Mental-health problems, including anxiety and depression, are pretty common among the aging population. A report on National Mental Health Development in China (2017–2018) indicated that 11.51–22.02% were suffering from depression disorders among the Chinese older population, and 15–39.86% were struggling with anxiety disorders[1]. The China Health and Retirement Longitudinal Study (CHARLS) reported that the prevalence estimate of depression disorder was up to 33.09% [2]. As the number of older adults is rapidly growing, prevention, screening, and treatment of mental health problems in this population increasingly become a heavy burden to individuals, families, and even the whole society [3].
Several instruments have been developed or adapted for elderly populations to screen for general mental health problems, and The Kessler-6 screening measure (K6) is among these widely used ones [4]. It comprises six questions, which were drawn from the 10-item version of the Kessler Psychological Distress Scale for the purpose of screening severe mental illness among the general population fast and accurately [5, 6]. It may also be used in some clinical situations[7]. Moreover, due to effectiveness and efficiency, it is widely employed in major global and national surveys, such as the WHO World Mental Health (WMH) Survey, the US National Health Interview Survey[5], the Australian National Survey of Mental Health and Well-Being [8], the Canadian National Population Health Survey[9], the South African Stress and Health study[10]. The China Family Panel Studies also included the K6 in the longitudinal survey in the waves of the year 2010 and the year 2014[11].
However, researchers have not reached a consensus about the factor structure of the K6, which is vital in understanding and interpreting responses on this scale. The K6 was developed as a one-factor instrument at the beginning[6]. The one-factor model with all six items loading on a single factor is confirmed in the majority of studies [5, 8, 12–19]. Nevertheless, other factor solutions were proposed in a few studies. Mewton and colleagues found a modified single-factor model with residual correlations among some items had a better fit with the data in a large Australian adolescent sample [4]. Kessler et al. reported that a two-factor model (with an item ("Everything was an effort") loading on the second factor) emerged in an Indian sample [5]. Lee et al. indicated that a two-factor solution has the best fit, with three items ("Nervous", "Restless or fidgety", and "Everything was an effort") on the anxiety factor, another three items ("Hopeless", "Depressed", and "Worthless") on the depression factor in a sample of Hong Kong residents [20]. Bessaha showed that a two-factor model and a second-order two-factor model outperformed other factor solutions in responses from a large sample of American emerging adults on the K6 [21]. In the two-factor solution, four items formed the depression factor, and the rest two items ("Nervous" and "Restless or fidgety") formed the anxiety factor. Easton et al. demonstrated the performance of Bassaha's two-factor model was better than the unidimensional model among a sample of Palestinian social workers[22]. In a more recent study, we derived a two-factor model with exploratory factor analysis (EFA), with three items("Depressed", "Nervous", and "Restless or fidgety") loaded on the anxiety factor and the other three items("Hopeless", "Everything was an effort ", and "Worthless ") on the depression factor[3]. We also compared it with previous models with confirmatory factor analysis (CFA) and found that only this model was acceptable regarding model-data fit indexes. Therefore, in the present study, our first aim was to use a similar procedure to examine the dimensionality of the K6 in the elder sample with two waves of longitudinal survey data.
Measurement invariance (MI) refers to whether an instrument performs equivalently under different conditions [23]. Because researchers and practitioners often make comparisons on scores on instruments among different groups or settings, measurement invariance is considered an essential psychometric property of an instrument. Previous studies have examined measurement invariance of the K6 for gender, age, cultural groups and so on. Some confirmed measurement invariance of the K6 for various groups by conducting a series of multi-group confirmatory factor analyses. Peiper et al. demonstrated full measurement invariance across gender, age and race in a large sample of Idaho students by conducting a series of multi-group confirmatory factor analyses [19]. Ferro established full measurement invariance for age (between youth and adult) and sex (between male and female youth) in a Canadian sample [24]. However, the others indicated measurement non-invariance between different groups. Drapeau et al. found the unidimensional structure of the K6 held partial scalar invariance across gender among a large sample of Canadian adults. They also confirmed longitudinal partial metric invariance across gender and over 12 years [9]. Mewton et al. examined the sex-based measurement invariance in a large general population sample of adolescents and found a lack of measurement invariance in the threshold of all k6 items [4]. Shon explored the measurement equivalence of the K6 between Chinese and Korean immigrants in the US, and found measurement invariance held for the younger groups but not for older groups between Chinese and Korean immigrants. Cotton et al. examined measurement invariance across sex and age groups in a sample of help-seeking youth in Australia, and reported weak invariance across sex, and strong invariance across age [25]. In addition, some researchers attempted to address the measurement invariance issue with an item response theory approach. Sunderland et al. conducted differential item functioning analyses of the K6 with responses from Australian respondents aged between 16 and 85. They found significant item bias on one item (“Fatigue”) between the young and the old aged groups[26].
The prior studies have focused on the measurement invariance of the K6 across different groups. However, to our knowledge, no study has examined the longitudinal measurement invariance (LMI) of the K6. That is, measurement invariance across different time points in the same sample [27]. The k6 is often used in longitudinal studies, and researchers want to know whether some changes emerge during the period or developmental trajectories of psychological distress [28]. If there is no guarantee of the longitudinal measurement invariance, the interpretation could also be misleading. Several scholars have realized the research gap in longitudinal measurement invariance of the K6, and call for future studies to address this issue [24]. Therefore, the second aim of the study was to check the degree to which the K6 demonstrates measurement invariance across time.
In sum, the present study was undertaken to examine the dimensionality of the K6 in a national representative elder sample in China and test the longitudinal measurement invariance of the K6 across time among this population.