The College Student Subjective Wellbeing Questionnaire: A Brief ...

J Happiness Stud (2016) 17:463–484 DOI 10.1007/s10902-014-9606-4 RESEARCH PAPER

The College Student Subjective Wellbeing Questionnaire: A Brief, Multidimensional Measure of Undergraduate’s Covitality Tyler L. Renshaw • Sarah J. Bolognino

Published online: 17 December 2014 Springer Science+Business Media Dordrecht 2014

Abstract This study reports on the preliminary development and validation of the College Student Subjective Wellbeing Questionnaire (CSSWQ) with two subsamples of undergraduates. The CSSWQ is a brief, multidimensional, domain-specific measure of college students’ covitality—operationalized by a measurement model comprised of four first-order latent constructs (i.e., academic efficacy, college gratitude, school connectedness, and academic satisfaction) and one second-order latent construct (i.e., college student covitality). Results from exploratory factor analyses, conducted with the first subsample (n = 387), were used to refine a 15-item, four-subscale version of the CSSWQ, which demonstrated strong internal consistency and concurrent validity with several global indicators of subjective wellbeing. Results from confirmatory factor analyses, conducted with the second subsample (n = 584), corroborated the CSSWQ’s four-factor structure and supported the second-order latent construct of college-student covitality. Further concurrent validity analyses conducted with the second subsample, using latent-variable path analysis, indicated that the college-student covitality variable was a strong predictor of both psychological distress and psychological wellness. Analysis of variance also indicated that, when compared with global covitality status (i.e., below average, low average, high average, or above average), college-student covitality status had a stronger effect and thus incremental validity in relation to academic achievement. Implications for theory, research, and practice are discussed. Keywords

Subjective wellbeing Positive psychology Covitality Mental health

T. L. Renshaw (&) S. J. Bolognino Department of Psychology, Louisiana State University, 236 Audubon Hall, Baton Rouge, LA 70803, USA e-mail: [email protected]

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T. L. Renshaw, S. J. Bolognino

1 Introduction 1.1 Cultivating a Science of Covitality To date, most positive psychology research has identified, defined, and measured global, isolated positive traits and investigated their relation to other personality traits or qualityof-life outcomes. Research has demonstrated, for example, that dispositional gratitude is positively associated with prosocial behavior, life satisfaction, and positive affect (McCullough et al. 2002); that optimism buffers against depression and uncomfortable physical symptoms during periods of high stress (Scheier and Carver 1985); and that hope is a significant predictor of college GPA and graduation rates (Curry et al. 1997). Because these global positive traits have desirable outcome correlates, interventions have been designed and tested to cultivate these traits in individuals. Examples of such interventions include gratitude journaling exercises (Emmons and McCullough 2003) and hope visualization interventions (Feldman and Dreher 2012). Recently, however, a new line of inquiry has moved away from targeting isolated positive traits and towards measuring and intervening with combinations of positive traits. A distinguishing characteristics of this new line of research is its concern with population-based service delivery, which has fueled the development and testing of screening instruments and prevention programs that target a variety of positive psychology traits (cf. Renshaw et al. 2014a; Seligman et al. 2009). A key concept emerging from this latest wave of research is covitality, which has been contrasted with comorbidity and defined as ‘‘the synergistic effect of positive mental health resulting from the interplay among multiple positive-psychological building blocks’’ (Furlong et al. 2014, p. 3). Statistically speaking, covitality has been further operationalized as ‘‘the latent, second-order positive mental health construct accounting for the presence of several co-occurring, first-order positive mental health indicators’’ (Furlong et al. 2014, p. 3). For our purposes, we redefine covitality as an individual’s cumulative subjective wellbeing, which, at the most basic level, consists of a combination of emotional, cognitive, social, and behavioral components—how people feel, think, relate, and act—that are either valued for their own sake (e.g., life satisfaction and connectedness) or because they function to attain things that are valued for their own sake (e.g., self-efficacy and perseverance), or possibly both (e.g., positive emotions). To illustrate how covitality is analogous to other latent constructs used in psychological research and practice, it can be compared to the development and use of the full-scale Intelligence Quotient (IQ) commonly used in cognitive ability testing (Furlong et al. 2014). Just as the full-scale IQ score is considered a better representation of students’ overall cognitive functioning and a better predictor of their achievement than isolated index or subtest scores, the covitality score is considered a better representation of students’ cumulative subjective wellbeing and a better predictor of their quality-of-life outcomes than individual positive psychology traits (e.g., gratitude and grit) or domains (e.g., engaged living and belief-in-self; cf. Renshaw et al. 2014a). The rationale underlying covitality is also grounded in the cumulative assets theory of childhood resiliency, which posits that increased numbers of internal assets (e.g., school engagement) and external assets (e.g., supportive caregiver relationships) are predictive of desirable health, achievement, and other quality-of-life outcomes (e.g., Scales 1999). Covitality theory takes the cumulative assets theory a step further by statistically verifying both the structure of the various latent constructs that are posited as well as the relations among such constructs, ensuring that each is empirically distinct from the others as well as a significant contributor to cumulative subjective wellbeing (Renshaw et al. 2014a). Research regarding covitality was initiated with a sample of college students, using five

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global positive psychological indicators: hedonia, optimism, self-efficacy, hope, and gratitude (Jones et al. 2013). Following, covitality studies were conducted with samples of elementary students (Furlong et al. 2013) and secondary students (Furlong et al. 2014; Renshaw et al. 2014b; You et al. 2013), using several of the indicators noted above as well additional positive traits, such as self-awareness, persistence, social support, and empathy. Findings from these few studies suggest that the covitality index is a flexible and promising meta-indicator of students’ cumulative subjective wellbeing, as different operationalizations have demonstrated convergent validity with self-reported academic achievement, perceptions of school safety, substance use, depressive symptoms, psychological wellbeing indicators, and other common risk and asset variables (e.g., Furlong et al. 2013, 2014; You et al. 2013.) 1.2 Toward a College-Specific Covitality As inquiry into the covitality construct has progressed, the utility of global versus domainspecific covitality has become a subject worthy of investigation. This concern with domain-specificity is derived from the cumulative assets theory of childhood resiliency, which distinguishes between family-, school-, and community-specific assets and their relation to youths’ outcomes (e.g., Scales 1999). As an initial effort to explore the viability of a domain-specific covitality for elementary students, the Positive Experiences at School Scale (PEASS) was developed to measure school-specific gratitude (e.g., ‘‘I am thankful that I get to learn new things at school’’), optimism (e.g., ‘‘I expect good things to happen at my school’’), zest (e.g., ‘‘I get really excited about my school projects’’), and persistence (e.g., ‘‘When I get a bad grade, I try even harder the next time’’; Furlong et al. 2013, 2014) within the school context. Although it seems reasonable that school-specific positive psychology traits, such as those measured by the PEASS, are better predictors of important school-related outcomes (e.g., attendance and achievement), this initial study did not measure the global counterparts of these domain-specific traits (e.g., general gratitude compared to school gratitude) and thus could not investigate the incremental validity of domain-specific versus global versions of covitality. One of the purposes of the present study, then, was to further progress a science of covitality by exploring the incremental validity of global versus domain-specific measures of students’ cumulative subjective wellbeing. Just as the PEASS was developed to assess the school-grounded covitality of elementary students, the present study developed a domain-specific measure of college-student covitality—the College Student Subjective Wellbeing Questionnaire (CSSWQ)—and tested it against a parallel measure of global covitality, which was derived from preexisting measures that the CSSWQ was modeled after. Given that the CSSWQ was developed for use as a population-based screening instrument for assessing, responding to, and monitoring the positive dimension of college students’ mental health (cf. Dowdy et al. 2010), it was intentionally designed as a brief measure of cumulative subjective wellbeing. As such, only one or two relevant indicators were selected to represent each wellbeing domain, resulting in a measurement model consisting of five college-grounded positive psychology traits: college gratitude (emotional domain), academic self-efficacy and academic satisfaction (cognitive domain), school connectedness (social domain), and academic grit (behavioral domain). Research has shown that the global versions of each of these positive psychology traits are significantly related to various socially desirable outcomes, and thus we hypothesized that domain-specific versions of these traits would have incremental validity in relation to college student outcomes. For example, gratitude, which has been defined as the positive

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emotional response experienced in relation to receiving a benefit from an external source, has been related to greater life satisfaction and positive emotion, lower levels of depression and anxiety, and greater levels of empathy, forgiveness, and prosocial behavior (Emmons and McCullough 2003; McCullough et al. 2002). Self-efficacy, defined as an individual’s belief in his or her ability to perform or accomplish a specific task, has been shown to be a protective factor against depression and anxiety disorders and a predictor of academic achievement (Maddux and Meier 1995; Putwain et al. 2013). Furthermore, life satisfaction, defined as a general subjective appraisal of one’s quality of life, has been related to greater success in work (e.g., higher productivity and quality of work) and personal relationships (e.g., longer marriages and stronger social support networks) as well as better physical health (e.g., stronger immune system) and emotional health (e.g., lower stress levels; Erdogan et al. 2012; Lyubomirsky et al. 2005). Moreover, social connectedness, which we define as the perception of harmonious and supportive relationships, has been shown to be associated with increased classroom participation, enhanced overall learning, and greater mental and physical health (Frisby and Martin 2010; Hawkley and Cacioppo 2010). And, finally, grit, defined as perseverance and passion for pursuing long-term goals, has been found to be an important predictor of various learning behaviors and achievement outcomes (Duckworth et al. 2007, 2010). 1.3 Purposes of the Present Study Using the five selected subjective wellbeing indicators described above—gratitude, selfefficacy, life satisfaction, social connectedness, and grit—the overarching purpose of the present study was to inquire into the viability and incremental validity college-specific subjective wellbeing indicators and domain-specific covitality. That said, our sub-purposes in this study were threefold. First, we proposed an initial conceptual model of college student covitality, based on the five subjective wellbeing indicators noted above, and developed associated items to test in a brief, multidimensional, self-report measure—the CSSWQ. Following this initial groundwork, we investigated the psychometric properties of the CSSWQ by testing the data-model fit of our proposed measurement model with a subsample of college students, refining the measure based on these initial findings, and then evaluating the internal reliability and concurrent validity of this revised measure. Finally, we reevaluated the psychometric properties of the refined version of the CSCQ by investigating the internal reliability and concurrent validity of its measurement model with another, larger, subsample of college students. Given these purposes, we hypothesized that our proposed college-student covitality model, operationalized by the CSSWQ, would (a) indicate a conceptually-and-statistically-sound multidimensional latent-trait structure, (b) evidence at least adequate internal consistency, (c) demonstrate concurrent validity with its counterpart global traits and other indicators of psychological wellbeing and distress, and, when compared with global covitality, (d) show greater incremental validity in relation to self-reports of academic achievement.

2 Method 2.1 Participants The present sample consisted of 971 undergraduate college students attending a large public university located in the southern region of the United States. For data analysis purposes, this

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initial sample was randomly split into two subsamples using the random-sampling procedure in SPSS version 20, with Subsample 1 (S1) consisting of 40 % of the participants (n = 387) and Subsample 2 (S2) consisting of the remaining 60 % (n = 584). Participants in both subsamples were predominantly female (S1 = 74.9 %, S2 = 72.3 %) and had a mean age of 20 years (SD = 1.6). Within both subsamples, the majority of participants self-identified as White/Caucasian (S1 = 80.6 %, S2 = 75.9 %), with far fewer identifying as Black/African American (S1 = 11.4 %, S2 = 13 %), Hispanic/Latino (S1 = 2.8 %, S2 = 3.3 %), Asian/ Pacific Islander (S1 = 3.1 %, S2 = 4.5 %), and ‘‘other’’ ethnicities (S1 = 2.2 %, S2 = 3.4 %). Both subsamples contained students who were in various years of enrollment at the university, with first-year students being the most prevalent (S1 = 34.1 %, S2 = 35.1 %), followed by second-year (S1 = 25.1 %, S2 = 24.1 %), third-year (S1 = 23 %, S2 = 24.8 %), and fourth-or-more-year students (S1 = 17.9 %, S2 = 16 %). All participants were recruited via an online research management system administered by the university’s Department of Psychology, which was only accessible to students enrolled in undergraduate psychology courses. Participation in the study was open to all undergraduates who were at least 18 years of age and was not restricted by academic major, mental health, or any other personal characteristics. Each participant used a secure online server to complete the survey, which consisted of a series of demographic questions followed by various self-report instruments of global and domain-specific subjective wellbeing (see the Measures subsection, below) that took approximately 20–30 min to complete, and each received partial course credit for participation in the study. Given the nature of the online survey system, all items were required to be completed—with no missing data—prior to participants receiving partial course credit. Any incomplete surveys with missing data were thus excluded from the potential participant pool. Approval from the authors’ university’s Institutional Review Board was obtained prior to beginning the study, and informed consent was acquired for all participants prior to their completion of the survey. Following data collection, all data were downloaded and processed into a secure electronic database, where all participants’ responses were then screened for plausible response patterns. 2.2 Measures 2.2.1 College Student Subjective Wellbeing Questionnaire The CSSWQ was designed as a brief, domain-specific, multidimensional measure of positive psychology traits that are representative of college students’ cumulative subjective wellbeing or covitality. As such, this measure was developed by identifying a handful of domain-general indicators of subjective wellbeing and then adapting their item wording to be domain-specific, targeting college student functioning as opposed to global life functioning. The intent of the study, then, was not to hypothesize or test new subjective wellbeing constructs or to create completely new measures, but rather to test the incremental validity between global and domain-specific measures of the same fundamental constructs as assessed via similar measures. For the purposes of the present study, we selected five core subjective wellbeing constructs that have been frequently researched in positive psychology—self-efficacy, gratitude, grit, connectedness, and life satisfaction (cf. Seligman and Peterson 2004)—and then posited domain-specific versions of these constructs that could be assessed via adapted measures: academic self-efficacy, college gratitude, academic grit, school connectedness, and academic satisfaction. Similar to other studies of covitality (e.g., Furlong et al. 2013; Jones et al. 2013), these five core constructs were not intended to serve as an exhaustive model of college students’ subjective

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Table 1 Hypothesized Scales and Test-Items for the College Student Subjective Wellbeing Questionnaire Satisfaction with Academics Scale SAS-1

I really enjoy my classes

SAS-2

I am happy with my academic major

SAS-3

Overall, my experiences in my classes have been excellent

SAS-4

I have had a great academic experience at [name of university]

SAS-5

I am happy with how I’ve done in my classes

SAS-6

I am satisfied with my academic achievement since coming to [name of university]

Academic Grit Scale AGS-1

New ideas and projects never distract me from my schoolwork

AGS-2

Academic setbacks don’t discourage me

AGS-3

I am a hard worker in my classes

AGS-4

I maintain my focus on schoolwork that takes more than a few weeks to complete

AGS-5

I finish whatever class assignments or projects I begin

AGS-6

I am a diligent student

School Connectedness Scale SCS-1

I feel like a real part of [name of university]

SCS-2

People here notice when I’m good at something

SCS-3

People at this school are friendly to me

SCS-4

I can really be myself at this school

SCS-5

I feel proud of belonging to [name of university]

SCS-6

Other students here like me the way I am

Academic Self-Efficacy Scale ASES-1

I take good notes in class

ASES-2

I perform well on tests, no matter the subject

ASES-3

I figure out a way to solve any problems that I have in my classes

ASES-4

I am an organized and effective student

ASES-5

I possess the necessary academic skills needed to succeed in college

ASES-6

I study well for my classes

College Gratitude Scale CGS-1

I am so thankful that I’m getting a college education

CGS-2

If I had to list everything I felt grateful for about my academic experience at [name of university], it would be a very long list

CGS-3

I appreciate the things I have learned in my college classes

CGS-4

I am grateful to the professors and other students who have helped me in class

CGS-5

I feel thankful for the opportunity to learn so many new things

CGS-6

I am grateful for the people who have helped me succeed in college

wellbeing; rather, they were intended to function as a representative sample of indicators commonly included within the domain of subjective wellbeing. During the initial development phase, six test-items—each intentionally worded to assess participants’ perceptions of school-grounded experiences—were developed for each core construct (see Table 1). All items comprising the hypothesized Academic Self-Efficacy Scale (ASES) were original to this study, were modeled after items from the General Self-Efficacy Scale (GSES; see below), and were arranged along a seven-point response

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scale (1 = strongly agree, 2 = disagree, 3 = slightly agree, 4 = neutral, 5 = slightly agree, 6 = agree, 7 = strongly agree). The hypothesized College Gratitude Scale (CGS) was comprised of original items modeled after items from the Gratitude Questionnaire-6 (GQ-6; see below) and used the same seven-point response scale as the items for the ASES. For the hypothesized Academic Grit Scale (AGS), items from the Short Grit Scale (SGS; see below) were modified with college-specific language, yet the measure’s original fivepoint response scale was retained (1 = not like me at all, 2 = not much like me, 3 = somewhat like me, 4 = mostly like me, 5 = very much like me). Unlike the previous two scales, all items for the hypothesized School Connectedness Scale (SCS) were selected directly from preexisting items included in the Psychological Sense of School Membership Scale (Goodenow 1993; see below), which is arranged upon a five-point response scale (1 = not at all true, 2 = somewhat true, 3 = moderately true, 4 = very true, 5 = completely true) and functions as a domain-specific measure of connectedness that has similar item structure and content to the positively-phrased items representing global social connectedness found in the UCLA Loneliness Scale-Revised (Russell et al. 1980; see below). Thus, no new items were adapted to create the SCS. Finally, the hypothesized Satisfaction with Academics Scale (SAS) was comprised of original items modeled after items from the Satisfaction With Life Sale-5 (SWLS-5; see below) and used the same seven-point response scale as the items from the ASES and CGS. Following the item-development phase, the pilot version of the CSSWQ consisted of 30 items. Given that the CSSWQ was designed to be used for population-based or schoolwide screening purposes, this original item pool was intended to be refined, via exploratory factor analyses, to a 20-item instrument, comprised of five four-item subscales. However, because findings from exploratory factor analyses (EFA) suggested that a four-factor solution—instead of the hypothesized five-factor structure—was deemed the best datamodel fit for Subsample 1, and given that EFA findings for one subscale yielded only three quality items (see the Results section, below), the refined version of the CSSWQ was ultimately comprised of 15 items representing three of the hypothesized subscales—the CGS, SCS, and the SAS—and one revised subscale: the Academic Efficacy Scale (AES), which was comprised of items from both the hypothesized ASES and AGS. This shortened measure, which consists of only half of the original items tested in the pilot measure, is considered the most current version of the CSSWQ. 2.2.2 General Self-Efficacy Scale The GSES is a 10-item measure for assessing global self-efficacy (Scholz et al. 2002). All items are worded positively (e.g., ‘‘I can always manage to solve difficult problems if I try hard enough’’) and are situated along a four-point response scale (1 = not at all true, 2 = hardly true, 3 = moderately true, 4 = exactly true). The GSES has been demonstrated to have adequate to strong internal reliability, a unidimensional factor structure, concurrent validity with emotionality and performance variables, and to be relatively stable across international samples (Scholz et al. 2002; Schwarzer et al. 1997). The domainspecific adaptation of the GSES that was included in and tested as part of the CSSWQ in the present study was the Academic Self-Efficacy Scale, described above. 2.2.3 Short Grit Scale The SGS is an eight-item measure for assessing perseverance and passion for pursuing long-term goals (Duckworth and Quinn 2009). Half of the items are worded positively

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(e.g., ‘‘I am diligent’’) while the other half are worded negatively (e.g., ‘‘New ideas and projects sometimes distract me from previous ones’’) and are thus reverse-scored. All items are arranged along a five-point response scale (1 = not like me at all, 2 = not much like me, 3 = somewhat like me, 4 = mostly like me, 5 = very much like me). Research has shown that the SGS has adequate to strong internal reliability and concurrent validity with educational attainment, performance, and resiliency variables (Duckworth and Quinn 2009; Kleiman et al. 2013). The domain-specific adaptation of the SGS that was included in and tested as part of the CSSWQ in the present study was the Academic Grit Scale, described above. 2.2.4 Satisfaction with Life Scale-5 The SWLS-5 was used to assess how satisfying respondents judge their lives to be overall (Diener et al. 1985). All five items are worded positively (e.g., ‘‘The conditions of my life are excellent’’) and response options are arranged on a seven-point scale (1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree). The SWLS-5 has been shown to have strong internal and test–retest reliability, a unitary factor structure, and concurrent validity with other emotional wellbeing measures (Diener et al. 1985; Pavot and Diener 1993; Pavot et al. 1991). The domain-specific adaptation of the SWLS-5 that was included in and tested as part of the CSSWQ in the present study was the Satisfaction with Academics Scale, described above. 2.2.5 Gratitude Questionnaire-6 The GQ-6 is a six-item measure for assessing dispositional gratitude (McCullough et al. 2002). Four of its items are worded positively (e.g., ‘‘I have so much in life to be grateful for’’), while the other two are phrased negatively (e.g., ‘‘When I look at the world, I don’t see much to be grateful for’’) and are thus reverse-scored. All items are arranged on a seven-point response scale (1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neutral, 5 = slightly agree, 6 = agree, 7 = strongly agree). Research has shown that the GQ-6 has strong internal reliability, a unitary factor structure, and concurrent validity with a variety of emotionality and personality variables (McCullough et al. 2002, 2004). The domain-specific adaptation of the GQ-6 that was included in and tested as part of the CSSWQ in the present study was the College Gratitude Scale, described above. 2.2.6 Psychological Sense of School Membership Scale The PSSMS is an 18-item measure for assessing students’ feelings and perceptions of belongingness within their school community (Goodenow, 1993). Thirteen of its items are positively worded (e.g., ‘‘People at this school are friendly to me’’), while five items are phrased negatively (e.g., ‘‘I wish I were in a different school’’) and were thus reversescored. Response options for all items were arranged along a five-point scale (1 = not at all true, 2 = somewhat true, 3 = moderately true, 4 = very true, 5 = completely true). Given that the PSSMS was designed for use with adolescents, small adaptations were made to enhance the age-appropriateness of item wording (e.g., ‘‘teachers’’ was changed to ‘‘professors’’). For both adolescents and college students, the PSSM has been shown to have adequate to strong internal reliability and concurrent validity with other important

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school-related variables (e.g., Freeman et al. 2007; Goodenow). For the purposes of this study, several items were selected from the PSSMS to represent the SCS, described above, as it was the only measure that was identified to have preexisting school-specific items that were similar to in structure and content to the global social connectedness items included in the LS-R, which is described below. 2.2.7 UCLA Loneliness Scale-Revised The 20-item LS-R was used to assess perceptions of harmonious and supportive interpersonal relationships (Russell et al. 1980). Eleven of its items are worded negatively (e.g., ‘‘I lack companionship’’), while nine are positively phrased (e.g., ‘‘I feel in tune with the people around me’’), and all items are arranged along a four-point response scale (1 = never, 2 = rarely, 3 = sometimes, 4 = often). Although the positive items are typically reverse-scored to generate a global loneliness score, for the purposes of this study the negative items were reverse-scored to generate a global social connectedness score. Research has demonstrated that the LS-R has excellent internal and test–retest reliability as well as concurrent validity with emotionality, personality, and other relationship and social behavior variables (Russell 1996; Russell et al. 1980). In the present study, the LS-R was used as the domain-general or global counterpart to the SCS, which was derived from the PSSMS items, described above. 2.2.8 Positive and Negative Affect Schedule The PANAS is a 20-item measure consisting of two subscales, one assessing global positive affect (PANAS-P) and the other global negative affect (PANAS-N; Watson et al. 1988). Each subscale consists of 10 feeling words (e.g., ‘‘interested,’’ ‘‘irritable,’’ ‘‘attentive,’’ and ‘‘ashamed’’) and respondents rate the degree to which they experienced each during the past week, using a five-point response scale (1 = not at all, 2 = a little, 3 = moderately, 4 = quite a bit, 5 = extremely). Studies have demonstrated that the PANAS subscales have strong internal consistency, moderate to strong test–retest reliability, concurrent validity with each other as well as other measures of emotionality, and that the overall measure has a bidimensional factor structure (Crawford and Henry 2004; Watson et al. 1988). 2.2.9 Subjective Happiness Scale The four-item SHS was used to assess global happiness (Lyubomirksy and Lepper 1999). Three of the four items are positively worded, with two items assessing general selfperceptions of happiness (e.g., ‘‘In general, I consider myself…’’) and the other two items assessing perceptions of one’s happiness relative to one’s peers (e.g., ‘‘Some people are generally not very happy. Although they are not depressed, they never seem as happy as they might be. To what extent does this characterization describe you?’’). The one negatively phrased item is reverse-scored, and all items are arranged along seven-point response scales that have differing qualitative anchors, depending on the item stem (1 = not a very happy person… 7 = a very happy person; 1 = less happy… 7 = more happy; 1 = not at all… 7 = a great deal). The SHS has been shown to have adequate to strong internal consistency and test–retest reliability, a unidimensional factor structure, and concurrent validity with various emotionality and relationship variables (Lyubomirsky et al. 2011; Lyubomirksy and Lepper 1999).

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2.2.10 Depression–Anxiety–Stress Scales-21 The DASS-21 is composed of three subscales, assessing depression, anxiety, and stress (Antony et al. 1998). Each subscale consists of 7 items (e.g., depression: ‘‘I felt that I had nothing to look forward to’’; anxiety: ‘‘I felt I was close to panic’’; stress: ‘‘I found it hard to wind down’’) and response options are arranged on a four-point scale (0 = did not apply to me, 1 = applied to me some of the time, 2 = applied to me a good part of the time, 3 = applied to me most of the time). The DASS-21 subscales have been shown to have strong internal reliability, a tridimensional factor structure, convergent validity with each other and other measures of depression and anxiety (Page et al. 2007), and concurrent validity with other emotionality variables (Henry and Crawford 2005). For the purposes of the present study, only the depression subscale (DASS-21-D) was used as a concurrent validity indicator of subjective distress. 2.2.11 Grade-Point Average Participants’ overall academic achievement was assessed via self-reported GPA. Because standardized testing initiatives that crosscut academic majors are rare at the undergraduate level, GPA was considered the most objective and universal indicator of college students’ academic achievement. Given the university’s grading standards, students’ potential GPAs ranged from 0 (indicating all F, or non-passing, grades) to 4 (indicating all A, or highpassing, grades). Previous research has indicated that college students’ GPAs are significantly, negatively associated with emotional distress and significantly, positively correlated with emotional wellbeing, albeit at levels usually characterized by small effect sizes (Richardson et al. 2012). 2.3 Data Analyses Two phases of primary data analyses were conducted. In Phase One analyses, the datamodel fit of our proposed college student subjective wellbeing model, operationalized by the test-version of the CSSWQ, was examined via exploratory factor analyses (EFA), using the Maximum Likelihood extraction method with a Promax (oblique) rotation. Results from this series of EFA were used to develop a refined, shortened version of the CSSWQ. Following, the internal reliability of the CSSWQ’s subscales were tested (using Cronbach’s a), and their concurrent validity was evaluated in relation to their global counterpart traits (using Pearson r correlations with the GSES, SGS, GQ-6, LS-R, and SWLS-5). All Phase One analyses were conducted with Subsample 1 using SPSS version 20. In Phase Two analyses, the psychometric properties of the refined CSSWQ were reevaluated via confirmatory factor analyses (CFA), using the Maximum Likelihood estimation method. Following confirmation of the factor structure, the internal reliability of the CSSWQ’s subscales and composite scale were examined, using the item (‘2) and construct (H) coefficients recommended by Mueller and Hancock (2008). The CSSWQ’s concurrent validity was then evaluated, using a latent-variable path analysis (LVPA) that extended the measurement model to predict global psychological wellness (indicated by the SHS and PANAS-P) and global psychological distress (indicated by the DAS-21-D and PANAS-N). Furthermore, the incremental validity of college-student covitality status versus global covitality status was tested in relation to academic achievement, using a between-subjects univariate analysis of variance (ANOVA), followed by post hoc tests. All

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Phase Two analyses were conducted with Subsample 2 using either AMOS version 20 (for the CFA and LVPA) or SPSS version 20 (for the ANOVA and post hoc tests).

3 Results 3.1 Phase One: Subsample 1 3.1.1 Exploratory Factor Analyses The original EFA conducted with the 30-item test-version of the CSSWQ yielded seven factors with Eigen values [ 1, which accounted for 63.45 % of the total variance. However, inspection of the scree plot and results from the parallel analysis both suggested a four-factor solution. Thus, four-, five-, and six-factor solutions were estimated and findings from each were compared with the original seven-factor solution. After inspecting the pattern matrices yielded by each potential solution, the intercorrelations of the resulting factors for each solution, and the item-content of each factor indicated by each solution, the four-factor solution was identified as the best data-model fit, as it most closely resembled the hypothesized five-factor conceptual framework, minimized the number of high cross-loading and non-loading items, and indicated the most robust factor loadings. Findings from the four-factor solution indicated that AGS-2, SAS-1, and SAS-3 were high cross-loading items, while ASES-6, SAS-2, and AGS-2 were non-loading items. These six items were therefore dropped from the final four-factor solution. Additionally, further examination of factor-item content suggested that ASES-3 had poor conceptual fit with its co-loading factor-items (i.e., SAS-4, SAS-5, and SAS-6), and thus it was also dropped from the final solution. Finally, given that we intended to develop the CSSWQ as a brief, population-based screening measure, only the four highest-loading remaining items for each factor were maintained for the final four-factor solution. Because one of the factors, representing the SAS, only had three high-loading items remaining following the paring procedures, no further items were removed. Thus, the final EFA solution consisted of 15 selected items, compared to the original 30 pilot items, which accounted for 68.54 % of the total variance and loaded strongly onto four theoretically-sound factors, representing the Academic Efficacy Scale (AES), College Gratitude Scale (CGS), School Connectedness Scale (SCS), and Satisfaction with Academics Scale (SAS; see Table 2). 3.1.2 Reliability and Distribution Analyses Reliability analyses of the revised, 15-item CSSWQ indicated that all scales had strong internal consistency, with Cronbach’s a C .80. Descriptive statistics further indicated that the AES, SCS, and SAS were approximately normally distributed (skewness and kurtosis \ 1), while the distribution of the CGS was significantly negatively skewed and leptokurtic, similar to its global counterpart scale, the GQ-6 (see Table 3). 3.1.3 Concurrent Validity Analyses Bivariate correlations of the CSSWQ subscales with each other indicated significant, positive relations ranging from r = .24 (AES, SCS) to .56 (AES, SAS). Similarly,

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Table 2 Final-solution EFA pattern matrix for the College Student Subjective Wellbeing Questionnaire Item

Factor/scale Academic efficacy

College gratitude

School connectedness

Satisfaction with academics

SAS4

-.04

.14

.13

.66

SAS5

.16

-.08

-.04

.83

SAS6

-.04

-.02

-.04

.98

AGS3

.83

-.02

-.02

-.10

AGS6

.64

.12

-.02

.11

SCS1

.06

-.04

.60

.06

SCS3

-.05

-.04

.77

.07

SCS4

-.04

-.02

.74

.03

SCS6

.07

.10

.74

-.16

ASES4

.73

-.02

.06

.03

ASES6

.73

-.05

-.01

.04

CGS1

-.02

.58

.06

.05

CGS4

-.05

.67

.08

.06

CGS5

.00

.74

-.04

.00

CGS6

.05

.84

-.09

-.06

All high-loading factor coefficients ([.30) are formatted in bold font SAS Satisfaction with Academics Scale, AGS Academic Grit Scale, SCS School Connectedness Scale, ASES Academic Self-Efficacy Scale, CGS College Gratitude Scale

Table 3 Descriptive statistics of primary study variables: Subsample 1 Construct

Scale

# Items

Min., Max.

M

SD

Skew.

Kurt.

a .81

Academic efficacy

AES

4

6, 24

16.98

4.34

-.40

-.68

College gratitude

CGS

4

10, 28

24.78

3.26

-1.54

3.12

.80

School connectedness

SCS

4

4, 20

14.10

3.34

-.44

-.21

.80

Satisfaction with academics

SAS

Self-efficacy

GSES

3

3, 21

13.52

4.66

-.47

-.57

.88

10

19, 40

31.74

4.19

.15

-.29

.87

.13

-.42

.77

Grit

SGS

8

16, 40

26.56

4.71

Gratitude

GQ-6

6

17, 35

31.8

3.45

Social connectedness

LS-R

20

31, 79

63.72

10.32

Life satisfaction

SWLS-5

5

5, 35

24.70

6.92

-1.6

3.00

.67

-.84

.05

.91

-.60

-.33

.90

Min., Max. minimum and maximum observed scale scores, Skew. skewness, Kurt kurtosis, AES Academic Efficacy Scale, CGS College Gratitude Scale, SCS School Connectedness Scale, SAS Satisfaction with Academics Scale, GSES General Self-Efficacy Scale, SGS Short Grit Scale, GQ-6 Gratitude Questionnaire6, LS-R UCLA Loneliness Scale-Revised, SWLS-5 Satisfaction With Life Scale-5

correlations of the CSSWQ subscales with their counterpart global trait scales indicated significant, positive relations ranging from r = .26 (AES, GSES) to .64 (AES, SGS). Moreover, correlations of the CSSWQ subscales with their non-counterpart global trait scales indicated significant, positive relations ranging from r = .11 (SAS, GSES) to .45 (CGS, LS-R; see Table 4).

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Table 4 Bivariate correlations among primary study variables: Subsample 1 Scale

1.

2.

3.

4.

5.

6.

7.

1.

AES

1

2.

CGS

.28

3.

SCS

.24

.43

4.

SAS

.56

.24

.28

5.

GSES

.26

.37

.29

.11*

6.

SGS

.64

.25

.19

.39

.36

7.

GQ-6

.28

.32

.34

.20

.29

.25

8.

LS-R

.29

.45

.55

.27

.36

.35

.49

9.

SWLS5

.43

.39

.50

.46

.38

.44

.47

8.

9.

1 1 1 1 1 1 1 .64

1

AES Academic Efficacy Scale, CGS College Gratitude Scale, SCS School Connectedness Scale, SAS Satisfaction with Academics Scale, GSES General Self-Efficacy Scale, SGS Short Grit Scale, GQ-6 Gratitude Questionnaire-6, LS-R UCLA Loneliness Scale-Revised, SWLS-5 Satisfaction With Life Scale-5 * Correlation significant at the p \ .05 level. All other correlations significant at the p \ .01 level

3.2 Phase Two: Subsample 2 3.2.1 Confirmatory Factor Analyses Two CFA were conducted using the 15-item CSSWQ derived from the Phase One analyses. Model 1 estimated a fully-correlated measurement model with four first-order latent traits (i.e., academic efficacy, school connectedness, college gratitude, and satisfaction with academics), while Model 2 estimated a second-order latent-trait model in which the four first-order latent traits were structured as indicators of the higher-order latent trait of college-student covitality. Findings from both CFA indicated adequate data-model fits (Model 1: v2 = 221.53, df = 84, p \ .001, CFI = .967, SRMR = .050, RMSEA [90 % CI] = .053 [.045, .062]; and Model 2: v2 = 272.74, df = 86, p \ .001, CFI = .955, SRMR = .067, RMSEA [90 % CI] = .061 [.053, .069]). Furthermore, findings from both models indicated that all factor loadings, for all first-order latent variables as well as the second-order latent trait, were significant and robust in the hypothesized direction. Given that the data-model fit statistics and the factor loadings for both models were comparable, and considering that Model 2 was more parsimonious, the second-order model, which estimated college-student covitality as a higher-order latent trait, was identified as the CSSWQ’s preferred measurement model (see Fig. 1). 3.2.2 Reliability and Distribution Analyses Reliability analyses using the factor loadings from the second-order CSSWQ measurement model indicated that all items had adequate reliabilities (‘2 C .37), that the four first-order latent traits (i.e., academic efficacy, school connectedness, college gratitude, and satisfaction with academics) had strong reliabilities (H C .80), and that the second-order latent trait (i.e., college-student covitality) also had adequate reliability (H = .79; see Fig. 1). Descriptive statistics indicated that, similar to the findings from the Phase One analyses, the AES, SCS, and SAS were approximately normally distributed (skewness and kurtosis \ 1), while the distribution of the CGS was significantly negatively skewed and leptokurtic, again similar to its counterpart global scale, the GQ-6 (see Table 5).

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Fig. 1 Preferred CFA Measurement Model for the College Student Subjective Wellbeing Questionnaire. Unstandardized loading fixed to 1.0; thus, no significance level computed. *Factor loading significant at the p \ .01 level

3.2.3 Concurrent Validity Analyses The LVPA, which extended the preferred, second-order CSSWQ measurement model to predict the latent constructs of global psychological distress (indicated by the DAS-21-D and PANAS-N) and global psychological wellbeing (indicated by the SHS and PANAS-P), indicated an adequate data-model fit (v2 = 557.15, df = 146, p \ .001, CFI = .923, SRMR = .079, RMSEA [90 % CI] = .070 [.063, .076]) and estimated that all factor

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477

Table 5 Descriptive statistics of primary variables: Subsample 2 Construct

Scale

Academic efficacy

AES

College gratitude

CGS

School connectedness Satisfaction with academics Self-efficacy

GSES

Grit

SGS

# Items/ indicators

SD

Skew

Kurtosis

a/H

Min., max.

M

4

4, 24

17.42

4.37

-.55

-.39

.87

4

8, 28

24.75

3.67

-1.75

3.59

.85

SCS

4

5, 20

14.39

3.23

-.25

-.48

.80

SAS

3

3, 21

13.65

4.64

-.44

-.79

.92

10

10, 40

31.85

4.45

-.25

.96

.89

8

13, 40

27.18

4.78

.00

-.10

.76

Gratitude

GQ-6

6

16, 42

36.56

4.73

-1.36

2.16

.71

Social connectedness

LS-R

20

32, 80

64.01

10.26

-.77

-.26

.91

Life satisfaction

SWLS-5

5

5, 35

25.18

6.31

-.58

-.19

.89

Happiness

SHS

4

4, 28

20.78

4.86

-.66

-.17

.85

Positive affect

PANAS-P

10

14, 50

35.73

7.45

-.27

-.33

.89

Depression

DAS-21-D

7

0, 21

4.34

4.36

1.31

1.42

.90

Negative affect

PANAS-N

10

10, 50

20.14

12.17

1.00

1.00

.89

Grade-point average

GPA

1

.80, 4

3.05

.54

-.64

.78

–

Min., Max. minimum and maximum observed scale scores, Skew. skewness, Kurt. kurtosis, AES Academic Efficacy Scale, CGS College Gratitude Scale, SCS School Connectedness Scale, SAS Satisfaction with Academics Scale, GSES General Self-Efficacy Scale, SGS Short Grit Scale, GQ-6 Gratitude Questionnaire6, LS-R UCLA Loneliness Scale-Revised, SWLS-5 Satisfaction With Life Scale-5, SHS Subjective Happiness Scale, PANAS-P Positive and Negative Affect Schedule-Positive, DAS-21-D Depression Anxiety Stress Scales-21-Depression, PANAS-P Positive and Negative Affect Schedule-Negative, GPA grade point average

School Connect.

.66†

.97† -.70*

Academic Efficacy

Psychological Distress

Depression

.64* Negative Affect

.65* Student Covitality .76*

.54*

Satisfaction with Acad.

.70†

.97*

College Gratitude

Psychological Wellness

Happiness

.73* Positive Affect

Fig. 2 LVPA Model for the College Student Subjective Wellbeing Questionnaire. Unstandardized loading fixed to 1.0; thus, no significance level computed. *Factor loading or standardized path coefficient significant at the p \ .01 level

standardized path coefficients, extending to all observed and latent variables, were significant and robust in the hypothesized direction (see Fig. 2). Moreover, the resulting squared multiple correlations (R2) indicated that the college-student covitality factor

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accounted for approximately 49 % and 94 % of the variance in the global psychological distress and psychological wellness constructs, respectively. Concurrent validity was further explored by examining the incremental validity of participants’ college-student and global covitality statuses on their self-reported GPA. Collegestudent and global covitality statuses were determined post hoc via a multi-step process, which included (a) conducting a CFA to verify the hypothesized structure of global covitality (i.e., five observed indicators—GSES, SGS, GQ-6, LS-R, and SWLS-5—loading onto an underlying latent variable (data-model fit statistics: v2 = 25.62, df = 5, p \ .001, CFI = .969, SRMR = .035, RMSEA [90 % CI] = .084 [.054, .118], H = .79), (b) transforming all subscale scores into z-scores, (c) summing these standardized subscale scores to create the CollegeStudent Covitality Composite (CSCC = AESz ? CGSz ? SCSz ? SASz) and the Global Covitality Composite (GCC = GSESz ? SGSz ? GQ-6z ? LS-Rz ? SWLS-5z), (d) ensuring that both composite variables were approximately normally distributed (see Table 4), and then (e) assigning participants to one of four status groups for both types of covitality, based on the position of their composite scores within the respective sampling distributions, using a fourgroup categorization schema common to standardized testing, assessment, and screening (i.e., below average = composite score \-1 SD [nCSCC = 93, nGCC = 104]; low average = -1 SD \ composite score \ 0 SD [nCSCC = 181, nGCC = 168]; high average = 0 SD \ composite score \ 1 SD [nCSCC = 221, nGCC = 219]; above average = composite score [ 1 SD [nCSCC = 89, nGCC = 93]). This methodological procedure was undertaken to essentially simulate the utility of the CSSWQ as a classification instrument for college students’ subjective wellbeing. Using these grouping variables, a pair of univariate between-subjects ANOVA yielded main effects for student-covitality status on GPA, F (3, 580) = 41.03, p \ .001, R2 = .18, as well as for global covitality status on GPA, F (3, 580) = 10.49, p \ .001, R2 = .05. Furthermore, post hoc comparisons yielded various significant between-group differences for the effects of both covitality statuses on GPA (see Table 6). Additionally, to provide a metric for evaluating the magnitude of differences across comparisons of covitality Table 6 Post-hoc comparisons of covitality statuses on grade point average: Subsample 2 Grouping variable

Subgroup (A)

College-student covitality

Global covitality

BA

M Diff. (A - B)

SE

p

g [95 % CI]

LA

-.22

.06

.004

.39 [.33, .46]

HA

-.52

.06

\.001

1.10 [1.05, 1.15]

(B)

AA

-.68

.07

\.001

1.35 [1.28, 1.42]

LA

HA

-.30

.05

\.001

.53 [.45, .61]

AA

-.46

.06

\.001

.87 [.81, .93]

HA

AA

-.16

.06

.05

.37 [.32, .42]

BA

LA

-.19

.06

.024

.31 [.25, .38]

HA

-.30

.06

\.001

.57 [.51, .63]

LA HA

AA

-.38

.08

\.001

.66 [.58, .74]

HA

-.11

.05

.175

.23 [.18, .29]

AA

-.19

.07

.03

.36 [.29, .42]

AA

-.08

.07

.630

.14 [.09, .20]

M Diff mean score difference between A and B, g [95 % CI] Hedge’s g with 95 % confidence interval, BA below average, LA low average, HA high average, AA above average

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479

statuses, standardized mean-difference effect sizes (Hedge’s g) were calculated for all post hoc comparisons. Findings from these calculations indicated a range of small to large effect sizes (g = .31 to 1.35), with the smallest effects observed in comparisons of the high-average and above-average groups and the largest effects observed in comparisons of the below-average and above-average groups (see Table 6).

4 Discussion 4.1 Interpretation of Results The overarching purpose of the present study was to inquire into the viability and incremental validity of college-specific subjective wellbeing indicators and domain-specific covitality via developing and testing the CSSWQ. To this end, the first and second subpurposes of this study were to develop an initial conceptual model and associated testitems for the CSSWQ, and then to explore the psychometric properties of this measure. Findings from the Phase One-Subsample 1 EFA yielded a four-factor structure for the CSSWQ that was more parsimonious than our hypothesized five-factor structure and still theoretically coherent. Three of our original hypothesized scales were supported via EFA findings (i.e., the CGS, SCS, and SAS), while items from the other two hypothesized scales (i.e., the ASES and AGS) loaded onto a single factor, which, following content analysis, was called the Academic Efficacy Scale (items: ‘‘I am a hard worker in my classes,’’ ‘‘I am a diligent student,’’ ‘‘I am an organized and effective student,’’ and ‘‘I study well for my classes’’). Although we originally conceptualized academic self-efficacy as an indicator of cognitive wellbeing and academic grit as an indicator of behavioral wellbeing, the content of the AES suggest that the underlying construct is more representative of behavioral wellbeing. Thus, the refined, 15-item version of the CSSWQ was comprised of one subscale representing each of the emotional (i.e., CGS), cognitive (i.e., SAS), social (i.e., SCS), and behavioral domains (i.e., AGS) of college students’ cumulative subjective wellbeing. Reliability analyses of these subscales indicated that they demonstrated strong internal consistency, and correlational analyses of these subscales with each other as well as with their global trait counterpart scales (i.e., the GSES, SGS, GQ-6, LS-R, and SWLS5) indicated only small-to-moderate statistically-significant positive relations—suggesting that, compared to the global measures, the CSSWQ’s domain-specific scales indeed measured related-yet-distinct constructs. Following these initial analyses, the third and final sub-purpose of the present study was to reevaluate the psychometric properties of the refined, 15-item version of the CSSWQ with an additional subsample. Findings from the Phase Two-Subsample 2 CFA confirmed the previously identified four-factor structure of the CSSWQ and, furthermore, indicated that its four first-order latent factors loaded well onto the hypothesized second-order latent factor of college-student covitality. Reliability analyses further indicated adequate to strong reliability for all items, the four first-order constructs, and the second-order covitality construct. Taken together, these findings suggest that the CSSWQ could be used to assess four domain-specific aspects of college students’ subjective wellbeing, and that its four subscales could be combined to represent college-grounded, cumulative subjective wellbeing. Moreover, findings from the subsequent LVPA provided initial concurrent validity for this second-order measurement model, demonstrating that the college-student covitality factor was a strong, negative predictor of global subjective distress and a strong, positive predictor of global subjective wellbeing.

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Additionally, by analyzing the between-group effects of college-student and global covitality statuses—operationalized as below average, low average, high average, or above average, according to standardized composite scores—on academic achievement, further concurrent validity and initial incremental validity evidence was provided for the CSSWQ. Specifically, ANOVA findings yielded main effects for both college-student and global covitality statuses on self-reported GPA, showing that college-student covitality accounted for substantially more of the variance in GPA than did global covitality status (i.e., 18 % compared to 5 %). Findings from the post hoc comparisons indicated that the observed effects were obtained in the hypothesized direction, with higher covitality-status groups showing greater mean GPAs than lower covitality-status groups. Furthermore, consideration of standardized mean-difference effect sizes (Hedge’s g) indicated that the differences between college-student covitality status groups yielded greater effects on GPA than did the differences between global covitality status groups, suggesting that the domainspecific measure had incremental validity in relation to academic achievement. Taken together, then, results from both phases of analyses suggest that the CSSWQ is a promising instrument for assessing college students’ cumulative, domain-specific subjective wellbeing, and, moreover, that college-student covitality is a viable, higher-order construct for further inquiry within subjective wellbeing studies. 4.2 Limitations and Future Research Despite the promising findings reviewed above, results from the present study should be considered in light of a few methodological limitations. Foremost, given that the participants were derived from a convenience sample of self-selected college students, the findings may not be representative of the population of interest. To remedy this limitation, we recommend that future research with the CSSWQ seek to employ stratified random sampling procedures. Additionally, the present sample was comprised entirely of college students from a university in the southern region of the United States and therefore has limited generalizability to students in other geographic and international locales. To address this shortcoming, we recommend future studies replicate and extend our analyses with diverse samples of college students, investigating measurement invariance among participants of differing genders, ethnicities, and locations. Furthermore, because all of the measures in the present study were self-reported, the data may be skewed or confounded by social-desirability effects (e.g., participants self-reporting higher GPAs than were actually obtained). And because the majority of measures were self-report rating scales, the data might also be biased by common-method variance (i.e., the variance attributable to the measurement method rather than to the constructs represented by the measures; Podsakoff et al. 2003). To account for these potential sources of error, we recommend that future research investigating the CSSWQ expand the repertoire of concurrent and predictive validity measures to include different types of self-report measures (e.g., frequency estimates of academic and coping behaviors) as well as more objective measures (e.g., university-reported GPA, attendance, and graduation rates). 4.3 Implications for Theory and Practice Given the findings reviewed above, results from the present study have a few noteworthy implications for both theory and practice. Regarding theory, this study offers further empirical support for the covitality construct. Specifically, findings from this study, along with those from a recent investigation by Jones et al. (2013), corroborate the validity of

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covitality within a college student sample. That said, this study is also the first that we know of to posit and provide evidence in support of a domain-specific version of college students’ cumulative subjective wellbeing—showing that the CSSWQ not only has concurrent validity with its counterpart global wellbeing measures, other wellbeing indicators, and subjective distress indicators, but that it also has incremental validity in relation to academic achievement. Although the recent development and investigation of schoolspecific measures of subjective wellbeing with primary and secondary students (e.g., Furlong et al. 2013; Renshaw et al. 2014b) have explored and validated school-grounded versions of covitality, the present study is the first, at least that we know of, to investigate the incremental validity of college-specific covitality compared to global covitality. Thus, in addition to further refining and investigating different operationalizations of the covitality construct, we recommend that future studies continue to explore the incremental validity of domain-specific covitality in relation to global covitality, especially in relation to domain-specific outcomes in schools (e.g., academic behaviors and achievement). Regarding practice, findings from this study suggest that the CSSWQ may be a promising population-based screening instrument for assessing, responding to, and monitoring the positive dimension of college students’ mental health (cf. Dowdy et al. 2010). Findings from this study were used to refine the CSSWQ into a brief measure (15 items), verify its multidimensional latent structure, and demonstrate its concurrent validity with academic achievement, psychological distress, and psychological wellness indicators— suggesting that the CSSWQ is an efficient and targeted measure of college students’ cumulative subjective wellbeing. Although the role and utility of population-based mental health screening is gaining increasing attention in primary and secondary school settings, it has received far less consideration in college and university settings. That said, with some studies indicating up to 50 % of college students self-reporting mental health problems (e.g., Blanco et al. 2008; Zivin et al. 2009) and other studies suggesting the importance of subjective wellbeing indicators in predicting college-student outcomes (e.g., Eklund et al. 2011; Renshaw and Cohen 2014), greater efforts to implement mental health screening, prevention, and promotion programs on college campuses appear warranted. Given this context, we suggest that the CSSWQ may be used in practice as a well-rounded, promising measure of the positive dimension of college students’ mental health. And thus, in closing, we recommend that future research also explore the treatment validity of the domainspecific traits assessed by the CSSWQ, because to be truly fruitful for practice, such traits must not only be measurable, as they have been demonstrated to be herein, but also amenable to intervention.

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