The relationship between chronic disease self-efficacy and nutritional status, functional ability and quality of life in older adults at risk of hospital readmission

Background and significance: Older adults with chronic diseases are at increasing risk of hospital admission and readmission. Approximately 75% of adults have at least one chronic condition, and the odds of developing a chronic condition increases with age. Chronic diseases consume about 70% of the total Australian health expenditure, and about 59% of hospital events for chronic conditions are potentially preventable. These figures have brought to light the importance of the management of chronic disease among the growing older population. Many studies have endeavoured to develop effective chronic disease management programs by applying social cognitive theory. However, limited studies have focused on chronic disease self-management in older adults at high risk of hospital readmission. Moreover, although the majority of studies have covered wide and valuable outcome measures, there is scant evidence on examining the fundamental health outcomes such as nutritional status, functional status and health-related quality of life. Aim: The aim of this research was to test social cognitive theory in relation to self-efficacy in managing chronic disease and three health outcomes, namely nutritional status, functional status, and health-related quality of life, in older adults at high risk of hospital readmission. Methods: A cross-sectional study design was employed for this research. Three studies were undertaken. Study One examined the nutritional status and validation of a nutritional screening tool; Study Two explored the relationships between participants. characteristics, self-efficacy beliefs, and health outcomes based on the study.s hypothesized model; Study Three tested a theoretical model based on social cognitive theory, which examines potential mechanisms of the mediation effects of social support and self-efficacy beliefs. One hundred and fifty-seven patients aged 65 years and older with a medical admission and at least one risk factor for readmission were recruited. Data were collected from medical records on demographics, medical history, and from self-report questionnaires. The nutrition data were collected by two registered nurses. For Study One, a contingency table and the kappa statistic was used to determine the validity of the Malnutrition Screening Tool. In Study Two, standard multiple regression, hierarchical multiple regression and logistic regression were undertaken to determine the significant influential predictors for the three health outcome measures. For Study Three, a structural equation modelling approach was taken to test the hypothesized self-efficacy model. Results: The findings of Study One suggested that a high prevalence of malnutrition continues to be a concern in older adults as the prevalence of malnutrition was 20.6% according to the Subjective Global Assessment. Additionally, the findings confirmed that the Malnutrition Screening Tool is a valid nutritional screening tool for hospitalized older adults at risk of readmission when compared to the Subjective Global Assessment with high sensitivity (94%), and specificity (89%) and substantial agreement between these two methods (k = .74, p < .001; 95% CI .62-.86). Analysis data for Study Two found that depressive symptoms and perceived social support were the two strongest influential factors for self-efficacy in managing chronic disease in a hierarchical multiple regression. Results of multivariable regression models suggested advancing age, depressive symptoms and less tangible support were three important predictors for malnutrition. In terms of functional status, a standard regression model found that social support was the strongest predictor for the Instrumental Activities of Daily Living, followed by self-efficacy in managing chronic disease. The results of standard multiple regression revealed that the number of hospital readmission risk factors adversely affected the physical component score, while depressive symptoms and self-efficacy beliefs were two significant predictors for the mental component score. In Study Three, the results of the structural equation modelling found that self-efficacy partially mediated the effect of health characteristics and depression on health-related quality of life. The health characteristics had strong direct effects on functional status and body mass index. The results also indicated that social support partially mediated the relationship between health characteristics and functional status. With regard to the joint effects of social support and self-efficacy, social support fully mediated the effect of health characteristics on self-efficacy, and self-efficacy partially mediated the effect of social support on functional status and health-related quality of life. The results also demonstrated that the models fitted the data well with relative high variance explained by the models, implying the hypothesized constructs under discussion were highly relevant, and hence the application for social cognitive theory in this context was supported. Conclusion: This thesis highlights the applicability of social cognitive theory on chronic disease self-management in older adults at risk of hospital readmission. Further studies are recommended to validate and continue to extend the development of social cognitive theory on chronic disease self-management in older adults to improve their nutritional and functional status, and health-related quality of life.

Study of leukemia inhibitory factor polymorphism within an Australian multiple sclerosis population

OBJECTIVE: To examine a polymorphism within the 3' untranslated region of the leukemia inhibitory factor gene for an association with multiple sclerosis within an Australian case-control population. METHODS: A test group of 121 unrelated multiple sclerosis patients, of Caucasian origin, and 121 controls, matched for ethnicity, sex and age (+/-5 years) were included in the study. The LIF 3' UTR StuI polymorphism was genotyped by restriction fragment length polymorphism analysis. Statistical analysis of genotype and allele frequencies included Hardy-Weinberg law and conventional contingency table analysis incorporating the standard chi-squared test for independence. RESULTS: Allelic and genotype frequencies did not demonstrate a significant association between the case and control groups for the tested LIF 3' UTR StuI polymorphism. CONCLUSION: The results indicate that the LIF 3' UTR StuI polymorphism is not associated with multiple sclerosis, however we cannot exclude the hypothesis that other polymorphic alleles of LIF could be implicated in MS susceptibility.

No role for estrogen receptor 1 gene intron 1 Pvu II and exon 4 C325G polymorphisms in migraine susceptibility

Background We have previously reported an association between the estrogen receptor 1 (ESR1) gene exon 8 G594A polymorphism and migraine susceptibility in two independent Australian cohorts. In this paper we report results of analysis of two further single nucleotide polymorphisms (SNPs) in the ESR1 gene in the same study group, the T/C Pvu II SNP in intron 1 and the C325G SNP in exon 4, as well as results of linkage disequilibrium (LD) analysis on these markers. Methods We investigated these variants by case-control association analysis in a cohort of 240 migraineurs and 240 matched controls. The SNPs were genotyped using specific restriction enzyme assays. Results were analysed using contingency table methods incorporating the chi-squared statistic. LD results are presented as D' statistics with associated P values. Results We found no evidence for association of the Pvu II T/C polymorphism and the C325G polymorphism and migraine susceptibility and no evidence for LD between these two SNPs and the previously implicated exon 8 G594A marker. Conclusion We have found no role for the polymorphisms in intron 1 and exon 4 with migraine susceptibility. To further investigate our previously implicated exon 8 marker, we suggest the need for studies with a high density of polymorphisms be undertaken, with particular focus on markers in LD with the exon 8 marker.

Association analysis of a highly polymorphic CAG Repeat in the human potassium channel gene KCNN3 and migraine susceptibility

Background Migraine is a polygenic multifactorial disease, possessing environmental and genetic causative factors with multiple involved genes. Mutations in various ion channel genes are responsible for a number of neurological disorders. KCNN3 is a neuronal small conductance calcium-activated potassium channel gene that contains two polyglutamine tracts, encoded by polymorphic CAG repeats in the gene. This gene plays a critical role in determining the firing pattern of neurons and acts to regulate intracellular calcium channels. Methods The present association study tested whether length variations in the second (more 3') polymorphic CAG repeat in exon 1 of the KCNN3 gene, are involved in susceptibility to migraine with and without aura (MA and MO). In total 423 DNA samples from unrelated individuals, of which 202 consisted of migraine patients and 221 non-migraine controls, were genotyped and analysed using a fluorescence labelled primer set on an ABI310 Genetic Analyzer. Allele frequencies were calculated from observed genotype counts for the KCNN3 polymorphism. Analysis was performed using standard contingency table analysis, incorporating the chi-squared test of independence and CLUMP analysis. Results Overall, there was no convincing evidence that KCNN3 CAG lengths differ between Caucasian migraineurs and controls, with no significant difference in the allelic length distribution of CAG repeats between the population groups (P = 0.090). Also the MA and MO subtypes did not differ significantly between control allelic distributions (P > 0.05). The prevalence of the long CAG repeat (>19 repeats) did not reach statistical significance in migraineurs (P = 0.15), nor was there a significant difference between the MA and MO subgroups observed compared to controls (P = 0.46 and P = 0.09, respectively), or between MA vs MO (P = 0.40). Conclusion This association study provides no evidence that length variations of the second polyglutamine array in the N-terminus of the KCNN3 channel exert an effect in the pathogenesis of migraine.

Non-inherited maternal HLA alleles are associated with rheumatoid arthritis

Background. Rheumatoid arthritis (RA) is strongly associated with a series of HLA-DRB1 alleles that encode a conserved sequence of amino acids (70Q/R K/R R A A74) in the DRβ1 chain, known as the shared epitope (SE). However 30% of patients are negative for DRB1*04 and 15% are SE-negative. Exposure to these alleles as non-inherited maternal antigens (NIMA) might explain this discrepancy. We undertook a family study to investigate the role of NIMA in RA. Methods. One hundred families, including the RA proband and both parents, were recruited. HLA-DRB1 genotyping was performed using an allele-specific polymerase chain reaction by standard methods. The frequencies of NIMA and non-inherited paternal antigens (NIPA) were compared using contingency tables and a two-tailed P test. We then reviewed four previously published studies of NIMA in RA and conducted an analysis of the combined data Results. We identified 36 families in which the proband was DRB1*04-negative and 13 in which the proband lacked the SE. There was an excess of DRB1*04 and SE NIMA (P=0.05) compared with NIPA. Combined analysis with previous studies showed that 53/231 mothers (23%) versus 25/205 fathers (12%) had a non-inherited DRB1*04 (P=0.003) and 30/99 mothers versus 18/101 fathers had a non-inherited SE allele (P=0.03). Conclusion. A role for HLA NIMA in RA is suggested by these results.

Expert elicitation into Bayesian networks, Part 4 of 4: eliciting a conditional probability table

An introduction to eliciting a conditional probability table in a Bayesian Network model, highlighting three efficient methods for populating a CPT.

Information sharing with key suppliers : a contingency approach

This paper focuses on information sharing with key suppliers and seeks to explore the factors that might influence its extent and depth. We also investigate how information sharing affects a company’s performance with regards to resource usage, output, and flexibility. Drawing from transaction cost- and contingency theories, several factors, namely environmental uncertainty, demand uncertainty, dependency and, the product life cycle stage are proposed to explain the level of information shared with key suppliers. We develop a model where information sharing mediates the (contingent) factors and company performance. A mail survey was used to collect data from Finnish and Swedish companies. Partial Least Squares analysis was separately performed for each country (n=119, n=102). There was consistent evidence that environmental uncertainty, demand uncertainty and supplier/buyer dependency had explanatory power, whereas no significance was found for the product life cycle stage. The results also confirm previous studies by providing support for a positive relationship between information sharing and performance, where output performance was found to be the most strongly related

A decision table method for randomness measurement

Data quality has become a major concern for organisations. The rapid growth in the size and technology of a databases and data warehouses has brought significant advantages in accessing, storing, and retrieving information. At the same time, great challenges arise with rapid data throughput and heterogeneous accesses in terms of maintaining high data quality. Yet, despite the importance of data quality, literature has usually condensed data quality into detecting and correcting poor data such as outliers, incomplete or inaccurate values. As a result, organisations are unable to efficiently and effectively assess data quality. Having an accurate and proper data quality assessment method will enable users to benchmark their systems and monitor their improvement. This paper introduces a granules mining for measuring the random degree of error data which will enable decision makers to conduct accurate quality assessment and allocate the most severe data, thereby providing an accurate estimation of human and financial resources for conducting quality improvement tasks.

Building shared situational awareness in surgery through distributed dialogue

Background Failure to convey time-critical information to team members during surgery diminishes members’ perception of the dynamic information relevant to their task, and compromises shared situational awareness. This research reports the dialog around clinical decisions made by team members in the time-pressured and high-risk context of surgery, and the impact of these communications on shared situational awareness. Methods Fieldwork methods were used to capture the dynamic integration of individual and situational elements in surgery that provided the backdrop for clinical decisions. Nineteen semi structured interviews were performed with 24 participants from anaesthesia, surgery, and nursing in the operating rooms of a large metropolitan hospital in Queensland, Australia. Thematic analysis was used. Results: The domain “coordinating decisions in surgery” was generated from textual data. Within this domain, three themes illustrated the dialog of clinical decisions, i.e., synchronizing and strategizing actions, sharing local knowledge, and planning contingency decisions based on priority. Conclusion Strategies used to convey decisions that enhanced shared situational awareness included the use of “self-talk”, closed-loop communications, and “overhearing” conversations that occurred at the operating table. Behaviours’ that compromised a team’s shared situational awareness included tunnelling and fixating on one aspect of the situation.