Predictors Related to Quality of Life in Pregnant Women

Background

Assessment of quality of life (QoL) during pregnancy can be a starting point for streamlining and promoting the humanization of evidence-based healthcare. We aimed to determine the life quality in pregnant women and its predictors.

Methods

A cross-sectional study was conducted on pregnant women from Slovakia from March 2020 to January 2021. A method of purposive sampling was used. The research sample consisted of 393 women (age 29.11±4.65) with physiological pregnancy. Questionnaire method was used. The first part of the questionnaire consisted of a set of questions focused on identification items, which also represented the investigated predictors. The second part was the standardized questionnaire "Quality Of Life-Gravidity Questionnaire"(QOLGRAV), with Cronbach's alpha value of 0.74. The received data were analysed using descriptive and inferential statistics.

Results

The average life quality score was 18.79±5.04, which oscillates at the level of very good life quality. The lower life quality was recorded in connection with physical changes, satisfaction with social life, concerns about childbirth management failure and a need for physical activity reduction. Education (P=0.008), course of pregnancy (P=0.001), support from healthcare professionals (P=0.003) and concerns about COVID-19 (P=0.001) were the predictors of life quality.

Conclusion

The proven significant predictors of life quality of pregnant women have shown that healthcare professionals should pay increased attention to the pregnant women with higher education and with problematic pregnancy, positively support and motivate pregnant women and be even more attentivedue to the current COVID-19 pandemic.

Virtual patients: an option for future distance midwifery education?

BACKGROUND

The objective is to introduce the creating a set of virtual patients (VPs) to support distance midwifery education as well as the impact of distance education by means of VPs on knowledge, skills, motivation, clinical practice, and student satisfaction.

METHODS

VPs were created using OpenLabyrinth (OL). The impact of the distance education was assessed using a feedback questionnaire.

RESULTS

When creating our own VPs, the design and development phase can be considered the most difficult. On a scale of 1 (agree) to 4 (disagree), the student feedback rates were mostly positive (1.04-2.13). A high degree of agreement was associated with the acquisition of theoretical knowledge (1.15-1.28) and skills (1.43).

CONCLUSIONS

The creation of our own VPs is challenging for teachers due to its unconventional character. The students expressed great satisfaction with distance learning, but lacked face-to-face contact with the patient.

Creation of virtual patients for midwifery education

OBJECTIVE

The objective of the study was to create several new, original virtual patients (VPs) in the Slovak language, especially for educational purposes in midwifery.

SETTING

Virtual patients have been created for the needs of university midwifery education in Slovakia.

MODEL

The creation of the six virtual patients basically consisted of three fixed stages: preparation, design and development, implementation into the virtual environment. We used the Open Labyrinth (OL) virtual environment, an open-source system for creating VPs. The VPs include six various scenarios of the most common problems seen in midwifery practice: preterm birth, perinatal loss, gestational diabetes, ineffective breastfeeding, postpartum bleeding and sudden home birth.

FINDINGS

Currently, six original virtual patients are used in university midwifery education in Slovakia. We use them for contact teaching as well as self-study of students. They present the first VPs in Slovakia and the Czech Republic created in academic settings in these countries.

CONCLUSIONS

The future perspective of a virtual patient as an interactive process between the student and the medium is that it can deepen and improve learning outcomes, solve specific midwifery issues, and reduce mistakes in the clinical environment.