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In nursing homes, elderly and oldest-old residents often have multiple comorbidities and disabilities. A multivariate procedure was able to identify the fundamental dimensions describing residents' variation on a number of health measures. These profiles predicted differences in service use so they had predictive validity. Thus, multivariate procedures may help identify clinically distinct groups in studies where complex measures are made.

Research has shown that the nursing home patient population is quite heterogeneous in terms of both individual patient characteristics and service needs. Furthermore, existing administrative classifications do a poor job of representing this heterogeneity. As a consequence we have conducted an analysis of the individual and service characteristics of two types of patients represented in the National Nursing Home Survey of 1977 (i.e., patients whose primary source of payment was Medicare and patients whose primary payment source was not Medicare). In this analysis we identified patterns of individual characteristics within the two patient groups and showed how these patterns related to their service needs. The logic of the model permitted us both to establish patterns of characteristics within the two payment types and to examine the implications of individual heterogeneity remaining in the classification. This makes the methodology useful both as a research tool for understanding the nature of the nursing home population and as a tool for studying the consequences of various classification schemes for questions of identifying service patterns and needs as well as the evaluation of policy options.

Purpose This study aims to examine the factors affecting intellectual capital disclosure (ICD), especially in the agriculture and mining sectors in Indonesia and Thailand. Additionally, this study discusses the difference in ICD levels between Indonesia and Thailand. Design/methodology/approach The sample used is companies listed on the Indonesia Stock Exchange and Stock Exchange of Thailand from 2013 to 2017. The method used is a content analysis of 380 annual reports (150 from Thailand and 230 from Indonesia). This study uses a panel regression model. Variables tested are firm size, market shares, minority shareholders, profitability, leverage and the focus on ICD components such as human capital disclosure, structural capital disclosure and relational capital disclosure. Findings IC disclosures in financial statements are generally oriented to past events and focus more on the human capital component. Overall, ICDs in Thailand are more qualified than in Indonesia. The findings support the stakeholder and legitimacy theories. It was found that the greater the company’s resources, the higher the quality of disclosure of all intellectual capital (IC) components. Conversely, when associated with the position in the market, companies reduce the disclosures. As the company has gained the government’s legitimacy, management’s passion for revealing more about its ICD is diminishing. Research limitations/implications This study focuses on the agriculture and mining sectors in Indonesia and Thailand. The annual report is the primary medium to observe IC in qualitative and quantitative ways, yet firms would use other means to disclose their IC. This study deploys the content analysis method, in which the determination of scores is based on the researchers’ judgment. Originality/value This study contributes to the ICD-related literature by focusing on the agriculture and mining industries and multinational scopes. The ICD valuation is extended to the quality of disclosures, in which numerical and monetary figures also support the disclosures. This study also examined minority shareholders’ role in ICD quality, which is infrequent in ICD literature.

Background Non-exercise (N-EX) questionnaires have been developed to determine maximal oxygen consumption (VO2max) in healthy populations. There are limited reliable and validated N-EX questionnaires for the HIV+ population that provide estimates of habitual physical activity and not VO2max. Objectives To determine how well regression equations developed previously on healthy populations, including N-EX prediction equations for VO2max and age-predicted maximal heart rates (APMHR), worked on an HIV+ population; and to develop a specific N-EX prediction equation for VO2max and APMHR for HIV+ individuals. Methods Sixty-six HIV+ participants on stable HAART completed 4 N-EX questionnaires and performed a maximal graded exercise test. Results Sixty males and 6 females were included; mean (SD) age was 49.2 (8.2) years; CD4 count was 516.0 ± 253.0 cells·mn−3; and 92% had undetectable HIV PCR. Mean VO2max was 29.2 ± 7.6 (range, 14.4–49.4) mL·kg−1·min−1. Despite positive correlations with VO2max, previously published N-EX VO2max equations produced results significantly different than actual VO2 scores (P < .0001). An HIV+ specific N-EX equation was developed and produced similar mean VO2max values, R = 0.71, when compared to achieved VO2max (P = .53). Conclusion HIV+ individuals tend to be sedentary and unfit, putting them at increased risk for the development of chronic diseases associated with a sedentary lifestyle. Based on the level of error associated with utilizing APMHR and N-EX VO2max equations with HIV+ individuals, neither should be used in this population for exercise prescription.