SHORT REPORT Open Access Bifactor model of the CASP-12’ s general factor for measuring quality of life in older patients Matthew J. Kerry To the editor Patients’ subscores on quality of life (QoL) measures can provide diagnostic information about strengths and weak- nesses of respondents’ performance in specific areas. Such diagnostics may help with identification of potential at-risk individuals. Subscores may also help with modify- ing extant care-treatment programs, particularly those among patient-preferred specific functionalities [1]. The Control, Autonomy, Self-realization and Pleasure (CASP) measure is one, popular QoL measure example with such subscore potential, which will be of focal interest in the current short report [2]. The CASP builds on psychology needs-satisfaction models to emphasize wellbeing across its four titled do- mains [3]. The shortened version of the original CASP-19 scale, was designed specifically for use in the Survey of Health, Ageing and Retirement in Europe (SHARE) study (CASP-12) [4], representing two combined factors: 1)Con- trol/Autonomy, and 2) Self-realization/Pleasure. Extant psychometric studies of the CASP-12 have been limited by classical measurement approaches. For example, the proposed combination of CASP’ s first two subscales for greater stability contradicts the retention of its other, two shorter subscales exhibiting higher internal reliabilities. Also, proposed combining (or, parceling) of items for fit- ting unidimensional prediction models potentiates further upward-bias from subdomain-criterion relations. The current short report’ s primary aim is to psycho- metrically inspect the CASP-12 with modern measure- ment’ s item response theory (IRT). This is important, because increasing usage is potentially unproductive due to incomplete inspection of the CASP’ s internal psycho- metric structure, such as general factor strength and substantive multidimensionality [5]. This limits, among other things, the CASP-12’ s equating across studies that use different subsets of items, as well as hindering the CASP’ s expansion to new items when CASP-12’ s core-pool has not been IRT-calibrated. The current study will identify and extending initial findings from SHARE’ s older-adult general population and examine CASP-12’ s uni- /multi -dimensionality in a patient-spe- cific sample from the Irish Longitudinal Study on Ageing (TILDA) [6]. Since the early, 1990’ s days of QoL research, investiga- tors have generally agreed that physical, mental, and so- cial health subdomains are inseparable, that is, QoL is a fairly broad construct [7]. As mentioned in this author’ s earlier IRT evaluation of another health measure– “broader constructs are stabilized with broad factors” [8]. As the CASP’ s author reassures researchers that “those who simply require a single index” may sum the CASP-12, it is important to first-determine if unidimen- sional usage in prediction models is reasonably unbiased by ignoring subdomains. As the CASP constructor’ s con- cluded, “…strength of the inter-domain correlations…. confirm our belief that QoL is a unitary phenomenon which is the product of the interactions between the do- mains” [2]. This interpretation of general QoL as-caused by inter-domain interactions is important, because it contradicts the commonly accepted second-order CASP model, which hierarchically represents general QoL as causally preceding variation on its four specific domains (control, autonomy, self-realization, pleasure). If, instead, the CASP’ s general QoL factor is correctly interpreted as ‘emerging’ from diverse manifestations represented by subdomains, then within-domain variation may be more accurately viewed more-so as nuisance variation that can and should be statistically treated as such in the meas- urement of QoL [9, 10]. For example, Sexton and others’ have suggested to covary residuals for CASP’ s negatively worded items “arising from method effects” [11]. Fitting this alternative view, the bifactor model is a viable competitor to the second-order hierarchical model that will be empirically compared on model-data fit, as well Correspondence: kerr@zhaw.ch Zurich University of Applied Sciences (ZHAW) - Institute of Health Sciences, Technikumstrasse 71, 8041 Zurich, Switzerland Journal of Patient- Reported Outcomes © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Kerry Journal of Patient-Reported Outcomes (2018) 2:57 https://doi.org/10.1186/s41687-018-0078-x