For older people, transitioning from their familiar homes to nursing homes is a profoundly influential life event with uncertainty and stress. Because it not only means the conversion of aging from home care to institutional care but also represents the mutual adjustment of older people to the new living environment, such as the disruption of the previous social relationships and the formation of new ones.1 Nursing home adjustment can be defined as a process of overcoming discomfort, regulating negative emotional and behavioral reactions, and eventually forming a new concept of collective life and self-orientation.2,3 According to the transition process framework presented by Brandburg, the transition process consists of four consecutive components: initial reaction, transitional influences, adjustment, and acceptance.4 Among them, the adjustment process is more likely to be intervened and critical in preventing adverse transitional influences associated with relocation stress. Therefore, it is essential to develop appropriate measurement instruments to directly assess nursing home adjustment, which helps to promote better acceptance of older adults residing in the nursing home.

The nursing home adjustment scale (NHAS) was designed based on the Korean language by Lee in 2007.5 This scale is a psychometric instrument for the quantitative measurement of older people's adjustment to nursing home residence, including relocation distress symptoms (eight items), making friends (four items), acceptance of new residence (six items), difficulty in group life (three items), and having self-worth (two items), a total of 23 items. As one of the most used measurement instruments in this field, it has been utilized in some studies among older people residing in nursing homes in South Korea.2,6, 7, 8 In 2015, the author developed the English version of the NHAS to measure the level of nursing home adjustment for older adults who speak English.9 In 2019, the NHAS was translated from Korean to Chinese and validated among older adults in Fujian Province by Xiao et al.10 Subsequently, only one study conducted in Jiangsu Province employed the Chinese version of the NHAS (C-NHAS) for the measurement of adjustment.11

For the C-NHAS, the evidence on its applicability to Chinese older people is still insufficient. Fujian and Jiangsu Provinces are both located in the southeast coastal region of China and are widely considered to be economically developed. China has vast territories, and the unevenness of development levels in different regions of China is worthy of consideration. Specifically, older people who reside in economically developed areas tend to possess higher socioeconomic status (SES), and SES has been recognized to be associated with social support, social participation, self-rated health, and psychological distress among older people.12,13 Additionally, as an important aspect of SES, the educational attainment of responders may have a direct effect on their correct response to the measurement tool. These social- and economic-related factors have been demonstrated to be associated with nursing home adjustment levels in older adults as well.3,14 On the other hand, there are also differences in the dominant types of nursing homes in different regions. More for-profit nursing homes are available in economically developed areas, which aim to provide comparatively higher levels of service and amenities. Older adults seeking to dwell in for-profit nursing homes tend to be more concerned with aspects such as interpersonal relationships with others, and their satisfaction with the long-term care facilities, and gradually develop a conceptual understanding of adjustment. Thus, it is reasonable to assume that populations of older adults in different SES are heterogeneous. However, there is no research to validate the application of the C-NHAS in less developed areas of China.

Furthermore, the psychometric characteristics of the NHAS were not examined adequately. There are still no studies to examine the psychometric properties of the NHAS based on item response theory (IRT). To date, researchers have primarily employed classic test theory (CTT) to assess the psychometric properties of the entire NHAS,5,9,10 which routinely ignored the characteristics of individual responses to a single item. In contrast, as a typical representation of modern testing theory (MTT), IRT assesses the properties of each item and thus does not rely on a combination of items and allows for generalizing testing results across samples and items.15,16 As a modern psychometric validation analysis approach in IRT, Rasch model has been applied for reanalysis in numerous psychometric instruments in recent years.17, 18, 19 In Rasch model, the latent trait (eg, nursing home adjustment) of respondents is assumed to be reflected by a specific test (aka measurement instrument), and the total score is typically used as an estimate of this potential. The latent trait of testers should be unidimensional, meaning that all items that make up a given test aim to measure the same latent trait. Meanwhile, no correlation exists between items for respondents, they are locally independent. Rasch analysis is based on the principle that the probability of a person responding correctly to a graded response item only depends on the individual's ability and the item's difficulty (both measured on a logit scale).20,21 Thus, more detailed information on the interaction between the measurement tool and the respondents can be provided by applying Rasch analysis. Besides, Rasch model assumes that the response to each item is consistently independent of personal characteristics such as age, gender, or cultural background, and applies the differential item functioning (DIF) to measure the potential bias at the item level. This can provide the foundation for the measurement invariance of instruments22 Although, compared to CTT, Rasch analysis has the limitation in the exploration of the factor structure of the entire scale,23,24 its use can help confirm the unidimensionality of each subscale by judging the fitness of Rasch model. As such, a combination of the two methods can provide a more comprehensive evaluation of the psychometric properties of an instrument and identify the most efficacious version.

The objective of this study is to psychometrically test the C-NHAS using CTT and Rasch analysis among older people living in long-term care facilities in central China and to provide further evidence on its applicability in Chinese older adults.