Psychometric Properties of the Turkish Version of the Developmental Support Competency Scale for Nurses (DSCS-N)

Evaluation of the psychometric properties of the Turkish version of the Skin-to-Skin Contact Scale for nurses

RATIONALE

Skin-to-skin contact is the practice with the highest level of evidence that increases the growth, development, and healing rate of the newborn. Neonatal nurses are also the best practitioners of skin-to-skin contact.

AIMS

This study examined the psychometric properties of the Turkish version of the Skin-to-Skin Contact Scale for nurses.

METHODS

This descriptive, correlational, and cross-sectional study was carried out with 226 neonatal and pediatric nurses between July 2022 and July 2023. The data were collected using an online questionnaire, including a descriptive information form and a skin-to-skin contact scale for nurses. Data were analyzed by explanatory and confirmatory factor analysis, Cronbach's alpha, and item-total score analysis.

RESULTS

It was determined that the scale consisted of 20 items and four sub-dimensions and that those four sub-dimensions explained 53.01% of the total variance. All factor loads were higher than 0.30 in the explanatory and confirmatory factor analyses. All the fit indices were higher than 0.80, and the Root Mean Square Error of Approximation (RMSEA) was less than 0.080 in the confirmatory factor analysis. Cronbach's alpha was determined to be 0.89 for the total scale and greater than 0.70 for all sub-dimensions.

CONCLUSIONS

The Skin-to-Skin Contact Scale for nurses was determined to be a valid and reliable measurement tool for Turkish nurses. It is recommended that the scale be used regularly in clinics to determine nurses' attitudes towards skin-to-skin contact.

Psychometric properties of the Turkish version of the developmental care scale for neonates with congenital heart disease

OBJECTIVE

Developmental care for newborns with congenital heart disease (CHD) improves cardiac and respiratory patterns. According to the American Heart Association, developmental care in newborns with CHD is important for improving neurodevelopmental outcomes. This study aimed to evaluate the validity and reliability of the Turkish version of the Developmental Care Scale for Neonates with Congenital Heart Disease.

METHODS

This was a methodological, descriptive study conducted with 169 nurses from a tertiary-level NICU. The Demographical Information Form and the Developmental Care Scale for Neonates with Congenital Heart Disease were used to collect the data. The scales' language and content validity, construct validity, and internal consistency were also assessed.

RESULTS

The scale consists of 31 items and four subscales. Factor loadings ranged from 0.44 to 0.82 and explained 65% of the total variance. Fit indices indicate that the model is acceptable. Cronbach's α was 0.95 for the entire instrument, 0.91 for developing the external environment subscale, 0.94 for assessing family well-being, 0.86 for the caregiver activities toward the neonate, and 0.82 for the basic need subscale. Item-total correlations ranged between 0.34 and 0.75, according to the item analysis results.

CONCLUSIONS

The Turkish version of the Developmental Care Scale for Neonates with Congenital Heart Disease is valid and reliable. The use of this scale could improve the performance of neonatal intensive care nurses in providing developmental care to newborns with CHD as well as the quality of care.

Firm-Level Analysis of Global Supply Chain Network: Role of Centrality on Firm’s Performance

Over the past few years, academics and practitioners have started paying more attention to analyze and understand value creation and business models from a business ecosystem perspective. Such business ecosystems have been constructed based on the connected networks of people, firms, industries, and countries. Developing strategies to help sustain the firms’ competitive advantage in business ecosystems is a key challenge for businesses and policymakers worldwide. Recent disruptions to global supply chains due to the COVID-19 pandemic have exposed the high risk and challenges of managing sustainable global and intertwined supply chain networks. Using the data mined from financial records, the present study constructs the global supply chain network of the auto manufacturing sector. The data from 32,396 notable first-tier forward and backward supply chain connections were mined to build the global supply chain network in this sector. The global supply chain network structure was analyzed using centrality measures and clustering analysis. We utilized path analysis to explore the effect of various supply chain centrality measures on firms' financial performance, investment risk, and market value volatility. The findings provide new insight into our understanding of the relationship between the firm's location characteristics in the global supply chain ecosystem and various aspects of the asset's performance. Furthermore, discussions are presented about strategies that support sustainable collaborative value creation and sustainable competitiveness of businesses across the global manufacturing ecosystems. The research method used in this study has the potential to be applied to several industries.