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Electronic Health Literacy Among Magnetic Resonance Imaging and Computed Tomography Medical Imaging Outpatients: Cluster Analysis.

ABSTRACT: BACKGROUND:Variations in an individual's electronic health (eHealth) literacy may influence the degree to which health consumers can benefit from eHealth. The eHealth Literacy Scale (eHEALS) is a common measure of eHealth literacy. However, the lack of guidelines for the standardized interpretation of eHEALS scores limits its research and clinical utility. Cut points are often arbitrarily applied at the eHEALS item or global level, which assumes a dichotomy of high and low eHealth literacy. This approach disregards scale constructs and results in inaccurate and inconsistent conclusions. Cluster analysis is an exploratory technique, which can be used to overcome these issues, by identifying classes of patients reporting similar eHealth literacy without imposing data cut points. OBJECTIVE:The aim of this cross-sectional study was to identify classes of patients reporting similar eHealth literacy and assess characteristics associated with class membership. METHODS:Medical imaging outpatients were recruited consecutively in the waiting room of one major public hospital in New South Wales, Australia. Participants completed a self-report questionnaire assessing their sociodemographic characteristics and eHealth literacy, using the eHEALS. Latent class analysis was used to explore eHealth literacy clusters identified by a distance-based cluster analysis, and to identify characteristics associated with class membership. RESULTS:Of the 268 eligible and consenting participants, 256 (95.5%) completed the eHEALS. Consistent with distance-based findings, 4 latent classes were identified, which were labeled as low (21.1%, 54/256), moderate (26.2%, 67/256), high (32.8%, 84/256), and very high (19.9%, 51/256) eHealth literacy. Compared with the low class, participants who preferred to receive a lot of health information reported significantly higher odds of moderate eHealth literacy (odds ratio 16.67, 95% CI 1.67-100.00; P=.02), and those who used the internet at least daily reported significantly higher odds of high eHealth literacy (odds ratio 4.76, 95% CI 1.59-14.29; P=.007). CONCLUSIONS:The identification of multiple classes of eHealth literacy, using both distance-based and latent class analyses, highlights the limitations of using the eHEALS global score as a dichotomous measurement tool. The findings suggest that eHealth literacy support needs vary in this population. The identification of low and moderate eHealth literacy classes indicate that the design of eHealth resources should be tailored to patients' varying levels of eHealth literacy. eHealth literacy improvement interventions are needed, and these should be targeted based on individuals' internet use frequency and health information amount preferences.

SUBMITTER: Hyde LL

PROVIDER: S-EPMC6737886 | biostudies-other | 2019 Aug

REPOSITORIES: biostudies-other

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Electronic Health Literacy Among Magnetic Resonance Imaging and Computed Tomography Medical Imaging Outpatients: Cluster Analysis.

Hyde Lisa Lynne LL Boyes Allison W AW Mackenzie Lisa J LJ Leigh Lucy L Oldmeadow Christopher C Riveros Carlos C Sanson-Fisher Rob R

Journal of medical Internet research 20190828 8

<h4>Background</h4>Variations in an individual's electronic health (eHealth) literacy may influence the degree to which health consumers can benefit from eHealth. The eHealth Literacy Scale (eHEALS) is a common measure of eHealth literacy. However, the lack of guidelines for the standardized interpretation of eHEALS scores limits its research and clinical utility. Cut points are often arbitrarily applied at the eHEALS item or global level, which assumes a dichotomy of high and low eHealth litera ...[more]

PMID: 31464188

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Project description:BACKGROUND:Electronic health (eHealth) literacy is needed to effectively engage with Web-based health resources. The 8-item eHealth literacy scale (eHEALS) is a commonly used self-report measure of eHealth literacy. Accumulated evidence has suggested that the eHEALS is unidimensional. However, a recent study by Sudbury-Riley and colleagues suggested that a theoretically-informed three-factor model fit better than a one-factor model. The 3 factors identified were awareness (2 items), skills (3 items), and evaluate (3 items). It is important to determine whether these findings can be replicated in other populations. OBJECTIVE:The aim of this cross-sectional study was to verify the three-factor eHEALS structure among magnetic resonance imaging (MRI) and computed tomography (CT) medical imaging outpatients. METHODS:MRI and CT outpatients were recruited consecutively in the waiting room of one major public hospital. Participants self-completed a touchscreen computer survey, assessing their sociodemographic, scan, and internet use characteristics. The eHEALS was administered to internet users, and the three-factor structure was tested using structural equation modeling. RESULTS:Of 405 invited patients, 87.4% (354/405) were interested in participating in the study, and of these, 75.7% (268/354) were eligible. Of the eligible participants, 95.5% (256/268) completed all eHEALS items. Factor loadings were 0.80 to 0.94 and statistically significant (P<.001). All reliability measures were acceptable (indicator reliability: awareness=.71-.89, skills=.78-.80, evaluate=.64-.79; composite reliability: awareness=.89, skills=.92, evaluate=.89; variance extracted estimates: awareness=.80, skills=.79, evaluate=.72). Two out of three goodness-of-fit indices were adequate (standardized root mean square residual (SRMR)=.038; comparative fit index (CFI)=.944; root mean square error of approximation (RMSEA)=.156). Item 3 was removed because of its significant correlation with item 2 (Lagrange multiplier [LM] estimate 104.02; P<.001) and high loading on 2 factors (LM estimate 91.11; P<.001). All 3 indices of the resulting 7-item model indicated goodness of fit (?211=11.3; SRMR=.013; CFI=.999; RMSEA=.011). CONCLUSIONS:The three-factor eHEALS structure was supported in this sample of MRI and CT medical imaging outpatients. Although further factorial validation studies are needed, these 3 scale factors may be used to identify individuals who could benefit from interventions to improve eHealth literacy awareness, skill, and evaluation competencies.

Project description:The aim of this study was to analyze the computed tomography (CT) and magnetic resonance imaging (MRI) findings of dermatofibrosarcoma protuberans (DFSP), with a view to improving the diagnosis of this kind of tumor. A total of 27 cases of histopathologically confirmed DFSP were analyzed retrospectively. Of these, 18 patients underwent a CT scan and 9 patients underwent an MRI. All patients underwent unenhanced and contrast-enhanced examinations; 1 patient underwent multiphrase CT enhancement examination. Imaging characteristics, including location, shape, size, number, edge, and attenuation or intensity of each lesion, both unenhanced and contrast enhanced, were analyzed. Of the 27 cases, 24 were solitary, 2 had 2 nodules, and 1 had multiple confluent tumors. The lesion with multiple confluent tumors was ill defined and irregular; the other lesions were oval or round, well-defined nodules or masses. The unenhanced CT images showed 19 homogenous isodense lesions. There was no calcification in any of the patients. The contrast-enhanced CT images showed intermediate and marked nonhomogeneous enhancement in 13 lesions, intermediate homogeneous enhancement in 4 lesions, and a mild heterogeneous enhancement in 2 lesions. MR T1-weighted images revealed 1 ill-defined and 9 well-defined homogeneous isointense lesions. T2-weighted images showed homogeneous hyperintensity to the muscles in 6 lesions, 3 mild hyperintense lesions with hypointense lesions, and 1 mixed, mild hyperintense and isointense lesion. Contrast-enhanced T1-weighted images demonstrated intermediate and marked nonhomogeneous enhancement in 9 lesions and intermediate homogeneous enhancement in 1 lesion. DFSP is characterized by a subcutaneous well-defined soft tissue nodule or mass on plain CT/MR scans, and shows intermediate-to-marked enhancement on contrast-enhanced CT/MR scans. The imaging findings for DFSP are nonspecific, but may help to define the diagnosis in an appropriate clinical setting.

Project description:The aim of the present study was to investigate the imaging characteristics of ovarian fibrothecoma. The cases of 25 female patients with pathologically confirmed ovarian fibrothecomas were retrospectively reviewed. Tumor location, size, density, signal intensity, cystic degeneration, calcification, enhancement pattern and ascites were assessed by computed tomography (CT) (n=20) and magnetic resonance imaging (MRI) (n=5). Clinical and histological features were also evaluated. The results revealed that 23 (92.0%) patients were postmenopausal, with a mean age ± standard deviation (SD) of 60.7±10.8 years old. All 25 tumors were unilateral and a thickened endometrium was observed in 7 (28.0%) patients. In total, 24 (96.0%) tumors appeared to have well-defined boundaries, with 1 (4%) tumor exhibiting an obscure boundary. Tumors had a mean size of 9.8±5.3 cm. Solid and predominantly solid masses were found in 16 cases (64.0%), and cystic and predominantly cystic masses were found in 9 patients (36.0%). Solid regions of masses exhibited hypodensity or isodensity in 24 patients (96.0%), with 1 patient (4.0%) exhibiting hyperdensity. The mean CT value (± SD) was 44.2±12.8 HU (range, 31-79HU) in unenhanced images. All masses exhibited isointensity or slight hypointensity on T1-weighted imaging, and tumor parenchyma also exhibited slight hypointensity or isointensity on T2-weighted imaging compared with the myometrium, with or without areas of patchy hyperintensity. Contrast-enhanced CT or MRI scans were performed on 19 patients, and the solid components (94.7%) exhibited mild to moderate enhancement in 18 patients and 1 patient (5.3%) exhibited intense enhancement. Tumor size was positively correlated with the tumor cystic degeneration (r=0.77, P<0.001) and ascites (r=0.41, P<0.001). Therefore, ovarian fibrothecoma typically presents as solid or predominant solid masses with clear boundaries; the parenchyma of the tumor exhibits isodensity on CT scans, slight hypointensity or isointensity on MRI and mild enhancement following contrast-medium injection. The thickened endometrium observed in postmenopausal woman may also be a valuable imaging feature.

Project description:The cholangiopathies are a diverse group of biliary tract disorders, many of which lack effective treatment. Murine models are an important tool for studying their pathogenesis, but existing noninvasive methods for assessing biliary disease in vivo are not optimal. Here we report our experience with using micro-computed tomography (microCT) and nuclear magnetic resonance (MR) imaging to develop a technique for live-mouse cholangiography. Using mdr2 knockout (mdr2KO, a model for primary sclerosing cholangitis (PSC)), bile duct-ligated (BDL), and normal mice, we performed in vivo: (1) microCT on a Siemens Inveon PET/CT scanner and (2) MR on a Bruker Avance 16.4?T spectrometer, using Turbo Rapid Acquisition with Relaxation Enhancement, IntraGate Fast Low Angle Shot, and Half-Fourier Acquisition Single-shot Turbo Spin Echo methods. Anesthesia was with 1.5-2.5% isoflurane. Scans were performed with and without contrast agents (iodipamide meglumine (microCT), gadoxetate disodium (MR)). Dissection and liver histology were performed for validation. With microCT, only the gallbladder and extrahepatic bile ducts were visualized despite attempts to optimize timing, route, and dose of contrast. With MR, the gallbladder, extra-, and intrahepatic bile ducts were well-visualized in mdr2KO mice; the cholangiographic appearance was similar to that of PSC (eg, multifocal strictures) and could be improved with contrast administration. In BDL mice, MR revealed cholangiographically distinct progressive dilation of the biliary tree without ductal irregularity. In normal mice, MR allowed visualization of the gallbladder and extrahepatic ducts, but only marginal visualization of the diminutive intrahepatic ducts. One mouse died during microCT and MR imaging, respectively. Both microCT and MR scans could be obtained in ?20?min. We, therefore, demonstrate that MR cholangiography can be a useful tool for longitudinal studies of the biliary tree in live mice, whereas microCT yields suboptimal duct visualization despite requiring contrast administration. These findings support further development and application of MR cholangiography to the study of mouse models of PSC and other cholangiopathies.

Dataset Information

Electronic Health Literacy Among Magnetic Resonance Imaging and Computed Tomography Medical Imaging Outpatients: Cluster Analysis.

Publications

Electronic Health Literacy Among Magnetic Resonance Imaging and Computed Tomography Medical Imaging Outpatients: Cluster Analysis.

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