Research in Community and Public Health Nursing

Original Articles

[English] Influencing Factors Affecting Caregivers’ Service Quality for the Elderly with Dementia: Focusing on Dementia Knowledge, Work Value, and Job Performance Confidence: Doo Ree Kim, Kwang Hwan Kim, Soo Yeon Lee, Sun Hee Han, Gi Ran Lee; J Korean Acad Community Health Nurs. 2021;32(3):233-242. Published online September 30, 2021; DOI: https://doi.org/10.12799/jkachn.2021.32.3.233

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Purpose
The purpose of this study was to verify influencing factors affecting service quality provided by caregivers working for the elderly with dementia.
Methods
Data were collected using a self-reported questionnaire from 214 caregivers in a long-term care facility in D city. The data were analyzed with service quality, dementia knowledge, work value, and job performance confidence. For data analysis, the descriptive statistics, t-test, one-way ANOVA, Pearson correlation coefficients, and multiple regression were performed using SPSS/WIN 21.0 program.
Results
There were significant differences in service quality depending on the health status. Factors influencing service quality were work value, and job performance confidence with R² value of 38%. The highly influencing factors were work value, and job performance confidence.
Conclusion
The results of this study indicate that the effort to improve the service quality of caregivers should focus on work value and job performance confidence.

Citations

Citations to this article as recorded by

The subjectivity of care workers’ perception on remaining functional ability care: A Q methodology approach
Hyunjung Doo, Soonmi Park
Journal of Korean Gerontological Nursing.2023; 25(1): 56. CrossRef

[English] Acceptance Measure of Quality Improvement Information System among Long-term Care Workers: A Psychometric Assessment: Tae Hoon Lee, Young il Jung, Hongsoo Kim; J Korean Acad Community Health Nurs. 2017;28(4):513-523. Published online December 31, 2017; DOI: https://doi.org/10.12799/jkachn.2017.28.4.513

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Abstract PDF

PURPOSE
We evaluated the psychometric properties of a questionnaire on the acceptance of the quality improvement information system (QIIS) among long-term care workers (mostly nurses).
METHODS
The questionnaire composes of 21 preliminary questions with 5 domains based on the Technology Acceptance Model and related literature reviews. We developed a prototype web-based comprehensive resident assessment system, and collected data from 126 subjects at 75 long-term care facilities and hospitals, who used the system and responded to the questionnaire. A priori factor structure was developed using an exploratory factor analysis and validated by a confirmatory factor analysis; its reliability was also evaluated.
RESULTS
A total of 16 items were yielded, and 5 factors were extracted from the explanatory factor analysis: Usage Intention, Perceived Usefulness, Perceived Ease of Use, Social Influence, and Innovative Characteristics. The five-factor structure model had a good fit (Tucker-Lewis index [TLI]=.976; comparative fit index [CFI]=.969; standardized root mean squared residual [SRMR]=.052; root mean square error of approximation [RMSEA]=.048), and the items were internally consistent(Cronbach's Î±=.91).
CONCLUSION
The questionnaire was valid and reliable to measure the technology acceptance of QIIS among long-term care workers, using the prototype.

Citations

Citations to this article as recorded by

Reliability and Validity Analysis of the Korean Version of the Affinity for Technology Interaction Scale
Taehui Kim, Seyeon Park, Miri Jeong
Healthcare.2023; 11(13): 1951. CrossRef
Effectiveness of a Technology-Enhanced Integrated Care Model for Frail Older People: A Stepped-Wedge Cluster Randomized Trial in Nursing Homes
Hongsoo Kim, Young-il Jung, Gi-Soo Kim, Hyoungshim Choi, Yeon-Hwan Park, Suzanne Meeks
The Gerontologist.2021; 61(3): 460. CrossRef
Validation of an integrated service model, Health-RESPECT, for older patients in long-term care institution using information and communication technologies: protocol of a cluster randomised controlled trial
Jung-Yeon Choi, Kwang-il Kim, Hongsoo Kim, Young-il Jung, In-Hwan Oh, Seungyeon Chun, Gi-Soo Kim, Jae-Young Lim, Jin Young Ko
BMJ Open.2020; 10(10): e038598. CrossRef

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