Dataset Information

Development and testing of the hemodialysis symptom distress scale (HSD-22) to identify the symptom cluster by using exploratory factor analysis.

ABSTRACT:

Background

Patients receiving hemodialysis (HD) often experience multiple symptoms concurrently and these symptoms may impact their quality of life. A valid and reliable tool is needed to assess the symptom distress of patients receiving HD in terms of the perspective of symptom clusters. Although many studies have explored symptom clusters related to patients receiving HD, the clusters formed had problems with overlapping, vagueness, lack of cluster-specificity, and difficulty in discerning their common mechanism under the cluster.

Aims

To develop reliable measurement tool to identify the symptom clusters of patients undergoing HD.

Design

A cross-sectional descriptive study.

Methods

To examine the physiological properties of the HD symptom distress (HSD) scale, 216 participants were recruited from a HD center of a medical university hospital in southern Taiwan from February 2019 to April 2019. Construct validity was evaluated by exploratory factor analysis (EFA), and the internal consistency and test-retest reliability were estimated by Cronbach's alpha and intraclass correlation coefficient (ICC).

Results

The CVI value of the HSD was 0.89. The HSD scale was composed of five factors with 22 items, including insufficient energy/vitality, cardiac-pulmonary distress, sleep disturbance, musculoskeletal distress, and gastrointestinal distress, with factor loading ranging from 0.62 to 0.87, explaining 65.5% of the total variance. Cronbach's alpha coefficient of the HSD total scale was 0.93, and five subscales ranged from 0.73 to 0.89. The test-retest reliability was 0.92 (p < 0.001) by using the intraclass correlation coefficient (ICC) for the HSD-22 scale.

Conclusion / implication

Theoretical testing from our study indicated that the HSD-22 scale had satisfactory validity and reliability. Therefore, this assessment tool can be employed to identify the symptom clusters of patients receiving HD in the clinical setting. Such identification enables healthcare professionals to provide interventions to release patients' symptom distress efficiently.

SUBMITTER: Chen MC

PROVIDER: S-EPMC8042879 | biostudies-literature |

REPOSITORIES: biostudies-literature

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