Health Literacy, Stress and Quality of Life in Heart Failure Patients

March 18, 2026 updated by: Cheng-Hsin General Hospital

Using Machine Learning to Analyze the Prediction and Correlation of Health Literacy, Stress and Quality of Life in Heart Failure Patients

Heart failure is showing a trend of affecting younger individuals. Middle-aged heart failure patients are often the economic backbone of their families. Studies have also pointed out that approximately 38.5% of patients with acute heart failure are re-hospitalized within a year of discharge due to worsening symptoms. Patients with lower health literacy tend to have poorer health outcomes and higher re-hospitalization rates. However, there is limited research on the life and work stress, health literacy, and quality of life of middle-aged heart failure patients. Therefore, this study aims to use machine learning to analyze and predict the correlations between health literacy, stress, and quality of life in heart failure patients.

This research is a cross-sectional correlational study, adopting convenience sampling. The study subjects are cardiology patients aged 18-65 diagnosed with heart failure classified as NYHA II or above by specialists at a regional teaching hospital in northern Taiwan. Data collection took place in the outpatient and inpatient departments of cardiology and cardiothoracic surgery. Structured questionnaires were used for one-on-one interviews, including basic demographic information of heart failure patients, the Chinese version of the European Health Literacy Survey Questionnaire (HLS-EU-Q47), the Chinese version of the Brief Resilience Scale (BRS), the Perceived Stress Scale (PSS), and the Minnesota Living with Heart Failure Questionnaire (MLHFQ). Data will be recorded using Excel, and statistical analysis will be conducted using SPSS version 22. Descriptive statistics such as percentages, means, and standard deviations will be used to describe the demographic and variable distributions. Independent t-tests, ANOVA, and Pearson correlation coefficient will be used to analyze correlations between variables. Machine learning will be employed to analyze and predict quality of life factors in heart failure patients. It is hoped that the results of this study can provide references for nursing practice, help with clinical patient assessment, and improve the quality of care for patients.

Study Overview

Status

Completed

Conditions

Study Type

Observational

Enrollment (Actual)

158

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Taiwan
      • Taipei, Taiwan, 112
        • Cheng Hsin General Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Heart failure patients

Description

Inclusion Criteria:

  • The study subjects are cardiology patients aged 18-65 diagnosed with heart failure classified as NYHA II or above by specialists at a regional teaching hospital in northern Taiwan

Exclusion Criteria:

  • 1.severe mental disease.2. terminal stage of other disease such as cancer.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Minnesota Living with Heart Failure Questionnaire
Time Frame: one year

Use the Chinese version of the Minnesota Heart Failure Quality of Life to assess quality of life.

Use the Chinese version of the Minnesota Heart Failure Quality of Life Questionnaire.There are 21 questions in total, scored from 0 to 5, with a total score of 105. The higher the score, the more serious the impact of the disease on life.
one year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
health literacy
Time Frame: one year

Use the Chinese version of European Health Literacy Survey Questionnaire (HLS-EU-Q) to assess health literacy .

Use the Chinese version of HLS-EU-Q.There are 47 questions in total. Based on a four-point Likert scale, Total score 0-50. 0-25 means Inadequate,26-33 means Problematic,34-42 means Sufficient,43-50 means Excellent.
one year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Cheng-Hsin General Hospital

Investigators

  • Study Director: Hei-Fen Hwang, PhD, Natinal Taipei University of Nursing and Health Sciencs

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

November 20, 2024

Primary Completion (Actual)

November 3, 2025

Study Completion (Actual)

November 3, 2025

Study Registration Dates

First Submitted

March 18, 2025

First Submitted That Met QC Criteria

April 10, 2025

First Posted (Actual)

April 11, 2025

Study Record Updates

Last Update Posted (Actual)

March 19, 2026

Last Update Submitted That Met QC Criteria

March 18, 2026

Last Verified

March 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • (1133)113A-63

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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