Cross-Cultural Adaptation and Validation of the Dagbani Readiness for Hospital Discharge Scale–New Mother

Elsevier

Available online 19 August 2022

Journal of Obstetric, Gynecologic & Neonatal NursingAbstract

The Readiness for Hospital Discharge Scale–New Mother (RHDS-NM), originally developed for use in English-speaking populations, is an instrument designed to measure women’s perceptions of readiness for hospital discharge after birth. We translated and cross-culturally adapted the RHDS-NM into Dagbani and conducted reliability and validity assessments of the new Dagbani RHDS-NM in the Tamale Metropolitan Area, Ghana. The average scale-level content validity index was excellent at 1.00. The Dagbani RHDS-NM had a Cronbach’s α reliability coefficient of .94. Exploratory factor analysis indicated four factors with Cronbach’s α reliability coefficients of .958, .915, .899, and .667 that represented the Personal Status, Knowledge, Expected Support, and Coping Ability subscales, respectively. Our findings provide initial evidence to support the reliability and validity of the Dagbani RHDS-NM.

Section snippetsReadiness for Hospital Discharge Scale

The original RHDS (Weiss & Piacentine, 2006) was developed in English and includes 21 items to measure patient perceptions of discharge readiness in the United States. Weiss and Piacentine (2006) provided initial evidence to support the construct validity, predictive validity, and reliability of the RHDS. The RHDS was translated into French (Mabire et al., 2015), Turkish (Kaya, Sain Guven, Teleş, et al., 2018), Portuguese (Siqueira et al., 2018), Bahasa (Hariati et al., 2020), and Chinese (Chen

Design

We conducted a three-phase project. Phase 1 included forward translation and back translation, Phase 2 included pilot testing and adaptation through expert panel review, and Phase 3 included psychometric evaluation of the validity and reliability of the Dagbani RHDS-NM. The scale was translated and adapted for use in the local context among women in the postpartum period in Tamale, Ghana. We used an institutional-based cross-sectional study for the psychometric assessment of the scale. We

Participant Characteristics

Our sample included 151 participants ranging in age from 18 to 45 years, with a mean age of 28.2 years (see Table 1). Most participants (57.6%) had a monthly income of less than 500 Ghanaian cedi (GHC), or approximately US$81, and no participants had a monthly income of more than 2,000 GHC, or approximately US$325. Most participants (88.1%) were currently married, 68.9% completed at least some level of education, and 31.1% never attended school. It was the first pregnancy for 38.4% of

Discussion

It is essential for nurses, midwives, and other health care workers to be able to properly care for women in a variety of socioeconomic and cultural contexts. Therefore, reliably translated and validated instruments are needed in different settings to ensure objective measurements of the characteristics and experiences that can be used to improve clinical care in diverse populations. Our findings show that the adapted 22-item Dagbani RHDS-NM has acceptable initial evidence of validity and

Conclusion

The Dagbani RHDS-NM may be used to measure maternal discharge readiness after childbirth with four subscales. Additional research is needed to test this instrument in larger and more diverse Ghanaian samples to better represent the Ghanaian population and further improve the scale’s psychometric properties.

Uncited reference

Weiss et al., 2006.

Conflict of Interest

The authors report no conflicts of interest or relevant financial relationships.

Funding

None.

Yenupini Joyce Adams, PhD, RNC-MNN, is a visiting assistant professor, Keough School of Global Affairs and affiliated faculty, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN.

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Yenupini Joyce Adams, PhD, RNC-MNN, is a visiting assistant professor, Keough School of Global Affairs and affiliated faculty, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN.

Elizabeth Lau, MSGH, BSN, RN, is a doctoral student, College of Science, University of Notre Dame, Notre Dame, IN.

Jessica Young, MS, is a data science consultant, Center for Social Science Research, University of Notre Dame, Notre Dame, IN.

Ethel Emefa Ehla, BA, is a project manager, Savana Signatures, Tamale, Ghana, West Africa.

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© 2022 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

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