Refining Caregiver Reaction Assessment (CRA) Instrument Using Rasch Measurement Model Validation

Introduction: Stroke is known to cause various degrees of dependency, leading to sensory, and motor deficits. In most cases, family members take on the responsibility of home care, without the assistance of medical professionals. This can lead to emotional challenges such as financial crises, role pressure, physical health issues, social life stress, and spiritual strain. In this context, an instrument called Caregiver Reaction Assessment (CRA) has been designed to gauge the workload of family caregiver on the aspects of item difficulty, reliability, as well as validity of person and item. The instrument must be subjected to repeated validity and reliability testing for accurate measurement of the intended construct. Therefore, this study aimed to assess the psychometric properties of CRA instrument using Rasch analysis, with a focus on aspects of item difficulty, reliability, as well as validity of person and item. Materials and methods: A cross-sectional design was used in the investigation with a total of 65 family caregivers as samples. CRA instrument was then used to gauge family caregiver burden, while data was processed with Winstep 5.2.4.0 software. Results: The results showed that based on Rasch model analysis, the item reliability index was 0.94, and the participant reliability index was 0.85 with a 0.87 Cronbach's alpha value. MNSQ and ZSTD's outfits had infit and outfit values for items Q3, Q9, and Q20. The hardest item to approve was Q9, with a logit of 1.48. Conclusion: CRA instrument could help gauge family caregiver burden, particularly those who care for stroke patients

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Publication Details

Journal
Malaysian Journal of Medicine and Health Sciences
Published
2025-05-15
DOI
https://doi.org/10.47836/mjmhs.21.s3.4
Primary Topic
Health Education and Validation
Type
article
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article

Refining Caregiver Reaction Assessment (CRA) Instrument Using Rasch Measurement Model Validation

Mateus Sakundarno Adi, Miftafu Darussalam, Onny Setiani, Untung Sujianto
Malaysian Journal of Medicine and Health Sciences
Health Education and Validation
article

Refining Caregiver Reaction Assessment (CRA) Instrument Using Rasch Measurement Model Validation

Mateus Sakundarno Adi, Miftafu Darussalam, Onny Setiani, Untung Sujianto
article en

Abstract

Introduction: Stroke is known to cause various degrees of dependency, leading to sensory, and motor deficits. In most cases, family members take on the responsibility of home care, without the assistance of medical professionals. This can lead to emotional challenges such as financial crises, role pressure, physical health issues, social life stress, and spiritual strain. In this context, an instrument called Caregiver Reaction Assessment (CRA) has been designed to gauge the workload of family caregiver on the aspects of item difficulty, reliability, as well as validity of person and item. The instrument must be subjected to repeated validity and reliability testing for accurate measurement of the intended construct. Therefore, this study aimed to assess the psychometric properties of CRA instrument using Rasch analysis, with a focus on aspects of item difficulty, reliability, as well as validity of person and item. Materials and methods: A cross-sectional design was used in the investigation with a total of 65 family caregivers as samples. CRA instrument was then used to gauge family caregiver burden, while data was processed with Winstep 5.2.4.0 software. Results: The results showed that based on Rasch model analysis, the item reliability index was 0.94, and the participant reliability index was 0.85 with a 0.87 Cronbach's alpha value. MNSQ and ZSTD's outfits had infit and outfit values for items Q3, Q9, and Q20. The hardest item to approve was Q9, with a logit of 1.48. Conclusion: CRA instrument could help gauge family caregiver burden, particularly those who care for stroke patients

Malaysian Journal of Medicine and Health SciencesVol. 21(s3)
Openalex Percentile: Top 65%
Health Education and Validation
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