Digital Jealousy Scale (DJS)

Abstract

The Digital Jealousy Scale (DJS; Gubler et al., 2023) was developed to capture romantic jealousy feelings specifically triggered by social media and online communication. The DJS is designed to be applicable across various social media platforms (e.g., Facebook, YouTube) and measures social media-induced jealousy (SoMJ) as a unidimensional construct. This construct incorporates cognitive, affective, and behavioral aspects of jealousy, consistent with the work of Muise et al. (2009) and Tandon et al. (2020). The final DJS consists of 9 items. Data for the scale’s development and validation were collected from three heterogeneous samples in Germany and the United Kingdom. Following the ITC Guidelines for Translating and Adapting Tests (International Test Commission, 2017), the items underwent translation into English and subsequent back-translation into German. Confirmatory factor analysis supported a one-factor structure, which demonstrated a very good fit to the collected data. The internal consistency, construct validity, convergent validity, discriminant validity, and measurement invariance of the DJS were all reported.

Keywords

Digital Jealousy; Romantic Jealousy; Social Media-Induced Jealousy

Authors

Gubler, Danièle Anne; Schlegel, Katja; Richter, Marina; Kapanci, Tugba; Troche, Stefan Johannes

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Purpose

The DJS is designed to measure social media-induced romantic jealousy.

Validity

Construct Validity: The model’s fit indices, with a freely estimated correlation between the two latent variables, showed a very good fit: χ2(151) = 186.146, p = .027, CFI = .998, RMSEA = .019, and SRMR = .042. A very strong positive correlation was observed between digital jealousy and romantic jealousy (r = .861). The DJS also exhibited similar associations with self-esteem, attachment styles, and the Big Five personality dimensions as the more general romantic jealousy scale, further highlighting the high overlap between the DJS and romantic jealousy.

Convergent Validity: Convergent validity between the DJS and Facebook jealousy in the English sample was assessed using Structural Equation Modeling (SEM). The model demonstrated a good fit to the data: χ2(593) = 697.298, p = .002, CFI = .997, RMSEA = .028, and SRMR = .075. The results indicated a very strong positive correlation (r = .873) between the DJS and the Facebook jealousy scale.

Reliability

Internal Consistency: The Cronbach’s alpha coefficients for the DJS were ≥.89, while the omega (ω) coefficients were ≥.90, indicating high internal consistency.

Factor Analysis

Confirmatory Factor Analysis: The final 9-item DJS was confirmed to be one-dimensional through Confirmatory Factor Analysis (CFA).

Measurement Invariance: Strict invariance was established across gender and relationship status. This finding suggests that any observed differences between men and women, as well as between singles and non-singles, are attributable to genuine differences in digital jealousy rather than variations in response behavior.

Instrument: Digital Jealousy Scale (DJS)

Test Type: Original

Format: Items are rated on a six-point Likert response scale, ranging from 1 (strongly disagree) to 6 (strongly agree).

Language Available: English; German

Population Group: Male; Female

Age Group: Adolescence (13-17 yrs); Adulthood (18 yrs & older); Young Adulthood (18-29 yrs); Thirties (30-39 yrs); Middle Age (40-64 yrs)

Population Details:

• Location: Germany; United Kingdom

• Respondents: University Students; German-Speaking Adults; English-Speaking Adults; Individuals in a Committed Romantic Relationship; Individuals Not in a Committed Romantic Relationship

Test Methodology: Test Validity; Construct Validity; Convergent Validity; Discriminant Validity; Test Reliability; Internal Consistency; Factor Analysis; Confirmatory Factor Analysis; Measurement Invariance; Structural Equation Modeling

Keywords

Digital Jealousy; Romantic Jealousy; Social Media-Induced Jealousy

Authors

Author ORCID Identifier:

• Gubler, Danièle Anne: http://orcid.org/0000-0003-4317-9939

• Schlegel, Katja: http://orcid.org/0000-0003-3768-5544

• Troche, Stefan Johannes: http://orcid.org/0000-0002-0961-1081

Affiliation:

• Gubler, Danièle Anne: University of Bern, Department of Psychology

• Schlegel, Katja: University of Bern, Department of Psychology

• Richter, Marina: University of Witten/Herdecke, Department of Psychology and Psychotherapy

• Kapanci, Tugba: University of Witten/Herdecke, Department of Psychology and Psychotherapy

• Troche, Stefan Johannes: University of Bern, Department of Psychology

Email Addresses:

• Troche, Stefan Johannes: [email protected]

Correspondence Address:
Troche, Stefan Johannes: University of Bern, Institute of Psychology, Fabrikstrasse 8, Bern, Switzerland, 3012, [email protected]

Permissions & Fee and Test Year

Permissions: Contact Corresponding Author

Fee: No

Test Year: 2023

References

Gubler, D. A., Schlegel, K., Richter, M., Kapanci, T., & Troche, S. J. (2023). The green-eyed monster in social media – Development and validation of a Digital Jealousy Scale. Psychological Test Adaptation and Development, 4(1), 13–27. https://doi.org/10.1027/2698-1866/a000033

Items of the Digital Jealousy Scale (DJS)

No data is Available