Aim: This study aimed to translate the partner breastfeeding influence scale (PBIS) to the Afaan Oromo language and determine its psychometric properties.
Methods: A cross-sectional study involving 320 fathers of infants under six months old was conducted with a 4-week retest. The scale underwent translation and back-translation before its psychometric evaluation. Its content validity was determined using the Content Validity Index (CVI), while construct validity was assessed through Exploratory Factor Analysis (EFA). The scale's reliability was evaluated using Cronbach's alpha and intraclass correlation coefficient (ICC). Mean differences in father breastfeeding support by sociodemographic factors were analysed using independent t-tests and one-way ANOVA.
Results: The EFA conducted on the scale resulted in a 31-item with a five-component structure, demonstrating excellent reliability. The overall scale showed a Cronbach's alpha of 0.96, while the subscales for breastfeeding savvy, helping, appreciation, breastfeeding presence, and responsiveness recorded Cronbach's alpha values of 0.88, 0.92, 0.89, 0.89, and 0.74, respectively. The scale demonstrated high test-retest reliability (ICC = 0.96) and strong content validity (item-level CVI: 0.86-1.00; scale-level CVI: 0.98). Father's age, number of children, education, employment, and income correlated significantly with their breastfeeding support levels.
Conclusion: The study found that the Afaan Oromo version of the Partner Breastfeeding Influence Scale (PBIS-AO) is a reliable and valid tool for assessing father support for breastfeeding among Afaan Oromo-speaking fathers in Ethiopia.
Implications To Practice: The validated tool can enhance evidence-based practice by providing healthcare professionals with reliable instruments to evaluate patient outcomes, interventions, and informed decisions on breastfeeding practices.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.pedn.2025.01.005 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Measuring the role of fathers on breastfeeding success: Psychometric properties of Ethiopia's Afaan Oromo version of the partner breastfeeding influence scale.
J Pediatr Nurs
January 2025
School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China. Electronic address:
Aim: This study aimed to translate the partner breastfeeding influence scale (PBIS) to the Afaan Oromo language and determine its psychometric properties.
Methods: A cross-sectional study involving 320 fathers of infants under six months old was conducted with a 4-week retest. The scale underwent translation and back-translation before its psychometric evaluation.
A topic modeling approach for analyzing and categorizing electronic healthcare documents in Afaan Oromo without label information.
Sci Rep
December 2024
Department of CSE, Adama Science and Technology University, Oromia, Ethiopia.
Afaan Oromo is a resource-scarce language with limited tools developed for its processing, posing significant challenges for natural language tasks. The tools designed for English do not work efficiently for Afaan Oromo due to the linguistic differences and lack of well-structured resources. To address this challenge, this work proposes a topic modeling framework for unstructured health-related documents in Afaan Oromo using latent dirichlet allocation (LDA) algorithms.
View Article and Find Full Text PDFPsychometric evaluation of the Afaan Oromo version of the exclusive breastfeeding social support scale among Ethiopian women.
Midwifery
November 2024
School of Nursing, The Hong Kong Polytechnic University, Hong Kong. Electronic address:
Problem: There is a lack of validated tools for assessing social support for Exclusive Breastfeeding (EBF) practice in Ethiopia.
Background: Validating instruments ensures culturally appropriate and reliable data collection for effective research and interventions.
Aim: This study aimed to translate the exclusive breastfeeding social support scale into the Afaan Oromo language (EBFSS-AO) and test its psychometric properties among Ethiopian women.
AI-based disease category prediction model using symptoms from low-resource Ethiopian language: Afaan Oromo text.
Sci Rep
May 2024
Department of Computer Science and Engineering, Adama Science and Technology University, Adama, Ethiopia.
Automated disease diagnosis and prediction, powered by AI, play a crucial role in enabling medical professionals to deliver effective care to patients. While such predictive tools have been extensively explored in resource-rich languages like English, this manuscript focuses on predicting disease categories automatically from symptoms documented in the Afaan Oromo language, employing various classification algorithms. This study encompasses machine learning techniques such as support vector machines, random forests, logistic regression, and Naïve Bayes, as well as deep learning approaches including LSTM, GRU, and Bi-LSTM.
View Article and Find Full Text PDFBarriers to equitable healthcare services for under-five children in Ethiopia: a qualitative exploratory study.
BMC Health Serv Res
May 2024
School of Public Health, Addis Ababa University College of Health Science, Addis Ababa, Ethiopia.
Background: Disparities in child healthcare service utilization are unacceptably high in Ethiopia. Nevertheless, little is known about underlying barriers to accessing child health services, especially among low socioeconomic subgroups and in remote areas. This study aims to identify barriers to equity in the use of child healthcare services in Ethiopia.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!