Analysis Of Influencing Factors Of Care Burden Of Family Caregivers Of Parkinson’s Disease And Construction Of Risk Prediction Model

Objective:To clarify the incidence of care burden of family caregivers with Parkinson’s disease,reveal the risk factors of caregiver burden in families with Parkinson’s disease,construct a risk prediction model of caregiver burden in families with Parkinson’s disease,and provide scientific basis for medical staff to identify high-risk groups with care burden and their preventive interventions.Methods:A total of 251 pairs of Parkinson’s disease patients and their caregivers who visited the outpatient and inpatient department of neurology of a tertiary hospital in Shanxi Province from April 2022 to September 2022 were selected as the research subjects,and the caregivers used the self-compiled caregiver general condition questionnaire,zarit burden interview,general self-efficacy scale,social support rating scale,hospital anxiety and depression scale,simplified coping style questionnaire,and the quality of relationship index for data collection.Patients were collected using self-compiled patient general questionnaire,modified Hoehn&Yahr grading scale,unified parkinson’s disease rating scale-part III,activity of daily living scale,hospital anxiety and depression scale and mini-mental state examination.Through monofactor analysis,Spearman correlation analysis,Lasso regression analysis and multivariate logistic regression analysis,the influencing factors of care burden of caregivers in families with Parkinson’s disease were discussed,and the risk prediction model of caregiver burden of caregivers with Parkinson’s disease was established in R language.According to the same screening criteria,131 pairs of patients and their caregivers who visited the outpatient and inpatient departments of two tertiary hospitals in Shanxi Province from October 2022 to December2022 were selected as external verification sets,and the models were externally verified.The predictive performance of the model is verified by sensitivity and calibration.Results:1.Among the 251 pairs of patients and caregivers,a total of 194 caregivers had a care burden,and the incidence of care burden was 77%,including 53% of mild burden,18% of moderate burden,and 6% of severe burden.Carers with Parkinson’s disease families score higher personal burden than responsibility burden score.2.The results of Monofactor analysis showed that there were statistically significant differences(P(27)05.0)in the average daily care time,number of co-participants in caregiving,physical health status,per capita monthly household income,life satisfaction,general self-efficacy score,social support score(subjective support,objective support,utilization of support),anxiety score,depression score,positive coping score,negative coping score,and intimacy satisfaction score of caregivers.The difference in medical insurance type,sleep quality,whether or not to take antidepressant /anti-anxiety drugs,H-Y clinical stage,activity of daily living score(physical self-maintenance,instrumental activities of daily living),anxiety score,depression score,and simple intelligent mental state examination scale score were statistically significant(P(27)05.0).3.Lasso regression analysis showed that when lambda.1se=0.02383,the variables had the best results,corresponding to six variables: medical insurance type,sleep quality,number of people participating in nursing together,caregiver’s life satisfaction,caregiver’s positive coping style,and intimacy satisfaction score.4.The results of logistic regression analysis showed that the type of medical insurance,sleep quality,the number of people participating in nursing together,the satisfaction of caregivers with life,and the positive coping style of caregivers were independent factors affecting the care burden of family caregivers.5.In this study,a nomogram model was constructed that can accurately predict the risk of care burden in family caregivers with Parkinson’s disease.6.Risk prediction model verification: internal verification shows that the area under the curve is 0.961,the 95% CI is 0.940～0.983,the average absolute error of the consistency between the predicted value and the true value is 0.039,and the sensitivity is0.912 and the specificity is 0.943 when the best truncation value is 0.685;the external verification shows that the area under the curve is 0.919,and the 95%CI is 0.852～ 0.985,the average absolute error of the consistency between the predicted value and the true value is 0.069,and the sensitivity is 0.960 and the specificity is 0.818 when the best truncation value is 0.807.Conclusion:1.The incidence of caregiver burden in families with Parkinson’s disease is high,and the burden felt by the caregiver care activity itself is greater than the responsibility burden of the caregiver role.2.The care burden of family caregivers with Parkinson’s disease is affected by a variety of factors,including: average daily care time of caregivers,number of people participating in caregiving,physical health status,per capita monthly income of the family,life satisfaction,general self-efficacy,social support level(subjective support,objective support,utilization of support),anxiety,depression,positive coping style,negative coping style,intimate relationship satisfaction,patient’s medical insurance type,sleep quality,taking antidepressant/anti-anxiety drugs,H-Y clinical stage,abilities of daily living(physical self-maintenance,instrumental activities of daily living),anxiety,depression,cognitive function.Among them,the type of medical insurance of patients,the quality of patients’ sleep,the number of people participating in nursing together,caregiver’s life satisfaction,and the positive coping style of caregivers are independent factors affecting the care burden of family caregivers.3.The nomogram model for predicting the risk prediction of care burden of family caregivers with Parkinson’s disease constructed in this study has been verified to have good prediction efficiency,and can provide personalized prediction probability related to clinical decision-making more accurately,which can provide a tool for medical staff to predict the risk of caregiver burden in families with Parkinson’s disease.