The Use of the Partner Surveillance Scale in Instagram: Psychometric Evaluation Based on the Graded Response Model
Abstract
The use of social media, especially Instagram, has become an increasingly powerful form of daily activity. This social media affects the romantic relationship of people, where people in relationships can conduct surveillance on the behaviors of their partner. This study provides an analysis of the psychometric properties of the Indonesian version of the Partner Surveillance Scale which contains 15 items and used a 4-point Likert scale format. The study recruited 214 female university students aged 17-23 years old, who used Instagram. The Graded Response Model (GRM) method was applied. As a result, the Indonesian version of the Partner Surveillance Scale was proved to have good psychometrics properties and had good fit to the GRM. All assumptions of GRM were met and the scale had high reliability. But, it should be noted that some items did not fit well with the model. The results of this study also provide an alternative to the use of Confirmatory Factor Analysis (CFA) in analyzing polytomous data with GRM. This study concluded that the psychometric properties of the Partner Surveillance Scale were good.
Keywords
DOI: 10.22146/jpsi.36860
References
Adams, R. J., Wu, M. L. & Wilson, M. (2012). The Rasch rating model and disordered threshold controversy. Educational and Psychological Measurement, 72(4), 547-573. doi: 10.1177/0013164411432166
AERA, APA, & NCME (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education) Joint Committee on Standards for Educational and Psychological Testing (1999). Standards for educational and psychological testing. Washington, DC: AERA.
Alhabash, S., & Ma, M. (2017). A tale of four platforms: Motivations and uses of Facebook, Twitter, Instagram, and Snapchat among college students? Social Media + Society, 1-13, doi: 10.1177/2056305117691544
Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43(4), 561-573. doi: 10.1007/BF02293814
Andrich, D. (2004). Controversy and the Rasch model: a characteristic of incompatible paradigm? Medical Care, 42(1), 1-16. doi: 10.1097/01.mlr.0000103528.48582.7c
Baker, F. B., & Kim, S. H. (2004). Item response theory: parameter estimation techniques (2nd ed.). Boca Raton, FL: CRC Press
Baulch, E., & Pramiyanti, A. (2018). Hijabers on Instagram: Using visual social media to construct the ideal Muslim woman. Social Media + Society, 1-15, doi: 10.1177/2056305118800308
Brown, I. (2015). Social media surveillance. In R. Mansell & P. H. Ang (Eds.), The international encyclopedia of digital communication and society, Hoboken, NJ: John Wiley & Sons, Inc.
Cai, L., Thissen, D., & du Toit, S. H. C. (2015a). IRTPRO for Windows (Version 3.0) [Computer software]. Lincolnwood, IL: Scientific Software International.
Cai, L., Thissen, D., & du Toit, S. H. C. (2015b). IRTPRO users guide. Lincolnwood, IL: Scientific Software International
Cai, L., Yang, J. S., & Hansen, M. (2011). Generalized full-information item bifactor analysis, Psychological Methods, 16(3), 221-248. doi: 10.1037/a0023350
Casaló, L. V., Flavián, C., & Ibáñez-Sánchez, S. (2017). Understanding consumer interaction on Instagram: The role of satisfaction, hedonism, and content characteristics. Cyberpsychology, Behavior, and Social Networking, 20(6), 369-375. doi: 10.1089/cyber.2016.0360
Chen, W. H., & Thissen, D. (1997). Local dependence indexes for item pairs using item response theory. Journal of Educational Behavioral Statistics, 22(3), 265–289. doi: 10.3102/10769986022003265
Crişan, D. R., Tendeiro, J. N., & Meijer, R. R. (2017). Investigating the practical consequences of model misfit in unidimensional IRT models. Applied Psychological Measurement, 41(6), 439-455. doi: 10.1177/0146621617695522
Darvell, J., Walsh S. P., & White, K. M. (2011). Facebook tells me so: Applying the theory of planned behavior to understand partner-monitoring behavior on Facebook. Cyberpsychology, Behavior and Social Networking, 14(12), 717-722. doi: 10.1089/cyber.2011.0035
de Ayala, R. J. (1994). The influence of multidimensionality on the graded response model. Applied Psychological Measurement, 18(2), 155-170. doi: 10.1177/014662169401800205
de Ayala, R. J. (2009). The theory and practice of item response theory. New York, NY: Guilford Press.
de Vries, D. A., Moller, A. M., Wieringa, M. S., Eigenraam, A. W. & Hamelink, K. (2017). Social comparison as the thief of joy: Emotional consequences of viewing strangers’ Instagram posts. Media Psychology, 22(2), 222-245. doi: 10.1080/15213269.2016.1267647
Depaoli, S., Tiemensma, J. & Felt, J. M. (2018). Assessment of health surveys: fitting a multidimensional graded response model. Psychology, Health & Medicine, 23(1), 13-31. doi: 10.1080/13548506.2018.1447136
Edelen, M. O., & Reeve, B. B. (2007). Applying item response theory (IRT) modelling to questionnaire development, evaluation, and refinement. Quality of Life Research, 16(1), 5–18. doi: 10.1007/s11136-007-9198-0
Elphinston, R. A. & Noller, P. (2011). Time to face it! Facebook intrusion and the implications for romantic jealousy and relationship satisfaction. Cyberpsychology, Behavior and Social Networking, 14(11), 631-635. doi: 10.1089/cyber.2010.0318
Embretson, S. E. & Reise, S. P. (2000). Item response theory for psychologist. Mahwah, NJ: Lawrence Erlbaum Associates
Farrugia, R. C., (2013). Facebook and relationships: A study of how social media use is affecting long-term relationships (Unpublished Master’s Thesis). Rochester, NY: Rochester Institute of Technology.
Forero, C., & Maydeu-Olivares, A. (2009). Estimation of IRT graded response models: Limited versus full information methods. Psychological Methods, 14(3), 275–299. doi: 10.1037/a0015825
Fox, J. & Tokunaga, R. S. (2015). Romantic partner monitoring after breakups: Attachment, dependence, distress, and post-dissolution online surveillance via social networking sites. Cyberpsychology, behavior, and social networking, 18(9), 491-498. doi: 10.1089/cyber.2015.0123
García-Pérez, M. A. (2017). An analysis of (dis)ordered categories, thresholds, and crossings in difference and divide-by-total IRT models for ordered responses. The Spanish Journal of Psychology, 20(10), 1-27. doi: 10.1017/sjp.2017.11
Green, B. F., Bock, R. D., Humphreys, L. G., Linn, R. L., & Reckase, M. D. (1984). Technical guidelines for assessing computerized adaptive tests. Journal of Educational Measurement, 21(4), 347-360. doi: 10.1111/j.1745-3984.1984.tb01039.x
Hambleton, R. K., & Jones, R. W. (1994) Item parameter estimation errors and their influence on test information functions. Applied Measurement in Education, 7(3), 171-186. doi: 10.1207/s15324818ame0703_1
Hubley, A. M., & Zumbo, B. D. (2013). Psychometric characteristics of assessment procedures: An overview. In K. F. Geisinger (Ed.), APA handbook of testing and assessment in psychology (pp. 319). Washington, D.C.: American Psychological Association Press.
Huggins-Manley, A. C. & Han, H. (2017). Assessing the sensitivity of weighted least squares model fit indexes to local dependence in item response theory models. Structural Equation Modeling: A Multidisciplinary Journal, 24(3), 331-340. doi: 10.1080/10705511.2016.1247355
Instagram. (2018). Instagram statistics. Retrieved from instagram.com/press (8 June 2018)
Kang, T., & Chen, T. (2008). Performance of the generalized S-X2 item fit index for polytomous IRT models. Journal of Education Measurement, 45(4), 391–406. doi: 10.1111/j.1745-3984.2008.00071.x
Linacre, J. (2010). Two perspectives on the application of Rasch models. European Journal of Physical and Rehabilitation Medicine, 46(2), 309-310.
Lup, K., Trub, L., & Rosenthal, L. (2015). Instagram #instasad? Exploring associations among Instagram use, depressive symptoms, negative social comparison, and strangers followed. Cyberpsychology, Behavior, and Social Networking, 18(5), 247–252. doi: 10.1089/cyber.2014.0560
Lyndon, A., Bonds-Raacke, J., & Cratty, A. D. (2011). College students’ Facebook stalking of ex-partners. Cyberpsychology, Behavior, and Social Networking, 14(12), 711-716. doi: 10.1089/cyber.2010.0588
Manvelyan, C. (2016). Pics or it didn’t happen: Relationship satisfaction and its effects on Instagram use. Colloquy, 12, 87-100.
Marshall, T. C. (2012). Facebook surveillance of former romantic partners: associations with post breakup recovery and personal growth. Cyberpsychology, Behavior, and Social Networking, 15(10), 521–526. doi: 10.1089/cyber.2012.0125
Marshall, T. C., Bejanyan, K., Di Castro, G. & Lee, R. A. (2013). Attachment styles as predictors of Facebook-related jealousy and surveillance in romantic relationships. Social Psychology, 20(1), 1-22. doi: 10.1111/j.1475-6811.2011.01393.x
Maydeu-Olivares, A. (2013). Why should we assess the goodness-of-fit of IRT models? Measurement: Interdisciplinary Research and Perspectives, 11(3), 127-137.
Maydeu-Olivares, A. (2015). Evaluating the fit of IRT models. In S. P. Reise & D. A. Revicki (Eds.), Handbook of item response theory modeling: Applications to typical performance assessment (pp. 111–127). New York: Routledge.
Maydeu-Olivares, A., & Joe, H. (2006). Limited information goodness-of-fit testing in multidimensional contingency tables. Psychometrika, 71(4), 713-732. doi: 10.1007/s11336-005-1295-9
McFarland, L. A. & Ployhart, R. E. (2015). Social media: A contextual framework to guide research and practice. Journal of Applied Psychology, 100(6), 1653-1677. doi: 10.1037/a0039244
Muise, A., Christofides, E., & Desmarais, S. (2014). “Creeping” or just information seeking? Gender differences in partner monitoring in response to jealousy on Facebook. Personal Relationships, 21(1), 35-50. doi: 10.1111/pere.12014
Muraki, E. (1990). Fitting a polytomous item response model to likert-type data. Applied Psychological Measurement, 14(1), 59-71. doi: 10.1177/014662169001400106
Petscher, Y., Mitchell, A. M., & Foorman, B. R. (2015). Improving the reliability of student scores from speeded assessments: an illustration of conditional item response theory using a computer-administered measure of vocabulary. Reading and Writing, 28(1), 31-56. doi: 10.1007/s11145-014-9518-z
Pew Research Center. (2018). Social media use in 2018. Washington, DC: Pew Research Center
Rainie, L., Brenner, J., & Purcell, K. (2012). Photos and videos as social currency online. Retrieved from www.pewinternet.org/2012/09/13/photos-and-videos-as-social-currencyonline/ (8 June 2018)
Reeve, B., & Fayers, P. (2005). Applying item response theory modelling for evaluating questionnaire item and scale properties. In P. M. Fayers & R. D. Hays (Eds.), Assessing quality of life in clinical trials: Methods and practice (2nd ed., pp. 55-73), Oxford, UK: Oxford University Press
Reise, S. P. (1999). Personality measurement issues viewed through the eyes of IRT. In S. E. & S. L. Hershberger (Eds.), The new rules of measurement: What every psychologist and educator should know (pp. 219– 241). Mahwah, NJ: Erlbaum.
Ridgway, J. L., & Clayton, R. B. (2016). Instagram unfiltered: Exploring associations of body image satisfaction, Instagram #Selfie posting, and negative romantic relationship outcomes. Cyberpsychology, Behavior and Social Networking, 19(1), 2-7. doi: 10.1089/cyber.2015.0433
Rodriguez, L. M., DiBello, A. M., Overup, C. S., Neighbors, C. (2015). The price of distrust: trust, anxious attachment, jealousy, and partner abuse. Partner Abuse, 6(3), 298-319. doi: 10.1891/1946-6560.6.3.298
Samejima, F. (1969). Estimation of ability using a response pattern of graded scores, Psychometrika Monograph, 17. Richmond, VA: Psychometric Corporation
Samejima, F. (1994). Estimation of reliability coefficients using the test information function and its modifications. Applied Psychological Measurement, 18(3), 229-244. doi: 10.1177/014662169401800304
Samejima, F. (2016). Graded Response model. In W. van der Linden (Ed.), Handbook of item response theory (Vol. 1, pp. 85-100), Berlin: Springer
Serafinelli, E. (2017). Analysis of photo sharing and visual social relationships: Instagram as a case study. Photographies, 10(1), 91-111. doi: 10.1080/17540763.2016.1258657
Sörbom, D. (1989). Model modification. Psychometrika, 54(3), 371-384. doi: 10.1007/BF02294623
Stover, A. M., McLeod, L. D., Langer, M. M., Chen, W-H., & Reeve, B. B. (2019). State of the psychometric methods: patient-reported outcome measure development and refinement using item response theory. Journal of Patient-Reported Outcomes, I(1), 50. doi: 10.1186/s41687-019-0130-5
Tay, L., Vermunt, J. K., & Wang, C. (2013). Assessing the Item Response Theory with covariate (IRT-C) procedure for ascertaining differential item functioning. International Journal of Testing, 13(3), 201-222. doi: 10.1080/15305058.2012.692415
The British Psychological Society. (2012). e-Professionalism: Guidance on the use of social media by clinical psychologists. Leicester, UK: The British Psychological Society
Tokunaga, R. S. (2011). Social networking site or social surveillance site? Understanding the use of interpersonal electronic surveillance in romantic relationships. Computers in Human Behavior, 27(2), 705-713. doi: 10.1016/j.chb.2010.08.014
Tokunaga, R. S. (2016). Interpersonal surveillance over social network sites: applying a theory of negative relational maintenance and the investment model. Journal of Social and Personal Relationships, 33(2), 171-190. doi: 10.1177/0265407514568749
Umar, J. (2012). Mengenal lebih dekat konsep reliabilitas skor tes. Jurnal Pengukuran Psikologi dan Pendidikan Indonesia (JP3I), 2(2), 126-140.
Umar, J. (2014). Kerancuan dalam penggunaan istilah “construct reliability”. Jurnal Pengukuran Psikologi dan Pendidikan Indonesia (JP3I), 3(4), 393-400.
Wirth, R. J., & Edwards, M. C. (2007). Item factor analysis: current approaches and future directions. Psychological Methods, 12(1), 58-79. doi: 10.1037/1082-989X.12.1.58.
Zhang, J. (2012). The impact of variability of item parameter estimators on test information function. Journal of Educational and Behavioral Statistics, 37(6), 737-757. doi: 10.3102/1076998612458321
Refbacks
- There are currently no refbacks.
Copyright (c) 2020 Jurnal Psikologi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.