scholarly journals Organizational Health Literacy in a Hospital—Insights on the Patients’ Perspective

2021 ◽  
Vol 18 (23) ◽  
pp. 12646
Author(s):  
Johanna Sophie Lubasch ◽  
Mona Voigt-Barbarowicz ◽  
Nicole Ernstmann ◽  
Christoph Kowalski ◽  
Anna Levke Brütt ◽  
...  
Keyword(s):  
Health Literacy ◽  
Structural Equation ◽  
Information Needs ◽  
Patient Characteristics ◽  
Organizational Health ◽  
Patient Survey ◽  
Equation Model ◽  
University Hospital ◽  
Patient Reported ◽  
Patients Perspective

Health literacy-sensitive communication has been found to be an important dimension of organizational health literacy measured from the patients’ perspective. Little is known about the role of health literacy-sensitive communication in complex care structures. Therefore, our aim was to assess which hospital characteristics (in terms of process organization) and patient characteristics (e.g., age, chronic illness, etc.) contribute to better perceptions of health literacy-sensitive communication, as well as whether better health literacy-sensitive communication is associated with better patient reported experiences. Data were derived from a patient survey conducted in 2020 in four clinical departments of a university hospital in Germany. Health literacy-sensitive communication was measured with the HL-COM scale. Data from 209 patients (response rate 24.2%) were analyzed with a structural equation model (SEM). Results revealed that no patient characteristics were associated with HL-COM scores. Better process organization as perceived by patients was associated with significantly better HL-COM scores, and, in turn, better HL-COM scores were associated with more patient-reported social support provided by physicians and nurses as well as fewer unmet information needs. Investing into good process organization might improve health literacy-sensitive communication, which in turn has the potential to foster the patient–provider relationship as well as to reduce unmet information needs of patients.

scholarly journals Exploring COVID-19 Anxiety in Iranian Adult Based on Health Literacy by Moderating Demographic Variables: A Structural Equation Model

Heliyon ◽  
2021 ◽  
pp. e07336
Author(s):  
Fatemeh Mohammadkhah ◽  
Abbas Shamsalinia ◽  
Fatemeh Shirinkam ◽  
Mahboubeh Daneshnia ◽  
Amaneh Mahmoudian ◽  
...  
Keyword(s):  
Health Literacy ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Equation Model ◽  
Demographic Variables

scholarly journals The Effect of YouTube eWOM on Consumer Buying Interest

Revista CEA ◽  
2020 ◽  
Vol 6 (12) ◽  
pp. 167-179
Author(s):  
Amar Nuriman Izudin ◽  
Endang Ruswanti ◽  
Moehammad Unggul Januarko
Keyword(s):  
Structural Equation ◽  
Information Needs ◽  
Information Quality ◽  
Reasoned Action ◽  
Equation Model ◽  
Quality Information ◽  
Analysis Techniques ◽  
Adoption Model ◽  
Acceptance Model ◽  
Information Adoption

YouTube creates valuable social media opportunities in eWOM content. Individuals currently discuss products and other matters with their friends and new acquaintances over the internet. The purpose of this study was to determine the effect of YouTube eWOM conversations on consumer buying interest. Based on the Information Adoption Model (AIM) and the Theory of Reasoned Action (TRAM), we developed a new conceptual model: The Information Acceptance Model (IACM). In this quantitative study, the population under analysis, composed of followers of a YouTube channel, was selected using purposive sampling so that the number of respondents was 200. We implemented data analysis techniques using the Structural Equation Model with Lisrel. The results show that information quality, information credibility, information needs, information usefulness, information adoption, and attitude towards information influence consumer buying interest.

scholarly journals Modeling the communication-satisfaction relationship in hospital patients

2019 ◽  
Vol 7 ◽  
pp. 205031211984792 ◽  
Author(s):  
Daniel Pelletier ◽  
Isabelle Green-Demers ◽  
Pierre Collerette ◽  
Michael Heberer
Keyword(s):  
Patient Satisfaction ◽  
Patient Experience ◽  
Structural Equation ◽  
Strong Relationship ◽  
Patient Characteristics ◽  
Integrated Approach ◽  
Communication Satisfaction ◽  
The Other ◽  
University Hospital ◽  
Equation Modeling

Objectives: Although it has long been known that communication with medical professionals presents a strong relationship with patient satisfaction, research on this topic has been hindered by conceptual and methodological issues (e.g. single-item measures, inclusion of idiosyncratic patient characteristics, etc.). Using a more comprehensive and integrated approach, this study had two objectives: to document the multidimensional structure of the Picker Patient Experience–15, and to test a patient communication/satisfaction model that organizes its dimensions in a conceptually logical array of relationships. First, the factorial structure of the Picker Patient Experience–15 was hypothesized to comprise five dimensions: communication with patient, with family, addressing fears/concerns, preparation for discharge, and patient satisfaction. Second, the hypothesized model included positive relationships between all four communications dimensions, on the one hand, and patient satisfaction, on the other. Within communication dimensions, communication with patient was hypothesized to be the incipient factor for other dimensions, and thus to be positively associated with the other three forms of communication. Methods: This research is based on a single time point design, which relied on administrative and questionnaire data. The study was conducted at a large University Hospital in Switzerland. The sample included 54,686 patients who received inpatient treatment, excluding those who were cared for in the intensive and intermediate care units. Patients filled out, over a 5-year period, the Picker Patient Experience questionnaire (PPE-15) after discharge (overall response rate of 41%). Results: The proposed five-factor structure of the Picker Patient Experience–15 was successfully supported by the results of a confirmatory factor analysis. Moreover, the hypothesized network of associations between communication and satisfaction latent constructs was substantiated using structural equation modeling. With the exception of the association between preparation for discharge and patient satisfaction, the hypothesized model was fully corroborated. Conclusion: A more in-depth understanding of patient satisfaction can be achieved when it is studied as a multifaceted phenomenon.

The Process of Patient Engagement in Outpatient Cardiac Rehabilitation Programs

2019 ◽  
Vol 36 (4) ◽  
pp. 233-251 ◽  
Author(s):  
Sepideh Jahandideh ◽  
Elizabeth Kendall ◽  
Samantha Low-Choy ◽  
Kenneth Donald ◽  
Rohan Jayasinghe ◽  
...  
Keyword(s):  
Cardiac Rehabilitation ◽  
Patient Engagement ◽  
Structural Equation ◽  
Causal Structure ◽  
Healthcare Providers ◽  
Equation Model ◽  
University Hospital ◽  
Rehabilitation Programs ◽  
Therapeutic Engagement ◽  
New Information

AbstractThe primary aim of this study was to test the causal structure of the model of therapeutic engagement (MTE) for the first time, to examine whether the model assists in understanding the process of patient engagement in cardiac rehabilitation (CR) programs. This study used a prospective design, following up patients from the Gold Coast University Hospital Cardiology ward who attended Robina Cardiac Rehabilitation Clinic. A structural equation model of the interactions among the proposed variables within the three stages of the MTE (intention to engage in CR programs, CR initiation, and sustained engagement) revealed significant relationships among these variables in a dataset of 101 patients who attended a CR program. However, no relationship was discerned between outcome expectancies and patient intention to engage in CR. Patients’ willingness to consider the treatment also mediated the relationship between perceived self-efficacy and patient intention to engage in CR. These findings help clarify the process proposed by Lequerica and Kortte (2010) in the context of patient engagement in CR programs. The findings also reveal information on how patients engage in CR programs. Importantly, this provides new information for healthcare providers, enabling them to more effectively engage patients according to their stage of engagement.

scholarly journals The effect of high blood pressure-health literacy, self-management behavior, self-efficacy and social support on the health-related quality of life of Kazakh hypertension patients in a low-income rural area of China: a structural equation model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qinghua Zhang ◽  
Feifei Huang ◽  
Lei Zhang ◽  
Shasha Li ◽  
Jingping Zhang
Keyword(s):  
Social Support ◽  
Blood Pressure ◽  
Health Literacy ◽  
Self Efficacy ◽  
Structural Equation ◽  
Equation Model ◽  
Self Management ◽  
Management Behavior ◽  
Hypertensive Patients ◽  
Therapeutic Adherence

Abstract Background Health-Related Quality of Life (HRQoL) of hypertensive patients is not only affected by the disease itself but also by some subjective factors. Low health literacy is prevalent among ethnic minorities. Considering the Kazakh-Chinese people have the highest prevalence of hypertension in Xinjiang, and the High Blood Pressure-Health Literacy (HBP-HL) has not been included in the study of HRQoL. The synergistic effects and the potential mechanism HBP-HL, self-management behavior, therapeutic adherence, self-efficacy, social support on HRQoL remain unclear. This study aimed to introduce the HBP-HL, and develop a structural equation model (SEM) to identify the factors influencing of the HRQoL among Kazakh hypertensive patients. Methods The data was obtained by questionnaire survey and physical examination in 2015. Patients with hypertension were recruited through random cluster sampling in Kazakh settlements in Xinjiang. Firstly, the blood pressure was measured. Then the one-for-one household interviews were conducted by Kazakh investigators. The questionnaires regarding HBP-HL, HRQoL, self-management behavior, therapeutic adherence, self-efficacy, and social support were used to collect data. Finally, SEM was constructed, and p ≤ 0.05 was taken as significant. Results The data was analysed by SPSS18.0 and AMOS18.0 software. 516 Kazakh hypertension patients were recruited, and 94.4% of them had a relatively low HBP-HL score. The mean standardized scores of HRQoL, self-management, therapeutic adherence were poor; they were 63.5, 66.2, and 64.4, respectively. But 96.1% and 98.3% of the participants had high levels of self-efficacy and social support. The SEM of the HRQoL had a good overall fit (χ2/df = 2.078, AGFI = 0.944, GFI = 0.968, CFI = 0.947, IFI = 0.949, RMSEA = 0.046). The model indicated that the HBP-HL has the highest correlation with HRQoL, following with self-management behavior, social support, and self-efficacy. Conclusions Low HBP-HL is a major influenced factor of HRQoL among Kazakh hypertensive patients. Future programs should consider HBP-HL as the breakthrough point when designing targeting intervention strategies.

scholarly journals STRUCTURAL EQUATION MODEL OF ARTICLES COVID-19 ON SOCIAL MEDIA TO HEALTH LITERACY AND BEHAVIOR AMONG HEALTH INFORMATION STUDENTS

2021 ◽  
Vol 4 (1) ◽  
pp. 9-16
Author(s):  
Evina Widianawati ◽  
Widya Ratna Wulan ◽  
Ika Pantiawati
Keyword(s):  
Social Media ◽  
Health Literacy ◽  
Health Behavior ◽  
Health Information ◽  
Direct Effect ◽  
Structural Equation ◽  
Descriptive Analysis ◽  
Good Health ◽  
Equation Model ◽  
Equation Modeling

The COVID-19 infodemic is spreading through social media and website requires people to be able to evaluate information during a pandemic. Health literacy is the key to evaluating the infodemic and to get the decision making on health behavior. Health information students primarily use digital technologies such as social media to get information about covid-19 so that students need to have good health literacy to evaluate infodemic. The purpose of this study was to determine the effect of covid-19 article content on health literacy and health behavior among health information students. Data were collected using a questionnaire on 142 health information students then analyzed descriptively and using the structural equation modeling (SEM) method. The results of the descriptive analysis show that 70% of students access covid-19 information through social media mainly using Instagram, where more than half of students access covid-19 article content <= once a day by reading and liking the article. Based on the results of SEM, it is known that the most important factor of the article content is trustworthy content, the most important factor of health literacy is adherence to prevention and the most important factor of health behavior is reducing contact with other people. From the results of the SEM effect test, it is known that there is a direct effect of content articles on health literacy of 51%. On the other hand, there is a direct effect from health literacy to health behavior of 63,4% and there is no significant effect from content articles to health behavior.

Estimating the effects of patient-reported outcome (PRO) diarrhea and pain measures on PRO fatigue: Data analysis from a phase II study of abemaciclib monotherapy, a CDK4 and CDK6 inhibitor, in patients with HR+/HER2- breast cancer after chemotherapy for metastatic disease—MONARCH 1.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1060-1060 ◽  
Author(s):  
Mark Boye ◽  
Katherine Houghton ◽  
Donald E Stull ◽  
Claire Ainsworth ◽  
Gregory L Price
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
Brief Pain Inventory ◽  
Patient Reported Outcome ◽  
Equation Model ◽  
Open Label ◽  
Cross Sectional ◽  
Her2 Breast Cancer ◽  
Patient Reported ◽  
Eortc Qlq

1060 Background: Investigators reporting treatment-emergent adverse events (TEAEs) in the 3rdline or greater abemaciclib MONARCH1 Phase 2 study observed Grade 1-3 diarrhea, fatigue, and abdominal pain in 90, 65, and 39% of the patients (n = 132). Unknown is the extent that diarrhea and overall pain add to fatigue in this setting. Using patient-reported outcome (PRO) measures, we conducted cross-sectional and longitudinal multivariate analyses to estimate these effects. Methods: Data came from a single-arm, open-label study of previously-treated patients with mBC. Throughout the study, the Brief Pain Inventory and the EORTC QLQ-C30 v3 were co-administered. All constructs and items from these two questionnaires –except EORTC Items 25 and 28 (memory and financial difficulties) - were used to estimate the Structural Equation Model (SEM) and the direct and indirect effects of pain and diarrhea on fatigue. Extended pattern mixture modeling (ePMM) – a latent variable modeling method that allows the explicit analysis of missing data and identifies subgroups with differential changes over time – was used to explore these relationships from screening through cycle 8. Results: SEM results showed that at cycle 2 of treatment, pain was a significant predictor of fatigue (b = 0.68; P < 0.001; CI 0.48 – 0.90); diarrhea was not a significant predictor of fatigue (b = 0.06; P = 0.12; CI -0.04 – 0.17). ePMM results across eight 30-day cycles found three fatigue subgroups: no change, improvement, worsening then improvement. Belonging to a similar pain subgroup predicted belonging to the corresponding fatigue subgroup (ref class was no change; improving b = 5.03, P = 0.004; worsening b = 22.01, P < 0.001); the same was not true for diarrhea and fatigue (ref class was no change; improving b = 0.213, P = 0.75; worsening b = 0.04, P = 0.97). Conclusions: These results suggest that for patients undergoing 3rd line or greater mBC treatment, pain is a significant predictor of fatigue early and over the course of the trial. However, diarrhea is not a significant predictor of fatigue. Clinical trial information: NCT02102490.

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