Purpose: This study aimed to measure treatment burden in adults diagnosed with multiple chronic conditions transitioning from a skilled nursing facility to home.Design: Prospective, two-time point, cohort design utilizing convenience sampling from one skilled nursing facility in Northeast, Ohio.Methods: Seventy-four men and women participated answering self-report questions measuring treatment burden at two time points: prior to discharge and 30 days after discharge.Results: t-test analysis determined treatment burden was not statistically different between time points (p > .05). Multivariate analysis explained 23% of treatment burden's variance, with the severity of multiple chronic conditions and the presence of a caregiver predicting treatment burden (p < .05). Conclusion:Findings were contrary to our hypothesis of this population being at risk for high treatment burden.Clinical Relevance: Moderate, fluctuating levels of treatment burden suggest that it is possible to estimate demands of treatment prior to discharge from the skilled nursing facility to better inform discharge planning. KeywordsGeriatrics; multiple chronic conditions; patient transfer; self-management; treatment burden The care of individuals diagnosed with one or more chronic health conditions is one of the most challenging and complex issues facing the U.S. healthcare system today. Chronic health conditions are defined as medical conditions lasting greater than 1 year and requiring ongoing medical attention and/or limiting activities of daily living (Hwang, Weller, Ireys, & Anderson, 2001). One in four Americans are diagnosed with multiple chronic conditions (MCCs), which are defined as two or more chronic conditions (Ward, Schiller, & Goodman, 2014), and recent data suggest that MCCs are a major contributor to poor health outcomes
Aim: (1) describe the percentage of people living with HIV (PLWH) experiencing high levels of treatment burden who are at risk for self-management non-adherence, and (2) examine the relationship between known antecedent correlates (the number of chronic conditions, social capital, and age) of self-management and treatment burden while controlling for sample socio-demographics. Background: Chronic condition self-management is key to maintaining optimal health in the aging population of PLWH. Despite the efforts of providers, patients, and caregivers, self-management non-adherence is still a factor contributing to poor chronic condition self-management and subsequent poor health outcomes. Recent research has identified treatment burden as a risk factor of poor chronic disease self-management adherence. Method: Cross-sectional, secondary analysis of a sub-sample of 103 community dwelling, men and women diagnosed with HIV/AIDS derived from a larger parent study examining physical activity patterns in PLWH. Results: Participants reported an overall low level of treatment burden (M = 22.84; SD = 24.57), although 16% (n = 16) of the sample indicated experiencing high treatment burden. The number of chronic conditions (r = 0.25; p ≤ .01) and social capital (r = −0.19; p = .03) were significantly correlated with treatment burden. Multivariate analysis testing known antecedent correlates of treatment burden was statistically significant (p < .05), but only explained 8% of treatment burden’s variance. Conclusion: Findings have implications for nursing care of PLWH demonstrating a subset of PLWH experience high treatment burden related to chronic condition self-management. Findings also identify characteristics of PLWH who may be at high risk for treatment burden and subsequent self-management non-adherence.
AimTo examine the association between symptoms severity and treatment burden in people living with HIV.DesignCorrelational, secondary analysis of data from participants diagnosed with HIV enrolled in a descriptive, cross‐sectional study examining physical activity patterns.MethodsWe analysed data from 103 men and women using self‐report data collected between March 2016 ‐ February 2017. Our primary statistical analyses consisted of explanatory multivariate modelling with individual PROMIS‐29 scores representing symptom severity and treatment burden measured using the Treatment Burden Questionnaire‐13.ResultsGreater symptom severity was associated with higher levels of cumulative treatment burden as well as higher levels of task‐specific medication and physical activity burden. Multivariate regression analyses revealed that fatigue was a risk factor of cumulative treatment burden as well as task‐specific medication and physical activity treatment burden. Effect sizes of multivariate models ranged from small (0.11) to medium (0.16). Additionally, post hoc analyses showed strong correlations between fatigue and other measured symptoms.ConclusionFindings support extant treatment burden literature, including the importance of addressing symptom severity in conjunction with treatment burden screening in the clinical setting. Results also suggest clinical interventions focused on the reduction of fatigue could reduce treatment burden in people living with HIV. Strong correlations between fatigue and other symptoms indicate the potential for reducing fatigue by addressing other highly clustered symptoms, such as depression.ImpactPeople living with HIV exhibiting higher levels of fatigue are at high risk for treatment burden and poorer self‐management adherence. Clinicians should consider incorporating symptom and treatment burden assessments when developing, tailoring and modifying interventions to improve self‐management of HIV and other co‐morbid conditions.
People living with HIV (PLHIV) are increasingly diagnosed with comorbidities which require increasing self-management. We examined the effect of a self-management intervention on neurocognitive behavioral processing. Twenty-nine PLHIV completed a two-group, 3-month randomized clinical trial testing a self-management intervention to improve physical activity and dietary intake. At baseline and 3 months later, everyone completed validated assessments of physical, diet, and neurocognitive processing (functional magnetic resonance imaging [fMRI]–derived network analyses). We used linear mixed effects modeling with a random intercept to examine the effect of the intervention. The intervention improved healthy eating ( p = .08) but did not improve other self-management behaviors. There was a significant effect of the intervention on several aspects of neurocognitive processing including in the task positive network (TPN) differentiation ( p = .047) and an increase in the default mode network (DMN) differentiation ( p = .10). Self-management interventions may influence neurocognitive processing in PLHIV, but those changes were not associated with positive changes in self-management behavior.
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