Health Literacy and Patient-Reported Outcomes: A Cross-Sectional Study of Underserved English- and Spanish-Speaking Patients With Type 2 Diabetes

2015 ◽  
Vol 20 (sup2) ◽  
pp. 4-15 ◽  
Author(s):  
Elizabeth A. Hahn ◽  
James L. Burns ◽  
Elizabeth A. Jacobs ◽  
Pamela S. Ganschow ◽  
Sofia F. Garcia ◽  
...  
2020 ◽  
Vol Volume 14 ◽  
pp. 2231-2242
Author(s):  
Heather L Gelhorn ◽  
Kristina S Boye ◽  
Huda Shalhoub ◽  
Louis S Matza ◽  
Jessica B Jordan ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Daniel Tajdar ◽  
Dagmar Lühmann ◽  
Regina Fertmann ◽  
Tim Steinberg ◽  
Hendrik van den Bussche ◽  
...  

Abstract Background Low health literacy is believed to be associated with behaviours that increase the risk of type 2 diabetes. But there is limited knowledge on the relation between health literacy (HL) and diabetes risk, and whether improving HL could be a potential prevention strategy. Therefore, the main purpose of this study was to examine the link between HL and diabetes risk among non-diabetic adults. Methods We used data from the Hamburg Diabetes Prevention Survey, a population-based cross-sectional study in Germany. One thousand, two hundred and fifty-five non-diabetic subjects aged 18–60 years were eligible. The German Diabetes Risk Score (GDRS, ranging 0 to 123 points) was used to determine the individual risk of type 2 diabetes. The short version of the European Health Literacy Questionnaire (HLS-EU-Q16, ranging 0 to 16 points) was applied to assess the individual self-reported HL. Subjects were asked to self-estimate their diabetes risk, which was then compared with the calculated GDRS. Descriptive statistics were calculated to investigate group differences in the GDRS and self-estimated diabetes risk. Linear as well as logistic regression models were performed to analyse potential influencing variables of the GDRS as well as incorrect self-estimated diabetes risk. In three nested statistical models for each outcome, these analyses were adjusted for age, gender, educational level and the presence of chronic conditions. Results According to the criteria of the GDRS, 996 (79.4%) subjects showed “low risk”, 176 (14.0%) “still low risk”, 53 (4.2%) “elevated risk”, and 30 (2.4%) “high to very high risk” to develop type 2 diabetes within the next 5 years. In the statistical models including all control variables, subjects with “inadequate HL” scored 2.38 points higher on the GDRS (95% CI 0.378 to 4.336; P = 0.020) and had a 2.04 greater chance to estimate their diabetes risk incorrectly (OR 2.04; 95% CI 1.33 to 3.14; P = 0.001) compared to those with “sufficient HL”. Conclusion The risk of type 2 diabetes is increased in people with inadequate self-reported HL. People with high diabetes risk and inadequate HL might be provided with educational programs to improve diabetes knowledge and reduce behavioural risk factors.


2021 ◽  
Vol 29 (Supplement_1) ◽  
pp. i30-i30
Author(s):  
J Wells ◽  
A El-Husseini ◽  
A Jaffar ◽  
K Dolgin ◽  
G Hubert ◽  
...  

Abstract Introduction The average medication adherence (MA) among patients in developed countries living with a chronic disease is estimated to be roughly 50%.(1) Non-adherence is multi-factorial, owing to socio-economic and clinical factors, as well as arguably the most important factor, patients’ health beliefs and experiences. Patient Reported Outcome Measures (PROMs) are often uni-dimensional in their assessment of drivers of MA. This study has evaluated a novel PROM as part of a wider international research initiative focused on Type 2 Diabetes (T2D) which assesses four key factors of MA referred to as Social (S), Psychological (P), Usage (U) and Rationale (R), in short SPUR®. Aim To compare the validity of SPUR® against previously validated PROMs in patients with T2D. Methods This South London cross-sectional study surveyed adult participants with a confirmed diagnosis of T2D prescribed a minimum of one anti-hyperglycaemic medicine. Surveys were administered face-to-face by community pharmacists using a convenience sampling method based on interactions with pharmacy patients. The survey consisted of questions relating to socio-demographic and clinical data, the SPUR® tool and three previously validated PROMs (BeMQ-General®, MARS-10® and BeMQ-Specific®) as comparators to evaluate factors P, U and R respectively. The Medication Possession Ratio (MPR), a measure of a patient’s pill count in a given time period, was used as an objective comparator of adherence. Pearson’s correlation coefficients (r) were calculated to determine the strength of association between the validated PROMs and SPUR®, with T tests used as a measure of significance (p=<0.05) as an evaluation of validity for SPUR®. Results The survey response rate was 21.6% (n=149/690). The modal age range for participants was 60–69 years of age (40.1%, n=60). Participants were predominantly educated to degree level (29.5%, n=44), White (48.3%, n=72) and retired (28.9%, n=43). Overall, 47.6% (n=71) of participants identified as female. Body Mass Index (BMI) data were available for 88.6% (n=132) of the sample with 42.4% (n=56/132) reporting a BMI >30. In ascending order, moderate to strong positive correlations were observed between SPUR® and the comparative PROMs for factors P (r=0.464, p=<0.0001), U (r=0.595, p=<0.0001) and R (r=0.719, p=<0.0001), indicating SPUR® to be a reliable measure of those MA factors. When assessing MA objectively, SPUR® demonstrated the strongest correlation (r=0.281, p=<0.0001) to MPR compared with the validated tools, with MARS-10® as the closest comparator (r=0.266, p=0.001). Despite this, SPUR® did not overestimate MA, 83.8% (n=125) of the sample was identified as adherent based on MPR compared to 53% (n=79) with SPUR®. The latter more closely reflecting HbA1c data which identified 55.4% (n=31/56) as adherent. Conclusion Study strengths include the implementation of validated PROMs and two objective MA measures; however, the study sample size was limited. SPUR® has demonstrated its validity against validated PROMs whilst predicting adherence levels without exaggeration, which is often attributed to crude objective measures such as MPR.(2) SPUR® may therefore holistically identify the multiple factors linked to non-adherence, thus supporting the design of individualised interventions.. Such interventions are deemed by the World Health Organisation as potentially more impactful than developing new treatments.(1) References 1. Eduardo Sabaté (WHO/NMH/CCH). Adherence to long-term therapies: policy for action. World Heal Organ. Published online 2001. 2. Long JA, Wang A, Medvedeva EL, et al. Glucose control and medication adherence among veterans with diabetes and serious mental illness: Does collocation of primary care and mental health care matter? Diabetes Care. Published online 2014. doi:10.2337/dc13-0051


BMJ Open ◽  
2014 ◽  
Vol 4 (2) ◽  
pp. e004180 ◽  
Author(s):  
Jonas Gordilho Souza ◽  
Daniel Apolinario ◽  
Regina Miksian Magaldi ◽  
Alexandre Leopold Busse ◽  
Flavia Campora ◽  
...  

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 2393-PUB
Author(s):  
KENICHIRO TAKAHASHI ◽  
MINORI SHINODA ◽  
RIKA SAKAMOTO ◽  
JUN SUZUKI ◽  
TADASHI YAMAKAWA ◽  
...  

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