Dementia Ready: Comparing Approaches for Building Caregiver Readiness and Knowledge of Dementia

Despite the rising prevalence of dementia and the high cost and complexity of care for people with dementia, most dementia care is provided at home by informal caregivers who are not clinically trained. Building caregiver readiness and knowledge of dementia is key to supporting quality care and desirable health outcomes, such as preventing falls and reducing nursing home admissions. We sought to determine and compare the impact of two interventions—Resilient Living with Dementia (RLWD) and Care of Persons with Dementia in their Environments (COPE)—and of their combined delivery (both RLWD and COPE) on increasing caregiver readiness and knowledge of dementia. Between January 2019 and March 2021, 77 caregivers of people with dementia in Connecticut participated in RLWD and/or COPE and completed the Alzheimer’s Disease Knowledge Scale (ADKS) and the Preparedness for Caregiving Scale (PCGS) at baseline and at four-month and ten-month follow-ups. Analyses were conducted to compare outcomes by intervention(s). From baseline to four months and to ten months, we observed statistically significant (p < .05) improvement on the ADKS among participants in RLWD, and on the PCGS among participants in COPE and among participants in RLWD. The most substantial impact on PCGS was observed among participants in both COPE and RLWD. No improvement in the ADKS was observed among participants in only COPE, but ADKS improvement was observed at four months among participants in COPE and RLWD. Findings suggest that the benefits of COPE and RLWD for building dementia caregiver readiness are complementary and mutually reinforcing.

Drug knowledge discovery via multi-task learning and pre-trained models

Background Drug repurposing is to find new indications of approved drugs, which is essential for investigating new uses for approved or investigational drug efficiency. The active gene annotation corpus (named AGAC) is annotated by human experts, which was developed to support knowledge discovery for drug repurposing. The AGAC track of the BioNLP Open Shared Tasks using this corpus is organized by EMNLP-BioNLP 2019, where the “Selective annotation” attribution makes AGAC track more challenging than other traditional sequence labeling tasks. In this work, we show our methods for trigger word detection (Task 1) and its thematic role identification (Task 2) in the AGAC track. As a step forward to drug repurposing research, our work can also be applied to large-scale automatic extraction of medical text knowledge. Methods To meet the challenges of the two tasks, we consider Task 1 as the medical name entity recognition (NER), which cultivates molecular phenomena related to gene mutation. And we regard Task 2 as a relation extraction task, which captures the thematic roles between entities. In this work, we exploit pre-trained biomedical language representation models (e.g., BioBERT) in the information extraction pipeline for mutation-disease knowledge collection from PubMed. Moreover, we design the fine-tuning framework by using a multi-task learning technique and extra features. We further investigate different approaches to consolidate and transfer the knowledge from varying sources and illustrate the performance of our model on the AGAC corpus. Our approach is based on fine-tuned BERT, BioBERT, NCBI BERT, and ClinicalBERT using multi-task learning. Further experiments show the effectiveness of knowledge transformation and the ensemble integration of models of two tasks. We conduct a performance comparison of various algorithms. We also do an ablation study on the development set of Task 1 to examine the effectiveness of each component of our method. Results Compared with competitor methods, our model obtained the highest Precision (0.63), Recall (0.56), and F-score value (0.60) in Task 1, which ranks first place. It outperformed the baseline method provided by the organizers by 0.10 in F-score. The model shared the same encoding layers for the named entity recognition and relation extraction parts. And we obtained a second high F-score (0.25) in Task 2 with a simple but effective framework. Conclusions Experimental results on the benchmark annotation of genes with active mutation-centric function changes corpus show that integrating pre-trained biomedical language representation models (i.e., BERT, NCBI BERT, ClinicalBERT, BioBERT) into a pipe of information extraction methods with multi-task learning can improve the ability to collect mutation-disease knowledge from PubMed.

ANALYSIS OF WILLINGNESS TO PAY CONTRIBUTIONS IN THE MEMBERSHIP OF THE NATIONAL HEALTH INSURANCE IN REGENCY OF BANYUASIN

BPJS Kesehatan as the manager of the National Security Program (JKN), can be an appropriate health insurance to reduce the risk of people bearing health costs from their own pocket (out of pocket) in a very large and can lead to poverty. This study aims to analyze the willingness to pay JKN contributions to farmers in Banyuasin Regency in order to identify community groups that need subsidies from the government. This research is an analytical study with cross sectional design. The population of this research is all residents who work as farmers and have not registered as JKN participants with a total sample of 176 people. data analysis used chi square test and logistic regression test. This study found that the willingness to pay JKN contributions of Rp22.028 per person per month. The determinants of willingness to pay contributions in JKN membership are family income, food expenditure, non-essential food expenditure, non-food expenditure, number of family members, history of catastrophic disease, knowledge of contributions, and the ability to pay JKN contributions. The most dominant factor affecting the willingness to pay is non-essential food expenditure. The willingness to pay the JKN dues is still low. The ability to pay contributions is influenced by income, food expenditure, non-essential food expenditure, total non-food expenditure, number of family members, history of catastrophic disease, knowledge of contributions, and the ability to pay JKN contributions.

Assessment of Disease Knowledge, Medication Adherence, HRQOL in COPD Patients at a South Indian Tertiary Care Hospital

Introduction: Chronic obstructive pulmonary disease (COPD) is a progressive, life-threatening disease of the lungs, gradually causes breathlessness and predisposes to exacerbations and serious illness. The main objectives of the study are to evaluate disease knowledge, medication adherence, and health-related quality of life among COPD patients. Methodology: A Hospital-based, single-entered prospective observational study was conducted at a government general hospital, Andhra Pradesh. India after ethical committee approval. This study was conducted for 6 months with a sample size of 80 patients. Results: According to our study, the majority of the patients 36 (45%) don’t have disease knowledge, where a few numbers of patients 7 (8.75%) is having disease knowledge as per BCKQ score values. 11.25% of patients have the lowest MMAS scores whereas 58.75% were found to have higher MMAS scores and 37.5% of total patients have higher CAT scores, and 12.5% of patients have lower CAT scores. Conclusion: We found that majority of the patients have poor disease knowledge, lower adherence to medication regimens, and substandard HRQOL. Keywords: COPD knowledge, medication adherence, and HRQOL.

Cultural Adaptation and Validation of the Malay Chronic Kidney Disease Self-Management Instrument (MCKD-SM)

Background: There is growing evidence that self‐management behaviour can improve outcomes for patients with chronic kidney disease (CKD). However, there are no measures available in Malay to effectively assess self-management of CKD. The aim of this study was to translate, culturally adapt, and validate the Malay Chronic Kidney Disease Self-Management (MCKD-SM) for Malay-speaking health professionals and patients. Methods: This study was carried out in two phases: translation and cultural adaptation, and validation. Instruments were translated from English to Malay then adapted and validated in a sample of 337 patients with CKD stages 3-4 attending a nephrology clinic in a tertiary hospital in Malaysia. Construct validity was evaluated by exploratory factor analysis. Reliability of the instrument was assessed by internal consistency and test‐retest reliability. The correlations between MCKD-SM and kidney disease knowledge, MCKD-SM and self-efficacy were hypothesised a priori and investigated. Results: The Malay version of the Chronic Kidney Disease Self-Management instrument has 29 items grouped into three factors: “Understanding and Managing my CKD”, “Seeking Support” and “Adherence to Recommended Regimen”. The three factors accounted for 56.3 % of the total variance. Each factor showed acceptable internal reliability with Cronbach’s α from 0.885-0.960. 2-week intra-rater test-retest reliability intraclass correlation coefficient values for all items ranged between 0.938 to 1.000. MCKD-SM scores significantly correlates with kidney disease knowledge (r = 0.366, p < 0.01) and self-efficacy (r = 0.212, p < 0.01).Conclusion: The Malay version of the CKD-SM was found to be a valid and reliable patient‐reported outcome measure of pre-dialysis CKD self-management behaviour in the Malay-speaking population.