Turkish Adaptation of the Positive–Negative Relationship Quality (PN-RQ) Scale: A Reliability and Validity Study

Abstract

Background: The present study investigates the reliability and validity of the Positive–Negative Relationship Quality (PN-RQ) scale in Turkey. This study aims to test different factorial models including orthogonal factors model, correlated factors model, one-factor model, and bifactor model. Methods: In order to determine the validity and reliability of the scale, two studies were performed. The first was carried out with emerging adults (university students) who were in a romantic relationship (148 females, 43 males, and 2 unknown) and had the main purpose to examine the structure validity of the measurement tool in the Turkish sample with an exploratory analysis. Study 2 was performed online with 513 married adults (359 females, 149 males, and 5 unknown); confirmatory findings and criterion validity studies were added. Results: Exploratory factor analyses revealed that relationship quality had a two-factor structure and that there was also a negative relationship between the factors. Confirmatory factor analyses on the married sample showed that the bi-factor model provided evidence for the multidimensional nature of the scale. Both studies demonstrated high internal consistency. Conclusion: There is evidence for reliability and validity in the Turkish version of the PN-RQ scale to measure both positive and negative aspects of the relationship. The PN-RQ scale will be highly functional for social and clinical psychologists who work on close relationship issues in Turkey.

A Polish Adaptation and Validation of the Positive–Negative Relationship Quality (PN-RQ) Scale

“…The positive and negative sub-scales correlated positively and negatively in high degree, respectively, with the global measure of RAS relationship quality; this remains in line with the results obtained from the American (Rogge et al, 2016) and Turkish (Araz et al, 2019) samples. These and other international results suggest that although the bidimensional PN-RQ scale captures the quality of romantic relationships from a different perspective than the unidimensional scale, it measures the same culturally universal construct.…”

“…The reliability coefficients (Cronbach's α) in three studies by the authors of the PN-RQ (Rogge et al, 2016) ranged from .94 to .96 for the positive subscale, and from .84 to .95 for the negative subscale. Similar reliability coefficients were obtained by the authors of the Turkish adaptation of this tool: .93 for the positive subscale and .90 for the negative subscale (Araz et al, 2019).…”

“…The results of the confirmatory factor analysis, as was the case with the original (Rogge et al, 2016) and Turkish versions of the scale (Araz et al, 2019), showed that out of the four tested models (two correlated factors, two uncorrelated factors, one factor, bi-factor), the bi-factor model best fitted the data; this is the most multifaceted model as it simultaneously captures two correlated dimensions of relationship quality (positive and negative) and its one global dimension. The relatively strong negative correlation between the positive and negative PN-RQ subscales corresponds to the simultaneous interdependence and distinctiveness of the dimensions of relationship quality that are assumed in the bi-factor model and the neurobiological foundations of human experience (cf.…”

“…Based on the theory that partners in romantic relationships experience both positive and negative feelings towards each other which are partially independent of each other, Rogge, Fincham, Crasta and Maniaci (2016) developed the Positive-Negative Relationship Quality (PN-RQ) scale. Other researchers consider the concepts of relationship quality and relationship satisfaction to be synonymous and refer to a two-dimensional construct (Araz, Güngör, & Aşçı, 2019). The PN-RQ tool consists of two subscales with eight positive and negative relationship definitions, to which respondents respond on a 6-point scale that ranges from 0 = not at all to 5 = completely true.…”

“…We verified the tool's factor structure by testing alternative factorial models: a correlated factor model, an orthogonal (uncorrelated) factor model, a one-factor model and a bi-factor model (see Brunner et al, 2012;Dunn & McCray, 2020). Of these, like Araz et al (2019), we assumed that the bi-factor model achieves the greatest conceptual clarity. This model simultaneously groups test items into two separate but correlated factors and one global factor.…”