A phubbing scale tested in Bangladesh, Iran, and Pakistan: confirmatory factor, network, and Rasch analyses.
Confirmatory factor analysis
Differential item functioning
Measurement invariance
Network analysis
Rasch model
Smartphone behaviors
Journal
BMC psychiatry
ISSN: 1471-244X
Titre abrégé: BMC Psychiatry
Pays: England
ID NLM: 100968559
Informations de publication
Date de publication:
18 10 2023
18 10 2023
Historique:
received:
02
05
2023
accepted:
04
10
2023
medline:
23
10
2023
pubmed:
19
10
2023
entrez:
18
10
2023
Statut:
epublish
Résumé
Phubbing, a phenomenon of ignoring others in face-to-face conversations due to mobile phone use, can be assessed using a Phubbing Scale (PS). Recently, the PS has been shortened into an eight-item version, the PS-8. However, psychometric properties of the PS-8 among Iranian, Bangladeshi and Pakistani individuals remain understudied, especially using advanced psychometric testing, such as Rasch and network analyses. Participants residing in Iran, Bangladesh, and Pakistan (n = 1902; 50.4% females; mean age = 26.3 years) completed the PS-8 and the Internet Disorder Scale-Short Form (IDS9-SF) via an online survey. Network analysis was used to examine if PS-8 items were differentiated from IDS9-SF items; confirmatory factor analysis (CFA) was used to examine the factor structure and measurement invariance of the PS-8; Rasch modeling was used to examine the dimensionality of the PS-8 and differential item functioning (DIF). Network analysis showed that PS-8 items were clustered together with a distance to the IDS9-SF items. The CFA results supported a two-factor structure of the PS-8, and the two-factor structure was found to be invariant across countries and women and men. Rasch model results indicated that the two PS-8 subscales were both unidimensional and did not display DIF across countries and gender/sex. The PS-8 is a feasible and robust instrument for healthcare providers, especially mental health professionals, to quickly assess and evaluate individuals' phubbing behaviors.
Sections du résumé
BACKGROUND
Phubbing, a phenomenon of ignoring others in face-to-face conversations due to mobile phone use, can be assessed using a Phubbing Scale (PS). Recently, the PS has been shortened into an eight-item version, the PS-8. However, psychometric properties of the PS-8 among Iranian, Bangladeshi and Pakistani individuals remain understudied, especially using advanced psychometric testing, such as Rasch and network analyses.
METHODS
Participants residing in Iran, Bangladesh, and Pakistan (n = 1902; 50.4% females; mean age = 26.3 years) completed the PS-8 and the Internet Disorder Scale-Short Form (IDS9-SF) via an online survey. Network analysis was used to examine if PS-8 items were differentiated from IDS9-SF items; confirmatory factor analysis (CFA) was used to examine the factor structure and measurement invariance of the PS-8; Rasch modeling was used to examine the dimensionality of the PS-8 and differential item functioning (DIF).
RESULTS
Network analysis showed that PS-8 items were clustered together with a distance to the IDS9-SF items. The CFA results supported a two-factor structure of the PS-8, and the two-factor structure was found to be invariant across countries and women and men. Rasch model results indicated that the two PS-8 subscales were both unidimensional and did not display DIF across countries and gender/sex.
CONCLUSION
The PS-8 is a feasible and robust instrument for healthcare providers, especially mental health professionals, to quickly assess and evaluate individuals' phubbing behaviors.
Identifiants
pubmed: 37853354
doi: 10.1186/s12888-023-05251-4
pii: 10.1186/s12888-023-05251-4
pmc: PMC10583412
doi:
Substances chimiques
antibiotic PS 8
82837-65-8
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
763Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
Références
Chang KC, Chang YH, Yen CF, et al. A longitudinal study of the effects of problematic smartphone use on social functioning among people with schizophrenia: Mediating roles for sleep quality and self-stigma [published online ahead of print, 2022 Apr 7]. J Behav Addict. 2022;11(2):567–576. https://doi.org/10.1556/2006.2022.00012
BankMyCell. How Many Phones Are in the World? [Internet]. 2022 [cited 2022 Jul 6]. Available from: https://www.bankmycell.com/blog/how-many-phones-are-in-the-world .
Chen CY, Chen IH, O'Brien KS, Latner JD, Lin CY. Psychological distress and internet-related behaviors between schoolchildren with and without overweight during the COVID-19 outbreak. Int J Obes (Lond). 2021;45(3):677–686. https://doi.org/10.1038/s41366-021-00741-5
doi: 10.1038/s41366-020-00696-9
pubmed: 33495523
Fung XCC, Siu A, Potenza MN, O'Brien KS, Latner JD, Chen CY, Chen IH, Lin CY. Problematic use of internet-related activities and perceived weight stigma in schoolchildren: A longitudinal study across different epidemic periods of COVID-19 in China. Front Psychiatry. 2021;12:675839. https://doi.org/10.3389/fpsyt.2021.675839 . PMID: 34211473; PMCID: PMC8240199.
doi: 10.3389/fpsyt.2021.675839
pubmed: 34108898
pmcid: 8183469
Chen CY, Chen IH, Hou WL, Potenza MN, O'Brien KS, Lin CY, Latner JD. The relationship between children’s problematic Internet-related behaviors and psychological distress during the onset of the COVID-19 pandemic: A longitudinal study. J Addict Med. 2022 May/Jun 01;16(3):e73–e80. https://doi.org/10.1097/ADM.0000000000000907 . PMID: 34138935.
Chen IH, Chen CY, Pakpour AH, Griffiths MD, Lin CY, Li XD, Tsang HWH. Problematic internet-related behaviors mediate the associations between levels of internet engagement and distress among schoolchildren during COVID-19 lockdown: A longitudinal structural equation modeling study. J Behav Addict. 2021;10(1):135–48. PMID: 32116294; PMCID: PMC7997945.
doi: 10.1556/2006.2021.00006
pubmed: 33570506
pmcid: 8969851
Chen CY, Chen IH, Pakpour AH, Lin CY, Griffiths MD. Internet-related behaviors and psychological distress among schoolchildren during the COVID-19 school hiatus. Cyberpsychol Behav Soc Netw. 2021;24(10):654–63. https://doi.org/10.1089/cyber.2020.0562 .
doi: 10.1089/cyber.2020.0562
pubmed: 33877905
Chen IH, Chen CY, Liu CH, Ahorsu DK, Griffiths MD, Chen YP, Kuo YJ, Lin CY, Pakpour AH, Wang SM. Internet addiction and psychological distress among Chinese schoolchildren before and during the COVID-19 outbreak: A latent class analysis. J Behav Addict., :Xu P, Chen JS, Chang YL, Wang X, Jiang X, Griffiths MD, Pakpour AH, Lin CY. (2022). Gender Differences in the Associations Between Physical Activity, Smartphone Use, and Weight Stigma. Frontiers in Public Health, 10, 862829. https://doi.org/10.3389/fpubh.2022.862829 .
Ahorsu DK, Adjorlolo S, Nurmala I, Ruckwongpatr K, Strong C, Lin C-Y. Problematic Porn Use and cross-cultural differences: A brief review. Curr Addict Rep. 2023;10:572–80. https://doi.org/10.1007/s40429-023-00505-3 .
doi: 10.1007/s40429-023-00505-3
Alimoradi Z, Lotfi A, Lin CY, Griffiths MD, Pakpour AH. Estimation of Behavioral Addiction Prevalence During COVID-19 Pandemic: A Systematic Review and Meta-analysis. Curr Addict Rep. 2022;9(4):486–517. https://doi.org/10.1007/s40429-022-00435-6 .
doi: 10.1007/s40429-022-00435-6
pubmed: 36118286
pmcid: 9465150
Kakul F, Javed S. Internet Gaming Disorder: An Interplay of Cognitive Psychopathology. Asian J Soc Health Behav. 2023;6:36–45. https://doi.org/10.4103/shb.shb_209_22 .
doi: 10.4103/shb.shb_209_22
Ruckwongpatr K, Chirawat P, Ghavifekr S, Gan WY, Tung SEH, Nurmala I, Nadhiroh SR, Pramukti I, Lin C-Y. Problematic Internet Use (PIU) in Youth: A Brief Literature Review of Selected Topics. Curr Opin Behav Sci. 2022;46:101150. https://doi.org/10.1016/j.cobeha.2022.101150 .
doi: 10.1016/j.cobeha.2022.101150
Ghazi FR, Gan WY, Tung SEH, et al. Problematic Gaming in Malaysian University Students: Translation and Psychometric Evaluation of the Malay Language Versions of Gaming Disorder Test and Gaming Disorder Scale for Young Adults. Eval Health Prof. 2023;1632787231185845. https://doi.org/10.1177/01632787231185845 .
Chotpitayasunondh V, Douglas KM. The effects of phubbing on social interaction. J Appl Soc Psychol. 2018;48(6):304–16. https://doi.org/10.1111/jasp.12506 .
doi: 10.1111/jasp.12506
Karadağ E, Tosuntaş ŞB, Erzen E, Duru P, Bostan N, Şahin BM, et al. Determinants of phubbing, which is the sum of many virtual addictions: a structural equation model. J Behav Addict. 2015;4(2):60–74. https://doi.org/10.1556/2006.4.2015.005 .
doi: 10.1556/2006.4.2015.005
pubmed: 26014669
pmcid: 4500886
García-Castro FJ, Abreu AM, Rando B, Blanca MJ. The Phubbing Scale (PS-8) in the Portuguese population: psychometric properties. Psicologia, reflexao e critica: revista semestral do Departamento de. Psicologia da UFRGS. 2022;35(1):7. https://doi.org/10.1186/s41155-022-00209-z .
doi: 10.1186/s41155-022-00209-z
Al-Saggaf Y, O'Donnell SB. Phubbing: perceptions, reasons behind, predictors, and impacts. Hum Behav Emerg Technol. 2019;1(2):132–40. https://doi.org/10.1002/hbe2.137 .
doi: 10.1002/hbe2.137
Błachnio A, Przepiorka A. Be aware! If you start using Facebook problematically you will feel lonely: phubbing, loneliness, self-esteem, and Facebook intrusion. A cross-sectional study. Soc Sci Comput Rev. 2019;37(2):270–8. https://doi.org/10.1177/0894439318754490 .
doi: 10.1177/0894439318754490
Blanca MJ, Bendayan R. Spanish version of the Phubbing Scale: Internet addiction, Facebook intrusion, and fear of missing out as correlates. Psicothema. 2018;30(4):449–54. https://doi.org/10.7334/psicothema2018.153 .
doi: 10.7334/psicothema2018.153
pubmed: 30353848
Davey S, Davey A, Raghav SK, Singh JV, Singh N, Błachnio A, Przepiórka A. Predictors and consequences of Phubbing among adolescents and youth in India: an impact evaluation study. J Fam Community Med. 2018;25(1):35–42. https://doi.org/10.4103/jfcm.JFCM_71_17 .
doi: 10.4103/jfcm.JFCM_71_17
Ivanova A, Gorbaniuk O, Błachnio A, Przepiórka A, Mraka N, Polishchuk V, Gorbaniuk J. Mobile phone addiction, phubbing, and depression among men and women: a moderated mediation analysis. Psychiatry Q. 2020;91(3):655–68. https://doi.org/10.1007/s11126-020-09723-8 .
doi: 10.1007/s11126-020-09723-8
Yam FC, Kumcağız H. Adaptation of general phubbing scale to Turkish culture and investigation of phubbing levels of university students in terms of various variables. Addicta: Turk J Addict. 2020;7(1):48–60. https://doi.org/10.5152/addicta.2020.19061 .
doi: 10.5152/addicta.2020.19061
Błachnio A, Przepiórka A, Gorbaniuk O, Bendayan R, McNeill M, Angeluci A, Abreu AM, Ben-Ezra M, Benvenuti M, Blanca MJ, Brkljacic T. Measurement invariance of the Phubbing Scale across 20 countries. Int J Psychol. 2021;56(6):885–94. https://doi.org/10.1002/ijop.12842 .
doi: 10.1002/ijop.12842
pubmed: 34169522
Borgatti SP, Mehra A, Brass DJ, Labianca G. Network analysis in the social sciences. Science. 2009;323:892–5. https://doi.org/10.1126/science.1165821 .
doi: 10.1126/science.1165821
pubmed: 19213908
Lecuona O, Lin CY, Rozgonjuk D, Norekvål TM, Iversen MM, Mamun MA, Griffiths MD, Lin TI, Pakpour AH. A Network Analysis of the Fear of COVID-19 Scale (FCV-19S): A Large-Scale Cross-Cultural Study in Iran, Bangladesh, and Norway. Int J Environ Res Public Health. 2022;19(11):6824. https://doi.org/10.3390/ijerph19116824 .
doi: 10.3390/ijerph19116824
pubmed: 35682405
pmcid: 9180255
Li L, Mamun MA, Al-Mamun F, Ullah I, Hosen I, Zia SA, Poorebrahim A, Pourgholami M, Lin CY, Pontes HM, Griffiths MD, Pakpour AH. A network analysis of the Internet Disorder Scale-Short Form (IDS9-SF): A large-scale cross-cultural study in Iran, Pakistan, and Bangladesh. Curr Psychol. 2022. https://doi.org/10.1007/s12144-022-03284-8 . Advance online publication.
doi: 10.1007/s12144-022-03284-8
pubmed: 36593906
pmcid: 9797384
Chang CC, Su JA, Tsai CS, Yen CF, Liu JH, Lin CY. Rasch analysis suggested three unidimensional domains for Affiliate Stigma Scale: additional psychometric evaluation. J Clin Epidemiol. 2015;68(6):674–83. https://doi.org/10.1016/j.jclinepi.2014.11.023 .
doi: 10.1016/j.jclinepi.2014.11.023
pubmed: 25748074
Chang KC, Wang JD, Tang HP, Cheng CM, Lin CY. Psychometric evaluation using Rasch analysis of the WHOQOL-BREF in heroin-dependent people undergoing methadone maintenance treatment: further item validation. Health Qual Life Outcomes. 2014;12:148. https://doi.org/10.1186/s12955-014-0148-5 .
doi: 10.1186/s12955-014-0148-5
pubmed: 25277717
pmcid: 4190329
Fan CW, Chen JS, Addo FM, Adjaottor ES, Amankwaah GB, Yen CF, Ahorsu DK, Lin CY. Examining the Validity of the Drivers of COVID-19 Vaccination Acceptance Scale using Rasch Analysis. Expert Rev Vaccines. 2022;21(2):253–60. https://doi.org/10.1080/14760584.2022.2045221 .
doi: 10.1080/14760584.2022.2045221
pubmed: 34845953
Lin CY, Griffiths MD, Pakpour AH. Psychometric evaluation of Persian Nomophobia Questionnaire (NMP-Q): Differential item functioning and measurement invariance across gender. J Behav Addict. 2018;7(1):100–8. https://doi.org/10.1556/2006.7.2018.08 .
doi: 10.1556/2006.7.2018.08
pubmed: 29444607
pmcid: 6035024
Mamun MA, Alimoradi Z, Gozal D, Manzar MD, Broström A, Lin CY, Huang RY, Pakpour AH. Validating Insomnia Severity Index (ISI) in a Bangladeshi Population: Using Classical Test Theory and Rasch Analysis. Int J Environ Res Public Health. 2021;18(19):10217. https://doi.org/10.3390/ijerph181910217 .
doi: 10.3390/ijerph181910217
Lin CY, Hwang JS, Wang WC, Lai WW, Su WC, Wu TY, Yao G, Wang JD. Psychometric evaluation of the WHOQOL-BREF, Taiwan version, across five kinds of Taiwanese cancer survivors: Rasch analysis and confirmatory factor analysis. J Formos Med Assoc. 2019;118(1 Pt 1):215–22. https://doi.org/10.1016/j.jfma.2018.07.007 .
doi: 10.1016/j.jfma.2018.07.007
pubmed: 29661488
Li L, Chen I-H, Mamun MA, Mamun FA, Ullah I, Hosen I, Malik NI, Fatima A, Poorebrahim A, Pourgholami M, Potenza MN, Lin C-Y, Pakpour AH. Nomophobia Questionnaire (NMP-Q) Across China, Bangladesh, Pakistan, and Iran: Confirmatory Factor Analysis, Measurement Invariance, and Network Analysis. Int J Ment Health Addict. 2023. https://doi.org/10.1007/s11469-023-01154-3 . advanced online publication.
doi: 10.1007/s11469-023-01154-3
pmcid: 10127977
Zamani F, Talepasand S, Taghinezhad A. Psychometric properties of the phubbing scale among Iranian students. Health Educ Health Promot. 2020;8(1):25–30. https://doi.org/10.29252/j.health.8.1.25 .
doi: 10.29252/j.health.8.1.25
Pontes HM, Griffiths MD. The development and psychometric properties of the internet disorder scale–short form (IDS9-SF). Addicta: Turk J Addict. 2016;3:303–18. https://doi.org/10.15805/addicta.2016.3.0102 .
doi: 10.15805/addicta.2016.3.0102
Hsieh MH, Chen YC, Ho CH, Lin CY. Validation of Diabetes Knowledge Questionnaire (DKQ) in the Taiwanese Population—Concurrent Validity with Diabetes-Specific Quality of Life Questionnaire Module. Diabetes Metab Syndr Obes. 2022;15:2119–26.
doi: 10.2147/DMSO.S369552
Lin CY, Tsai CS, Fan CW, Griffiths MD, Chang CC, Yen CF, Pakpour AH. Psychometric Evaluation of Three Versions of the UCLA Loneliness Scale (Full, Eight-Item, and Three-Item Versions) in Taiwanese Sexual Minority Men. Int J Environ Res Public Health. 2022;19(15):8095.
doi: 10.3390/ijerph19138095
pubmed: 35805754
pmcid: 9265606
Leme DE, Alves EV, Lemos VD, Fattori A. Network analysis: a multivariate statistical approach for health science research. Geriatr Gerontol Aging. 2020;14(1):43–51.
doi: 10.5327/Z2447-212320201900073
Gan WY, Tung SEH, Ruckwongpatr K, et al. Evaluation of two weight stigma scales in Malaysian university students: weight self-stigma questionnaire and perceived weight stigma scale [published correction appears in Eat Weight Disord. 2023 Jul 22;28(1):61]. Eat Weight Disord. 2022;27(7):2595–2604. https://doi.org/10.1007/s40519-022-01398-3
doi: 10.1007/s40519-022-01398-3
pubmed: 35474190
Hu YL, Chang CC, Lee CH, Liu CH, Chen YJ, Su JA, Lin CY, Griffiths MD. Associations between Affiliate Stigma and Quality of Life among Caregivers of Individuals with Dementia: Mediated Roles of Caregiving Burden and Psychological Distress. Asian J Soc Health Behav. 2023;6:64–71. https://doi.org/10.4103/shb.shb_67_23 .
doi: 10.4103/shb.shb_67_23
Poon LYJ, Tsang HWH, Chan TYJ, Man SWT, Ng LY, Wong YLE, Lin CY, Chien CW, Griffiths MD, Pontes HM, Pakpour AH. Psychometric properties of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF): A systematic review. J Med Internet Res. 2021;23(10):e26821.
doi: 10.2196/26821
pubmed: 34661543
pmcid: 8561410
Chen IH, Wu PL, Yen CF, Ullah I, Shoib S, Zahid SU, Bashir A, Iqbal N, Addo FM, Adjaottor ES, Amankwaah GB, Ahorsu DK, Griffiths MD, Lin CY, Pakpour AH. Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S): Evidence of measurement invariance across five countries. Risk Manag Healthc Policy. 2022;15:435–45.
doi: 10.2147/RMHP.S351794
pubmed: 35300274
pmcid: 8922466
Pramukti I, Strong C, Chen IH, Yen CF, Rifai A, Ibrahim K, Pandin MGR, Subramaniam H, Griffiths MD, Lin CY, Ko NY. The Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S): Measurement invariant evidence for its nine-item version in Taiwan, Indonesia, and Malaysia. Psychol Res Behav Manag. 2022;15:1617–25.
doi: 10.2147/PRBM.S363757
pubmed: 35791407
pmcid: 9250771
Lin CY, Luh WM, Yang AL, Su CT, Wang JD, Ma HI. Psychometric properties and gender invariance of the Chinese version of the self-report Pediatric Quality of Life Inventory Version 4.0: short form is acceptable. Qual Life Res. 2012;21:177–82.
doi: 10.1007/s11136-011-9928-1
pubmed: 21574017
Chen IH, Chang YL, Yang YN, et al. Psychometric properties and development of the Chinese versions of Gaming Disorder Test (GDT) and Gaming Disorder Scale for Adolescents (GADIS-A). Asian J Psychiatr. 2023;86:103638. https://doi.org/10.1016/j.ajp.2023.103638 .
doi: 10.1016/j.ajp.2023.103638
pubmed: 37285663
Wu TY, Huang SW, Chen JS, et al. Translation and Validation of the Gaming Disorder Test and Gaming Disorder Scale for Adolescents into Chinese for Taiwanese Young Adults. Compr Psychiatry. 2023;124:152396. https://doi.org/10.1016/j.comppsych.2023.152396 .
doi: 10.1016/j.comppsych.2023.152396
pubmed: 37295061
Fan CW, Chen JS, Addo FM, Adjaottor ES, Amankwaah GB, Yen CF, Ahorsu DK, Lin CY. Examining the Validity of the Drivers of COVID-19 Vaccination Acceptance Scale using Rasch Analysis. Expert Rev Vaccines. 2022;21(2):253–60.
doi: 10.1080/14760584.2022.2011227
pubmed: 34845953
Nadhiroh SR, Nurmala I, Pramukti I, Tivany ST, Tyas LW, Zari AP, Poon WC, Siaw YL, Kamolthip R, Chirawat P, Lin CY. Weight stigma in Indonesian young adults: Validating the indonesian versions of the weight self-stigma questionnaire and perceived weight stigma scale. Asian J Soc Health Behav. 2022;5:169–79. https://doi.org/10.4103/shb.shb_189_22 .
doi: 10.4103/shb.shb_189_22
Saffari M, Fan CW, Chang YL, et al. Yale Food Addiction Scale 2.0 (YFAS 2.0) and modified YFAS 2.0 (mYFAS 2.0): Rasch analysis and differential item functioning. J Eat Disord. 2022;10(1):185. https://doi.org/10.1186/s40337-022-00708-5 .
doi: 10.1186/s40337-022-00708-5
pubmed: 36443860
pmcid: 9703721
Chang C-C, Lin C-Y, Gronholm PC, Wu T-H. Cross-validation of two commonly used self-stigma measures, Taiwan versions of the Internalized Stigma Mental Illness scale and Self-Stigma Scale-Short, for people with mental illness. Assessment. 2018;25(6):777–92. https://doi.org/10.1177/1073191116658547 .
doi: 10.1177/1073191116658547
pubmed: 27385391