A Comparison of Strengths and Interests Protocols in Career Assessment and Counseling

Abstract

This study examined the relative performance of three career counseling protocols: a strengths-based protocol, an interest-based protocol, and a protocol that combined strengths and interests. Outcome measures included career exploration, occupational engagement, career decision self-efficacy, hope, positive and negative affect, and life satisfaction pre- and post-intervention. The participants consisted of 82 undergraduate students enrolled in a career and life-planning course. Each participant received a career counseling intervention and a Strong Interest Inventory (SII), StrengthsFinder, or both the SII and StrengthsFinder interpretation. While all three groups showed significant gains from pretest to posttest on most outcomes, results suggest the interests protocol (IP) was the most effective approach when considering the conservation of resources. However, results also merit further exploration of the combined protocol (CP; strengths plus interests) given the greatest gains were achieved by this approach on all but one construct, though not significantly different from the IP. Implications are discussed.

Keywords

strengths career intervention career assessment career course positive psychology career exploration

Discussing client interests has long been an integral part of the career counseling process. Exploring interests is postulated to help clients make informed decisions about occupational and educational choices, provide information to counselors that helps guide career exploration, and help clients identify unknown interests and solidify existing interests (Hansen, 2005). The Strong Interest Inventory (SII) is the instrument most commonly used by career counselors and vocational psychologists and the instrument most frequently recommended to trainees (Watkins, 1994). The SII has proven itself a reliable, valid, and useful tool when working with clients (Donnay, Morris, Schaubhut, & Thompson, 2005).

Over the past two decades, the positive psychology movement has been increasingly supported through both theory and outcomes of psychological interventions (see Magyar-Moe, Owens, & Conoley, 2015). The purpose of this study was to examine whether career counseling protocols might similarly benefit from the inclusion of a strengths component. Specifically, outcomes related to three different career counseling interventions were compared: one focused on interests alone, another focused on strengths alone, and the last included a combination of both strengths and interests.

Interests in Career Assessment and Counseling

While the definition of “interest” is a point of contention, there are several things upon which career theorists agree: Interests are developed by a combination of nature and nurture (Hansen, 2005) and “interests develop from what we do well and what we enjoy doing” (Linley, 2006, p. 319). At a basic level, career interests indicate the strength of preferences for particular occupational activities and contexts (Holland, 1997). The progenitor of career counseling, Frank Parsons (1909), postulated that person–environment fit was integral for selecting an optimal career path and that successful career decisions are guided by matching individual traits to occupational characteristics. Some version of this model has dominated vocational theory for the past century (Savickas, 2000), and it is still the dominant model in the practice of career counseling (James & Gilliland, 2003). Personal interests have played a prominent role in the quest to match pertinent individual characteristics with potential vocational/educational opportunities. Although protocols are varied and usually multidimensional, the interpretation of an interest inventory is the cornerstone of career counseling interventions (Tinsley & Chu, 1999).

Interest-based counseling techniques are the most common interventions employed by career counselors (Betsworth & Fouad, 1997), and the literature base related to the role of interests in career assessment is long and robust (Betsworth & Fouad, 1997; Harrington & Long, 2013). There are innumerable interest inventories available for use by career counselors, though many include other aspects pertinent to career exploration, such as confidence indicators or environmental preferences. The most popular interest inventories include the SII (Donnay, Thompson, Morris, & Schaubhut, 2004), the Self-Directed Search (Holland, 1994), and the Kuder Occupational Interest Survey (Zytowski, 2001).

Two meta-analyses of the effects of career interventions (Oliver & Spokane, 1988; Whiston, Sexton, & Lasoff, 1998) have demonstrated the positive effects they have on general functioning, such as interviewing ability, writing skills, problem-solving skills, self-esteem, and cognitive complexity. A number of career-specific domains have also been found to be significantly improved by career counseling, with particularly robust improvements in “career certainty decidedness” and “career maturity.” Both of the meta-analyses indicate that individual career counseling is more effective than either group counseling or computer-based interventions. More specifically, career counseling techniques that utilize interest interventions have been found to increase career exploration (Randahl, Hansen, & Haverkamp, 1993) and reduce vocational decision-making difficulties (Di Fabio & Gideon, 2013).

The effectiveness of interest inventories can be measured by a number of ways. Several studies have focused on the “congruence” between idiosyncratic interests as measured by interest inventories and the educational or occupational track subsequently selected. Among college students, the concurrent match rates between interest assessments and college major exceed 70% (Hansen & Neuman, 1999). Based on a review of the research, Betz (2008) concluded that people tend to choose and remain in congruent environments. Further, Betz, Borgen, and Harmon (2006) determined that approximately 80% of the variance associated with differences across groups in educational/occupational fields are associated with the environmental themes examined by Holland’s Occupational Theme (RIASEC) interest scores. Overall, it appears that interest assessments reflect the environments toward which individuals eventually gravitate.

There is less certainty regarding how well interest–environment congruence can predict one’s ability to thrive within a particular environment. A meta-analysis by Spokane, Meir, and Catalano (2000) suggests that congruence is only weakly related (correlation coefficient of approximately .25) to important outcome factors such as job satisfaction and performance. A follow-up study found an even weaker relationship (correlation coefficient of .17) between measures of vocational success and congruence, and these outcomes were significantly moderated by factors such as culture and gender (Tsabari, Tziner, & Meir, 2005). These results have led some to conclude that although interest inventories offer important information, they have limited utility when interpreted in isolation (Prediger, 1999).

Interest-based counseling techniques rely on the assumption that the results will be accurately interpreted by the counselor, communicated with fidelity, understood by the client, and remembered long enough for the client to generate and enact a strategy. Studies indicate that recall of information provided to clients regarding scores on interest inventories such as the SII is generally poor (Hansen, Kozberg, & Goranson, 1994; Tinsley & Chu, 1999), and approximately half of the information that was recalled was erroneous (Swanson et al., 2006). The quality of recall increases when the interpretation of results contains less information (Swanson et al., 2006) and when feedback incorporates an element of verbal persuasion (Luzzo & Day, 1999). Further, clients who perceived the interpretive feedback session to be interactive and personally relevant viewed the information as more influential (Hanson, Claiborn, & Kerr, 1997).

Given the popularity and utility of interest-based assessments and techniques, it is worth considering ways to augment career counseling protocols in order to address problems associated with the applicability and personal utility of interest information. Chartrand, Borgen, Betz, and Donnay (2002) emphasized the importance of analyzing and discussing career self-efficacy as a means to increase career exploration behaviors and self-relevance. They suggest that the integration of interest and self-efficacy will lead to a more informative, holistic, and helpful prioritization of available options than will a single focus on interests. The authors also recommend exploring vocational options for which the client is both high in interest and high in confidence. Thus, career counseling interventions may specifically increase either interest levels or confidence to expand the number of careers that fall into this category. Chartrand et al. described how interventions based on Bandura’s (1977) self-efficacy theory may be used throughout the career counseling process, with the explicit goal of increasing vocational confidence. Broadly, these interventions include (a) supplying a sense of performance accomplishment by recommending small, elementary tasks that have a high chance of success, such as basic classes, workshops, or community education; (b) interacting with and observing successful models with whom the client closely identifies (i.e., same ethnicity, gender, etc.); (c) fostering antianxiety coping mechanisms to promote self-sufficiency and facilitate approach behavior; and (d) explicit reinforcement of client behavior by therapists and others.

Betz and Schifiano (2000) tested the effects of a three-session intervention designed to increase self-efficacy for women with high interest but low self-efficacy for “realistic” career domains. The treatment had a significant influence on participant’s self-efficacy in this area. According to Betz and Schifano, the average change in self-efficacy would result in a significantly different interpretation when engaged in career counseling. The change in self-efficacy scores was sufficient to change the interpretation for realistic careers from marginal importance to one that would be considered a “high priority” for the average program participant, indicating that the intervention influenced the participants’ self-efficacy to such a degree that it altered assessment results.

In summary, it appears that interest inventories provide valuable information to career counselors and clients alike. However, their usefulness can be significantly improved through the assessment and integration of personally relevant information and increasing client self-efficacy. A strengths-based approach is, potentially, one way to efficiently augment interest-based counseling techniques.

Strengths’ Presence in Vocational Psychology

In its most simplistic definition, strengths are what people do well. More specifically, strengths are a “capacity for behaving, thinking, or feeling in a way that allows optimal functioning and performance in the pursuit of valued outcomes” (Linley & Harrington, 2006, p. 88). Strengths, as defined by Hodges and Clifton (2004), are an extension of and develop from talents or “naturally recurring patterns of thought, feeling, and behavior that can be productively applied” (p. 257). Strengths represent the near-perfect performance of a task through the combination of one’s talents, knowledge, and skills. The optimal use of human strengths has been the goal of vocational psychology since the work of the field’s founder, Frank Parsons. Parson’s goal was to help people make a “wise” vocational choice. He strove to do so by implementing a three-step process, which included exploration of the self, exploration of the world of work, and selection of opportunities that represent a fit between the two (Robitschek & Woodson, 2006).

Following Parson’s lead, vocational psychology has established a long history of focusing on individuals’ strengths and improving lives (Robitschek & Woodson, 2006). This positive focus can easily be observed through the positive language used in vocational research, including “improving job satisfaction” (Holland, 1997), “career well-being” (Kidd, 2008), and “work hope” (Juntunen & Wettersten, 2006). Although no vocational theory explicitly claims to borrow elements from positive psychology, themes between the two are very similar and they often share an emphasis on self-esteem and self-efficacy (Robitschek & Woodson, 2006). For example, Brown and Krane (2000) reported that satisfying work strongly correlates with overall life satisfaction. Tinsley, Hinson, Tinsley, and Holt (1993) found that work provides opportunities for feelings of accomplishment and satisfaction and expressions of altruism and responsibility.

Savickas (2003) argued that, contrary to Seligman’s (1998) claim that psychology needed to reinstate its goal of “building human strength,” counseling psychology (including vocational psychology) has continuously pursued this goal. Savickas outlined a career adaptability taxonomy of coping attitudes, beliefs, and competencies that subsumes the virtues identified by Seligman (1998), including courage, optimism, interpersonal skill, hope, perseverance, and work ethic. Savickas posited that career education and counseling can help build client strengths.

Identifying and promoting strengths offers a unique perspective for individuals seeking a career or those who are currently in one. Prior to the career exploration process (e.g., asking questions, gathering information, and interacting with various environments related to the world of work; Super, 1983), identifying strengths would likely be beneficial to determine how they can be applied to the available options. Once an individual is actively participating in a career, Ondeck (2002) postulated careers and lifestyles can be self-directed to revolve around these strengths. Likewise, Linley (2006, p. 318) posited individuals can “play to their strengths” or effectively adapt to varying environments by using one’s strengths.

The extent to which an individual can adapt to their work roles and environment is an essential component to maintaining life satisfaction. Bellah, Madsen, Sullivan, Swidler, and Tipton (1996) defined three ways an individual may orient themselves to their occupations: They may consider it a job, a career, or a calling. Individuals with a job orientation do not value their work and are primarily motivated by money, whereas individuals with a career orientation are likely to enjoy their work and are motivated by both primary (i.e., money) and secondary (i.e., social status) sources. People with a calling orientation enjoy and value what they do in and of itself. Not surprisingly, individuals with a calling orientation are more satisfied with their work and their lives. Wrzesniewski, McCauley, Rozin, and Schwartz (1997) found that across occupations, individuals fell into all three categories. Moreover, individuals within the same occupation fell into all three categories evenly. This suggests individuals have the ability to create positive meaning in their work (Wrzesniewski, 2003), and the use of strengths may contribute to this goal (Linley, 2006). Further, modifying specific occupational tasks and the way individuals interact with people they work with can create more satisfaction and lead to a calling orientation (Wrzesniewski, 2003).

Strength-Based Assessment and Interventions

There are currently two measures of strengths that exist for the adult population. These include the VIA Inventory of Strengths (VIA-IS; Peterson & Seligman, 2004) and the Clifton StrengthsFinder (Asplund, Lopez, Hodges, & Harter, 2005).

The incorporation of strength identification and development in interventions designed for the student population has shown substantial success across a number of domains. Gallup conducted a four-year study at an urban high school involving a strength-based intervention (Harter, 1998). Teachers administered talent-based interviews on incoming freshmen each year followed by individualized feedback to the students highlighting their strengths. Students who participated in the intervention had significantly fewer absences, were late to class less often, and had a higher grade point average (GPA) than those who did not participate.

Within the university population, several strength-based interventions have also shown success. Williamson (2002) conducted a study in which the intervention group took the StrengthsFinder, participated in two one-hour sessions about their strengths and a one-on-one advising session with a trained professional. Students who participated in the strengths intervention obtained higher GPAs. Austin (2005) found college freshman benefited from a strength-based intervention as well. As part of a six-week program, students took the StrengthsFinder, were asked to use their strengths in the academic setting, and discussed the development of their strengths with their instructors. The intervention group had significantly higher academic self-empowerment, efficacy, and expectancy as well as extrinsic motivation. Freshmen college students in a public speaking course also benefited from a strengths-based intervention (Cantwell, 2005). Students in the course participated in four sessions of a strength-based intervention, which included identifying strengths with the StrengthsFinder and identifying strengths they would intentionally use in reading a chapter in the course textbook, when studying for an exam, and throughout the course. Students who received the strengths intervention scored significantly higher on exams, performed significantly better on videotaped speeches that were rated blindly, and had significantly greater levels of academic engagement.

Strength-based interventions have also been successful in relation to the work environment. Employees at a warehouse completed the StrengthsFinder and participated in sessions to learn about their results and ask any questions (Connelly, 2002). The warehouse managers attended a four-day course that discussed the theory and practice of managing their employees with a strengths framework. Lastly, all employees came together for a half-day session to encourage thinking about the groups’ strengths and how to optimally work together. A year following this intervention, individual productivity had improved substantially.

Strengths in Career Assessment and Counseling

While theory and research in academic and work settings suggest identifying strengths and implementing strengths-based interventions are beneficial, there has only been one study that has examined the effects of identifying strengths and implementing a strengths-based intervention in a career counseling context (Littman-Ovadia, Lazar-Butbul, & Benjamin, 2014). This intervention involved four counseling sessions with a sample of unemployed adults. The participants learned about their VIA strengths and were asked to use their strengths in their job search. The strengths-based intervention led to increased use of strengths (as did the comparison group) and increased self-esteem but no increase in career exploration or life satisfaction. At a three-month follow-up, the strengths-based group also reported a higher employment rate, and they rated the intervention as having made a greater contribution.

The Current Study

Few studies have examined the use of multiple assessment instruments in career interventions. Katz, Joyner, and Seaman (1999) demonstrated the combined use of the SII and the Myers–Briggs Type Indicator (MBTI) in career counseling was more effective than the use of either alone. Most of the studies that have used multiple instruments were published in the 1970s (Katz, Joyner, & Seaman, 1999; O’Neil, Price, & Tracey, 1979; Takai & Holland, 1979; Talbot & Birk, 1979). It is clear that further exploration is needed to examine the combined use of career-related instruments, including the use of strengths assessment.

Incorporating a strengths component into career counseling could potentially increase career exploration (Robitschek & Woodson, 2006) along with well-being (Dik & Hansen, 2008). Although theory supports the incorporation of strengths into career counseling (Robitschek & Woodson, 2006), to date, only one such study has examined the impact of utilizing strengths assessment in career counseling, and no such study exists with the college student population with a focus on a number of positive psychological outcome variables (i.e., hope, positive and negative affect, and life satisfaction). Examining the combined use of interest and strength instruments in career counseling has the potential to build upon effective techniques and provide additional options for interventions and assessments in career counseling.

Method

Participants

The participants in this study were 82 undergraduate students, 42 females and 40 males, who were enrolled in one of six available sections of a career- and life-planning course within one semester at a large Midwestern university. There were 26 students in the sections who utilized the interest protocol (IP), 25 students in the strengths protocol (SP), and 31 students in the combined protocol (CP). The mean age was 18.72 (SD = .81). Of the participants, 80.5% identified as Caucasian, 13.4% as African American, 2.4% as Latino, and 3.7% as another ethnicity. The sample consisted of 51.2% first-year students, 42.7% sophomores, 4.9% juniors, and 1.2% seniors. Classes included students across the range of ages and academic standing.

Instruments

Strong Interest Inventory

The version of the SII used in this study consisted of five sections, including scores on six general occupational themes (GOTs), 30 Basic Interests Scales (BISs), 122 Occupational Scales (OSs), 5 Personal Styles Scales (PSSs), and administrative indexes to identify unusual profiles (Donnay et al., 2005). In total, the SII consists of 193 items and utilizes a 5-point Likert-type scale for all items. The GOTs are based on Holland’s Theory and organized into six themes—realistic, investigative, artistic, social, enterprising, and conventional. All six GOTs have an internal consistency reliability of at least .90 and test–retest reliabilities averaging .87 across all themes. The GOTs are highly related to scores on Holland’s Vocational Preference Inventory (median Pearson’s r = .77). The BISs have a test–retest reliability ranging from .74 to .93 and the OSs range from .71 to .93. The internal consistency reliabilities for the PSSs range from .82 to .87 and have test–retest reliabilities ranging from .86 to .91 (Donnay et al., 2005).

Clifton StrengthsFinder

The StrengthsFinder consists of 360 items, of which 256 fall into 34 themes (Asplund et al., 2005). The strengths and corresponding internal consistency reliabilities include: achiever (α = .66), activator (α = .58), adaptability (α = .70), analytical (α = .72), arranger (α = .63), belief (α = .54), command (α = .67), communication (α = .71), competition (α = .70), connectedness (α = .60), consistency (α = .61), context (α = .54), deliberative (α = .70), developer (α = .65), discipline (α = .76), empathy (α = .58), focus (α = .70), futuristic (α = .68), harmony (α = .62), ideation (α = .60), includer (α = .59), individualization (α = .55), input (α = .50), intellection (α = .68), learner (α = .74), maximizer (α = .66), positivity (α = .75), relator (α = .50), responsibility (α = .65), restorative (α = .66), self-assurance (α = .67), significance (α = .68), strategic (α = .64), and winning others over (WOO; α = .76). After the students’ results are scored electronically, they receive a list of their top five strengths listed in order, and the rest of the strengths are not shared. The measure has shown internal consistency between .50 and .76. Test–retest correlations range between .52 and .84 for the various themes (Asplund et al., 2005). Validity has been established with the Big 5 (Harter & Hodges, 2003) and 16 PF (Asplund et al., 2005).

The Career Exploration Survey (CES)

The CES was created to measure the career exploration process, reactions to exploration, and beliefs about exploration (Stumpf, Colarelli, & Hartman, 1983). The CES has 59 items and is made up of 16 dimensions. Two dimensions, frequency and number of occupations considered, consist of only one item each. The dimensions and their corresponding internal consistency reliabilities include environmental exploration (α = .83), self-exploration (α = .88), number of occupations considered, intended-systematic exploration (α = .74), frequency, amount of information (α = .79), focus (α = .86), satisfaction with information (α = .85), explorational stress (α = .71), decisional stress (α = .85), employment outlook (α = .88), certainty of career exploration outcomes (α = .78), external search instrumentality (α = .67), internal search instrumentality (α = .89), method instrumentality (α = .80), and importance of obtaining preferred position (α = .81). The majority of the items utilize a Likert-type scale from 1 to 5, and a few items use a Likert-type scale from 1 to 7. Coefficient αs for each dimension are .67 or above, with 85% of the dimensions having αs of .75 or higher. The CES is also sensitive to change over time based upon behavioral changes in participants (e.g., reactions to information and beliefs about exploration).

Occupational Engagement Scale–Student (OES-Student)

The OES-Student (Cox, Krieshok, Bjornsen, & Zumbo, 2015) measures a college student’s engagement or “taking part in behaviors that contribute to the career decision-maker’s fund of information and experience of the larger world, not just the world as processed when a career decision is imminent,” ultimately aiding in adaptive career decision making (Krieshok, Black, & McKay, 2009, p. 284). The measure consists of 9 items and utilizes a Likert-type scale from 1 (not at all like me) to 5 (very much like me). The measure demonstrates adequate reliability, with a coefficient α of .84. The OES-S is positively correlated to a rational thinking style, vocational identity, and openness, conscientiousness, extroversion, and agreeableness in college students (Black, 2006) and in giftedness in high school students (McKay, 2008). The OES-S is positively related to several measures of well-being, college GPA, self-reported gains on several domains while in college, and vocational identity (Cox, 2008).

Career Decision Self-Efficacy—Short Form (CDSE-SF)

The CDSE-SF (Betz & Taylor, 2006) was created to measure one’s confidence in successfully completing the steps necessary to make a career decision. The measure consists of 25 items and utilizes a Likert-type scale from 0 (no confidence) to 5 (complete confidence). The internal consistency reliability yields an α of .94 for the total score. Several studies have demonstrated strong validity for the CDSE (see Betz & Luzzo, 1996).

Hope Scale

The Hope Scale (Snyder et al., 1991) consists of two subscales—the Pathways subscale, which measures an individual’s self-assessed ability to generate multiple routes to achieving a goal, and the Agency subscale, which measures an individual’s self-assessed motivation to achieve their goals. Each subscale has 4 items on a Likert-type scale from 1 (least like me) to 4 (most like me). Internal consistency coefficients were reported from .74 to .84 for the Total Hope score, from .71 to .76 for the Agency subscale, and from .63 to .80 for the Pathways subscale. Test–retest reliability for the total score was reported as .85 over 3 weeks (Anderson, 1988), .73 over 8 weeks (Harney, 1989), and .76 and .82 over 10 weeks (Gibb, 1990; Yoshinobu, 1989).

Positive and Negative Affect Schedule (PANAS)

The PANAS (Watson, Clark, & Telligent, 1988) measures individuals’ experience of a range of positive (e.g., excited and happy) and negative emotions (e.g., sad and ashamed) over a designated time period (e.g., “a few weeks”). The measure is comprised of two scales, Positive Affectivity and Negative Affectivity, and consists of 10 items for each scale on a 5-point Likert-type scale, ranging from 1 (very slightly or not at all) to 5 (extremely). Coefficient αs for the Positive and Negative subscales using “the last few weeks” time frame were .87 for both. Test–retest reliabilities at 8 weeks were .58 for the Positive subscale and .48 for the Negative subscale.

Satisfaction With Life Scale

The Satisfaction With Life Scale (SWLS; Deiner, Emmons, Larsen, & Griffin, 1985) measures global life satisfaction and consists of 5 items that are on a 7-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree). The SWLS coefficient α is reported as .87, and a two-month test–retest correlation coefficient was .82. The authors report adequate validity with other measures of subjective well-being.

Procedure

The interventions for this study were embedded in a full semester undergraduate course in career and life planning. Sections of the course were assigned to one of three conditions: SP, IP, or combined SP and IP. Each group engaged in two sessions, the first session for instrument interpretation and the second for career counseling. In order to control for threats to validity, the two sessions specific to this intervention included the second and third class sessions (of 30 total sessions), and posttesting occurred immediately after the third class session. Overall, the study, including pre- and posttest measure administration, took place over a four-week period.

Four counselors who were employees of a university career center were trained and provided with a protocol for each group. The six course sections and instructors were assigned randomly while also ensuring each counselor led two different groups (e.g., SP and CP) to control for counselor effects. Prior to the two intervention sessions, each participant took each (pretest) measure followed by the SII and the StrengthsFinder. During the first intervention session, each participant received group interpretations of the SII, StrengthsFinder, or both instruments. During the second intervention session, each participant took part in career-related activities catered to their group. Two weeks after the second intervention session, each participant again took the outcome measures (posttest). During those two weeks, students from all groups continued to participate in additional career class activities (e.g., college major’s card sort and e-scavenger hunt) that were consistent across all conditions.

Intervention Session 1

During the first intervention session for each group, the participants were asked to write a story about a time they were at their best (SP), a time they were engaging in an activity they were interested in (IP), or a time they were doing something they were interested in while at their best (CP). The counselor then provided a group interpretation of the StrengthsFinder (SP), SII (IP), or the StrengthsFinder and SII (CP). During the StrengthsFinder interpretation, the counselors discussed the discover (strength-based approach, strength development framework, and discover your strengths) and develop (develop your strengths and domains of leadership strengths) components of the StrengthsFinder report. For the SII interpretation, counselors used the steps recommended by Prince (2007): (a) review the assessment experience, (b) clarify the students’ expectations and goals for the interpretation, (c) provide an overview of the results, (d) discuss the GOTs, (e) discuss the BISs, (f) discuss the OSs, (g) discuss the PSSs, and (h) use the college profile page to summarize the results.

Following the test interpretations, the students completed a worksheet. For the SP, they wrote about when and how they used their strengths in the past and the results of doing so. For the IP, the students wrote about a past experience where they were engaged in their interests related to data, ideas, people, or things. For the CP, they wrote about a past experience where they used their strengths while engaging in their interests. Finally, the counselor assigned homework, asking the students to use one of their top five strengths (SP), participate in an activity they were interested in (IP), or participate in an activity they were interested in that allowed them to use one of their strengths (CP) and to write about that experience.

Intervention Session 2

The second intervention session began by discussing the homework and the students’ experience of the activity. Next, the counselor asked the students to participate in a visualization activity involving a time in their future where they were: (a) “working in a job where everything you do is easy and comes naturally—what makes it so for you? This is a job where your coworkers say, ‘wow, you’re really good at this!’ Describe that job.” (SP); (b) “working in a job you really love and enjoy—what makes it so interesting for you? What motivates you to come to work at this job? Describe that job.” (IP); and (c) “working in a job you really love, enjoy, and everything you do comes easy. What makes it so interesting for you? What makes it so easy for you? Describe that job.” (CP). The counselor then asked the students to write about what they visualized.

Next, the participants worked in groups of three to four to complete a worksheet requiring them to list three activities where they could use their strengths (SP), participate in their interests (IP), or use one of their strengths and participate in their interests (CP) in each of the following areas: student organizations, leadership opportunities, activities off campus, and part-time work/volunteer work. Each group shared with the rest of the class the activities they identified. Lastly, each student completed a goals work sheet where they listed one goal for the semester related to their academics, relationships, and (future) occupation that incorporated the use of one of their strengths (SP), interests (IP), or both strengths and interests (CP). For each goal, the students listed three steps to help achieve their goals.

Results

Repeated measures analysis of variance (ANOVA) was used to test main effects for Condition (interest, strengths, and combined) and Time (pre- and post-intervention) and interactions between condition and time for career exploration, occupational engagement, CDSE, hope, positive and negative affect, and life satisfaction. An a priori α level of .05 was employed.

A main effect emerged for Time. Without considering the type of intervention, participants showed significant increases in several components of career exploration: environmental exploration (related to occupations, jobs, and organizations), F(1, 79) = 70.31, p < .001; intended-systematic exploration, F(1, 79) = 16.16, p < .001; frequency (of career information sought), F(1, 79) = 11.11, p = .001; amount of information (acquired related to occupations, jobs, organizations, and oneself), F(1, 79) = 26.09, p < .001; focus, F(1, 79) = 36.67, p < .001; satisfaction with information, F(1, 79) = 31.89, p < .001; employee outlook, F(1, 79) = 11.57, p = .001; and certainty of career exploration outcomes, F(1, 79) = 7.37, p = .008. CDSE, F(1, 79) = 17.46, p < .001, also increased significantly following the intervention. Descriptive statistics and Wilks’ λ and effect size values for the main effects are included in Table 1. Occupational engagement, hope, and positive and negative affect did not show significant changes over the four weeks between pre- and post-test.

Table 1.
Means and Standard Deviations of Career Decision Self-Efficacy (CDSE), Career Exploration (CE) Variables, and Life Satisfaction.

Variable Condition

Interests Group Strengths Group Combined Group All Participants

Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Pre M (SD) Post M (SD) Wilks’ λ (η²)

CDSE 3.63 (0.43) 3.81 (0.56) 3.76 (0.42) 3.86 (0.48) 3.65 (0.47) 3.93 (0.51) 3.68 (0.44) 3.87 (0.51) .82 (.18)

Environmental exploration (CE) 12.81 (5.61) 16.46 (5.63) 13.00 (5.07) 16.44 (5.28) 10.42 (4.44) 15.19 (5.18) 11.96 (5.11) 15.98 (5.33) .53 (.47)

Frequency (CE) 1.38 (0.64) 1.73 (0.92) 1.20 (0.41) 1.64 (1.04) 1.32 (0.79) 1.61 (0.84) 1.30 (0.64) 1.66 (0.92) .88 (.12)

Amount of information (CE) 7.42 (2.42) 8.50 (2.30) 7.44 (2.80) 8.80 (2.45) 6.45 (2.73) 8.26 (2.61) 7.06 (2.67) 8.50 (2.45) .75 (.25)

Certainty of career exploration outcomes (CE) 7.00 (3.26) 7.88 (3.76) 7.84 (2.94) 7.80 (3.07) 7.48 (2.92) 9.10 (3.07) 7.44 (3.02) 8.32 (3.32) .92* (.08)

Focus (CE) 10.46 (5.23) 13.38 (5.57) 12.20 (4.75) 12.92 (5.26) 10.55 (4.82) 14.71 (4.87) 11.02 (4.93) 13.74 (5.21) .68* (.29)

Satisfaction with information (CE) 15.42 (5.71) 18.12 (5.55) 16.68 (5.26) 18.52 (4.76) 14.84 (6.22) 19.97 (4.68) 15.59 (5.76) 18.94 (5.00) .71 (.27)

Employee outlook (CE) 8.81 (2.59) 9.88 (2.37) 10.16 (2.53) 10.32 (2.31) 8.61 (3.23) 10.81 (2.24) 9.15 (2.88) 10.37 (2.29) .87 (.12)

Self-exploration (CE) 16.69 (4.22) 16.62 (4.22) 16.76 (4.42) 16.72 (3.88) 13.87 (4.31) 16.13 (3.73) 15.65 (4.48) 16.46 (3.89)

Intended exploration (CE) 7.04 (2.71) 8.46 (2.12) 7.64 (3.08) 7.84 (2.58) 5.84 (2.48) 7.81 (2.75) 6.77 (2.82) 8.02 (2.50) .83* (.16)

Life satisfaction 25.92 (4.73) 27.81 (4.39) 27.16 (5.91) 25.36 (7.22) 24.97 (8.15) 27.55 (6.49) 25.94 (6.54) 26.96 (6.17)

*p < .05. p < .01.

Several interactions involving Time by Condition on career exploration variables were found, with the greatest change in the CP from pre- to post-intervention: focus, Wilks’ λ = .88, F(2, 79) = 5.52, p = .006, η² = .09; satisfaction with information, Wilks’ λ = .93, F(2, 79) = 3.15, p = .048, η² = .05; and increase in employee outlook, Wilks’ λ = .93, F(2, 79) = 3.16, p = .048, η² = .07. The interaction between Time by Condition on life satisfaction was also greatest for the CP, Wilks’ λ = .92, F(2, 79) = 3.69, p = .029, η² = .02.

Guided by the interactions observed above, specific follow-up paired-samples t-tests were conducted within the three conditions in order to examine the changes in various constructs across time. They indicated a significant increase in focus, t(25) = −3.57, p = .001; satisfaction with information, t(25) = −2.28, p = .031; employee outlook, t(25) = −2.26, p = .033; and life satisfaction, t(25) = −2.20, p = .037, over time in the IP. Follow-up paired-samples t-tests demonstrated a significant increase in satisfaction with information, t(24) = −2.82, p = .009, over time in the SP. Lastly, follow-up paired-samples t-tests revealed an increase in focus, t(30) = −5.04, p < .001; satisfaction with information, t(30) = −5.13, p < .001; employee outlook, t(30) = −3.26, p = .003; and life satisfaction, t(30) = −2.17, p = .038, over time in the CP.

Follow-up ANOVAs were conducted to examine between-group differences by calculating difference scores between T1 and T2 for variables displaying significant interactions, thus allowing comparison across conditions. When examining a main effect for focus, there was a significant difference between the protocols, F(2, 79) = 5.52, p = .006. A Bonferroni post hoc test revealed the CP’s (M = 4.16, SD = 4.60) change over time was significantly greater than the SP (M = 0.72, SD = 2.19, p = .004). There was also a significant change in satisfaction with information, F(2, 79) = 3.15, p = .048. A Bonferroni post hoc test revealed the CP’s (M = 5.13, SD = 5.57) change over time was marginally greater than the SP (M = 1.84, SD = 3.26, p = .059). Employee outlook also significantly changed over time, F(2, 79) = 3.16, p = .048. A Bonferroni post hoc test revealed the CP’s (M = 2.19, SD = 3.75) change over time was significantly greater than the SP (M = 0.16, SD = 2.56, p = .044). Lastly, life satisfaction significantly changed over time, F(2, 79) = 3.69, p = .029. A Bonferroni post hoc test revealed the CP’s (M = 2.58, SD = 6.62) change over time was significantly greater than the SP (M = −1.80, SD = 7.52, p = .035).

Additional interactions involving Time by Condition on components of career exploration approached significance, including self-exploration, Wilks’ λ = .93, F(2, 79) = 2.80, p = .067, η² = .06, and intended exploration, Wilks’ λ = .93, F(2, 79) = 3.07, p = .052, η² = .06, with the greatest change in the CP. See Table 2 for intercorrelations between relevant variables.

Table 2.
Correlations of Career Decision Self-Efficacy (CDSE), Career Exploration (CE), and Life Satisfaction for All Participants.

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

1. T1 CDSE —

2. T1 environmental exploration .29 —

3. T1 frequency .08 .36** —

4. T1 amount of information .26* .75 .29 —

5. T1 certainty of CE outcomes .15 .56** .27* .49** —

6. T1 focus .26* .60** .22* .54 .45 —

7. T1 satisfaction with information .36 .62 .26* .47 .43 .66** —

8. T1 employee outlook .26* .53** .23* .52 .56 .51 .36 —

9. T1 self-exploration .41 .53 .18 .44* .25* .39 .32 .31** —

10. T1 intended exploration .26* .71 .29 .65 .42 .43 .37 .33 .46 —

11. T1 life satisfaction .06 .01 .11 .05 .12 −.02 .14 .04 .03 .09 —

12. T2 CDSE .64** .14 .15 .10 .22* .22* .31** .20 .24* .05 .14 —

13. T2 environmental exploration .26* .67 .44 .49 .55 .53 .51 .37 .30 .49 .22 .37 —

14. T2 frequency .21 .47 .28 .34 .36 .38** .25* .35** .23* .41 .02 .15 .48 —

15. T2 amount of information .18 .52 .22 .53 .41 .42 .49 .35 .12 .41 .16 .20 .55 .30 —

16. T2 certainty of CE outcomes .09 .40 .23* .28* .62 .38 .51** .27* .00 .30** .17 .26* .63 .36 .52 —

17. T2 focus .15 .40 .35 .37 .43 .68 .42 .37 .14 .27* .07 .33 .62 .33 .54 .52** —

18. T2 satisfaction with information .28* .49** .23* .44 .49 .50 .53 .34 .15 .31 .22* .31 .67 .33 .68 .61 .67 —

19. T2 employee outlook .09 .18 .14 .05 .36** .15 .26* .29** −.06 .00 .18 .26* .42 .32 .40 .59 .40 .50 —

20. T2 self-exploration .35 .30 .36 .30 .33 .32 .25* .25* .46 .35 .22* .51 .55 .36 .34 .31 .46 .38** .27* —

21. T2 intended exploration .29 .56 .37 .46 .44 .46 .48 .29 .25* .47 .19 .20 .75 .43 .53 .52 .56 .63 .28 .47 —

22. T2 life satisfaction .18 −.03 .08 −.10 .03 −.03 .10 −.04 .05 .04 .48 .25* .21 −.01 .11 .16 .19 .28* .24* .28** .21

N = 82.

*p < .05. **p < .01.

Discussion

Overall, regardless of condition, participants reported a significant increase in CDSE, as well as environmental exploration, intended exploration, frequency, amount of information, focus, satisfaction with information, employee outlook, and certainty of career exploration outcomes (each components of career exploration). Thus, regardless of the type of assessment and focus of the intervention (i.e., interests, strengths, or both interests and strengths), the intervention had a number of positive outcomes. These results add support to the long-standing finding that career interventions work, especially if they contain certain ingredients that have already been found to be helpful, such as writing and individual feedback (Oliver & Spokane, 1988; Whiston et al., 1998).

Several significant interactions were found, demonstrating that the CP outweighed the SP in the areas of focus, satisfaction with information, employee outlook, and life satisfaction. Broadly, the findings suggest the CP was more beneficial than the SP alone but not significantly different from the IP. As such, one could argue from the perspective of conserving resources, providing services focusing on interests alone is the most optimal. This finding, when placed alongside Swanson et al.’s (2006) finding that assessment feedback was better retained when there was less of it, adds to the appeal of using a single assessment. However, it is contrary to the earlier described finding by Katz et al. (1999) that showed SII and MBTI feedback combined was more potent than either by itself. Why this might be the case, and which instruments work best together or individually, is certainly ripe for further investigation.

However, despite the statistical equivalence of the CP and IP groups, an examination of the difference scores from T1 to T2 across all variables reveals that, with the exception of the variable frequency (which had the greatest change in the SP), all variables saw the greatest change in the CP condition. Although these changes were not statistically different from the IP, the trends are clear and suggest a number of benefits to administering and interpreting both the SII and StrengthsFinder and participating in corresponding interventions.

Despite the lack of statistical significance in this case, the aforementioned observations led us to conclude that the results suggest further study of combined protocols is merited. In particular, the intricacies of the who, how, and what variables and contexts need further exploration. In addition, while the IP and the CP showed an increase in life satisfaction, with the greatest change in the CP, the SP did not. Literature in positive psychology suggests identifying and developing strengths leads to greater well-being (Hodges & Harter, 2005; Seligman, Steen, Park, & Peterson, 2005). In this study, a focus on strengths alone did not increase life satisfaction, while focusing on the combination did. It seems possible that the expectation that interests would be part of one’s initial career exploration might have led to less improvement in life satisfaction over time when interests were omitted, corresponding to previous research that suggests feedback that is viewed as personally relevant is perceived as more influential (Hanson et al., 1997). Of course, any intervention that significantly changes global life satisfaction over a period of four weeks warrants further study.

From a theoretical perspective, the benefits associated with a strengths component would certainly not be a surprise. One might consider that feedback on two specific assessments might work together to increase gains as demonstrated in previous studies (Katz et al., 1999). While many career counselors have long asserted that feedback on interests is helpful, in some ways this method is limited, in the sense that individuals can have an interest in something without ever having engaged in any behaviors that would prove that interest or develop it. The difference between these two concepts is roughly analogous to the distinction between “liking” and “wanting.” Wanting requires no direct experience, as many people desire conditions or objects they have never encountered. However, knowledge of liking requires direct engagement with the world. Discrepancy between what one likes and what one wants results in the common experience of disappointment or surprise (Krieshok, Motl, & Rutt, 2011).

Considering occupational pursuits, it is relatively easy to identify and articulate what one wants—or in this case what an individual wants to believe he or she is interested in. It is far more difficult to garner evidence about what one likes based upon experiential engagement—evidence that may prove or disprove beliefs about potential areas of interest. Simply stated, “wanting is cheap; liking is expensive” (Krieshok, 2014). Adding feedback on strengths might potentiate the development of interests by pointing out that an individual has engaged in related behaviors enough to deem a particular area as a strength. While the StrengthsFinder materials are clear that what is being measured are talents (the raw material that needs to be developed into strengths), just using the word “strengths” conjures up the notion that this is something an individual is likely good at or skilled in. Simply informing someone they have a strength called “Learner” may challenge the individual to view themselves in a different way. “Yeah, I am a Learner.”

It is possible a combined approach can facilitate students’ awareness that although individuals have a number of interests and strengths, they may not be the most applicable for one’s career pursuits. Instead, a combination of using one’s strengths that are valued while engaging in activities one finds interesting may be most beneficial and rewarding. For instance, a student may be quite interested in music; however, his or her singing voice is awful. Lacking a strength in voice may limit his or her pursuit of a career in vocal performance. Conversely, a student may have a wonderful singing voice but lack an interest in the music profession. This is also not ideal. Rather, the student who has an exceptional singing voice who is simultaneously interested in a performance career possesses the combination that would likely lead to the most success and satisfaction. Thus, engaging in activities, courses, and careers that are simultaneously interesting and something an individual excels at (i.e., a strength) perhaps is most optimal functionally. Even if clients do not endorse changes postintervention in variables such as self-efficacy and career decision-making, receiving assessment results and processing them might be enough to motivate them to behave differently, to actually do something about their situation that would subsequently leave them feeling more efficacious and even more satisfied in the future. Of course, further research is needed to examine the longitudinal effects of these interventions.

Limitations to this study include a somewhat limited sample size, particularly with the number of dependent variables examined, demographics represented, as well as the brief period of time over which the participants were followed. In addition, the StrengthsFinder consists of some subscales with rather low internal reliabilities. Despite this, the authors chose to use the StrengthsFinder so an already established instrument could be used as a comparison to the SII, and compared to the VIA-IS, the StrengthsFinder was developed to aid career-related pursuits (Asplund et al., 2005). Additionally, these interventions were imbedded within a semester-long career course, albeit conducted during the very beginning of the semester. Thus, all three groups were undergoing additional, albeit the same, activities, even during the few weeks of the study.

It is encouraging that despite these limitations, all conditions showed significant gains across several of the outcomes in just four weeks. Of course it also argues for replication, both in other course arrangements as well as in noncourse individual and group interventions. A future study, involving a more potent strengths intervention, over a more extended period of time or that has greater power might return significant findings similar to those found by Littman-Ovadia and colleagues (2014). Future studies that also include longitudinal follow-up, as well as examine other outcomes, such as academic performance, retention, number of major changes, and time to graduation would be beneficial with the college student population. In conclusion, the results of this study suggest that a combined interest and strengths-based approach is at least as effective as a more traditional interest-based approach, and there is reason to suspect that strengths confer a number of important advantages.

Variable	Condition
CDSE	3.63 (0.43)	3.81 (0.56)	3.76 (0.42)	3.86 (0.48)	3.65 (0.47)	3.93 (0.51)	3.68 (0.44)	3.87 (0.51)	.82** (.18)
Environmental exploration (CE)	12.81 (5.61)	16.46 (5.63)	13.00 (5.07)	16.44 (5.28)	10.42 (4.44)	15.19 (5.18)	11.96 (5.11)	15.98 (5.33)	.53** (.47)
Frequency (CE)	1.38 (0.64)	1.73 (0.92)	1.20 (0.41)	1.64 (1.04)	1.32 (0.79)	1.61 (0.84)	1.30 (0.64)	1.66 (0.92)	.88** (.12)
Amount of information (CE)	7.42 (2.42)	8.50 (2.30)	7.44 (2.80)	8.80 (2.45)	6.45 (2.73)	8.26 (2.61)	7.06 (2.67)	8.50 (2.45)	.75** (.25)
Certainty of career exploration outcomes (CE)	7.00 (3.26)	7.88 (3.76)	7.84 (2.94)	7.80 (3.07)	7.48 (2.92)	9.10 (3.07)	7.44 (3.02)	8.32 (3.32)	.92* (.08)
Focus (CE)	10.46 (5.23)	13.38 (5.57)	12.20 (4.75)	12.92 (5.26)	10.55 (4.82)	14.71 (4.87)	11.02 (4.93)	13.74 (5.21)	.68* (.29)
Satisfaction with information (CE)	15.42 (5.71)	18.12 (5.55)	16.68 (5.26)	18.52 (4.76)	14.84 (6.22)	19.97 (4.68)	15.59 (5.76)	18.94 (5.00)	.71** (.27)
Employee outlook (CE)	8.81 (2.59)	9.88 (2.37)	10.16 (2.53)	10.32 (2.31)	8.61 (3.23)	10.81 (2.24)	9.15 (2.88)	10.37 (2.29)	.87** (.12)
Self-exploration (CE)	16.69 (4.22)	16.62 (4.22)	16.76 (4.42)	16.72 (3.88)	13.87 (4.31)	16.13 (3.73)	15.65 (4.48)	16.46 (3.89)
Intended exploration (CE)	7.04 (2.71)	8.46 (2.12)	7.64 (3.08)	7.84 (2.58)	5.84 (2.48)	7.81 (2.75)	6.77 (2.82)	8.02 (2.50)	.83* (.16)
Life satisfaction	25.92 (4.73)	27.81 (4.39)	27.16 (5.91)	25.36 (7.22)	24.97 (8.15)	27.55 (6.49)	25.94 (6.54)	26.96 (6.17)

Footnotes

Acknowledgments

We would like to thank Wendy Shoemaker for her assistance in coordinating the various sections of the career-planning course and her feedback on the career counseling activities. We would also like to thank Candice Ackerman, Heath Schechinger, Zac Schmidt, and Kelly Watson Muther for their assistance in serving as the career counselors.

Declaration of Conflicting Interests

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

Funding

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

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Variable	Condition
Variable	Interests Group		Strengths Group		Combined Group		All Participants
	Pre M (SD)	Post M (SD)	Pre M (SD)	Post M (SD)	Pre M (SD)	Post M (SD)	Pre M (SD)	Post M (SD)	Wilks’ λ (η²)
CDSE	3.63 (0.43)	3.81 (0.56)	3.76 (0.42)	3.86 (0.48)	3.65 (0.47)	3.93 (0.51)	3.68 (0.44)	3.87 (0.51)	.82** (.18)
Environmental exploration (CE)	12.81 (5.61)	16.46 (5.63)	13.00 (5.07)	16.44 (5.28)	10.42 (4.44)	15.19 (5.18)	11.96 (5.11)	15.98 (5.33)	.53** (.47)
Frequency (CE)	1.38 (0.64)	1.73 (0.92)	1.20 (0.41)	1.64 (1.04)	1.32 (0.79)	1.61 (0.84)	1.30 (0.64)	1.66 (0.92)	.88** (.12)
Amount of information (CE)	7.42 (2.42)	8.50 (2.30)	7.44 (2.80)	8.80 (2.45)	6.45 (2.73)	8.26 (2.61)	7.06 (2.67)	8.50 (2.45)	.75** (.25)
Certainty of career exploration outcomes (CE)	7.00 (3.26)	7.88 (3.76)	7.84 (2.94)	7.80 (3.07)	7.48 (2.92)	9.10 (3.07)	7.44 (3.02)	8.32 (3.32)	.92* (.08)
Focus (CE)	10.46 (5.23)	13.38 (5.57)	12.20 (4.75)	12.92 (5.26)	10.55 (4.82)	14.71 (4.87)	11.02 (4.93)	13.74 (5.21)	.68* (.29)
Satisfaction with information (CE)	15.42 (5.71)	18.12 (5.55)	16.68 (5.26)	18.52 (4.76)	14.84 (6.22)	19.97 (4.68)	15.59 (5.76)	18.94 (5.00)	.71** (.27)
Employee outlook (CE)	8.81 (2.59)	9.88 (2.37)	10.16 (2.53)	10.32 (2.31)	8.61 (3.23)	10.81 (2.24)	9.15 (2.88)	10.37 (2.29)	.87** (.12)
Self-exploration (CE)	16.69 (4.22)	16.62 (4.22)	16.76 (4.42)	16.72 (3.88)	13.87 (4.31)	16.13 (3.73)	15.65 (4.48)	16.46 (3.89)
Intended exploration (CE)	7.04 (2.71)	8.46 (2.12)	7.64 (3.08)	7.84 (2.58)	5.84 (2.48)	7.81 (2.75)	6.77 (2.82)	8.02 (2.50)	.83* (.16)
Life satisfaction	25.92 (4.73)	27.81 (4.39)	27.16 (5.91)	25.36 (7.22)	24.97 (8.15)	27.55 (6.49)	25.94 (6.54)	26.96 (6.17)

Variable	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21
1. T1 CDSE	—
2. T1 environmental exploration	.29**	—
3. T1 frequency	.08	.36**	—
4. T1 amount of information	.26*	.75**	.29**	—
5. T1 certainty of CE outcomes	.15	.56**	.27*	.49**	—
6. T1 focus	.26*	.60**	.22*	.54**	.45**	—
7. T1 satisfaction with information	.36**	.62**	.26*	.47**	.43**	.66**	—
8. T1 employee outlook	.26*	.53**	.23*	.52**	.56**	.51**	.36**	—
9. T1 self-exploration	.41**	.53**	.18	.44*	.25*	.39**	.32**	.31**	—
10. T1 intended exploration	.26*	.71**	.29**	.65**	.42**	.43**	.37**	.33**	.46**	—
11. T1 life satisfaction	.06	.01	.11	.05	.12	−.02	.14	.04	.03	.09	—
12. T2 CDSE	.64**	.14	.15	.10	.22*	.22*	.31**	.20	.24*	.05	.14	—
13. T2 environmental exploration	.26*	.67**	.44**	.49**	.55**	.53**	.51**	.37**	.30**	.49**	.22	.37**	—
14. T2 frequency	.21	.47**	.28**	.34**	.36**	.38**	.25*	.35**	.23*	.41**	.02	.15	.48**	—
15. T2 amount of information	.18	.52**	.22	.53**	.41**	.42**	.49**	.35**	.12	.41**	.16	.20	.55**	.30**	—
16. T2 certainty of CE outcomes	.09	.40**	.23*	.28*	.62**	.38**	.51**	.27*	.00	.30**	.17	.26*	.63**	.36**	.52**	—
17. T2 focus	.15	.40**	.35**	.37**	.43**	.68**	.42**	.37**	.14	.27*	.07	.33**	.62**	.33**	.54**	.52**	—
18. T2 satisfaction with information	.28*	.49**	.23*	.44**	.49**	.50**	.53**	.34**	.15	.31**	.22*	.31**	.67**	.33**	.68**	.61**	.67**	—
19. T2 employee outlook	.09	.18	.14	.05	.36**	.15	.26*	.29**	−.06	.00	.18	.26*	.42**	.32**	.40**	.59**	.40**	.50**	—
20. T2 self-exploration	.35**	.30**	.36**	.30**	.33**	.32**	.25*	.25*	.46**	.35**	.22*	.51**	.55**	.36**	.34**	.31**	.46**	.38**	.27*	—
21. T2 intended exploration	.29**	.56**	.37**	.46**	.44**	.46**	.48**	.29**	.25*	.47**	.19	.20	.75**	.43**	.53**	.52**	.56**	.63**	.28**	.47**	—
22. T2 life satisfaction	.18	−.03	.08	−.10	.03	−.03	.10	−.04	.05	.04	.48**	.25*	.21	−.01	.11	.16	.19	.28*	.24*	.28**	.21