This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Chiu-Chu Lin
Kaohsiung Medical University
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8947-467X
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Aims: To develop a theoretical and psychometrical reliable measurement tool to identify the symptom clusters of patients undergoing hemodialysis (HD).
Design: A cross-sectional descriptive study.
Methods: To examine the psychometric properties of the HD symptom distress (HSD) scale, 216 subjects were recruited from a HD center of 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 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 0.87. The test-retest reliability was 0.92 (p < 0.001) by using the intraclass correlation coefficient (ICC) for HSD-22 scale.
Conclusion: Results indicated that the HSD-22 scale had initial satisfactory validity and reliability. Therefore, this tool can be used to identify the symptom clusters of patients receiving HD.
Impact: Patients receiving HD often experienced multiple symptoms concurrently and 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 had explored symptom clusters related to patients receiving HD, the clusters form had problems with overlapping, vagueness, lack of cluster-specific, and difficulty in discerning their common mechanism under the cluster. Psychometric testing from our study indicated that the HSD-22 scale can be employed to identify the symptom clusters of patients receiving HD in the clinical setting. Such identification enables healthcare professionals provide interventions to release patients’ symptom distress efficiently.
Keywords
Exploratory Factor Analysis, Hemodialysis, Nursing, Scale, Symptom Distress, Symptom Cluster
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
View the published article at BMC Nephrology.
Version 1
Posted 22 Jul, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Learn more about our company.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Chiu-Chu Lin
Kaohsiung Medical University
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8947-467X
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
View the published article at BMC Nephrology.
Version 1
Posted 22 Jul, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Nephrology.
Aims: To develop a theoretical and psychometrical reliable measurement tool to identify the symptom clusters of patients undergoing hemodialysis (HD).
Design: A cross-sectional descriptive study.
Methods: To examine the psychometric properties of the HD symptom distress (HSD) scale, 216 subjects were recruited from a HD center of 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 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 0.87. The test-retest reliability was 0.92 (p < 0.001) by using the intraclass correlation coefficient (ICC) for HSD-22 scale.
Conclusion: Results indicated that the HSD-22 scale had initial satisfactory validity and reliability. Therefore, this tool can be used to identify the symptom clusters of patients receiving HD.
Impact: Patients receiving HD often experienced multiple symptoms concurrently and 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 had explored symptom clusters related to patients receiving HD, the clusters form had problems with overlapping, vagueness, lack of cluster-specific, and difficulty in discerning their common mechanism under the cluster. Psychometric testing from our study indicated that the HSD-22 scale can be employed to identify the symptom clusters of patients receiving HD in the clinical setting. Such identification enables healthcare professionals provide interventions to release patients’ symptom distress efficiently.
Loading...