Abstract
Background
Disrespect and abuse of laboring and child-birthing women in healthcare is a global problem that violates a woman’s right to respectful care. The abuse can be life-threatening and jeopardizes their rights to health, bodily integrity, and freedom from discrimination. This study aimed to understand the factors influencing nurse and midwife disrespect and abuse of child-birthing women in healthcare settings.
Methods
An exploratory, nonexperimental, cross-sectional design was used to identify correlates and predictors of disrespect and abuse of child-birthing women by nurses/midwives. Pearson product–moment correlation and hierarchical multiple regression analyses were used to explore the relationships between nurse intrapersonal, interpersonal (Nursing Incivility Scale), organizational/structural factors (Professional Practice Work Environment Inventory), and disrespect and abuse (Disrespect and Abuse Scale) toward women during labor and childbirth.
An online electronic survey was used to collect data from an international nursing and midwifery population from May 2021 to September 2021. Data were collected from 231 nurses and midwives.
Results
The standardized regression coefficients showed that gender, number of hours worked per week, and organizational/structural factors were all predictors of disrespect and abuse. Organizational/structural factors were the strongest predictor of disrespect and abuse, accounting for 20% of the variance in the regression model.
Discussion
These findings support the patient abuse in healthcare model, where researchers hypothesized that nurse/midwife intrapersonal, interpersonal, and organizational/structural factors contribute to patient abuse in healthcare settings. Work environment, gender, and number of hours worked per week were significant predictors of disrespect and abuse. The results of this study support future research that addresses unhealthy work environments and develops policies to transform the values and norms of labor and delivery.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Cited by
2 articles.
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