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Perceived Treatment Satisfaction and Effectiveness Facilitators Among Patients With Chronic Health Conditions: A Self-Reported Survey.

ABSTRACT: BACKGROUND:Approximately 50% of patients are nonadherent to prescribed medications. Patient perception regarding medication effectiveness has been linked to improved adherence. However, how patients perceive effectiveness is poorly understood. OBJECTIVE:The aim of this study was to elucidate factors associated with perceived treatment satisfaction and effectiveness among patients with chronic health conditions. METHODS:We conducted a descriptive study using a cross-sectional survey design. We administered a Web-based survey to participants with migraine, multiple sclerosis (MS), or rheumatoid arthritis (RA). Patients were recruited from established online communities of Health Union. Descriptive statistics, correlations, and comparison tests were used to examine outcomes. RESULTS:Data were collected from 1820 patients: 567 with migraine, 717 with MS, and 536 with RA. The majority of participants were female (1644/1820, 90.33%), >40 years old (1462/1820, 80.33%), and diagnosed >5 years ago (1189/1820, 65.33%). Treatment satisfaction and perceived medication effectiveness were highly correlated (r=0.90, P<.01). Overall, three temporal factors were positively correlated with satisfaction or perceived effectiveness: time on current medication (satisfaction rs=0.22, P<.01; effectiveness rs=0.25, P<.01), time since diagnosis (satisfaction rs=0.07, P<.01; effectiveness rs=0.09, P<.01), and time on treatment (effectiveness rs=0.08, P<.01). CONCLUSIONS:Findings validated the strong relationship between treatment satisfaction and perceived effectiveness. Understanding the (1) positive relationship between time and treatment satisfaction and effectiveness and (2) factors associated with determining medication effectiveness can help clinicians better understand the mindset of patients regarding treatment. Clinicians may be better prepared to elicit patient beliefs, which influence medication adherence, for people diagnosed with chronic health conditions.

SUBMITTER: Volpicelli Leonard K

PROVIDER: S-EPMC7084280 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Perceived Treatment Satisfaction and Effectiveness Facilitators Among Patients With Chronic Health Conditions: A Self-Reported Survey.

Volpicelli Leonard Kathryn K Robertson Courtney C Bhowmick Amrita A Herbert Leslie Beth LB

Interactive journal of medical research 20200306 1

<h4>Background</h4>Approximately 50% of patients are nonadherent to prescribed medications. Patient perception regarding medication effectiveness has been linked to improved adherence. However, how patients perceive effectiveness is poorly understood.<h4>Objective</h4>The aim of this study was to elucidate factors associated with perceived treatment satisfaction and effectiveness among patients with chronic health conditions.<h4>Methods</h4>We conducted a descriptive study using a cross-sectiona ...[more]

PMID: 32141836

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Project description:BackgroundAn inability to successfully recruit participants into clinical research has consequences that negatively affect the conduct and reliability of research studies. Understanding facilitators of research participation, namely motives for participation and preferred research outcomes, may improve recruitment and retention of clinical trials related to chronic pain. The present study explored research participation facilitators among individuals with chronic pain and their association with demographic characteristics, pain-related characteristics, and factors related to future research engagement.MethodsIndividuals from Michigan who were 18 years or older and self-reported having chronic pain completed an online survey assessing motives for research participation and desired research outcomes. Analyses were conducted in three stages. First, we evaluated underlying factors of motives for participation and research outcome preferences using principal components analysis. Second, we classified individuals according to their patterns of facilitators using latent profile analysis. Finally, we evaluated differences between facilitator profiles in demographic characteristics, pain-related characteristics, and factors related to future research engagement using χ2 analyses and Kruskal-Wallis rank sum tests.ResultsThree components of motives for research participation were identified: social engagement/enjoyment; pain improvement/advancing science; and compensation. Three components of research outcome preferences were identified: co-occurring symptom reduction; behavior reduction modification; and pain and function improvement. Four potential patient-centered profiles utilizing these dimensions of facilitators were identified that had unique demographic characteristics, research participation willingness, and treatment interest.ConclusionsOur data provide a framework of motives and research outcome preferences that may inform recruitment and retention in chronic pain research. It also gives an indication of who may respond best to active or passive recruitment strategies that appeal to a given motive or preferred outcome. This information may be useful for improving recruitment and to monitor any potential biases in participant samples.

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Project description:BackgroundIdentifying the medical conditions that are associated with poor health is crucial to prioritize decisions for future research and organizing care. However, assessing the burden of disease in the general population is complex, lengthy, and expensive. Claims databases that include self-reported health status can be used to assess the impact of medical conditions on the health in a population.ObjectiveThis study aimed to identify medical conditions that are highly predictive of poor health status using claims databases.MethodsTo determine the medical conditions most highly predictive of poor health status, we used a retrospective cohort study using 2 US claims databases. Subjects were commercially insured patients. Health status was measured using a self-report health status response. All medical conditions were included in a least absolute shrinkage and selection operator regression model to assess which conditions were associated with poor versus excellent health.ResultsA total of 1,186,871 subjects were included; 61.64% (731,587/1,186,871) reported having excellent or very good health. The leading medical conditions associated with poor health were cancer-related conditions, demyelinating disorders, diabetes, diabetic complications, psychiatric illnesses (mood disorders and schizophrenia), sleep disorders, seizures, male reproductive tract infections, chronic obstructive pulmonary disease, cardiomyopathy, dementia, and headaches.ConclusionsUnderstanding the impact of disease in a commercially insured population is critical to identify subjects who may be at risk for reduced productivity and job loss. Claims database studies can measure the impact of medical conditions on the health status in a population and to assess changes overtime and could limit the need to collect prospective collection of information, which is slow and expensive, to assess disease burden. Leading medical conditions associated with poor health in a commercially insured population were the ones associated with high burden of disease such as cancer-related conditions, demyelinating disorders, diabetes, diabetic complications, psychiatric illnesses (mood disorders and schizophrenia), infections, chronic obstructive pulmonary disease, cardiomyopathy, and dementia. However, sleep disorders, seizures, male reproductive tract infections, and headaches were also part of the leading medical conditions associated with poor health that had not been identified before as being associated with poor health and deserve more attention.

Dataset Information

Perceived Treatment Satisfaction and Effectiveness Facilitators Among Patients With Chronic Health Conditions: A Self-Reported Survey.

Publications

Perceived Treatment Satisfaction and Effectiveness Facilitators Among Patients With Chronic Health Conditions: A Self-Reported Survey.

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