-Inferred Self-Efficacy. *p < .05 To test the hypothesis that other-efficacy will moderate the relationship between RISE and counseling self-efficacy (Hypothesis 4), in Step 1, years of experience was entered as a control variable. In Step 2, RISE and other-efficacy were both entered into the regression equation but only RISE had a significant main effect, β= .54, p<.05; other-efficacy did not, β = - .01, p > 05. Together, experience, RISE, and other-efficacy accounted for 35% of the variance in self-efficacy. In Step 3, the interaction term of RISE x Other-efficacy was entered and explained 31 significant additional variance in self-efficacy, β= .13, p > .05; ΔR² = .01, ΔF (1, 235) = 4.41, p<.05. Results are presented in Table 5. Table 5. Hierarchical Multiple Regression Analysis Testing the Moderating Effect of Other-Efficacy on the Relationship between RISE and Counseling Self-Efficacy Step/ variable entered R² Adjusted R² ΔR² ΔF B SE β t p VIF Step1 .064 .060 .064* 16.270* Years .253 .063 .253* 4.034 .000 1.000 Step 2 .345 .336 .281* 50.518* Years .146 .055 .146* 2.670 .008 1.073 RISE .543 .065 .543* 8.296 .000 1.543 Other- Efficacy -.005 .064 -.005 -.074 .941 1.485 Step 3 .357 .346 .012* 4.406* Years .148 .054 .148* 2.724 .007 1.074 RISE .567 .066 .567* 8.594 .000 1.591 Other- Efficacy .054 .070 .055 .780 .436 1.774 RISE x Other- Efficacy .079 .038 .133* 2.099 .037 1.469 Note. N = 240. RISE = Relation-Inferred Self-Efficacy. *p < .05 Next, I used Interaction (Version 1.7.2211; Soper, 2011) to test the simple slopes for the association between RISE and self-efficacy at low (-1 SD), moderate (mean), and high (+1SD) levels of other-efficacy. Each of the simple slopes tests revealed a significant positive association between RISE and self-efficacy, but RISE was more strongly related to self-efficacy when other- efficacy was high (β= .65, p<.05) than when other-efficacy was low (β= .49, p<.05). This finding 32 indicates that the relationship between RISE and self-efficacy is stronger when supervisees believe their supervisors are more skilled as counselors and weaker when supervisees believe their supervisors are less skilled as counselors, providing support for hypothesis 4. See Figure 5. Note. ZTSE = Counseling Self-Efficacy; ZTRISE = Relation-Inferred Self-Efficacy; ZTOE = Other-Efficacy. Figure 5. Relationships between RISE and Self-Efficacy at Low, Medium, and High Levels of Other-Efficacy. To test hypothesis 5, in Step 1, years of experience was entered as a control variable. In Step 2, RISE and client difficulty were both entered into the regression equation but only RISE was a significant predictor of self-efficacy, β= .54, p<.05); client difficulty was not, β = .03, p > 05. Experience, RISE, and client difficulty jointly accounted for 35% of the variance in self- efficacy. In Step 3, the interaction term of RISE x client difficulty was entered but was not a significant predictor, β = -.06, p>.05; ΔR² = .01, ΔF (1, 235) = .1.67, p>.05. These results failed 33 to support the hypothesis that client difficulty would moderate the relationship between RISE and counseling self-efficacy (Hypothesis 5). Results presented in Table 6. Table 6. Hierarchical Multiple Regression Analysis Testing the Moderating Effect of Client Difficulty on the Relationship between RISE and Counseling Self-Efficacy Step/ variable entered R² Adjusted R² ΔR² ΔF B SE β t p VIF Step1 .064 .060 .064* 16.270* Years .253 .063 .253* 4.034 .000 1.000 Step 2 .345 .337 .281* 50.714* Years .151 .054 .151* 2.774 .006 1.062 RISE .544 .054 .544* 10.048 .000 1.056 Client difficulty -.028 .054 -.028 -.522 .597 1.044 Step 3 .350 .339 .005 1.673 Years .146 .054 .146* 2.680 .008 1.067 RISE .561 .056 .561* 10.081 .000 1.119 Client difficulty -.028 .054 -.028 -.517 .605 1.044 RISE x Client difficulty .057 .044 .070 1.293 .197 1.062 Note. N = 240. RISE = Relation-Inferred Self-Efficacy. For Client Difficulty, higher scores indicate less difficult clients. *p < .05 Testing for Mediation Regression analysis and bootstrapping procedures were conducted using the PROCESS macro for SPSS (Hayes, 2012) to test hypothesis 6. Results indicated that working alliance was a significant predictor of RISE, β = .58, SE = .05, p <.05; and that RISE was a significant predictor of self-efficacy, β = .59, SE = .07, p <.05. Working alliance was no longer a significant 34 predictor of self-efficacy after controlling for the mediator, RISE, β = -.03, SE = .07, p > .05, which is consistent with full mediation. Approximately 32% of the variance in self-efficacy was accounted for by the predictors (R² = .32). The indirect effect was tested using a bootstrap estimation approach with 1000 samples (Shrout & Bolger, 2002). These results indicate that the indirect coefficient was significant, β = .34, SE = .05, 95% CI = .24, .46, providing support for the hypothesis that RISE would fully mediate the relationship between supervisory working alliance and counseling self-efficacy. 35 Discussion This study was aimed at exploring (a) the relation of RISE beliefs (i.e., supervisees’ beliefs about how their supervisor views their counseling abilities) to supervisees’ own sense of counseling self-efficacy; (b) whether the RISE/counseling self-efficacy relationship was moderated by supervisees’ amount of counseling experience, other-efficacy beliefs, or client difficulty; and (c) whether RISE mediated the relationship between the supervisory working alliance and counseling self-efficacy. I will discuss the findings related to each of these objectives in this section. As hypothesized, supervisee relation-inferred self-efficacy (RISE) predicted supervisee counseling self-efficacy over and above years of counseling experience. This suggests that supervisee beliefs about how their supervisor views the supervisee’s counseling abilities helped inform how supervisees saw their own counseling skill when working with a specific client, even when supervisee experience level was controlled. This finding is consistent with the tripartite model of relational efficacy beliefs (Lent and Lopez, 2002) as well as with previous findings examining RISE and self-efficacy in other domains (Jackson et al., 2007, 2012a, 2013; Morrison & Lent, 2014). When supervisees believed that their clinical supervisors thinks they are capable of working well with a particular client, they were more likely to see themselves as capable of working well with that client, regardless of how many years of counseling experience they had. Other-efficacy was found to moderate the relationship between RISE and counseling self- efficacy such that when other-efficacy was high, RISE and counseling-self efficacy were more strongly related than when other-efficacy was low. Furthermore, the graphed relationship displayed a cross-over interaction such that supervisees who reported low RISE and high other- efficacy beliefs indicated having lower mean levels of counseling self-efficacy than supervisees 36 who reported low RISE and low other-efficacy beliefs. In contrast, supervisees who reported high RISE and high other-efficacy reported higher mean levels of counseling self-efficacy than supervisees who reported having high RISE and low other-efficacy beliefs. This provides support for the argument that supervisees’ beliefs about their supervisors’ perceptions of their counseling ability were more likely to affect the supervisee’s own sense of counseling ability when supervisees saw their supervisor as skilled in counseling. It is understandable that if a supervisor lacks credibility as a counseling efficacy source, because they are perceived by the supervisee to have limited counseling skill, then the supervisee is unlikely to use what they think the supervisor thinks of their counseling skill level to inform their perceptions of their own skill level. It is also possible that viewing one’s supervisor as having limited counseling skill may function as a protective factor when one believes that their supervisor does not see them as an efficacious therapist. Interestingly, neither years of experience nor level of client difficulty moderated the relationship between RISE and counseling self-efficacy. It appears that although supervisees with more counseling experience were more likely to see themselves as efficacious counselors, RISE was equally useful in predicting counseling self-efficacy, regardless of how little or how much counseling experience a supervisee had. These findings also suggest that RISE is equally predictive of counseling self-efficacy irrespective of how challenging the client is to work with. While it is possible that client difficulty may not influence the relationship between RISE and counseling self-efficacy, another possibility is that the operationalization and measurement of client difficulty contributed to non-significant findings. I used a measure of client functioning (GAF) to estimate how difficult a client was to work with. In reality, client difficulty is more complex and subjective than just the level of client functioning. For example, a client may be 37 relatively high functioning but still difficult for a supervisee to sit with, possibly because of the defenses that the client employs or because the supervisee experiences strong personal reactions to what the client shares. On the other hand, a client may be lower functioning but the supervisee may be familiar with their presenting issue and therefore not consider them difficult to work with. In either case, the GAF score would only reflect client functioning and would fail to assess the supervisee’s subjective experience of how difficult they find working with the client to be. Currently, no straightforward measure of client difficulty appears to exist. The construct might be assessed in future research simply by asking supervisees to rate how easy/difficult they find working with their client to be, either on a global dimension or along multiple dimensions (e.g., presenting problem, interpersonal style, psychological-mindedness, countertransference). Finally, RISE was found to fully mediate the relationship between supervisory working alliance and counseling self-efficacy. This is consistent with previous findings looking at the role RISE in advising relationships (Morrison & Lent, 2014). Supervisees who reported experiencing a stronger working alliance with their supervisor were more likely to perceive their supervisor as having confidence in their counseling ability and, subsequently, were more likely to have more confidence in their own counseling ability. Similar to Morrison and Lent’s (2014) analysis regarding advising relationships, when the supervisory working alliance is strong, it may signal to supervisees that their supervisor believes in their counseling ability. That is, from the supervisee’s perspective, supervisors may be seen as more committed to forging a strong working alliance when they see greater potential in the supervisee. The supervisees’ RISE beliefs, in turn, are likely to boost the supervisees’ view of themselves as capable counselors. Likewise, weaker working alliances may be interpreted as implying less faith in the supervisee’s capabilities (i.e., lower RISE beliefs) which, in turn, may weaken counseling self-efficacy. There 38 have been quite a few studies looking at the importance of a positive supervisory working alliance (see Watkins, 2011 for a review) but findings on the relationship between the supervisory working alliance and counseling self-efficacy have been mixed (Hanson, 2007; Ladany et al., 1999; Marmarosh et al., 2013). The results of this study support both the presence of a relationship between the working alliance and counseling self-efficacy and the mechanism through which they relate (i.e., RISE beliefs). Implications and Future Research The current findings offer a number of implications for training and future research. In combination with the original tripartite model and findings from studies in other domains (Lent & Lopez, 2002; Morrison & Lent, 2014), I used these results to create a conceptual model of counseling efficacy beliefs that includes perceptions about both the supervisor and client (see Figure 6). In this model I include a path from other efficacy to both supervisory working alliance (path A) and RISE beliefs (path B) based on the findings of this study as well as Morrison and Lent (2014) who found that other efficacy predicted advisory working alliance. Supervisory working alliance has a path to RISE (path C) and RISE then predicts counseling self-efficacy (path D). I have included paths from client difficulty to both RISE (path E) and counseling self- efficacy beliefs (path F) even though the path to self-efficacy beliefs was not supported in this study. This is because I suspect that this path might be supported if client difficulty were to be operationalized more accurately. I also included paths from experience to both RISE (path G) and self-efficacy (path H), which both were supported in this study. Finally, I included paths from the interaction variables of RISE x other efficacy (path I), RISE x client difficulty (path J), and RISE x experience (path K). Despite not having been supported in this study there is a strong theoretical argument for the role of both client difficulty and supervisee experience as 39 moderators of the relationship between RISE and counseling self-efficacy (Lent & Lopez, 2002). Furthermore, I suspect that if client difficulty had been measured differently then moderation may have been supported. Therefore, I have both potential moderators in the path model to be tested. 40 K RISE X Other efficacy RISE X Client difficulty Other efficacy Counseling self- efficacy RISE Supervisory working alliance Client difficulty Experience H A B C E D G F Figure 6. Hypothesized path model of counseling efficacy beliefs. J I RISE X Experience 41 The results of this study support the presence of a relational component in the development of self-efficacy generally, and counseling self-efficacy specifically. Supervisees’ beliefs about their supervisors’ perceptions of them consistently predicted how they viewed themselves. It would be interesting to see how supervisee perceptions about the beliefs of other individuals involved in counseling (e.g., training directors, peers) also relate to how they see their own ability. Interestingly, in a study of the use of client feedback in psychotherapy training, researchers found that when client feedback was included in supervision, trainee’s reports of self-efficacy did not increase, but they were more strongly related to client outcomes. This suggests that the feedback helped trainees to become more accurate in their assessment of their own skills (Reese et al., 2009). The supervision relationship appears to directly relate to relational beliefs via the working alliance. In addition, supervisee perceptions about how supervisors see their ability relates to how they see their own ability. Therefore, clinical supervision appears to provide a context in which counseling self-efficacy can be fostered. Not only should supervisors attend to the working alliance, they may also foster optimal counseling self-efficacy by attending to supervisee RISE beliefs. This might include monitoring both the verbal and non-verbal feedback they are providing to the supervisee. Previous research has suggested that supervisors tend to give more difficult feedback indirectly (Hoffman, Hill, Holmes, & Freitas, 2005) and that counseling self-efficacy shifts in the direction of the feedback provided (Daniels & Larson, 2001). In addition, supervisors might also explicitly ask supervisees not only how they think they are doing, but how they think the supervisor thinks they are 42 doing. Openness and immediacy have been linked to improved self-efficacy in past research (e.g., Knox, Edwards, Hess, & Hill, 2011). Using this type of immediacy with the supervisee not only allows for a discussion of the supervision relationship but also provides an opportunity to correct misperceptions that might exist. Investigating what cues supervisees attend to when forming perceptions about supervisor beliefs would be a beneficial direction for future research. Another direction for future research would be to look at the relational beliefs of both the supervisor and the supervisee by collecting dyadic data. For instance, this study assessed supervisees’ beliefs about how the supervisor viewed his or her counseling ability, but it would be particularly interesting to measure the supervisor’s actual (other-efficacy) beliefs about the supervisee’s ability and compare it to the supervisee’s RISE beliefs. It is easy to see how a supervisor’s beliefs about supervisee counseling ability could be communicated both directly through formal evaluations as well as less formally through interaction with the supervisee. How closely supervisor’s actual beliefs align with the supervisee’s perceptions of supervisor’s beliefs and what contributes to distortion in these perceptions may provide a valuable window on both the development of counseling self-efficacy as well as the process of supervision. Although this study focused on a relationship specific source of counseling self-efficacy, there is no research to date looking at cross-relational sources of counseling self-efficacy such as those suggested by Bandura (1997). It would be useful to investigate the predictive utility of the four primary experiential sources (i.e., performance accomplishments, vicarious learning, physiological and affective 43 reactions, and social persuasion) relative to counseling self-efficacy and to determine how these sources interrelate with the relationship-specific sources. This may allow an even more nuanced understanding of how counseling self-efficacy develops in trainees. Because of the mixed experience level of the participants, only counseling self-efficacy perceptions that focused on session management were used. It would be interesting to see if the results replicate when examining other kinds of counseling self-efficacy, such as counseling challenges (Lent et al., 2003), career counseling self- efficacy (Heppner et al., 1998), or multicultural counseling self-efficacy (Sheu et al. , 2012). Researchers looking at these kinds of counseling self-efficacy may gain a better understanding of how important relationships contribute to the development of these beliefs if they include a measure of RISE. One final implication relates to the recruitment strategy used to collect the data. Training directors and graduate students in helping fields are inundated with research participation requests and researchers sampling this population often struggle to get enough participants. This study engaged a number of strategies that may have helped in gathering data from this difficult to access population. First, personalized email requests were sent to each training director. Whenever possible, former alumnae of the researcher’s home institution who were in faculty positions were asked to send out the request in order to add legitimacy to the research request. One follow up email was sent two weeks after the first email. Finally, a chance at winning one of ten gift certificates was offered and the statistical probability that someone might win (one in twenty chance) was included in the recruitment email. 44 While this involved a more deliberate and time intensive approach to collecting the data, the results supported the effort. Limitations There are a number of limitations in the current study. First, the cross- sectional design cannot be used to establish causation. This design also does not allow for a test of bidirectional relations. For example, while I tested supervisory working alliance as a predictor of counseling self-efficacy, as Morrison and Lent (2014) point out, a reverse path is also theoretically possible. Similarly, without longitudinal data, the possibility that RISE mediates the relationship from counseling self-efficacy to the working alliance, instead of RISE mediating the relation of the working alliance to counseling self-efficacy, cannot be ruled out. In order to more adequately study the complex relationships among efficacy beliefs, longitudinal and experimental methods are needed. In addition, using regression to look at select relationships is a good first step, but future research would benefit from testing the full set of variables using a more sophisticated technique such as structural equation modeling (SEM). Second, the current study only examines the perspective of the supervisee. Supervisees’ evaluations of their own ability as well as how their supervisors see them are not necessarily accurate (Urbani, Smith, Maddux, Smaby, Torres-Rivera, & Crews, 2002), and there is no way to determine accuracy without collecting data apart from the supervisee. Lent and Lopez’s original tripartite model of efficacy beliefs incorporated the beliefs of both members of a dyad, allowing for a comparison between perceptions of beliefs and actual beliefs. Having the supervisor’s 45 perspective on the ability of the supervisee (i.e., the supervisor’s other efficacy) would provide a way of estimating the accuracy of the supervisee’s RISE perceptions. A logical next step would be to examine the perspectives of both supervisor and supervisee and see how they interrelate. Third, this study measured client-specific counseling self-efficacy and only considered the difficulty of one client the supervisee had been working with. The rationale behind this decision was that because RISE is specific to a particular relationship (i.e., supervision) and particular point in time (i.e., the present), it would predict counseling self-efficacy best when the latter was assessed at a similar level of specificity (i.e., principle of compatibility; Azjen, 2005). Lent, Hackett, and Brown (1998) suggested that client-specific counseling self-efficacy might be a better way to evaluate counseling self-efficacy within the context of a particular counseling relationship. The disadvantage of this approach is that the participants reported working with an average of 8 clients and there was no measure of how easy or difficult the rest of the participants’ clients were to work with. Previous research looking at the relationship between general and client-specific counseling self- efficacy found that general counseling self-efficacy related moderately to strongly with client-specific counseling self-efficacy over the course of four counseling sessions (Lent et al., 2006). This relationship between general and client-specific counseling self-efficacy was not captured in this study. An example of why this may be problematic is because two participants might have one equally difficult client but the rest of one participant’s case load could be significantly more difficult than the other’s. In this case it is possible that the rest of the case load may determine how 46 each participant rates both their general and client-specific self-efficacy. One way to address this would be to measure both general and client-specific counseling self- efficacy and see whether they differentially predict client-specific client difficulty (“How difficult would you rate your most difficult client?”) versus a more global evaluation of client difficulty (e.g, “How difficult would you rate your total client load?”). Fourth, I suspect that the measure I used to assess client difficulty only measured client functioning and failed to capture the subjective experience of the supervisee. A client’s level of functioning may relate to how difficult the supervisee perceives that client to be, but there may also be other factors to consider such as the amount of countertransference the supervisee experiences with the client, as well as how much experience or familiarity the supervisee has with that client’s particular concern. Future research might focus on understanding how supervisees determine whether a client is difficult to work with. Future research might also take a more multifaceted approach to measuring client difficulty. On the other hand, including a single item asking participants to indicate how difficult their client is to work with may be sufficient. Finally, this study only looked at counseling self-efficacy related to session management and used an altered version of the same measure to assess the three types of efficacy beliefs. Behaviors that participants were asked to rate were identical across measures; only the perspective of the participant (i.e., their beliefs about themselves, their beliefs about their supervisor’s perceptions, their beliefs about their supervisors) was varied. This may have created artificially inflated relations among 47 the relational efficacy variables. Despite this, all items loaded on to their expected factors, suggesting that they were in fact measuring distinct constructs. Future research might employ different altered counseling self-efficacy instruments to measure RISE and other-efficacy in order to minimize the possibility of artificially inflated relationships among the three kinds of efficacy beliefs. Conclusion Despite the study’s limitations, the current findings offer new insight into the role of efficacy beliefs in the context of the supervision relationship. Similar to what has been found in other contexts, RISE and other-efficacy may be important components in the development of counseling self-efficacy. The supervisor, as the one who works closest with the supervisee, may be in a unique position to help foster strong counseling self-efficacy beliefs, creating a more confident and competent supervisee. 48 Appendix A. Extended Literature Review The following literature review focuses on relational experiences hypothesized in the study as predictors of client-specific counseling self-efficacy. The relationship-specific source is relation-inferred self-efficacy (RISE). First, the definition of counseling self-efficacy and its relation to trainee outcomes will be discussed. Next, I will review conceptual and empirical writings on the tripartite model of efficacy beliefs as a foundation for studying relationship-specific sources of self-efficacy. This will be followed by a review of the empirical research on the relationship between supervisory working alliance and counseling self-efficacy. I will then briefly look at the empirical research on the relationship between counseling experience and self-efficacy. Finally, a summary will be provided. Counseling Self-Efficacy The concept of self-efficacy arose from Bandura’s early work on social cognitive theory (SCT; Bandura, 1986). He defined it as individuals’ beliefs about their ability to perform particular behaviors or sets of behaviors successfully. According to SCT, these beliefs play a key role in motivation and behavior, influencing whether an individual will attempt to perform an action, the amount of effort they will put into performing the action, their persistence in performing the action, and how successfully they will perform the action (Bandura, 1997). Lent et al. (1994) extended Bandura’s work by applying SCT to the career development process. Their theory extension focused initially on three aspects of career development: academic and career interest, choice, and performance. They 49 also incorporated contextual and personal variables, such as barriers and personality. Since its original formulation, many of the predictions of Social Cognitive Career Theory (SCCT) have received widespread support, including the relationship between self-efficacy and performance (e.g., Brown, Tramayne, Hoxha, Telander, Fan, & Lent, 2008). Larson (1998) attempted to extend SCT to the study of counselor development. In particular, Larson argued that counseling self-efficacy is the principal causal determinant of effective counseling and, as such, an important component of counselor training and performance. She defined counseling self- efficacy (CSE) as counselors’ beliefs regarding their ability to successfully perform counseling-related behaviors and navigate various clinical situations (Larson, 1998). Similar to what would be hypothesized by SCT and SCCT, the social cognitive model of counselor training (SCMCT) suggests that CSE affects how a counselor responds to particular situations, how much effort they expend, how persistent they are in the face of failure, and whether they take risks (Larson, 1998). SCMT assumes that counselors with higher counseling self-efficacy are more likely to set realistic counseling and supervision goals, to perceive their anxiety as a challenge, and to have self-aiding thoughts in counseling and supervision (Larson, 1998). In support, research has shown that counselors with higher counseling self-efficacy have more positive outcomes expectations, experience less distressing anxiety, and have more positive self-evaluations (see Larson & Daniels, 1998). Counseling self-efficacy and performance. The research on the relationship between counseling self-efficacy and performance has been less conclusive. In their 50 review of this research Larson and Daniels (1998) concluded that while there is some evidence that CSE relates positively to performance as rated by trained evaluators, when it comes to supervisor ratings the relationship is less clear. One possible explanation for this finding involves the varying and sometimes non-correspondent ways in which CSE and performance have been measured. The majority of the research on counseling self-efficacy has assessed general CSE. But Lent et al. (1998) point out that, in keeping with the principle of compatibility, it is sometimes more appropriate to examine counseling self-efficacy in narrower terms, specifically client- specific counseling self-efficacy. A mismatch between general counseling self- efficacy and performance with a specific client may account for part of the variability in findings. Sources of Self-Efficacy and the Tripartite Model Cross-relational sources of counseling self-efficacy refers to those learning experiences that occur outside of the context of a specific relationship, or more accurately, across all relationships. Bandura (1997) hypothesized that four types of experience serve as the primary sources of self-efficacy beliefs and that these sources varied in the strength of their influence. Enactive mastery experience, later termed performance accomplishments, was argued to be the most influential source under most conditions. Vicarious experience, also termed vicarious learning, was the second most influential, followed by verbal persuasion (also known as social persuasion) and physiological and affective states (Bandura, 1997). When Bandura formulated SCT, he did not focus explicitly on the development of self-efficacy regarding behaviors that are inherently relational in 51 nature (e.g., counseling); rather his focus was more on individual performance contexts (e.g., approaching a feared object). Lent and Lopez (2002) addressed this gap by extending SCT to the specific processes through which self-efficacy might develop and be maintained in close relationships. As a result, they created the tripartite model of relational efficacy beliefs, arguing for the presence of three separate but interconnecting forms of efficacy beliefs that arise within close relationships. These beliefs are separated into perceptions an individual has about their relationship partner’s ability to perform a particular action (i.e., other-efficacy), perceptions an individual has about the partner’s belief in the individual’s ability to perform a particular action (relation-inferred self-efficacy; RISE), and the perceptions an individual has about their own ability to perform a particular action (self-efficacy). Romantic relationships. There have been a limited of studies looking at the tripartite model and, interestingly, the majority of this research has been done in the context of physical activity (i.e., athletics, coaching, and physical activity classes). One of the earliest studies looking at relational beliefs examined romantic relationships (Lopez & Lent, 1991). Lopez and Lent (1991) surveyed the relational beliefs of 67 college students and then 3 months later followed up with 33 students to assess dyadic consensus, satisfaction, cohesion, and affectional expression using the Dyadic Adjustment Scale (DAS; Spanier, 1976). They found that the three efficacy beliefs were all strongly intercorrelated (r’s ranged from .63 to .84). Lopez and Lent (1991) also found that self-efficacy predicted dyadic adjustment and relationship satisfaction (β = .54 and .56, respectively), other-efficacy predicted dyadic adjustment and relationship satisfaction (β = .39 and .48, respectively), and RISE predicted 52 expected persistence (β = .49) over and above age, sex, and number of past relationships. Athlete dyads. Jackson et al. (2007, 2008) conducted two studies looking at relational efficacy beliefs in athlete dyads. In the first study, involving 60 athlete dyads in the UK, Jackson and colleagues (2007) investigated the relationships among both partners’ relational efficacy beliefs. They found that both other-efficacy and RISE predicted self-efficacy (B = .76 and .31, respectively). They also found that self-efficacy predicted commitment (B = .25) and other-efficacy predicted relationship satisfaction (B = .45). In the second study, Jackson and colleagues (2008) interviewed six international-level athlete dyads in the UK and content analyzed their responses. Participants were asked to write down the primary tasks required of them and their partners in their respective sports. They were then asked a series of questions regarding their level of efficacy beliefs (self-efficacy, other-efficacy, and RISE) and what they viewed as the antecedents and consequences of those beliefs. They found that RISE and other-efficacy were the most frequently cited antecedents to self- efficacy (15% and 13%, respectively), followed by past individual mastery achievements and physiological and emotional factors (9% and 7%, respectively). Past performance was the most frequently cited antecedent of other-efficacy (12%). Finally, verbal persuasion was the most frequently cited antecedent of RISE (13%), followed by self-efficacy and past mastery achievements (5% each). When it came to the consequences of efficacy beliefs, the most frequently cited outcome of self- efficacy was performance (8%), the most frequently cited consequence of other- 53 efficacy was affective responses (12%), followed by self-efficacy (10%), and the most frequently cited consequence of RISE was self-efficacy (19%). Athlete-coach dyads. Jackson, Knapp, and Beauchamp (2009) used the same interview format in a sample of 6 international level coach-athlete dyads in the UK. They found among athletes that RISE and verbal persuasion were the most frequently cited antecedents of self-efficacy (13% and 7%, respectively) and among coaches RISE was the second most frequently cited antecedent of self-efficacy, after experience (6% and 10%, respectively). They also found that verbal persuasion was the most frequently cited antecedent of RISE for both athletes and coaches (10% and 5%, respectively). In regard to consequences of self-efficacy, athletes cited performance and affective responses most frequently (4% and 4%, respectively), while coaches cited instruction followed by RISE (7% and 4%, respectively). For consequences of RISE, athletes and coaches both mentioned self-efficacy most frequently (9% and 4%, respectively). Jackson et al. (2010a, 2010b, 2011) conducted three more studies looking at relational efficacy beliefs in coach-athlete dyads. In the first study looking at 50 youth tennis athlete-coach dyads in the UK, Jackson and Beauchamp (2010a) investigated the relationships among both partners’ relational efficacy beliefs. They found that for athletes, self-efficacy, other-efficacy, and RISE were all strongly related to one another (r’s ranged from .48 to .65). In coaches, the only correlation that was not significant was between self-efficacy and other-efficacy (r = .21). Jackson and Beauchamp (2010a) also found that for both athletes and coaches self- efficacy predicted effort (B = .26), while other-efficacy predicted commitment, effort, 54 and satisfaction (B = .42, .47, and .37 respectively). Interestingly, RISE predicted increased commitment in coaches (B = .27) and decreased commitment in athletes (B = -.16). Jackson and Beauchamp (2010a) suggested one possible reason for this finding was that when athletes thought coaches were too confident in them they may have become complacent and less committed. In the second study, Jackson and colleagues (2010b) looked at 63 junior tennis athlete-coach dyads in the UK and found that self-efficacy predicted closeness (i.e., degree of liking, respect, and trust) in coaches (B = .52). They also found that other- efficacy was positively related to closeness and complementarity (i.e., inclusivity, responsiveness, and reciprocation) in athletes (B = .72 and .54, respectively) and RISE positively related to coach commitment (B = .46). In the final study, Jackson et al. (2011) performed a cluster analysis on 377 individual sports athletes in Australia to identify tripartite efficacy profiles in relationship to coaches. They found that self- efficacy, other-efficacy, and RISE were all significantly intercorrelated (r ranged from .54 to .67). Furthermore, they found that efficacy beliefs clustered in a concordant way, meaning that levels of self-efficacy, other-efficacy, and RISE tended to match and could be grouped into high, moderate, or low. In another study looking at relational beliefs in coaching dyads, Saville, Bray, Ginis, Cairney, Marinoff-Shupe, and Pettit (2014) conducted two qualitative studies using youth sport focus groups in Canada. In the first study, they interviewed 61 children enrolled in day camps; in the second study they interviewed 28 children enrolled in a community recreational sports program. In both studies they found that participants cited mastery experiences, social persuasion, and vicarious experiences 55 as antecedents of self-efficacy. They also found that general encouragement, efficacy building statements, instruction, focused interpersonal attention, expressiveness, and challenging/special opportunities were cited as sources of RISE. Student-instructor dyads. Jackson et al. (2012a, 2012b, 2013) conducted three studies looking at relational efficacy beliefs in students enrolled in physical activity classes. In a study of 516 Australian undergraduates, Jackson et al. (2012a) had students report their other-efficacy and RISE perceptions with respect to their instructor before class, and then report their self-efficacy, enjoyment, and effort after class. They also had an observer assess student achievement the following week. Using latent path analysis, they found that the path between other-efficacy and RISE was significantly correlated (β = .65) and that the paths from both RISE and other- efficacy to self-efficacy were positive and significant (β = .69 and .20, respectively). Furthermore, they found that self-efficacy mediated the relationships of both RISE and other-efficacy to the outcomes of achievement, effort, and enjoyment. In the second study, Jackson et al. (2012b) used Singaporean and Australian high school students to develop a measurement of self-efficacy, other-efficacy, and RISE and found that for participants in both countries the three relational efficacy beliefs were positively related to one another (r’s ranged from .49 to .72). In the final study, Jackson et al. (2013) investigated efficacy beliefs in English high school students using latent path analysis and found that the path between other-efficacy and RISE was significant (β = .68) and that the paths from both RISE and other-efficacy to self-efficacy were also significant (β = .59 and .28, respectively). Furthermore, 56 self-efficacy mediated the relationship of other-efficacy and RISE to exercise performance. Physical therapy dyads. In two final studies, Jackson, Dimmock, Taylor, and Hagger (2012c) looked at relational beliefs in exercise clients who were enrolled in a one-on-one aerobic exercise program and their physical therapists. In the first study they recruited 171 exercise clients and had their physical therapists rate only their engagement in exercise behavior. Using path analysis, they found that the three efficacy beliefs were positively intercorrelated (r’s ranged from .66 to .70). They also found significant paths from other-efficacy to relationship quality (β = .52), from self- efficacy to relationship quality (β = .26), and from RISE to relationship quality (β = .50). In the second study, Jackson et al. (2012c) recruited 68 dyads and looked at the efficacy beliefs of both the client and the physical therapists. They found that, for both therapists and clients, self-efficacy, other-efficacy and RISE beliefs were predictive of perceptions of relationship quality (β = .25, .31, and .31, respectively). Advising relationships. Morrison and Lent (2014) looked at the advising relationships in 274 doctoral students in a variety of academic fields to investigate the relationships among other-efficacy, RISE, research self-efficacy, the advisory working alliance, and research interest and productivity. Using structural equation modeling, they found significant paths from other-efficacy to the advisory working alliance (β = .41), advisory working alliance to RISE (β = .66), RISE to research self- efficacy (β = .53), and self-efficacy to research interest and productivity (β = .49 and .60, respectively). Furthermore, Morrison and Lent (2014) found that the advisory 57 working alliance fully mediated the path from other-efficacy to RISE and that RISE fully mediated the relation of the working alliance to research self-efficacy. Altogether, these studies suggest that the relational efficacy model offers explanatory utility in relationship dyads and groups. They also suggest that within the context of close relationships, RISE may exist as a relationship-specific source of self-efficacy information, and that other-efficacy may also play an important role. In a number of these studies, researchers have raised the possibility that other-efficacy may moderate the relationship between RISE and self-efficacy such that this relationship will be stronger when other-efficacy is high (e.g., Lent & Lopez, 2002; Morrison & Lent, 2014), but this has not been empirically tested. Lent and Lopez (2002) also suggest that the relationship between RISE and self-efficacy will be stronger when an individual is developing new skills, using existing skills in a new context, and reevaluating existing skills during a crisis or transition. However, these possibilities have also not been empirically tested as yet. Supervisory Working Alliance Clinical supervision involves a growth-promoting relationship between a supervisee and their supervisor that utilizes interpersonal processes such as mutual problem-solving, mentoring, instruction, evaluation, and role modeling of ethical practices (Falender & Shafranske, 2004). In their chapter review, Hill and Knox (2012) conclude that supervision appears to have an impact on supervisees, influencing awareness of others and self, motivation, autonomy, and self-efficacy, but that its impact on clients is less clear. They also state that the supervisory relationship, namely, the working alliance, may play a central part in how effective 58 supervision is, but that the mechanisms through which it works are unclear. The working alliance in supervision refers to the set of behaviors used interactively by supervisors and supervisees, to facilitate the supervisee’s learning (Efstation, Patton, & Cardash, 1990). Bordin (1983) argued that it consists of three factors, agreement on goals, agreement on tasks, and an affective bond. As Efstation et al. (1990) state, “Social influence occurs, we infer, through alliance building and maintaining activities performed by the participants” (p. 323). Findings on the relationship between the supervisory working alliance and counseling self-efficacy have been mixed but more recent findings tend to be supportive. Ladany, Ellis, and Friedlander (1999) looked at the relationship between supervisory working alliance and counseling self-efficacy in 107 counselor trainees using the Working Alliance Inventory – Trainee version (WAI-T; Bahrick, 1990) and the SEI (Friedlander & Snyder, 1983) at two time points roughly 8 weeks apart. Ladany et al. (1999) did not find a significant relationship between goals, tasks, bonds, and self-efficacy at either time point. They also did not find that change in goals, tasks, and bond predicted change in self-efficacy. Interestingly, they hypothesized that one possible reason for the lack of findings was that they did not account for some important moderating variable, such as peer feedback. They state, “…the overall training context in which trainees work, engaging in many learning experiences and receiving feedback from a multitude of sources, should be considered” (Ladany et al., 1999, p. 77). In contrast, Marmarosh et al. (2013) looked at the relationship between counseling self-efficacy and working alliance in 57 training therapists using a version 59 of the Working Alliance Inventory – Short form (WAI – S; Tracey & Kokotovic, 1989) altered to address the relationship between supervisees and supervisors, and the COSE (Larson et al., 1992). Results suggested that total working alliance and counseling self-efficacy were moderately correlated (r = .37). They also found that the working alliance significantly predicted counseling self-efficacy perceptions (β = .29), and accounted for 8% of the variance. When they conducted a path analysis to look at direct and indirect effects, they found that including paths from fearful and preoccupied attachment to counseling self-efficacy rendered the path coefficient from working alliance to counseling self-efficacy non-significant, but they did not offer an explanation for why this occurred. A major limitation of this study was the small number of participants; the analysis was likely underpowered, making it difficult to detect significant relationships. Finally, Hanson (2007) looked at the relationship between working alliance and counseling self-efficacy in 58 supervisor-supervisee dyads using the Supervisory Working Alliance Inventory (SWAI; Efstation et al., 1990) and the CASES (Lent et al., 2003). He found that out of working alliance, evaluation process (i.e., goal setting and feedback), and role stress, only the working alliance significantly predicted counseling self-efficacy (β = .55), accounting for 31% of the variance. Counselor experience Finally, there is evidence that counselor experience relates significantly to counseling self-efficacy. For instance, Lent et al.’s (2003) measurement development study divided counselors into three groups, based on how many years of helping or counseling experience they reported having: (a) less than a year, (b) 1 to 3 years, and 60 (c) greater than three years. Results suggested that counseling self-efficacy increased as a function of experience; the most experienced and intermediate groups reported higher counseling self-efficacy than the beginning group, and the more experienced group reported higher counseling self-efficacy than the intermediate group. In a later study, Lent et al. (2006) found that participants’ ratings of their client-specific counseling self-efficacy increased over sessions (partial ŋ² = .39). Sipps, Sugden, and Faiver (1988) looked at 78 graduate counseling students and found main effects for year of training. Efficacy expectations were lower for second year graduate students than first year graduate students. Efficacy expectations were significantly higher for third year graduate students than for first and second years, and significantly higher for fourth year graduate students than for first, second, and third year students. Summary The purpose of this review was to explore existing research on counseling self-efficacy, its relational sources, and its relationship to supervisory working alliance and counseling experience. Research on the tripartite model and the relationship-specific source of RISE, while not tested in the context of supervision, support the relationship between RISE and self-efficacy, as well as the importance of other-efficacy in the contexts of athletic partnerships, romantic relationships, and advising relationships. A number of studies found that self-efficacy, other-efficacy, and RISE were significantly related to one another as well as to important relationship outcomes such as commitment and relationship satisfaction. The research also offers some preliminary support for the connection between relationship quality and efficacy beliefs. Furthermore, research on the supervisory working 61 alliance largely supports its relationship with counseling self-efficacy. Therefore, additional research on the tripartite model of efficacy beliefs in relation to supervision, along with the supervisory working alliance, may help researchers to better understand the role of supervision in training. 62 Appendix B. Letter to the Directors and Participants Dear _____, My name is Ashley Morrison and I am a doctoral candidate in counseling psychology at the University of Maryland. I know you get many requests, but I am hoping that you will consider assisting me with my research study. Would you be willing to share my survey with students in the (school and program name)? I am conducting an IRB-approved dissertation study looking at the clinical and supervision experiences of counseling trainees. The purpose of this research is to gain a better understanding of how supervisory working alliance, counseling experience, and client difficulty contribute to trainees’ counseling related efficacy beliefs. This line of research is important as it will help inform what predicts counseling self-efficacy, particularly when working with difficult clients. If you are willing to share my survey, I have included the text to forward to your students along with the survey link in the section below the line. I would be happy to answer any questions you have if you are unsure and I can provide an IRB letter of approval upon request. Thank you so much for your time. Best, Ashley Hello fellow graduate student! Have you ever had to work with a particularly difficult or challenging client? Many of us have. I am interested in understanding how counseling trainees, such as you, use supervision and efficacy beliefs when working with difficult clients. You can help me by participating is this quick 10 minute online survey. But wait, there’s more! As a thank you, at the end of the survey you will be given the chance to enroll in a drawing where you are guaranteed a one in 20 chance to win a 20$ gift certificate to Amazon.com. Your survey responses will not be connected to your drawing entry. This study is expected to take no longer than 10 minutes of your time. To participate in the study, you need to • Be currently enrolled in a professional graduate program in a counseling related field • Be working with at least one client and receiving weekly clinical supervision • Be at least 18 years of age Participation is completely voluntary. The information you provide will be kept confidential and you have the option at any point in the survey to opt out. Please click the link below, which will take you to the survey: If you have any questions at all, please contact me at mmorris4@umd.edu or Dr. Robert Lent, at boblent@umd.edu. Thank you and good luck in your own research and counseling endeavors! Best, Ashley Morrison 63 ***************************** This project (721460-1) has been approved by the University of Maryland, College Park Institutional Review Board. This research is being conducted by Ashley Morrison, M.S., doctoral candidate in the Department of Counseling, Higher Education, and Special Education, under the supervision of Robert W. Lent, Ph.D., faculty advisor in the Department of Counseling, Higher Education, and Special Education at the University of Maryland, College Park. If you have any questions regarding your rights as a participant in this research, you can contact: University of Maryland College Park Institutional Review Board Office, 1204 Marie Mount, College Park, MD 20742 (301-405-0678;irb@umd.edu). 64 Appendix C. Informed Consent Form Project Title Counseling Self-Efficacy and the Relational Efficacy Model Purpose of the Study This research is being conducted by Ashley Morrison, MS, and Robert Lent, PhD from the Department of Counseling, Higher, and Special Education, at the University of Maryland, College Park. We are inviting you to participate in this research project because you are at least 18 years old, a doctoral student in a counseling field, seeing at least one client, and receiving weekly clinical supervision. The purpose of this research is to find out more about what influences counseling efficacy beliefs in counseling trainees in order to better understand how trainees develop these beliefs. Procedures The procedures of this study involve your completing a brief survey. It should require about 10 minutes of your time. The survey will ask you about your counseling efficacy beliefs, your clinical supervision relationship, and a rating of the difficulty level of a client you are currently seeing. The survey contains various statements that ask you to rate the extent to which each statement applies to you. For example, one item states “My supervisor helps me talk freely in our sessions.” You are asked to indicate the frequency with which this behavior occurs ranging from almost never (1) to almost always (7). Compensation At the end of the survey, you will be given the chance to enroll in a drawing by providing your email address. You are guaranteed a one in 20 chance to receive a 20$ gift certificate to Amazon.com. Your survey responses will not be connected to the email address you provide. Potential Risks and Discomforts There are no known risks associated with participating in this research study. Potential Benefits This research is not designed to help you personally, but the results may help the investigator learn more about how counseling trainees develop efficacy beliefs, especially when working with more difficult clients. Understanding how efficacy beliefs develop may help investigators develop interventions to help trainees improve their counseling efficacy beliefs. Confidentiality You will not be required to provide any information that may link your identity to your survey responses. We will do our best to minimize any potential loss of confidentiality. The data will be collected via an online survey provider and stored in the survey provider’s database, which is only accessible with a password. Once the information is downloaded from the online survey provider, it 65 will be stored in a password-protected computer. Permission will only be given to the investigators to access the data. Any reports based on the survey information will only present the results in aggregate form (e.g., group averages). Individual survey responses will never be reported. Right to Withdraw and Questions Your participation in this research is completely voluntary. You may choose not to take part at all. If you decide to participate in this research, you may stop participating at any time by closing your browser. If you decide not to participate in this study or if you stop participating at any time, you will not be penalized or lose any benefits to which you otherwise qualify. If you are an employee or student at the University of Maryland, your employability, grades, or standing within UMD will not be positively or negatively affected by your decision to participate in this study. If you decide to stop taking part in the study, if you have questions, concerns, or complaints, or if you need to report an injury related to the research, please feel free to contact the investigator(s): Ashley Morrison at mmorris4@umd.edu, 3204 Benjamin Building, University of Maryland, College Park, MD 20742; (706) 424-8652 Participant Rights If you have questions about your rights as a research participant or wish to report a research-related injury, please contact: University of Maryland College Park Institutional Review Board Office 1204 Marie Mount Hall College Park, Maryland, 20742 E-mail: irb@umd.edu Telephone: 301-405-0678 This research has been reviewed according to the University of Maryland, College Park IRB procedures for research involving human subjects. Statement of Consent By selecting your choice below you are indicating your right to consent or not consent electronically. Selecting “Yes, I Consent” and clicking on the “Continue” button below indicates that you are at least 18 years old and have read and understand the terms of this study and thus voluntarily agree to participate. You may print a copy of this consent form for your records. 66 If you do NOT wish to participate in this study, please select “No, I DO NOT Consent” and click “Continue” to decline participation. 67 Appendix D. Counseling Self-Efficacy (CLIENT-SPECIFIC) Counselor Activity Self-Efficacy Scale – Client-specific (CASES-S; Lent, Hoffman, Hill, Treistman, Mount, & Singley, 2003). Session Management Self-Efficacy Subscale 68 Appendix E. Supervisory Working Alliance Supervisory Working Alliance Inventory (SWAI; Efstation et al., 1990) 69 Appendix F. Relation-Inferred Counseling Self-Efficacy (CLIENT-SPECIFIC) Session Management Relation Inferred Self-Efficacy 70 Appendix G. Other Counseling Self-Efficacy Session Management Other-Efficacy 71 Appendix H. Client Difficulty Global Assessment of Functioning Scale (GAF; American Psychiatric Association, 1987) 72 Appendix I. Demographic Questions What is your gender? • Female • Male • Other What is your race/ethnicity? • American Indian or Alaskan Native • Asian • Black or African American • Hispanic or Latino • Native Hawaiian or Pacific Islander • White • Multiracial • Other Are you an international student? • Yes • No What is your age? How many years of counseling experience do you have? How many hours of supervised counseling experience do you have? What gender is the supervisor who supervises your work with your most difficult client? • Female • Male • Other What race/ethnicity is the supervisor who supervises your work with your most difficult client? • American Indian or Alaskan Native • Asian • Black or African American • Hispanic or Latino • Native Hawaiian or Pacific Islander • White • Multiracial • Other How many clients are you currently seeing on a regular (e.g., weekly) basis? How often do you meet with the supervisor who supervises your work with your most difficult client? 73 • Never • Less than once a month • Once a month • 2-3 times a month • Once a week • 2-3 times a week • Daily How many months have you and this supervisor been working together? Do you currently work with more than one supervisor? • Yes • No Which program are you enrolled in? • Counseling psychology • Clinical psychology • Other Which degree are you working on? • PhD • PsyD • Other In what setting are you currently seeing clients? You can select more than one setting if necessary. • Child/Adolescent Psychiatric or Pediatrics D Community Health Center • Community Mental Health Center • Consortium • Medical School • Prison or other Correctional Facility • Private General Hospital • Private Outpatient Clinic • Private Psychiatric Hospital • Psychology Department • School District • State/County/Other public Hospital • University Counseling Center • Veterans Affairs Medical Center • Other 74 References Alvarez, A. (1995). Perceptions of fraudulence, counseling self-efficacy, and satisfaction with work. Dissertation Abstracts International, 56, 2851. Anderson, S. L., & Betz, N. E. (2001). Sources of social self-efficacy expectations: Their measurement and relation to career development. Journal of Vocational Behavior, 58, 98-117. doi:10.1006/jvbe.2000.175 American Psychological Association (2014). Commission on accreditation 2014 annual report online summary data: Doctoral programs. Retrieved online from https://www.apa.org/ed/accreditation/about/research/2014-doctoral- summary.pdf Azjen, I, (2005). Attitudes, Personality, and Behavior. Maidenhead, England: Open University Press. Bahrick, A. S. (1990, September). Role induction for counselor trainees: Effects on the supervisory working alliance. Dissertation Abstracts International, 51, 1484. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ US: Prentice-Hall, Inc. Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY, US: W H Freeman/Times Books/ Henry Holt & Co. Betz, N. E. (1978). Prevalence, distribution, and correlates of math anxiety in college students. Journal of Counseling Psychology, 25, 441-448. doi:10.1037/0022- 0167.25.5.441 75 Betz, N., Borgen, F., & Harmon, L. (1996). Skills confidence inventory applications and technical guide. Palo Alto: Consulting Psychologists Press. Betz, N. E., & Hackett, G. (1983). The relationship of mathematics self-efficacy expectations to the selection of science-based college majors. Journal of Vocational Behavior, 23, 329-345. doi:10.1016/0001-8791(83)90046-5 Beverage, P. L. (1989). The relationship of evaluation in counseling supervision and counselor self-efficacy. Unpublished doctoral dissertation, University of Virginia, Charlottesville. Bordin, E. S. (1979). The generalizability of the psychoanalytic concept of the working alliance. Psychotherapy: Theory, Research & Practice, 16, 252-260. doi:10.1037/h0085885 Brown, S. D., Tramayne, S., Hoxha, D., Telander, K., Fan, X., & Lent, R. W. (2008). Social cognitive predictors of college students' academic performance and persistence: A meta-analytic path analysis. Journal of Vocational Behavior, 72, 298-308. doi:10.1016/j.jvb.2007.09.003 Cashwell, T. H., & Dooley, K. (2001). The impact of supervision on counselor self- efficacy. The Clinical Supervisor, 20, 39-47. doi:10.1300/J001v20n01_03 Daniels, J. (1997, December). The influence of performance feedback and causal attributions upon ratings of counseling self-efficacy. Dissertation Abstracts International Section A, 58, 2068. Daniels, J. A., & Larson, L. M. (2001). The impact of performance feedback on counseling self-efficacy and counselor anxiety. Counselor Education and Supervision, 41, 120-130. doi:10.1002/j.1556-6978.2001.tb01276.x 76 Efstation, J. F., Patton, M. J., & Kardash, C. M. (1990). Measuring the working alliance in counselor supervision. Journal of Counseling Psychology, 37, 322- 329. doi:10.1037/0022-0167.37.3.322 Falender, C. A., & Shafranske, E. P. (2004). Clinical supervision: A competency- based approach. Washington, DC: American Psychological Association Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149-1160. Fernando, D. M., & Hulse-Killacky, D. (2005). The Relationship of Supervisory Styles to Satisfaction with Supervision and the Perceived Self-Efficacy of Master's-Level Counseling Students. Counselor Education and Supervision, 44, 293-304. doi:10.1002/j.1556-6978.2005.tb01757.x Friedlander, M. L., Keller, K. E., Peca-Baker, T. A., & Olk, M. E. (1986). Effects of role conflict on counselor trainees' self-statements, anxiety level, and performance. Journal of Counseling Psychology, 33, 73-77. doi:10.1037/0022-0167.33.1.73 Friedlander, M. L., & Snyder, J. (1983). Trainees' expectations for the supervisory process: Testing a developmental model. Counselor Education and Supervision, 22, 342-348. doi:10.1002/j.1556-6978.1983.tb01771.x Gere, J., Martire, L. M., Keefe, F. J., Stephens, M. P., & Schulz, R. (2014). Spouse confidence in self-efficacy for arthritis management predicts improved patient health. Annals of Behavioral Medicine, 48, 337-346. doi:10.1007/s12160-014- 9608-9 77 Goldberg, S. B., Rousmaniere, T., Miller, S. D., Whipple, J., Nielsen, S. L., Hoyt, W. T., & Wampold, B. E. (2016). Do psychotherapists improve with time and experience? A longitudinal analysis of outcomes in a clinical setting. Journal of Counseling Psychology, 63, 1-11. doi:10.1037/cou0000131 Hancock, G. R. (2006). Power analysis in covariance structure modeling. In G. R. Hancock & R. O. Mueller (Eds), Structural equation modeling: A second course (pp. 69-115). Greenwich, CT: IAP. Hanson, M. G. (2007). Counselor self-efficacy: Supervision contributions, impact on performance, and mediation of the relationship between supervision and performance. Dissertation Abstracts International, 67, 4708. Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling [White paper]. Retrieved from http://www.afhayes.com/ public/process2012.pdf Heppner, M. J., O'Brien, K. M., Hinkelman, J. M., & Flores, L. Y. (1996). Training counseling psychologists in career development: Are we our own worst enemies? The Counseling Psychologist, 24, 105-125. doi:10.1177/0011000096241007 Hoffman, M. A., Hill, C. E., Holmes, S. E., & Freitas, G. F. (2005). Supervisor perspective on the process and outcome of giving easy, difficult, or no feedback to supervisees. Journal of Counseling Psychology, 52, 3-13. doi:10.1037/0022-0167.52.1.3 Hill, C. E., Baumann, E., Shafran, N., Gupta, S., Morrison, A., Rojas, A. P., Spangler, P. T., Griffin, S., Pappa, L., & Gelso, C. J. (2014). Is training effective? A 78 study of counseling psychology doctoral trainees in a psychodynamic/interpersonal training clinic. Journal of Counseling Psychology. Hill, C. E., & Kellems, I. S. (2002). Development and use of the helping skills measure to assess client perceptions of the effects of training and of helping skills in sessions. Journal of Counseling Psychology, 49, 264-272. doi:10.1037/0022-0167.49.2.264 Hill, C. E., & Knox, S. (2013). Training and supervision in psychotherapy. In Lambert, M. J. (Ed.), Bergin and Garfield's Handbook of psychotherapy and behavior change, 6th ed. (pp. 775-811). Hoboken, NJ: Wiley and Sons, Inc. Hill, C. E., Lent, R. W., Morrison, M. A., Pinto-Coelho, K., Jackson, J., & Kivlighan, D.(in press). Contribution of supervisor interventions to client change: The therapist perspective, The Clinical Supervisor. Jackson, B., & Beauchamp, M. R. (2010a). Self-efficacy as a metaperception within coach-athlete and athlete-athlete relationships. Psychology of Sport and Exercise, 11, 188-196. doi:10.1016/j.psychsport.2009.12.005 Jackson, B., Beauchamp, M. R., & Knapp, P. (2007). Relational efficacy beliefs in athlete dyads: An investigation using actor-partner interdependence models. Journal of Sport & Exercise Psychology, 29, 170-189. Jackson, B., Dimmock, J. A., Taylor, I. M., & Hagger, M. S. (2012c). The tripartite efficacy framework in client–therapist rehabilitation interactions: Implications for relationship quality and client engagement. Rehabilitation Psychology, 57, 308-319. doi:10.1037/a0030062 79 Jackson, B., Grove, J. R., & Beauchamp, M. R. (2010b). Relational efficacy beliefs and relationship quality within coach-athlete dyads. Journal of Social and Personal Relationships, 27, 1035-1050. doi:10.1177/0265407510378123 Jackson, B., Gucciardi, D. F., & Dimmock, J. A. (2011). Tripartite efficacy profiles: A cluster analytic investigation of athletes’ perceptions of their relationship with their coach. Journal of Sport & Exercise Psychology, 33, 349-415. Jackson, B., Knapp, P., & Beauchamp, M. R. (2008). Origins and consequences of tripartite efficacy beliefs within elite athlete dyads. Journal of Sport & Exercise Psychology, 30, 512-540. Jackson, B., Knapp, P., & Beauchamp, M. (2009). The coach-athlete relationship: A tripartite efficacy perspective. The Sport Psychologist, 23, 203-232. Jackson, B., Myers, N. D., Taylor, I. M., & Beauchamp, M. R. (2012a). Relational efficacy beliefs in physical activity classes: A test of the tripartite model. Journal of Sport & Exercise Psychology, 34, 285-304. Jackson, B., Whipp, P. R., Chua, K. P., Dimmock, J. A., & Hagger, M. S. (2013). Students’ tripartite efficacy beliefs in high school physical education: Within- and cross-domain relations with motivational processes and leisure-time physical activity. Journal of Sport & Exercise Psychology, 35, 72-84. Jackson, B., Whipp, P. R., Chua, K. P., Pengelley, R., & Beauchamp, M. R. (2012b). Assessment of tripartite efficacy beliefs within school-based physical education: Instrument development and reliability and validity evidence. Psychology of Sport and Exercise, 13, 108-117. doi:10.1016/j.psychsport.2011.10.007 80 Johnson, M. E. (1985). The relative effects of self-observation versus self-modeling on counselor trainees’ anxiety, recall, self-evaluations, self-efficacy expectations, and counseling performance. Unpublished doctoral dissertation, University of California, Santa Barbara. Johnson, E., Baker, S. B., Kopala, M., Kiselica, M. S., & Thompson, E. C. (1989). Counseling self-efficacy and counseling competence in prepracticum training. Counselor Education and Supervision, 28, 205-218. doi:10.1002/j.1556- 6978.1989.tb01109.x Jones, S. H., Thornicroft, G., Coffey, M., & Dunn, G. (1995). A brief mental health outcome scale: Reliability and validity of the Global Assessment of Functioning (GAF). The British Journal of Psychiatry, 166, 654-659. doi:10.1192/bjp.166.5.654 Kahn, J. H. (2001). Predicting the scholarly activity of counseling psychology students: A refinement and extension. Journal of Counseling Psychology, 48, 1-11. doi:10.1037/0022-0167.48.3.344 Kahn, J. H., & Schlosser, L. Z. (2010). The graduate research training environment in professional psychology: A multilevel investigation. Training and Education in Professional Psychology, 4, 183-193. doi:10.1037/a0018968 Kahn, J. H., & Scott, N. A. (1997). Predictors of research productivity and science- related career goals among counseling psychology doctoral students. The Counseling Psychologist, 25, 38-67. doi:10.1177/0011000097251005 Knox, S., Edwards, L. M., Hess, S. A., & Hill, C. E. (2011). Supervisor self- disclosure: Supervisees' experiences and perspectives. Psychotherapy, 48, 81 336-341. doi:10.1037/a0022067Kopala, M. (1987). The impact of supervisory interventions on self-efficacy and anxiety of counselors: An evaluation of the single case design. Unpublished doctoral dissertation, Pennsylvania State University. Ladany, N., Ellis, M. V., & Friedlander, M. L. (1999). The supervisory working alliance, trainee self-efficacy, and satisfaction. Journal of Counseling & Development, 77, 447-455. doi:10.1002/j.1556-6676.1999.tb02472.x Ladany, N., O'Brien, K. M., Hill, C. E., Melincoff, D. S., Knox, S., & Petersen, D. A. (1997). Sexual attraction toward clients, use of supervision, and prior training: A qualitative study of predoctoral psychology interns. Journal of Counseling Psychology, 44, 413-424. doi:10.1037/0022-0167.44.4.413 Ladany, N., Walker, J. A., Pate-Carolan, L., & Evans, L. G. (2007). Practicing counseling and psychotherapy: Insights from trainees, supervisors, and clients. London, England: Routledge. Larson, L. M. (1998). The SCMCT making it to 'the show': Four criteria to consider. The Counseling Psychologist, 26, 324-341. doi:10.1177/0011000098262008 Larson, L. M., Cardwell, T. R., & Majors, M. S. (1996). Counselor burnout investigated in the context of social cognitive theory. Paper presented at the American Psychological Association National Convention, Toronto, Canada. Larson, L. M., Clark, M. P., Wesely, L. H., Koraleski, S. F., Daniels, J. A., & Smith, P. L. (1999). Videos versus role plays to increase counseling self-efficacy in 82 prepractica trainees. Counselor Education and Supervision, 38, 237-248. doi:10.1002/j.1556-6978.1999.tb00574.x Larson, L. M., & Daniels, J. A. (1998). Review of the counseling self-efficacy literature. The Counseling Psychologist, 26, 179-218. doi:10.1177/0011000098262001 Larson, L. M., Koraleski, S., Henderson, L., Smith, P., Daniels, J. A., & Peterson, M. (1994). Developing self-efficacv in counseling interns: A multiple case study. Unpublished manuscript. Larson, L. M., Suzuki, L. A., Gillespie, K. N., Potenza, M. T., Bechtel, M. A., & Toulouse, A. L. (1992). Development and validation of the Counseling Self- Estimate Inventory. Journal of Counseling Psychology, 39, 105-120. doi:10.1037/0022-0167.39.1.105 Lent, R., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45, 79-122. doi:10.1006/jvbe.1994.1027 Lent, R. W., Cinamon, R., Bryan, N. A., Jezzi, M. M., Martin, H. M., & Lim, R. (2009). Perceived sources of change in trainees’ self-efficacy beliefs. Psychotherapy: Theory, Research, Practice, Training, 46, 317-327. doi:10.1037/a0017029 Lent, R. W., Hackett, G., & Brown, S. D. (1998). Extending social cognitive theory to counselor training: Problems and prospects. The Counseling Psychologist, 26, 295-306. doi:10.1177/0011000098262005Lent, R. W., Hill, C. E., & Hoffman, M. (2003). Development and validation of the Counselor Activity 83 Self-Efficacy Scales. Journal of Counseling Psychology, 50, 97-108. doi:10.1037/0022-0167.50.1.97 Lent, R. W., Hoffman, M. A., Hill, C. E., Treistman, D., Mount, M., & Singley, D. (2006). Client-specific counselor self-efficacy in novice counselors: Relation to perceptions of session quality. Journal of Counseling Psychology, 53, 453- 463. doi:10.1037/0022-0167.53.4.453 Lent, R. W., & Lopez, F. G. (2002). Cognitive ties that bind: A tripartite view of efficacy beliefs in growth-promoting relationships. Journal of Social And Clinical Psychology, 21, 256-286. doi:10.1521/jscp.21.3.256.22535 Lent, R. W., Lopez, F. G., & Bieschke, K. J. (1991). Mathematics self-efficacy: Sources and relation to science-based career choice. Journal of Counseling Psychology, 38, 424-430. doi:10.1037/0022-0167.38.4.424 Lent, R. W., Lopez, F. G., Brown, S. D., & Gore, P. A. (1996). Latent structure of the sources of mathematics self-efficacy. Journal of Vocational Behavior, 49, 292-308. doi:10.1006/jvbe.1996.0045 Little, T. D., Rhemtulla, M., Gibson, K., & Schoemann, A. M. (2013). Why the items versus parcels controversy needn’t be one. Psychological Methods, 18, 285- 300. doi:10.1037/a0033266 Lopez, F. G., & Lent, R. W. (1991). Efficacy-based predictors of relationship adjustment and persistence among college students. Journal of College Student Development, 32, 223-229. Lopez, F. G., Lent, R. W., Brown, S. D., & Gore, P. A. (1997). Role of social– cognitive expectations in high school students' mathematics-related interest 84 and performance. Journal of Counseling Psychology, 44, 44-52. doi:10.1037/0022-0167.44.1.44 Marmarosh, C. L., Nikityn, M., Moehringer, J., Ferraioli, L., Kahn, S., Cerkevich, A., & ... Reisch, E. (2013). Adult attachment, attachment to the supervisor, and the supervisory alliance: How they relate to novice therapists’ perceived counseling self-efficacy. Psychotherapy, 50, 178-188. doi:10.1037/a0033028 Matsui, T., Matsui, K., & Ohnishi, R. (1990). Mechanisms underlying math self- efficacy learning of college students. Journal of Vocational Behavior, 37, 225-238. doi:10.1016/0001-8791(90)90042-Z Mehr, K. E., Ladany, N., & Caskie, G. L. (2014). Factors influencing trainee willingness to disclose in supervision. Training and Education in Professional Psychology, doi:10.1037/tep0000028 Melchert, T. P., Hays, V. L., Wiljanen, L. M., & Kolocek, A. K. (1996). Testing models of counselor development with a measure of counseling self- efficacy. Journal of Counseling & Development, 74, 640-644. doi:10.1002/j.1556-6676.1996.tb02304.x Morrison, M., & Lent, R. W. (2014). The advisory working alliance and research training: Test of a relational efficacy model. Journal of Counseling Psychology, 61, 549-559. doi:10.1037/cou0000030 Munson, W. W., Stadulis, R. E., & Munson, D. G. (1986). Enhancing competence and self-efficacy of potential therapeutic recreators in decision making counseling. Therapeutic Recreation Journal, 20, 53-62. 85 O'Brien, K. M., & Heppner, M. J. (1996). Applying social cognitive career theory to training career counselors. The Career Development Quarterly, 44, 367-377. Orlinsky, D., Rønnestad, M. H., Ambühl, H., Willutzki, U., Botersman, J., Cierpka, M., & ... Davis, M. (1999). Psychotherapists' assessments of their development at different career levels. Psychotherapy: Theory, Research, Practice, Training, 36, 203-215. doi:10.1037/h0087772 Reese, R. J., Usher, E. L., Bowman, D. C., Norsworthy, L. A., Halstead, J. L., Rowlands, S. R., & Chisholm, R. R. (2009). Using client feedback in psychotherapy training: An analysis of its influence on supervision and counselor self-efficacy. Training and Education in Professional Psychology, 3, 157-168. doi:10.1037/a0015673 Russel, R.K., Crimmings, A. M., & Lent, R. W. (1984). Counselor training and supervision: Theory and research. In S. D. Brown & R. W. Lent (Eds.), Handbook of counseling psychology (pp.625-681). New York: Wiley. Sallis, J. F., Pinski, R. B., Grossman, R. M., Patterson, T. L., & Nader, P. R. (1988). The development of self-efficacy scales for health-related diet and exercise behaviors. Health Education Research, 3, 283-292. doi:10.1093/her/3.3.283 Saville, P. D., Bray, S. R., Ginis, K. M., Cairney, J., Marinoff-Shupe, D., & Pettit, A. (2014). Sources of self-efficacy and coach/instructor behaviors underlying relation-inferred self-efficacy (RISE) in recreational youth sport. Journal of Sport & Exercise Psychology, 36, 146-156. doi:10.1123/jsep.2013-0144 Sherer, M., & Adams, C. H. (1983). Construct validation of the Self-efficacy Scale. Psychological Reports, 53, 899-902. doi:10.2466/pr0.1983.53.3.899 86 Sheu, H., & Lent, R. W. (2007). Development and initial validation of the Multicultural Counseling Self-Efficacy Scale--Racial Diversity Form. Psychotherapy: Theory, Research, Practice, Training, 44, 30-45. doi:10.1037/0033-3204.44.1.30 Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological Methods, 7, 422-445. doi:10.1037/1082-989X.7.4.422 Sipps, G. J., Sugden, G. J., & Faiver, C. M. (1988). Counselor training level and verbal response type: Their relationship to efficacy and outcome expectations. Journal of Counseling Psychology, 35, 397-401. doi:10.1037/0022-0167.35.4.397 Soper, D. S. (2011). Interaction Version 1.7.2211 [Computer software]. Spanier, G. B. (1976). Measuring dyadic adjustment: New scales for assessing the quality of marriage and similar dyads. Journal of Marriage and the Family, 38, 15-28. doi:10.2307/350547 Spielberger, C. D. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press. Spielberger, C. D., Gorusch, R. L., & Lushene, R. E. (1970). Manual for the State- Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press. Tracey, T. J., & Kokotovic, A. M. (1989). Factor structure of the Working Alliance Inventory. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 1, 207-210. doi:10.1037//1040-3590.1.3.207 87 Urbani, S., Smith, M. R., Maddux, C. D., Smaby, M. H., Torres-Rivera, E., & Crews, J. (2002). Skills-based training and counseling self-efficacy. Counselor Education and Supervision, 42, 92-106. doi:10.1002/j.1556- 6978.2002.tb01802.x Warner, L. M., Schüz, B., Knittle, K., Ziegelmann, J. P., & Wurm, S. (2011). Sources of perceived self‐efficacy as predictors of physical activity in older adults. Applied Psychology: Health And Well-Being, 3, 172-192. doi:10.1111/j.1758-0854.2011.01050.x Watkins, C. J. (2011). Psychotherapy supervision since 1909: Some friendly observations about its first century. Journal of Contemporary Psychotherapy, 41, 57-67. doi:10.1007/s10879-010-9152-2 Watson, D. P. (1992). Counseling self-efficacy and counseling competence: A comparative study of clergy and counselors in training. Unpublished doctoral dissertation, Purdue University. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063-1070. doi:10.1037/0022- 3514.54.6.1063 White, N. K. (1996). The relationship between counselor-trainee extra-therapy characteristics and success in counselor training. Unpublished master’s thesis, California State University. 88 Yim, C., Chan, K. W., & Lam, S. K. (2012). Do customers and employees enjoy service participation? Synergistic effects of self- and other-efficacy. Journal of Marketing, 76, 121-140. doi:10.1509/jm.11.0205