PubMed · 15973901
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Sylvie Augy, Philppe Dejardin. [Memory consultation].. https://pubmed.ncbi.nlm.nih.gov/15973901/
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Siblings of persons with mental illness who assume primary caregiving roles experience substantial and tangible economic impacts associated with this responsibility. This study investigated mailed survey responses collected from 156 adult siblings of persons with mental illness from New York State to examine instrumental costs associated with providing support to siblings with illness. Genders of both siblings, severity of the relatives' mental illness, and number of surviving parents in the family distinguished those occupying primary caregiving responsibility from those not in primary roles. Current caregivers incurred greater instrumental costs in the form of financial expenses, time spent in care activities, and crisis involvement than did those who were not primary care providers. Additional demographic and behavioral factors related to siblings with and without illness were associated with specific dimensions of instrumental expenditure. As siblings become increasingly engaged in caregiving, social service professionals must assume leadership in promoting programs and policies that meaningfully support family involvement for relatives with mental illness.
In many areas of research, repeated binary measures often represent a two-state stochastic process, where individuals can transition among two states. In a behavioural or physical disability setting, individuals can flow from susceptible or subthreshold state, to an infectious or symptomatic state, and back to a subthreshold state. Quite often the transition among the states happens in continuous time but is observed at discrete, irregularly spaced timepoints which may be unique to each individual. Methods for analyses of such data are typically based on the Markov assumption. Cook (Biometrics 1999; 55:915-920) introduced a conditional Markov model that accommodates the subject-to-subject variation in the model parameters with random effects. We extend this model by adding a non-ignorable dropout component to the model. Specification of the distribution of the random effects is made to guarantee a closed form expression of the marginal likelihood. This methodology is illustrated by applications to a data set from a parasitic field infection survey, a data set from a cocaine treatment study, and a data set from an aging study. Simulations suggest that the shared parameter model is robust with respect to at least one alternative non-ignorable model.
BACKGROUND AND AIM: Health-related quality of life of patients with chronic liver disease has been shown to be impaired in numerous studies. However, the factors which influence health-related quality of life in treated chronic liver patients are not quite known. This is the first study to assess the impact of physical and psychosocial determinants on a weighted score of health-related quality of life in patients with chronic liver disease. METHODS: The data of 1175 chronic liver patients were used to assess the relationship between items of the disease-specific Liver Disease Symptom Index 2.0 and the Short Form (SF)-6D weighted utility score by means of linear regression analyses. RESULTS: Health-related quality of life was most strongly related to disease severity (B = -0.029) and joint pain (B = -0.023). Depression (B = -0.014), pain in the right upper abdomen (B = -0.014), decreased appetite (B = 0.014) and fatigue (B = -0.013) were also strongly related to health-related quality of life. In hepatitis C virus patients, disease severity (B = -0.037) and depression (B = -0.030) were strong determinants of health-related quality of life. CONCLUSIONS: This study shows that health-related quality of life in chronic liver patients is clearly determined by disease severity, joint pain, depression, decreased appetite and fatigue. These patients may benefit most from interventions aimed at improving adaptation to the symptoms described.