تجزیه و تحلیل اکتشافی اعتبار ساختاری در مورد سنجش Burden اسکیزوفرنی
Abstract
1- Background
2- Methods
3- Results
4- Discussion
5- Conclusion
References
Abstract
Background Various self-reported or clinician-reported (as a proxy) measures exist to quantify the burden of schizophrenia on patients. Evidence of the psychometric relationship between these measures to inform their practical use is limited. Objectives Our objective was to conduct an exploratory analysis of the construct validity of patient-reported (EQ-5D, SF-6D, WEMWBS, SQLS subscales of Psychosocial, Motivation, Symptoms) versus clinician-reported measures (PANSS, CGI-SCH, NSA-4, HoNOS-PbR) to inform future use of patient-reported measures for burden-of-illness assessment and/or economic evaluation.
Methods In an adult patient population with schizophrenia, construct validity was assessed in relation to convergent and known-group validity. Convergent validity was assessed using Spearman’s rank absolute correlation strength (ACS: weak ≤ 0.3, moderate = 0.3 < 0.5, strong ≥ 0.5) and graphically using locally weighted scatterplot smoothing (LOWESS) techniques. Known-group validity was assessed using Cohen’s d absolute efect size (AES: small ≤ 0.5, moderate = 0.5 < 0.8, large ≥ 0.8). Floor and ceiling efects were assessed as a proxy of sensitivity in this cross-sectional study. Statistical signifcance was assessed at the 5% threshold level (p < 0.05). Across head-to-head assessments, the frequency of producing the strongest ACS, largest AES, and statistically signifcant results determined the best overall construct validity. Results Overall, 304 patients consented to the study. In relation to statistically signifcant results, the SF-6D most frequently exhibited the strongest ACS and largest AES against the clinician-reported measure scores (ACS range 0.084–0.436; AES range 0.043–0.746), and the SQLS Motivation subscale most frequently exhibited the weakest/smallest values (ACS range 0.009–0.157; AES range 0.002–0.397), although these results were mixed according to the clinician-reported measure used for comparative analysis (ACS range 0.009–0.529; AES range 0.002–0.934).
Conclusion The SF-6D indicated the best (mostly moderate) construct validity but still missed the negative symptoms of the condition. Although further evidence is required to confrm or refute these exploratory results, compared with the EQ-5D, the SF-6D can be self-reported to better capture generic health-related quality-of-life aspects of schizophrenia for the purpose of economic evaluation. The lack of construct validity for SQLS Motivation and Symptoms subscales were hypothesized post-hoc to be representative of the complementary information elicited by the subscales not captured by the clinician-reported measures. Therefore, the SQLS can be self-reported to capture complementary (i.e., additional) information relative to clinician-reported measures.
Background
Schizophrenia is a mental health disorder characterized by a range of diferent psychological impacts, including changes in thinking and behavior. The health-related quality of life (HRQoL) and social burden of schizophrenia is large, afecting both patients and their caregivers, for example, their social and fnancial situation [1, 2]. Many outcome measures have been designed to assess the burden of schizophrenia. These measures may have diferent conceptual perspectives that can be condition specifc, such as the Schizophrenia Quality-of-Life Scale (SQLS) [3], designed to capture schizophrenia-specifc QoL aspects, or generic, such as the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) [4, 5], designed to capture broader outcomes and be applicable to more than one mental health condition. The WEMWBS has been assessed in individuals with schizophrenia but only as part of a mixed-diagnosis group [6], so it is unclear whether it is an appropriate measure for this population. Measures may also be categorised according to whether or not they are preference based; examples of preference-based measures include the three-level EuroQoL Five-Dimension (EQ-5D) [7, 8] and the Short-Form Six-Dimension (SF-6D) [9]. These preference-based measures are used to form a profle score that is converted into a preference-based index score (usually based on societal preferences) and thus allow economic evaluation of interventions using cost-utility analysis (CUA) to inform the allocation of resources by healthcare-governing agencies such as the UK National Institute for Health and Care Excellence (NICE) [10]. In CUA, QoL measured on a preference-based scale anchored at 0 (dead) to 1 (full health) is combined with length of life to generate quality-adjusted life-years (QALYs), allowing comparisons between interventions that afect quantity of life and/or QoL. However, while there can be “some confdence” in the use of generic measures (e.g., the SF-6D and EQ-5D) in patients with mood and anxiety disorders because of their demonstrated psychometric validity and responsiveness [11], this is not the case with schizophrenia. In patients with schizophrenia, the data are less conclusive [11–13], and it has been argued that preference-based measures focused on the impact of the mental disorder (rather than generic measures covering both physical and mental health) should instead be considered [11].