Strategies for Setting and Working on Mentee Goals
Evidence Rating for this Practice:
Promising (Effective: 1 Study; Promising: 3 Studies; Insufficient Evidence: 1 Study with 2 Tests of the Practice)
In 4 of the 5 studies reviewed, the methodology used for assessing effects of the practice met criteria for rigor and the practice was associated with better outcomes; 3 of these studies were designated as Promising and 1 was designated Effective. In one study, which had 2 tests of the practice, the methodology used for assessing effects of the practice did not meet criteria for rigor and the study thus was designated as Insufficient Evidence. Based on these review outcomes, the practice received an overall evidence rating of Promising.
Description of Practice:
Strategies for setting and working on mentee goals involve systematic efforts within programs to support mentee goal-setting and pursuit in mentoring relationships. These efforts can take several forms. Examples include training to enhance mentor skill in supporting mentees with setting and pursuing goals, match activity guidance for practice with setting and working on goals (e.g., resource materials or activity guides), and mentee training on how to set and pursue goals effectively with the help of their program mentors (Balcazar & Keys, 2014). The practice may also include systematic efforts to monitor the process of goal setting or progress and to celebrate goal achievement. Mentor training focused on goal-setting and pursuit may be provided before or at any point during the mentoring relationship and may include topics such as how and when to introduce goal setting into the relationship, the importance of working collaboratively with the mentee to identify and set goals, skills for engaging youth in goal-setting, and methods for assessing goal achievement (Balcazar & Keys, 2014). Additionally, training and other program supports may address any of the following components of iterative goal-setting and pursuit processes: 1) appraising self, 2) gathering information, 3) selecting goals, 4) planning, and 5) problem solving (Lau et al., 2017). The frequency, duration, and format of supports for goal-setting and pursuit can vary. For example, training may be delivered on a one-time basis in a group format or individually and may be provided either in-person or online. Training and support for goal-setting and pursuit may also be tailored to the backgrounds of a specific population of mentees (e.g., for older youth, the focus might be goals related to the transition to college or work) and/or to specific program goals (e.g., a program emphasizing educational outcomes may focus on academic goals). Goal-setting efforts may target short- and/or long-term goals; the emphasis, however, needs to be on setting and working toward goals that are specific and well-defined rather than general (e.g., being a better student).
This practice is consistent with recommended benchmarks for Training and Monitoring & Support in the Elements of Effective Practice for MentoringTM (Garringer, Kupersmidt, Rhodes, Stelter, & Tai, 2015). However, support for goal-setting and pursuit is distinguished from more general forms of mentor/mentee training and support by its intentional focus on promoting the types of skills and behaviors described above.
The primary goal of the practice is to support mentees with setting and working on personally-relevant goals.
Targeted Forms of Mentoring and Youth Populations:
This practice is potentially applicable to all forms of mentoring and the full range of youth who may be served by programs.
Theory and Background Research:
The focus of this practice on helping youth identify goals and take actions toward attaining them is consistent with the concept of intentional self regulation (ISR), which suggests that individuals can promote their own positive development and success in life by engaging in goal directed behavior (Arbeit et al., n.d.). The Baltes and Baltes Model of Selection, Optimization and Compensation (SOC) identifies goal selection (identifying, prioritizing, and committing to goals), goal pursuit (use of the most effective strategies and resources to achieve goals), and goal-maintenance (monitoring and adjusting strategies when faced with obstacles) as important processes central to ISR (Baltes, 1997). The expected influence of personally valued goal development and pursuit on youth behavior and on youth self-efficacy for self-regulation is also consistent with Social Cognitive Theory (Bandura, 1986).
A number of studies have linked goal-setting and pursuit to positive youth development outcomes (Lerner et al., 2005; Li et al., 2010; Zimmerman et al., 2007) and to decreased risk/problem behaviors (Gestdottir & Lerner, 2007). Participation in youth development programs also has been found to be predictive of ISR (Mueller et al., 2011). In line with these findings, mentoring programs with features of goals setting, particularly when goals-setting is done with youth participation, have demonstrated evidence of positive impacts on participating youth (Balcazar & Keys, 2014). Furthermore, mentor-mentee relationships characterized as high quality (e.g., as measured by closeness or duration) have been linked to greater improvements in youth goal-directed skills (Bowers et al, 2016), future planning, and confidence in goal-setting ability (Lau et al, 2017). Tests of structured approaches for documenting and measuring goal attainment, such as the goal attainment scaling (GAS; Balcazar & Keys, 2014) and the GPS to Success tool (Bowers et al., 2013), also highlight the reliability of using such tools in mentoring relationships. Measures of skills for goal setting and pursuit among youth for use in evaluating mentoring programs are also available in the Measurement Guidance Toolkit.
Corresponding Elements of Effective Practice:
This practice is most relevant to the areas of Training and Monitoring and Support within the Elements of Effective Practice.
The successful implementation of this practice is likely require staff to have a strong foundational understanding of conceptual frameworks and strategies for identifying, pursuing, and monitoring goal setting and attainment, including key considerations in their applications with youth.
Evidence Classification: Promising
DuBois and Keller (2017) tested the effects of strategies for setting and working on mentee goals within the Big Brothers Big Sisters (BBBS) community-based mentoring program in collaboration with the organization’s national office and 10 BBBS affiliates across the country. All youth were either new enrollees in the BBBS program or were being re-matched with a new mentor after a prior relationship had ended. Eligibility criteria for youth included being 10-16 years of age and being at elevated risk for delinquency due to any of the following circumstances: family low-income status, single-parent family, or having a parent incarcerated. All newly enrolled matches (i.e., the youth, his or her mentor, and the youth’s primary parent or guardian) were offered the opportunity to participate in the study, which involved random assignment to an intervention (standard program services plus intervention activities) or comparison (standard program services) condition. The study sample consisted of 806 youth with 400 in the intervention group and 406 in the comparison group. Participating youth had an average age of 12.19 years, were 61.9% female, and were predominantly African American (50.5%) or Latina/o (27.9%).
The practice was tested as part of a four-phase Step-It-Up-2-Thrive intervention model from the Thrive Foundation for Youth in which mentors used a range of practical strategies to promote youth thriving, including the 1) identification of youth interests and passions to ground motivation (“sparks”), 2) teaching that intelligence and other abilities are not innate but can be developed through effort (growth mindset), 3) cultivation of a range of indicators of positive youth development (e.g., competence), and 4) skills for setting and pursuing goals. In the final phase of the intervention, mentors and youth jointly determined one or two areas in which the youth wants to pursue growth and used a goal management system referred to as GPS (Goal selection, Pursuit of strategies, and Shifting of gears to overcome obstacles) to work on identified goals. Intervention activities included two staff-facilitated group activities for matches on topics in the intervention model (e.g., GPS skills), guided discussions and activities for matches to engage in on their own, staff briefings of parents on key concepts in the intervention model, and a 12-month anniversary meeting to reflect on program participation and youth progress.
Study outcomes were measured at baseline (prior to initiation of the match) and 15 months later. Youth-report measures assessed exposure to and response to intervention program content (for youth in the intervention condition) as well as perceived support from significant adults for thriving. Structural equation model (SEM) analysis evaluated a path model informed by the intervention model’s theory of change. The model tested whether intervention activities, when incorporated substantially into the mentoring relationship combined with a favorable response from the youth, promoted increased youth reports of support for thriving from adults. Gains in adult support for thriving were then hypothesized to strengthen intrapersonal resources for thriving (such as sparks) and these improvements, in turn, were expected to contribute to a reduction in problem behaviors. Youth in the intervention condition who reported positive engagement (participation in at least three of the six core facets of the intervention activities combined with reports of having found the activities to be enjoyable or helpful; n=150) were compared with a matched comparison group of youth in the standard services condition identified based on results of analyses of baseline and background predictors of positive engagement with the intervention components (n=150). Specific to this review, a supplementary SEM analysis evaluated whether positive engagement with the activities focused on promoting skills for goal setting and pursuit in their mentoring relationships was predictive of increased reports of support for thriving from adults.
Adult support for thriving
DuBois and Keller (2017) reported that there was a positive path in the SEM model from engagement with goal setting and pursuit activities to increased reports of thriving support from adults.
Study 2 (Two tests of the practice: Setting goals that focus on Little’s general development and Setting goals that focus on specific areas of Little’s development):
Evidence Classification: Setting goals that focus on Little’s general development – Insufficient Evidence; Setting goals that focus on specific areas of Little’s development – Insufficient Evidence
Wheeler & DuBois (2009) examined correlates of practices relating to setting and working on mentee goals as part of a survey of 113 BBBSA affiliates regarding their community-based mentoring programs; the sample included 80 affiliates with data available in BBBSA’s web-based AIM system. Data were collected via an online survey conducted between May and September of 2009. The response rate was 34 percent for all affiliates (i.e., 131 of 385 total) and 81 percent for affiliates with AIM data. The survey included a two questions about the affiliate’s current practices related to strategies for setting and working on mentee goals, including whether the affiliate set goals that focused on the Little’s general development (reported by 49% of affiliates) and whether the affiliate set goals that focused on specific areas of the Little’s development (academics, peer relationships, and risk behaviors, etc.; reported by 60% of affiliates).
Analyses examined the associations of the above described types of strategies for setting and working on mentee goals with average total scores on the BBBSA Strength of Relationship (SOR) survey as completed 3 months into the relationship by both the volunteer (Big Brother or Big Sister) and child as well as with measures of relationship duration (6 and 12 month retention rates, average match length). The outcome measures were all derived from the AIM system and thus the analyses were limited to the subset of 80 responding affiliates with AIM data. On average, sixty percent of mentors in these affiliates were female and 29 percent were non-white. Additionally, on average, 81 percent of children served by the affiliates lived in one-parent households, 19 percent had an incarcerated parent, and 21 percent qualified for free or reduced school lunch.
Analyses included bivariate correlations between the practice and outcome measures as well as partial correlations that controlled for any of several assessed affiliate characteristics (e.g., % of women volunteers, % of children with 2 or more risk factors) that had a significant or near-significant (p < .10) correlation with the outcome measure being considered.
3-month SOR child score
Wheeler & DuBois (2009) found that there was not a significant correlation between the youth-reported SOR scores with affiliate report of setting goals that focus on the Little’s general development or report of setting goals focused on specific area of the Little’s development.
3-month SOR volunteer score
Wheeler & DuBois (2009) found positive correlation between the 3-month volunteer-reported SOR scores and affiliate report of setting goals that focus on the Little’s general development that, although not statistically significant, was large enough to indicate an association of substantive magnitude. However, the corresponding correlation of affiliate report of setting goals focused on specific areas of the Little’s development was not significant with volunteer-reported SOR scores was not significant.
6-Month Match Retention Rate
Wheeler & DuBois (2009) found a positive correlation between 6 month match retention rates (i.e., the % that lasted at least six months) and affiliate report of setting goals that focus on the Little’s general development that, although not statistically significant, was large enough to indicate an association of substantive magnitude. The corresponding correlation between affiliate report of setting goals focused on specific areas of the Little’s development and 6-month match retention rate was not statistically significant.
12-Month Match Retention Rate
Wheeler & DuBois (2009) found no significant correlation between 12 month match retention rates (i.e. the % that lasted at least twelve months) and affiliate report of setting goals that focus on the Little’s general development. The corresponding correlation between affiliate report of setting goals focused on specific area of the Little’s development, although not statistically significant, was in a negative direction and large enough to indicate an association of substantive magnitude.
Average Match Length
Wheeler & DuBois (2009) found no significant correlation between average match length and affiliate report of setting goals that focus on the Little’s general development. The corresponding correlation between affiliate report of setting goals focused on specific area of the Little’s development, although not statistically significant, was in a negative direction and large enough to indicate an association of substantive magnitude.
Wheeler & DuBois (2009) also examined affiliate reports of the following other practices related to setting and working on goals: setting goals using a standardized tool and/or process to help identify goal (reported by 20% of affiliates), assessing progress towards goals using a standardized tool and/or process (reported by 19% of affiliates), and updating goals for each Little/match annually (reported by 36% of affiliates). Responses to these three questions were combined and analyzed as a multi-item practice scale. Wheeler & DuBois (2009) found that scores on this exhibited positive correlations with 3-month volunteer-reported and child-reported SOR scores; although not statistically significant, these associations were large enough to indicate associations of substantive magnitude. On the other hand, the multi-item practice scale exhibited a negative correlation with average match length that also, although not significant, was large enough to indicate an association of substantive magnitude. The multi-item practice scale was not correlated with 6-month or 12-month retention rates or average match length.
Evidence Classification: Effective
Powers and colleagues (2012) examined correlates of strategies for setting and working on mentee goals as part of a longitudinal, randomized evaluation of TAKE CHARGE, a self-determination enhancement intervention intended for youth in foster care with special education needs. The 12-month, multi-component, intervention used individual, weekly coaching sessions to assist youth in identifying and working towards personally valued transition goals, in developing and applying skills in problem-solving, self-regulation (e.g., focusing on own accomplishments), and partnership building (e.g., networking, negotiating) with other adults and agencies who are willing to help youth in the first years after exiting care. Weekly coaching was conducted during unscheduled school class periods, immediately before or after school, or in the evenings or on the weekends. Each participating youth developed an individualized transition plan that he/she shared with adults he/she considered important in his/her life (e.g., foster parent, teachers, social worker, etc.). In addition, the intervention also included 4 workshops. Each workshop included structured didactic, experiential, and fun components and was facilitated by young adult foster care alumni who were attending college, working successfully in a particular career, and/or had particular experiences in overcoming barriers to transition success. Workshop topics were selected by youth and included employment, postsecondary education, exiting foster care, and leading a transition meeting.
The study sample included 69 youth who were enrolled over three study waves and randomly assigned to intervention (n=33) or control (n=36) groups. Youth were recruited into the study from a list generated by the state foster care system of youth that were a) receiving special education services, b) 16.5 to 17.5 years of age, c) under the guardianship of the state’s Department of Human Services with at least 90 days in foster care, and d) attending a large school district in the study target area. Twenty-nine youth successfully completed the intervention with an average of 12.74 months and 50.36 hours spent in coaching. Coaches completed a Fidelity of Implementation checklist that tracked the delivery of key intervention components (e.g., when a skill was introduced or reviewed and how many times it was practiced or addressed); overall fidelity across all study waves averaged 90%. Youth in the control group participated in the Foster Care Independent Living Program (ILP), which included classes on transition topics such as budgeting, cooking, and preparing a resume, support from an ILP case manager, drop-in peer support, and assistance to apply for resources. Seventy-seven percent of youth in the control group reported participating in the ILP, 42% reported attending ILP classes, and 55% reported having an ILP case manager, with whom they had an average of 5.88 contacts.
Youth completed outcome measures at baseline, immediately following the intervention, and one year after the end of the intervention. Youth completed the ARC Self-determination Scale, a self-report measure that assesses four components of self-determination. Youth were also asked to describe their goals and accomplishments and total counts for each were used as measures of identification with goals and accomplishments, respectively. Youths’ transition planning knowledge and engagement was assessed using the Transition Planning Assessment, a 14-item Likert type scale with questions such as “I help run my transition planning meeting” and “I understand everything decided at the meeting”. Additionally, youth completed the Quality of Life Questionnaire and the Outcomes Survey, a measure that captures perceptions about readiness for independent living, was used to assess youth employment, education, living status, use of transition services, and other indicators of independent living. School data were collected from school records (i.e. transcripts, IEPs) and information about participants’ foster care experiences was gathered from a review of their DHS case files and electronic records. If there were any discrepancies between youth and school or agency reports, school or agency data were used in the evaluation.
Of the sixty-nine youth enrolled in the study and assessed at baseline, 60 were assessed at the end of the one year intervention period (29 intervention, 31 control), and 61 were assessed at the one year follow-up (29 intervention, 32 control). The mean age of participants who completed the study (i.e., provided one year follow-up data) was 16.8 years, with females accounting for 41% and Caucasians accounting for 50.8% of the sample. At baseline, 12% of participants were in the 12th grade, 56% were in 11th grade, 30% were in the 10th grade, and one was in the 9th grade. Youth had spent an average of 5.6 years in foster care, 76.4% were in non-relative foster care, and 42.6% had experienced neglect, whereas 27.9% reported experiencing sexual assault and 19.7% reported experiencing physical assault. Finally, 40.9% of youth were eligible for special education due to emotional/behavioral disabilities, 26.2% due to learning disabilities, 37.7% due to “other health impairments” which included Attention Deficit Disorder; 26% of youth received developmental disability services. There were no significant differences between youth in the intervention and control groups in terms of race/ethnicity, maltreatment, special education categories, or on any of the outcome measures.
Standard mixed model regression analyses compared baseline outcome measures with those at post-intervention and 1 year follow-up as well as post-intervention measures with 1 year follow-up measures. If the difference on an outcome measure between post-intervention and follow-up measures was not statistically significant, the average of scores for the two time points was compared to baseline scores on the measure. Effect sizes were calculated.
Powers and colleagues (2012) found a significant difference in self-determination scores between the intervention and control groups on the average of post-intervention and follow-up compared to baseline. Youth in the intervention group scored significantly higher than youth in the comparison group at both post-intervention and follow-up.
Identification of Accomplishments
There were no significant differences in reported number of accomplishments between the intervention and control groups for the average of the post-intervention and follow-up vs. the baseline. However, the groups were significantly different at post-intervention and follow-up, with youth in the intervention group reporting more accomplishments at each time point than did youth in the comparison group.
Identification of Transition Goals
There were no significant differences in reported number of transition goals between intervention and control groups over time. However, the groups did differ significantly at follow-up. Specifically, whereas number of goals reported by the control group of goals declined from baseline to both post-intervention and follow-up, for the intervention group this measure declined from baseline to post-intervention and then increased from post-intervention to follow-up.
Quality of Life
There was a significant difference in quality of life scores on the average of post-intervention and follow-up vs. baseline between the intervention and control groups. Compared to youth in the control group, youth in the intervention group reported significantly higher quality of life than the comparison group at both post-intervention and follow-up.
There were no significant differences between intervention and control groups in transition planning knowledge at either post-intervention or follow-up compared to baseline or at follow-up compared to post-intervention. However, youth in the intervention and control groups did differ significantly on this measure at post-intervention, with youth in the intervention group scoring significantly higher than youth in the control group.
Use of Transition Services
There were no significant differences between the intervention and control groups in use of transition services at either post-intervention or follow-up compared to baseline or at follow-up compared to post-intervention. However, there were differences between the groups at post-intervention and follow-up, indicating that youth in the intervention condition had access to more transition services than youth in the control condition at each time point.
Independent Living Activities
There were no significant differences between the intervention and control groups in level of engagement in independent living activities at either post-intervention or follow-up compared to baseline or at follow-up compared to post-intervention. However, there were differences between the groups at post-intervention and follow-up, indicating that youth in the intervention group had higher reported engagement in key independent living activities at each time point than did youth in the control group.
Evidence Classification: Promising
Powers and colleagues (2001) examined correlates of strategies for setting and working on mentee goals as part of a randomized evaluation of TAKE CHARGE for the Future, a multi-component intervention designed to promote self-directed participation in personally-relevant transition planning and preparation activities among youth with disabilities. The intervention model used a self-help focused curriculum and individual, 50-minute bi-weekly coaching sessions to support youth with identifying their transition goals, participating in their transition planning meetings, and formulating and carrying out strategies for goal attainment. Coaching was provided by an experienced secondary educator from the school district. The coach helped youth to identify and achieve three specific transition goals using three types of strategies: achievement – developing transition plans, actively participating in planning meetings, monitor own and others’ performance of transition activities, and problem solve to overcome obstacles; partnership development – with other people who could help in achieving goals; and self-regulation – strategies for tracking and rewards efforts and accomplishments, and managing frustration. The intervention also included monthly, 2-hour, interactive, community-based workshops for youth, their parents, and adult mentors covering topics selected by youth and their parents, including support services in college, managing money, and living independently. Mentors were those with similar disabilities, who lived independently, had an active vocation, and presented a positive view of disability and were matched to youth based on gender, interests, and similarity of challenge. Youth and their mentors were also invited to attend community activities, including visiting the mentor’s college or place of employment, and participating in a recreational activity such as skiing or skating. Parents also received additional information and support, such as a guide that described the intervention approach and telephone calls and home visits to review the youth’s progress.
Forty-three youth from four high schools in New Hampshire (n=14), Oregon (n=9), Wisconsin (n=10), and North Carolina (n=10) participated in the study. These youth were recruited from youth identified by educators at each school who met the following criteria: had a learning, emotional, orthopedic, or other health disability, received special education services, did not actively participate in their transition planning meetings, and lived with their families. Following parental consent to participate, youth were randomly assigned to the intervention group (n=21) or a wait-list control group (n=22). The mean age of participants in the intervention and control groups was 15.5 years, 60% were male, 74% were Euro-American, 7% were African American, 14% were Hispanic, and 5% were Asian, 42% were classified with a combination of disabilities. Furthermore, 43% of youth in the intervention group and 41% of youth in the control group had attended their prior year’s transition planning meeting, and mean scores on the Vineland Adaptive Behaviors Scale were 78.2 and 74.5, respectively, for youth in the intervention and control groups. Youth in the intervention and control groups did not differ significantly on any of the above factors.
Outcome measures were completed at baseline and following the intervention by youth, their parents, and an educator most familiar with the youth’s transition planning. Participating youth completed the Educational Planning Assessment (EPA), a 14-item Likert scale assessing their involvement in transition planning (example questions are “I meet with school staff before my meeting to plan it” and “I help run my transition planning meeting”). Parents and the identified educators also completed a version of the EPA. In addition, youth and parents completed the Transition Awareness Survey, a 14-item scale assessing their respective awareness of transition planning requirements and resources (example questions are “I understand the federal transition requirements as they apply to me” and “I am aware of agencies that can assist me with employment after I complete high school”). The Family Empowerment Scale, a 34-item measure that assesses the extent to which respondents perceive themselves as managing their day to day situations, accessing services, and advocating on behalf of others, was also completed by youth.
A repeated measures two-factor analysis of covariance was used to evaluate whether levels of change, from pre- to post-test, in scores on outcome measures differed between youth in the intervention and control groups. Analyses adjusted for participant age, adaptive function, ethnicity, gender, grade, site, and prior IEP meeting attendance. Effect sizes were calculated.
Powers and colleagues (2001) found that youth in the intervention group had significantly greater improvements in their involvement in educational planning activities compared to youth in the control group. Furthermore, both parents and educators in the intervention group reported significantly greater improvements in the student’s participation in educational planning.
Powers and colleagues (2001) found no significant difference between youth in the intervention and control groups in changes in transition awareness. The difference, however, favored the intervention group in a positive direction large enough to indicate an association of substantive magnitude. Furthermore, parents of youth in the intervention group had significantly greater improvements in reported transition awareness, from pre- to post-test, compared to parents of youth in the control group.
Powers and colleagues (2001) found that youth in the intervention group had significantly greater improvements in scores on the self-report measures of student empowerment from pre- to post-test compared to youth in the control group.
Youth participation in transition planning meetings was assessed via an observational coding system. More specifically, two observers coded videotaped transition meetings to measure student initiation (coded if the student initiated discussion or requested another person to initiate discussion), student participation (coded if student responded verbally to another participant’s initiation or demonstrated nonverbal engagement with the speaker), student non-participation (coded if the student did not engage verbally or nonverbally), other participant initiation (coded when other participant either initiated discussion or abruptly changed the topic of the youth’s conversation), other participant response to student (coded when other responded verbally or nonverbally to the youth), and other participant non-response to student (coded student initiation was followed by no response from the other participants). Mean inter-observer agreement ranged from 96% to 99% for the six coded categories.
In analyses of these observational data, Powers and colleagues (2001) found significant group differences in assessed levels of student initiation, student non-participation, other participant initiation, and other participant response to student. Youth in the treatment group were significantly more likely to initiate discussions and participate in discussions than youth in the control group. Additionally, other participants were significantly more likely to initiate discussions with and respond to youth in the intervention group than youth in the control group.
Evidence Classification: Promising
Collier (2009) examined correlates of strategies for setting and working on mentee goals as part of a multi-component evaluation of an e-mentoring program for high school students with mild learning disabilities that was designed to improve their ability to identify postsecondary career goals and the steps necessary to achieve them. College student mentors engaged students in transition-related learning modules designed around central thematic topics covering three primary areas: 1) discovering oneself, 2) exploring possibilities, and 3) creating an action plan. The student mentees accessed learning modules on a password-secured website from the student resource room or the computer lab at their high schools. Each learning module consisted of weekly lesson plans implemented over 12 weeks. Each lesson plan provided the mentors with structured materials, a list of activities, and additional tips to guide their mentees in career and education exploration. The mentors had the option of customizing the lesson plans to suit their mentees’ needs and interests. Each weekly scheduled lesson plan was implemented over two separate electronic contacts between the mentor and mentee. At the end of each module, mentees completed the Mentee Summary Review, in which they summarized what they had learned from their weekly interaction with their mentors. The mentors reviewed their mentees’ monthly summaries to track their progress in acquiring personal transition competency. Furthermore, the researcher was able to access and monitor all incoming and outgoing online correspondence between the mentor and mentee.
Additionally, all participating students were invited to the mentors’ university for two events during the semester. The first campus visit was an orientation to student resources on campus, such as Financial Aid, Career Services, Tutoring Services, and Center for Disability Studies, followed by a campus tour. A subgroup of mentors served as tour guides during the orientation visit. On the second campus visit, students viewed a video of a large college class to introduce them to what it was like to take a college-level course. Students and mentors then discussed the differences between high school and college classes and strategies for succeeding in college. Following this, the mentors and mentees had lunch together to provide further opportunity for in-person interaction and learning about each other.
Counselors and special educators at eight urban high schools referred students who were enrolled in the 10th through 12th grades, classified as having a learning disability, on an Individualized Educational Program (IEP), had at least a 4th grade reading level score, and had no history of mental illness. The study sample included 102 students who were randomly assigned, by grade and gender, into the intervention (n=51) or control (n=51) groups. Participating students were 54 percent male and 46 percent female. Most were white (71%) with the remaining students belonging to another racial or ethnic group (29%). The mentors were selected from a pool of college students who showed interest in participation and who were affiliated with the Special Education–Human Exceptionality program, a Service Learning Scholar, or a student with a disability recommended by the Center for Disability Services. Fifty-one college students were recruited to serve as mentors. Majority of mentors were female (8%) and white (84%), and 14% had a disability.
This evaluation assessed the impact of the intervention on transition competency, self-determination, academic connectedness, and social connectedness. Outcome measures were collected from students, their parents, and their special education teacher at the beginning (baseline) and end of the program. The Transition Competency Questionnaire consisted of 15 open-ended questions that required students to fill in the blanks related their involvement in planning, decision-making, and direction of their postsecondary career interests and goals. Responses were scored by the researcher based on a standardized rubric. In addition, special education teachers of the participating students were asked to evaluate the student-developed career/educational interests (part of the transition competency assessment) as realistic or not considering the student’s interests and disability. The parents and special education teacher of participating students were asked to rate their perceptions of the appropriateness of their student’s responses to the Transition Competency Questionnaire. Students’ level of self-determination was measured using the American Institution of Research’s Self-Determination Scale, which consists of 30 items assessing three constructs: capacity–opportunity, home and school, and knowledge–ability–perception. The Hemingway Measure of Adolescent Connectedness (MAC), a 78-items scale, was used to assess students’ connectedness with familial, social, and academic aspects of their lives. The Youth Mentoring Survey (YMS), a 25-item scale completed by students, was used to measure positive and negative perspectives of the mentoring relationship. Mentors also completed the Match Characteristics Questionnaire, 65-item scale that measures the mentor’s perspective on the quality of the mentoring relationship. Students also completed the Individualized Education Program Familiarity Survey, which consisted of 14 questions assessing student familiarity with their Individualized Education Program (IEP). Demographic information on students, including age, gender, disability classification, current grade level, GPA, free and reduced school lunch status, and access to a home computer, were extracted from school and IEP files.
Independent sample t-tests were conducted to test for baseline equivalency of the intervention and the control groups on the outcomes. The intervention and the control groups did not differ significantly on the outcomes at baseline. Repeated measures of analyses of variance were conducted to determine the overall effect of participation in the intervention on each outcome.
The intervention and control groups differed significantly in transition competency from pre- to post-intervention; youth in the intervention group improved in their transition competency scores from pre- to post-intervention, whereas scores for youth in the control group declined slightly during the same time period.
A significant difference was observed between the intervention and control groups in their self-determination scores from pre-to post-intervention. Youth in the intervention group showed a gain in their self-determination scores from pre- to post-intervention, whereas scores for youth in the control group remained about the same.
There was no significant difference between youth in the intervention and control groups in self-reported connectedness to the academic aspects of their lives.
The intervention and control groups differed significantly in self-reported social connectedness from pre- to post-intervention. Social connectedness scores increased from pre- to post-intervention for youth in the intervention group, but declined for those in the control group.
Collier (2009) also examined effects of the intervention on self-report familial connectedness and found no significant difference between youth in the intervention and the control groups. In addition, Collier (2009) tested for subgroup differences in intervention effects by student race (Caucasian vs. non-Caucasian), socioeconomic status, grade point average (GPA), grade level, and degree of realism (teachers’ evaluations of the realism of students’ goals). For white students, there was a greater estimated positive effect on transition competency than among nonwhite students. In addition, estimated benefits of the intervention for social connectedness were greater for students with a lower GPA in comparison with students with a higher GPA.
External Validity Evidence:
Variations in the Practice
The format of practices related to setting and working on mentee goals was limited in range across the reviewed studies. In four of the studies (Collier, 2009; DuBois & Keller, 2017; Powers et al, 2001, 2012), goal-setting was part of a multi-component mentoring intervention. Additionally, these studies involved the use of relatively structured, curriculum-based goal setting and pursuit activities that mentees and mentors worked on jointly. In contrast, Wheeler & DuBois (2009) provided limited information about the content areas addressed since BBBS affiliates were asked only to indicate whether they set goals focused on the Little’s development. Taken as a whole, available findings suggest the promise of relatively structured approaches to engaging mentors and mentees in interactions directed at goal setting and pursuit, whereas comparable evidence regarding the value of less structured approaches and other possible practice variations (e.g., separate training on goal setting and pursuit strategies for mentors) is lacking.
In 3 of the 4 studies for which evidence was found to support the practice (i.e., rating of Promising or Effective) the youth involved were identified as having a learning or other type of disability. As such, the effectiveness of the practice in relation to youth without identified disabilities is largely unstudied, although the remaining supportive study (DuBois & Karcher, 2017) did report supportive findings for a sample of youth identified as at risk for delinquency. Likewise, samples in the former three studies were predominantly White, whereas the DuBois & Keller (2017) sample was about half African American. The four supportive studies also primarily involved somewhat older youth (e.g., high school age). Notably, only one study tested for differences in effects of the practice across subgroups of youth (Collier, 2009). In sum, available findings provide only a limited basis for developing an understanding of the potentially similar and/or differential implications of this practice based on characteristics of the youth being mentored.
Mentors in the DuBois & Keller (2017) and Wheeler & DuBois (2009) studies were adult volunteer mentors, whereas in the two Power and colleagues (2001, 2012) studies, coaches were program staff, supervised graduate students, or secondary educators within the school district and in the Collier (2009) study mentors were college students, predominately female and white. The studies reviewed did not test for differences in effect of strategies for setting and working on mentee goals in relation to these mentor characteristics or others that potentially could be consequential for this practice, such as experience with use of goal-setting tools. Overall, evidence in support of this practice is concentrated on applications in which mentors have some level of professional experience or training in a helping profession, thus leaving the merits of use with other types of volunteers (e.g., general community volunteers) less clear.
All the studies in this review were conducted within mentoring programs that use a 1-to-1 mentoring format. Four of the five studies (Collier, 2009; DuBois & Keller, 2017; Powers et al, 2001; 2012) were conducted within multi-component programs (i.e., one that combined mentoring with other supports or services for the youth being mentored). Notably, one study Collier (2009) evaluated the practice within an e-mentoring program format with favorable results, thus suggesting the promise of the practice within programs utilizing both traditional face-to-face and web-based formats for mentor-mentee interaction. Furthermore, all of the programs evaluated in the reviewed studies provided opportunities for mentoring interaction in varied settings (e.g., in the Powers and colleagues studies (2001, 2012) mentoring interactions occurred within the school and the community and those in the Collier (2009) study occurred online as well as at a local college). Overall, understanding of the implications of this practice across varying program settings and structures is limited, in part due to a lack of tests for differences in potential effects of the practice along such dimensions within studies.
Three of the four studies reviewed with supportive evidence for the practice evaluated the effects of setting and working on mentee goals on outcomes related to the transition to independent living among young persons with identified disabilities (Collier, 2009; Powers et al., 2001, Powers et al., 2012). The remaining study (DuBois & Keller, 2017) evaluated the effects of the practice on youth perceptions of support received from adults for thriving, thus providing evidence of potential effects of the practice on a broader range of outcomes. Notably, no study, other than one which did not meet criteria for rigor, examined potential effects of the practice on mentoring relationship outcomes, such as duration or relationship quality. Overall, available findings do not provide a basis for understanding potential effects of this practice on the range of outcomes of potential interest.
Resources Available to Support Implementation:
Resources to support implementation of strategies for setting and working on mentee goals can be found under the Resources section of this website. These include:
Discovering the Possibilities: “C”ing the Future – This resource is geared towards helping young people explore college and careers opportunities. It contains a series of twelve modules designed to be completed during meetings between mentors and mentee. Each module follows a similar format with the following sub-sections: Background (a brief introduction to the topic and its relevance); Activity (step-by-step instructions for how to cover the topic with mentees); and Tips for Mentors (special instructions or things to keep in mind). One of the 12 modules focuses on helping mentees develop personal goals around exploring college and career options.
Finding Mentors, Findings Success – This resource is designed to help youth think about where they are at in life, what they liked from their previous mentoring relationships, and how future mentors could offer new forms of support and guidance. Planning worksheets and other prompts encourage the mentee to think about the help he or she will need in meeting goals, while tips on making “the ask” attempt to take some of the fear and awkwardness out of approaching someone and asking that person to take on a mentoring role.
Collier, M. L. (2009). An investigation study of the effects of e-mentoring on transition planning for secondary students with learning disabilities. Doctoral Dissertation. Salt Lake City, Utah: University of Utah.
DuBois, D. L., & Keller, T. (2017). Investigation of the integration of supports for youth thriving into a community-based mentoring program. Child Development. https://doi.org/10.1111/cdev.12887
Powers, L. E., Geenen, S., Powers, J., Pommier-Satya, S., Turner, A., Dalton, L. D., … Swank, P. (2012). My Life: Effects of a longitudinal, randomized study of self-determination enhancement on the transition outcomes of youth in foster care and special education. Children and Youth Services Review, 34, 2179–2187. https://doi.org/10.1016/j.childyouth.2012.07.018
Powers, L. E., Turner, A., Westwood, D., Matuszewski, J., Wilson, R., & Phillips, A. (2001). Take Charge for the Future: A controlled field-test of a model to promote student involvement in transition planning. Career Development for Exceptional Individuals, 24, 89–104. https://doi.org/10.1177/088572880102400107
Wheeler, M., & DuBois, D. L. (2009). Analysis of responses to agency practices survey for Big Brothers Big Sisters of America’s community-based mentoring program. Unpublished report prepared for Big Brothers Big Sisters of America.
Arbeit, M., Bowers, E., Chase, P., Napolitano, C., Lerner, J. V., & Lerner, R. M. (n.d.) Goal setting, pursuit of strategies, and shifting gears: A guide to the literature about intentional self regulation among youth. Medford, MA: Tufts University, Institute for Applied Research in Youth Development. Retrieved from http://www.thrivefoundation.org/wp-content/uploads/2014/11/GOAL-SETTING-PURSUIT-OF-STRATEGIES-AND-SHIFTING-GEARS.docx
Balcazar, F. E., & Keys, C. B. (2014). Goals in mentoring relationships. In D. L. DuBois & M. J. Karcher (Eds.), Handbook of youth mentoring (2nd ed., pp. 83–98). Thousand Oaks, CA: SAGE
Baltes, P.B. (1997). On the incomplete architecture of human ontogeny: Selection, optimization, and compensation as foundations of developmental theory. American Psychologist, 52, 366–380. http://dx.doi.org/10.1037/0003-066X.52.4.366
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall
Bowers, E. P., Wang, J., Tirrell, J. M., & Lerner, R. M. (2016). A cross-lagged model of the development of mentor-mentee relationships and intentional self-regulation in adolescence. Journal of Community Psychology, 44, 118–138. http://dx.doi.org/10.1002/jcop.21746
Bowers, E. P., Napolitano, C. M., Arbeit, M. R., Chase, P., Clickman, S. A., Lerner, R. M., and Lerner, J. V/ (2013). On the pathway towards thriving: Evaluating the effectiveness of tools to promote positive development and intentional self regulation in youth. Journal of Youth Development, 8, 1–28. Retrieved from https://doi.org/10.5195/jyd.2013.82
Garringer, M., Kupersmidt, J., Rhodes, J., Stelter, R., & Tai, T. (2015). Elements of effective practice for mentoring (4th ed.). Boston, MA: MENTOR: The National Mentoring Partnership.
Gestsdóttir, S., & Lerner, R. M. (2007). Intentional self-regulation and positive youth development in early adolescence: Findings from the 4-H Study of Positive Youth Development. Developmental Psychology, 43, 508–521. http://dx.doi.org/10.1037/0012-16188.8.131.528
Lau, W. S. Y., Zhou, X., & Lai, S. M. K. (2017). The development of mentoring-relationship quality, future-planning style, and career goal setting among adolescents from a disadvantaged background. PsyCh Journal, 6, 76–82. http://dx.doi.org/10.1002/pchj.152
Lerner, R. M., Lerner, J. V., Almerigi, J., Theokas, C., Phelps, E., Gestsdottir, S. . . . von Eye, A. (2005). Positive youth development, participation in community youth development programs, and community contributions of fifth grade adolescents: Findings from the first wave of the 4-H Study of Positive Youth Development. Journal of Early Adolescence, 25, 17–71. http://dx.doi.org/10.1177/0272431604272461
Li, Y., Lerner, J. V., & Lerner, R. M. (2010). Personal and ecological assets and academic competence in early adolescence: The mediating role of school engagement. Journal of Youth and Adolescence, 39, 801–815. https://doi.org/10.1007/s10964-010-9535-4
Mueller, M. K., Phelps, E., Bowers, E.P., Agans, J. P., Brown Urban, J. & Lerner, R. M. (2011). Youth development program participation and intentional self-regulation skills: Contextual and individual bases of pathways to positive youth development. Journal of Adolescence, 34, 1115–1125. https://doi.org/10.1016/j.adolescence.2011.07.010
Zimmerman, S., Phelps, E., & Lerner, R. M. (2007). Intentional self-regulation in early adolescence: Assessing the structure of selection, optimization, and compensations processes. European Journal of Developmental Science, 1, 272–299. https://doi.org/10.3233/DEV-2007-1310