Psychometrics of the Revised College Student Subjective Wellbeing Questionnaire

Abstract

The College Student Subjective Wellbeing Questionnaire (CSSWQ) is a 15-item self-report rating scale for measuring four classes of college-specific wellbeing behavior: academic efficacy, academic satisfaction, school connectedness, and college gratitude. The present study investigated the psychometrics of a revised version of this measure, which included an additional item measuring academic satisfaction (for the purposes of balancing the number of items across subscales) and standardized the response options for all items to a unified 7-point Likert-type scale (for the purposes of enhancing administration feasibility and scoring interpretability), with a sample of current U.S. college students (N = 401). Results indicated that responses to the revised version of the CSSWQ had adequate data–model fit to the proposed higher-order measurement model, that all factors were characterized by strong latent construct reliability, and that the higher-order factor demonstrated convergent validity with several domain-general measures of wellbeing and mental health problems. Implications for future research and practice are discussed.

Keywords

subjective wellbeing college students assessment measure development

Wellbeing is a broad construct used across the social, behavioral, and medical sciences to refer to all manner of healthy and successful human functioning (e.g., Biglan, Flay, Embry, & Sandler, 2012). When psychology is taken as the science of human behavior in context (Hayes, Barnes-Holmes, & Wilson, 2012), the term psychological wellbeing can be understood as constituting both private behaviors (i.e., cognitions and emotions) and public behaviors (i.e., verbal and physical actions) that are either personally or socially desirable (Renshaw, 2016c). Used in this way, the term wellbeing behavior can function as the companion construct to problem behavior, which is a commonly used term in applied psychology referring to all manner of behaviors (both private and public) that are personally or socially intolerable and thus warrant intervention. This broad conception of wellbeing is markedly distinct from traditional operationalizations of subjective wellbeing within the field of positive psychology, which have restricted the scope of the construct to subjective appraisals of private behaviors, such as life satisfaction, positive emotion, and happiness (see Diener, Oishi, & Lucas, 2009). Although this broader conception of wellbeing accounts for these traditional operationalizations, it also allows for a variety of other operationalizations—understanding subjective wellbeing not as an amalgam of particular private behaviors, but rather as a methodological strategy (i.e., self-report or self-appraisal) for measuring any relevant private or public behaviors that indicate successful or healthy functioning within a given context (Renshaw, 2016c). From this perspective, then, it is possible to frame a person’s self-appraisal of their public behavior (e.g., efficacy in meeting environmental demands) as an aspect of subjective wellbeing. This strategy is also just as applicable to domain-general wellbeing behavior (e.g., general efficacy) as it is to domain-specific wellbeing behavior (e.g., academic efficacy).

Within recent years, several multidimensional self-report behavior rating scales have been developed and validated for measuring students’ domain-general and domain-specific wellbeing behavior. These measures have been intended for use as basic research instruments as well as for practical purposes within school-based mental health frameworks, such as for universal screening, prevention and intervention planning, and progress monitoring. For example, the Social and Emotional Health Survey (SEHS) is comprised of several subscales measuring various domain-general wellbeing constructs with adolescent students, such as self-awareness, empathy, and optimism (private wellbeing behaviors) as well as persistence, self-efficacy, and self-control (public wellbeing behaviors), among others (Furlong, You, Renshaw, Smith, & O’Malley, 2014; Renshaw, 2016a; You et al., 2014). The Positive Experiences at School Scale (PEASS), on the contrary, consists of four subscales measuring school-specific wellbeing constructs with students in both primary and secondary schools, including gratitude, optimism, and zest (private wellbeing behaviors) as well as academic persistence (public wellbeing behavior; Furlong, You, Renshaw, O’Malley, & Rebelez, 2013; Renshaw, 2016b). Similar to the PEASS, the Student Subjective Wellbeing Questionnaire (SSWQ) is comprised of four subscales measuring school-specific wellbeing constructs with adolescent students: joy of learning and educational purpose (private wellbeing behaviors), plus school connectedness and academic efficacy (public wellbeing behaviors; Renshaw, 2015; Renshaw & Arslan, 2016; Renshaw, Long, & Cook, 2015).

Although these multidimensional measures of youth and student wellbeing have been developed with practical intentions, there is, to date, very little research demonstrating their clinical utility for informing school psychological practice. One emerging area of research with potential practical utility, however, is exploring the incremental validity of scores derived from subjective wellbeing measures considered in conjunction with results from traditional problem behavior measures when classifying students into mental health categories for informing intervention. Conceptualizing wellbeing and problem behavior as distinct yet related dimensions of mental health that each warrant assessment in their own right, the conceptual approach underlying this line of research has been described variously as the bidimensional, dual-factor, two-continua, or complete model of mental health. Findings from studies investigating this phenomenon have demonstrated that, compared with classification models considering only problem behavior or psychopathology indicators, classification models considering both problem behavior and subjective wellbeing have incremental validity for identifying students with increasing levels of concurrent and longitudinal risk across a variety of outcome domains (e.g., academic achievement, interpersonal relationships, and physical health). Indeed, the classification utility of the bidimensional model of mental health has been generalized across a variety of samples, including children in elementary school (Greenspoon & Sasklofske, 2001), adolescents in secondary schools (Suldo & Shaffer, 2008; Suldo, Thalji, & Ferron, 2011), young adults in postsecondary schools (Eklund, Dowdy, Jones, & Furlong, 2011; Renshaw & Cohen, 2014; Renshaw, Eklund, Bolognino, & Adodo, 2016), and adults in work-related contexts (Keyes, 2007).

Although findings from studies investigating the bidimensional mental health model appear empirically promising, one consistent limitation has been that measures used to assess wellbeing behavior have been far less comprehensive than those used to assess problem behavior (Renshaw & Cohen, 2014). This suggests an imbalance or bias regarding the import placed on each dimension of mental health during the assessment process—favoring measures of negative functioning over positive functioning. Thus, the development and validation of multidimensional measures of youth and student subjective wellbeing is especially likely to inform future research and practice in this area, providing a more robust means of assessing positive functioning that might help inform mental health service delivery in schools (see Dowdy et al., 2015, for an applied example toward this end). Although, as mentioned above, several multidimensional measures of student subjective wellbeing have been developed in recent years (e.g., the SEHS, PEASS, and SSWQ), it is noteworthy that the majority of work in this area has targeted primary and secondary students. Yet recent efforts have turned toward postsecondary students, seeking to both adapt preexisting measures of youth wellbeing for use with college students (e.g., the SEHS; Furlong, You, Shishim, & Dowdy, 2016) as well as to develop and validate new measures specifically designed for college students. The general purpose of the present study was to further probe the technical adequacy of one of the few available multidimensional and domain-specific wellbeing measures for postsecondary students: the College Student Subjective Wellbeing Questionnaire (CSSWQ; Renshaw & Bolognino, 2016).

The CSSWQ is a 15-item self-report rating scale for measuring four classes of college-specific wellbeing behavior: academic efficacy (four items), academic satisfaction (three items), school connectedness (four items), and college gratitude (four items; Renshaw & Bolognino, 2016). This measure was developed by identifying four common domain-general indicators of wellbeing behavior and their associated measures—self-efficacy (Schwarzer, Bäßler, Kwiatek, Schörder, & Xin Zhang, 1997), grit (Duckworth & Quinn, 2009), life satisfaction (Diener, Emmons, Larsen, & Griffin, 1985), gratitude (McCullough, Emmons, & Tsang, 2002), and social connectedness (Russell, Peplau, & Cutrona, 1980)—and then adapting the item wording of these instruments to be domain-specific by using language targeted to post-secondary school contexts. Selected constructs were not intended to be an exhaustive representation of all possible college-specific private and public wellbeing behaviors; rather, they were intended to be a representative sampling of such constructs. Findings from the CSSWQ’s original development study, which used two subsamples of largely White and mostly female college students (N = 971), indicated that responses to the measure yielded a psychometrically sound higher-order measurement model characterized by good data–model fit and strong internal reliability across factors and scales (H and α ≥ .80). Results from this development study also yielded initial convergent validity evidence, showing that the CSSWQ’s single higher-order factor (representing covitality or generalized college student wellbeing) was a strong predictor of both domain-general psychological distress (β = −.70) and psychological wellbeing (β = .97; Renshaw & Bolognino, 2016).

Given that no further research has been conducted to investigate the technical adequacy of the CSSWQ, the specific purpose of the present study was to further refine and validate this measure by (a) revising the instrument to include an additional item measuring academic satisfaction (for the purposes of balancing the number of items across subscales) as well as by standardizing the response options for all items to a unified 7-point Likert-type scale (for the purposes of enhancing administration feasibility and scoring interpretability), (b) investigating the structural validity of responses to this revised version of the measure, and (c) exploring the convergent validity of responses to the revised measure with valued concurrent outcomes (i.e., domain-general indicators of psychological distress, psychological wellbeing, and academic achievement). It was hypothesized that responses to the revised version of the CSSWQ would demonstrate strong psychometric properties akin to the original version.

Method

Participants and Sampling

Participants were 401 undergraduate college students attending a large university located in the southern region of the United States. The majority of participants were female (86.3%) and self-identified as White (76.8%). Also included in the sample were participants who self-identified as Black or African American (12.5%), Asian (3.7%), Indian (3.5%), Latino/a (2.5%), and Other ethnicities (1%). The mean age of participants was 20.12 years (SD = 2.66), and, at the time of the study, participants were in various years of enrollment at the university (first year = 28.7%, second year = 22.4%, third year = 30.2%, fourth year, or higher = 18.7%). 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 required that students be at least 18 years of age but was not restricted by any other personal characteristics. Each participant used a secure online server to complete the study survey, which consisted of a series of demographic questions followed by various self-report instruments (described below in the “Measures” section). All participants received partial course credit for completing the survey, which took approximately 20 to 30 min. Approval from the university’s institutional review board was obtained prior to beginning the study, and informed consent was acquired for all participants prior to initiating the online survey.

Measures

The CSSWQ (Renshaw & Bolognino, 2016) was the primary measure of interest in the present study. As mentioned above, the original CSSWQ was comprised of 15 self-report items measuring four college-specific wellbeing behaviors—academic satisfaction, academic efficacy, school connectedness, and college gratitude—and demonstrated strong psychometric properties. The revised version of the CSSWQ tested in the present study included an extra item measuring academic satisfaction (for the purposes of balancing the number of items across subscales), which was drafted to be conceptually consistent with the preexisting items in the scale. This revised version of the CSSWQ also standardized the response options for all items to a unified 7-point Likert-type scale (for the purposes of enhancing administration feasibility and scoring interpretability; 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neutral, 5 = slightly agree, 6 = agree, 7 = strongly agree). Findings regarding the technical adequacy of the revised version of the CSSWQ with the present sample are provided in the Results section.

The Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) was selected as a convergent validity measure for the CSSWQ because it is a widely used and technically adequate measure of global emotional experience. The Positive Emotions Scale (PES) of the PANAS was conceptualized as an indicator of private wellbeing behavior and was therefore hypothesized to have positive associations with scores derived from the CSSWQ, while the Negative Emotions Scale (NES) was conceptualized as an indicator of private problem behavior and was therefore hypothesized to have negative associations with CSSWQ scores. Both the PES and NES are comprised of 10 items asking participants to self-report their experiences of particular emotions (e.g., “afraid” or “excited”) during the last week and are arranged along a 5-point response scale (1 = not at all, 2 = a little, 3 = moderately, 4 = quite a bit, 5 = extremely). Responses to both scales were relatively normally distributed (skewness and kurtosis < |1|) and demonstrated strong internal reliability (PES α = .91, NES α = .88) with the present sample.

The Satisfaction With Life Scale (SLS; Diener et al., 1985) and the Adult Hope Scale (AHS; Snyder et al., 1991) were selected as additional convergent validity measures for the CSSWQ because they are widely used and technically adequate measures of global wellbeing behavior. The SLS consists of five self-report items assessing thoughts of life satisfaction (e.g., “In most ways my life is close to ideal”), which are arranged along a 7-point response scale (1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neutral, 5 = slightly agree, 6 = agree, 7 = strongly agree). The AHS is comprised of eight self-report items assessing self-appraisals of both goal-directed public behavior (e.g., “I energetically pursue my goals”) and goal-directed private behavior (e.g., “I can think of many ways to get out of a jam”), which are arranged along an 8-point response scale (1 = definitely false, 2 = mostly false, 3 = somewhat false, 4 = slightly false, 5 = slightly true, 6 = somewhat true, 7 = mostly true, 8 = definitely false). Responses to both scales were relatively normally distributed (skewness and kurtosis ≤ |1.5|) and evidenced strong internal reliability (SLS α = .88, AHS α = .91) with the present sample. A single item representing self-reported grade point average (GPA) was also used as a convergent validity measure for the CSSWQ, and responses to this item were likewise observed to be relatively normally distributed with the present sample. Scores derived from the SLS, AHS, and GPA were all hypothesized to have positive associations with scores from the CSSWQ.

The Beck Anxiety Inventory (BAI; Beck, Brown, Epstein, & Steer, 1988) and the Beck Depression Inventory–2 (BDI; Beck, Steer, Ball, & Ranieri, 1996) were selected as additional convergent validity measures for the CSSWQ given their wide use and established technical adequacy as self-report measures of problem behavior. The 21 items of the BAI are brief and directly phrased statements of symptoms associated with anxiety (e.g., “Nervous,” “Fear of losing control,” and “Scared”), which are arranged along a 4-point response scale (0 = not at all, 1 = mildly—but it didn’t bother me much, 2 = moderately—it wasn’t pleasant at times, 3 = severely—it bothered me a lot). The 21 items of the BDI are similarly phrased brief statements of symptoms associated with depression (e.g., “sadness,” “loss of pleasure,” and “self-dislike”), which are arranged along a 4-point response scale that is unique for each item and indicates progressing symptom severity (e.g., “Sadness”: 0 = I do not feel sad, 1 = I feel sad much of the time, 2 = I am sad all of the time, 3 = I am so sad or unhappy that I can’t stand it). Responses to both scales were relatively normally distributed (skewness and kurtosis < |1.5|) and demonstrated strong internal reliability with the present sample (BAI α = .92, BDI α = .93). Scores derived from both the BAI and BDI were hypothesized to have negative associations with scores from the CSSWQ.

Data Analyses

Given that no missing data were observed, no procedures were warranted to account for missingness. Several phases of data analyses were conducted to investigate the technical adequacy of the revised CSSWQ with the present sample. First, confirmatory factor analyses (CFAs) were conducted to investigate the measure’s higher-order latent structure. This was accomplished using a two-phase analytic approach recommended by Mueller and Hancock (2008), wherein the basic first-order measurement model is established via an initial CFA, followed by an another CFA that further specifies the structural features of the model, such as higher-order factors. To determine the goodness of data–model fit, a combination of absolute and incremental fit indices were evaluated. Comparative fit index (CFI) values between .90 and .95, standardized root mean square residual (SRMR) values < .08, and root mean square error approximation (RMSEA) values (with an accompanying 90% confidence interval) < .08 were considered to indicate adequate data–model fit, while CFI values > .95, SRMR values < .05, and RMSEA values < .05 were considered indicative of good data–model fit (Kenny, 2014; Kline, 2011). Regarding factor loadings, λ ≥ .50 were taken to be strong, as they accounted for ≥ 25% of the variance extracted from each item by the latent factor (ℓ²). For latent construct reliability, H ≥ .70 was considered desirable, as this suggests a strong intrafactor correlation over repeated administrations (Mueller & Hancock, 2008). Coefficient H was used as the preferred estimate of internal consistency reliability given that it is more appropriate than coefficient α for multidimensional measures and is less likely to overestimate or underestimate reliability (Widhiarso & Ravand, 2014). However, coefficient α was also calculated at the observed level for comparison purposes.

Beyond analyses conducted at the latent level, observed scale characteristics were also analyzed to investigate the distribution and internal reliability of responses to each of the CSSWQ scales with the present sample, using common decision rules to determine relative normality (skewness and kurtosis ≤ |2|) and internal consistency reliability (α ≥ .70). These same descriptive analyses were also conducted at the observed level for the convergent validity measures. Given that each of the convergent validity scales represented unidimensional constructs and that tau-equivalency measurement models were assumed, coefficient α was deemed a sufficient estimate of internal consistency reliability for these measures (Dunn, Baguley, & Brunsden, 2014). Following, convergent validity analyses were carried out by, first, conducting bivariate correlations between the observed CSSWQ scale scores and the criterion scores (i.e., PES, NES, SLS, AHS, BAI, BDI, and GPA), and, second, extending the higher-order CSSWQ measurement model into a latent variable path analyses (LVPA) that predicted each of the criterion variables. All latent-level analyses were conducted using Amos Version 22, whereas all observed-level analyses were conducted using SPSS Version 22. A combination of statistical significance level, relational directionality, and effect size magnitude were used to interpret convergent validity findings, using common decision rules for correlation (r) and multiple correlation (R²) coefficients (see Cohen, 1988).

Results

Structural Validity

Preliminary analyses indicated relative multivariate normality, and therefore CFA and LVPA were conducted using the Maximum Likelihood estimator. Findings from the Phase 1 CFA, which structured the 15 original and one revised CSSWQ items (16 total) as indicators of the four fully-correlated first-order latent factors (i.e., academic satisfaction, academic efficacy, school connectedness, and college gratitude), indicated adequate data–model fit across multiple indices (χ² = 372.38, df = 98, p < .001, SRMR = .055, CFI = .923, RMSEA [90% CI] = .084 [.075, .093]). The standardized factor loadings (λ) for this measurement model were robust across all four constructs, ranging from .60 to .92 (ℓ² range = .36-.85), and each factor had strong latent construct reliability, with H values ≥ .80 (see Table 1). Moderate to strong interfactor correlations were also observed between all latent variables (ϕ range = .44-.75). Given that the obtained RMSEA value was suboptimal, the residual correlation matrix and modification indices (MI) were explored to identify potential alterations to the structural model that might enhance data–model fit. Although several MI indicated small, incremental improvements to model fit could be obtained via covarying various item error terms or by adding regressions among items, these alterations did not appear warranted by the item content nor the goal of measurement development. Therefore, the original, parsimonious model was maintained for the higher-order CFA. Findings from the Phase 2 CFA, which extended the previous measurement model by structuring each of the four first-order factors as indicators of a single higher-order factor (i.e., covitality or generalized student wellbeing), indicated a similarly adequate data–model fit compared with the first-order model (χ² = 387.51, df = 99, p < .001, SRMR = .059, CFI = .919, RMSEA [90% CI] = .085 [.077, .094]). The additional standardized loadings for the second-order factor were also robust, ranging from .62 to .86 (ℓ² range = .38-.74), contributing to strong latent construct reliability (H = .87; see Table 1). Observed characteristics of responses to the CSSWQ subscales as well as the overall composite scale further indicated adequate to strong internal consistency (α ≥ .79) and relatively normal distributions (skewness and kurtosis < |2|)—the only exception being responses to the college gratitude scale, which were substantially negatively skewed and positively kurtotic (see Table 2).

Table 1.

CFA Results for the Revised CSSWQ.

Scale and items	λ₁	$l_{1}^{2}$	λ₂	$l_{2}^{2}$	H
Academic satisfaction	—	—	.83	.69	.92
I have had a great academic experience at (name of college).	.67	.45	—	—	—
I am happy with how I’ve done in my classes.	.86	.74	—	—	—
I am satisfied with my academic achievements since coming to (name of college).	.92	.85	—	—	—
I am pleased with how my college education is going so far.	.80	.64	—	—	—
Academic efficacy	—	—	.86	.74	.88
I am a hard worker in my classes.	.82	.67	—	—	—
I am a diligent student.	.86	.74	—	—	—
I am an organized and effective student.	.78	.61	—	—	—
I study well for my classes.	.73	.53	—	—	—
School connectedness	—	—	.62	.38	.85
I feel like a real part of (name of college).	.70	.49	—	—	—
People at this school are friendly to me.	.75	.56	—	—	—
I can really be myself at this school.	.79	.62	—	—	—
Other students here like me the way I am.	.79	.62	—	—	—
College gratitude	—	—	.71	.50	.80
I am so thankful that I’m getting a college education.	.60	.36	—	—	—
I am grateful to the professors and other students who have helped me in class.	.70	.49	—	—	—
I feel thankful for the opportunity to learn so many new things.	.75	.56	—	—	—
I am grateful for the people who have helped me succeed in college.	.73	.53	—	—	—
Total Student Wellbeing Scale.	—	—	—	—	.87

Note. CFA = confirmatory factor analysis; CSSWQ = College Student Subjective Wellbeing Questionnaire; λ₁ = item loadings for first-order factors; $l_{1}^{2}$ = indicator reliability for first-order factor items; λ₂ = first-order factor loading for second-order factor; $l_{2}^{2}$ = indicator reliability for second-order factor indicators; H = latent construct reliability for first-order and second-order factors.

Table 2.

Observed Scale Characteristics of the Revised CSSWQ.

CSSWQ Scale	M	SD	Min.	Max.	IQR	Skewness	Kurtosis	α
Academic satisfaction	21.65	4.84	6	28	6	−1.00	.48	.88
Academic efficacy	23.04	3.88	9	28	5	−.88	.63	.86
College gratitude	25.80	2.45	8	28	3	−2.23	9.80	.79
School connectedness	22.27	4.09	5	28	5	−1.10	1.67	.83
Total student wellbeing	92.76	12.24	37	112	16	−.94	1.18	.91

Note. CSSWQ = College Student Subjective Wellbeing Questionnaire; Min. = minimum scale value; Max. = maximum scale value; IQR = interquartile range.

Convergent Validity

Results from the series of bivariate correlations indicated that observed scores derived from each of the CSSWQ scales were significantly correlated with observed scores derived from each of the criterion measures (i.e., PES, AHS, SLS, NES, BAI, BDI, and GPA) and that the directionality of the associations was in the expected directions, with effect sizes indicating small-to-large relations across both positive and negative convergent measures (see Table 3). Results from the LVPA, which extended the higher-order measurement model of the CSSWQ so that the overall student wellbeing factor predicted each of the criterion variables, indicated no appreciable change in data–model fit and showed that the second-order factor was a statistically significant predictor of each criterion measure (p < .001). Relative variance in predictive power across the criterion variables was observed (PES β = .49, AHS β = .66, SLS β = 53, NES β = −.46, BAI β = −.34, BDI β = −.54, GPA β = .54) and consideration of the multiple correlations showed that the higher-order factor accounted for substantial proportions of the variance in each of the criterion variables, characterized by moderate-to-large effect sizes (PES R² = .24, AHS R² = .44, SLS R² = .28, NES R² = .21, BAI R² = .12, BDI R² = .29, GPA R² = .29).

Table 3.

Bivariate Correlations (r) for the Revised CSSWQ and Criterion Variables.

CSSWQ Scale	PES	AHS	SLS	NES	BAI	BDI	GPA
Academic satisfaction	.35	.49	.43	−.40	−.26	−.44	.50
Academic efficacy	.36	.51	.36	−.30	−.23	−.35	.48
College gratitude	.38	.48	.30	−.23	−.18	−.31	.17
School connectedness	.36	.44	.49	−.40	−.36	−.48	.11*
Total student wellbeing	.45	.60	.51	−.44	−.33	−.51	.42

Note. CSSWQ = College Student Subjective Wellbeing Questionnaire; PES = Positive Emotion Scale of the Positive and Negative Affect Schedule; AHS = Adult Hope Scale; SLS = Satisfaction with Life Scale; NES = Negative Emotion Scale of the Positive and Negative Affect Schedule; BAI = Beck Anxiety Inventory; BDI = Beck Depression Inventory; GPA = grade point average.

Significant at the p < .05 level; all other correlations significant at the p < .01 level.

Discussion

The purpose of the present study was to probe the technical adequacy of a revised version of the CSSWQ, which included an extra item measuring academic satisfaction (for the purposes of balancing the number of items across subscales) and standardized the response options for all items to a unified 7-point Likert-type scale (for the purposes of enhancing administration feasibility and scoring interpretability), with a sample of current college students that was demographically similar to the original development sample (cf. Renshaw & Bolognino, 2016). Findings from structural validity analyses confirmed the higher-order measurement model for responses to the revised version of the CSSWQ, while results from the convergent validity analyses provided positive evidence in favor of convergent validity for both observed scale scores and the higher-order latent factor score with concurrent measures of wellbeing and problem behavior.

Although the findings regarding the structural and convergent validity of the CSSWQ’s measurement model are promising, they warrant contextualization within the scope of the methodological limitations of the present study. First, participants were largely demographically homogeneous (i.e., majority White and female, attending a public university) and were obtained via convenience sampling. Generalization studies are thus warranted with larger and more diverse samples of college students prior to drawing conclusions regarding the generalizability of the technical adequacy of the revised version of the CSSWQ. Second, considering that all convergent criterion measures were collected concurrently using self-report behavior rating scales, findings may be biased by common-method variance (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Additional research is thus warranted to expand the repertoire of convergent criterion measures for the CSSWQ (e.g., informant-report, direct observation, permanent products, and school records). Third, given the demographic homogeneity of the sample paired with the relatively small sample size in the present study, advanced statistical analyses of the CSSWQ’s measurement invariance across key demographics (e.g., gender and race/ethnicity) could not be conducted. Therefore, future research with larger samples is warranted to investigate the ability of the CSSWQ to function as an equitable measure of college students’ multidimensional subjective wellbeing. Finally, the present study offers no data or direction regarding the potential treatment utility (see Hayes, Nelson, & Jarrett, 1987) of the CSSWQ for informing prevention or intervention efforts at the college level, and thus research is warranted to investigate the usefulness of scores derived from this measure within college-based mental health service delivery systems.

Overall, findings from the present study provide initial structural and convergent validity evidence in favor of using the revised version of the CSSWQ as a basic research measure and, potentially, as a practical instrument for informing mental health work. Although results suggest the measurement model for the revised version of the CSSWQ yielded slightly poorer (yet still adequate) data–model fit compared with the original measurement model (cf. Renshaw & Bolognino, 2016), the improvements in usability gained by including an additional item (for the purposes of balancing the number of items across subscales) and standardizing the response options for all items to a unified 7-point Likert-type scale (for the purposes of enhancing administration feasibility and scoring interpretability) appear to be reasonably appropriate relative to the minor statistical costs. However, rather than just assuming this cost–benefit trade-off tips toward the beneficial side of the scale, researchers interested in the continued development of this measure for both basic research and practical purposes are encouraged to pick-up where this study leaves off by further validating the revised version of the CSSWQ to empirically demonstrate this cost–benefit claim. In addition, classification utility research investigating the comparative and incremental validity of scores derived from the CSSWQ in relation to those from other measures assessing aspects of college student functioning—such as the SEHS (Furlong et al., 2016) and the Student Adaptation to College Questionnaire (Dahmus, Bernardin, & Bernardin, 1992)—is also warranted to more effectively guide the applied use of such instruments.

Footnotes

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.

Author Biography

Tyler L. Renshaw, PhD, is an assistant professor in the School Psychology Program within the Department of Psychology at Louisiana State University. His research interests are broadly focused on developing and validating measurement and intervention methods for promoting youths’ wellbeing and mental health in schools.

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