Abstract
BackgroundThe alignment method, a novel psychometric approach, represents a more flexible procedure for establishing measurement invariance in geographically, ethnically, or linguistically diverse samples, especially in large epidemiological surveys. Although the Hopkins Symptoms Checklist (HSCL-25) has been used extensively in the field to assess anxiety and depressive symptoms, questions remain about the comparability of findings when the instrument is applied across regions in large-scale national surveys.MethodsThe present study is the first in the field to apply the alignment method to test the structure and measurement invariance of the anxiety and depression dimensions of the HSCL-25 amongst Sri Lankan subpopulations (n = 8456) stratified by geographical regions, levels of past exposure to conflict, and ethnic composition.ResultsMultigroup CFA analysis yielded non-converging models requiring substantial modifications to the models. As a result, multigroup alignment analysis was applied and the results supported the bifactorial structure and measurement invariance of the HSCL-25 across eight (severe and moderate) conflict-affected districts. The alignment analysis based on a good-fitting configural model yielded a metric non-invariance of 22.22% and scalar non-invariance of 5.88% (both under the established 25% threshold). The bifactorial model outperformed the tripartite and other models. In comparison to the anxiety items, the depressive items showed higher levels of metric non-invariance across districts.ConclusionsOur findings demonstrate the methodological feasibility of applying the alignment method to test the structure and invariance of the HSCL across ethnically diverse populations living in conflict-affected districts in Sri Lanka. Further studies are needed to examine ethnicity and language factors more critically.
Highlights
The alignment method, a novel psychometric approach, represents a more flexible procedure for establishing measurement invariance in geographically, ethnically, or linguistically diverse samples, especially in large epidemiological surveys
Weighted chi-square tests indicated that the districts differed significantly in sociodemographic characteristics, ethnicity, exposure to displacement, and mental health indices
A novel aspect of our study is that it is the first in the post-conflict field and in psychiatry in general to employ the alignment method to examine the invariance of the Hopkins Symptoms Checklist (HSCL) in a nation-wide epidemiological survey undertaken in a country seven years following an extensive period of conflict that affected large sectors of the Sri Lankan population
Summary
The alignment method, a novel psychometric approach, represents a more flexible procedure for establishing measurement invariance in geographically, ethnically, or linguistically diverse samples, especially in large epidemiological surveys. The Hopkins Symptoms Checklist (HSCL-25) has been used extensively in the field to assess anxiety and depressive symptoms, questions remain about the comparability of findings when the instrument is applied across regions in large-scale national surveys. The Hopkins Symptoms Checklist (HSCL-25) has been used extensively in the field to assess anxiety and depressive symptoms [2], questions remain about the comparability of findings when the instrument is applied across regions, for example, in large-scale national surveys. Within the context of the field of transcultural mental health traumatology, measurement invariance allows assessment of the extent to which the construct under study is being understood and interpreted in a similar manner by respondent populations that may differ in cultural, ethnic, and linguistic backgrounds [3]. It has been argued that the requirements of metric and scalar invariance as specified within MGCFA may be overly restrictive when comparing inter-individual or between-group differences in mental health reports across cross-cultural groups, given that it is expected that responses will vary to some extent according to individual and cultural influences [7, 8]
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