The phantom in my pocket: Determinants of phantom phone sensations

Abstract

This study investigated the prevalence and antecedents of the so-called phantom phone sensations (PPS) phenomenon – the false perception that one’s cell phone is ringing, vibrating, or blinking. While previous studies have already addressed the impact of personality traits and cell phone usage patterns on the likelihood of experiencing phantom phone sensations, we were interested in additionally addressing the impact of situational context factors. An online questionnaire assessed especially cell phone usage patterns (e.g., frequency of cell phone usage), personality traits (e.g., Big Five, need for popularity), and contextual factors (e.g., awaiting a call, being in a noisy environment). Analyses (N = 249; 137 female) revealed that the majority of participants (83.5%) have experienced phantom phone sensations. Multivariate analysis methods indicated that, in particular, contextual factors regarding the social situation (awaiting a call) along with cell phone usage patterns are predictive for the experience of phantom phone sensations. Moreover, age was also found to have a high predictive value.

Keywords

Big Five personality traits cell phone attachment cell phone usage excessive cell phone usage mobile communication need for popularity phantom phone sensations smartphone usage

Get full access to this article

View all access options for this article.

References

Agre

P. E.

(2001). Welcome to the always-on world. IEEE Spectrum,38, 10–13. doi:10.1109/6.901159

Al-Ani

G. T. S.

Mohammed

N. H.

Hassan

A. E.

(2009). Evaluation of the sensation of hearing false mobile sounds (phantom ring tone; ringxiety) in individuals. The Iraqi Postgraduate Medical Journal, 8(1), 90–94.

Alliant International University. (2007, September 17). Cell phone users experience phantom ringing; suffer from ringxiety. ScienceDaily. Retrieved from www.sciencedaily.com/releases/2007/09/070914165302.htm

Aluja

García

L. F.

(2003). Relationships among extraversion, openness to experience, and sensation seeking. Personality and Individual Differences, 35, 671–680. doi:10.1016/S0191–8869(02)00244–1

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

Amos (Version 22) [Statistic software]. Ehningen, Germany: IBM SPSS Statistics.

Arlt

(2008). “Nicht-Erreichbarkeit” in der Mobilkommunikation: Eine medienpsychologische Experimentalstudie zur SMS-Kommunikation. [Nonaccessibility in mobile communication. A media psychological study on SMS usage]. Retrieved from http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-13789/Mobilkommunikation.pdf

Beukeboom

C. J.

Hartmann

Tanis

Vermeulen

(2012, May). Phantom phone calls: An investigation into the prevalence and predictors of imagined mobile phone calls. Paper presented at the Annual Conference of the International Communication Association, Phoenix, USA.

Bianchi

Phillips

J. G.

(2005). Psychological predictors of problem mobile phone use. CyberPsychology & Behavior, 8, 39–52. doi:10.1089/cpb.2005.8.39

10.

Billieux

(2012). Problematic mobile phone use: A literature review and a pathways model. Current Psychiatry Reviews, 8, 299–307. doi:10.2174/157340012803520522

11.

Billieux

Philippot

Schmid

Maurage

De Mol

van der Linden

(2014). Is dysfunctional use of the mobile phone a behavioural addiction? Confronting symptom-based versus process-based approaches. Clinical Psychology & Psychotherapy. Retrieved from http://www.uclep.be/wp-content/uploads/pdf/Pub/Billieux_CPP_2014.pdf

12.

Bleuel

H. S.

(2007). Generation Handy. Grenzenlos im Netz verführt [Generation cell phone]. Sankt Ingbert, Germany: Röhrig Universitätsverlag.

13.

Bond

(2010). Managing mobile relationships: Children’s perception of the impact of the mobile phone on relationships in their everyday lives. Childhood, 17, 514–529. doi:10.1177/0907568210364421

14.

Bortz

Döring

(2006). Forschungsmethoden und Evaluation: für Human-und Sozial-wissenschaftler [Research methods and evaluation: For human and social scientists]. Heidelberg, Germany: Springer.

15.

Bowlby

(1977). The making and breaking of affectional bonds: Aetiology and psychopa-thology in the light of attachment theory. British Journal of Psychiatry, 130, 201–210. doi:10.1192/bjp.130.3.201

16.

Bowlby

(1982). Attachment and loss: Retrospect and prospect. American Journal of Orthopsychiatry, 52, 664–678. doi:10.1111/j.1939–0025.1982.tb01456.x

17.

Byrne

B. M.

(2013). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). London, UK: Routledge.

18.

Chittaranjan

Blom

Gatica-Perez

(2013). Mining large-scale smartphone data for personality studies. Journal Personal and Ubiquitous Computing, 17, 433–450. doi:10.1007/s00779–011–0490–1

19.

Chóliz

(2010). Mobile phone addiction: A point of issue. Addiction, 105(2), 373–374.

20.

Costa

P. T.

McCrae

R. R.

(1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five Factor Inventory. Odessa, Ukraine: Psychological Assessment Resources.

21.

Devaraja

S. R.

Easley

Crant

J. M.

(2008). How does personality matter? Relating the five factor model to technology acceptance and use. Information Systems Research, 19, 93–105. doi:10.1287/isre.1070.0153

22.

Drouin

Kaiser

D. H.

Miller

D. A.

(2012). Phantom vibration among undergraduates: Prevalence and associated psychological characteristics. Computers in Human Behavior, 28, 1490–1496. doi:10.1016/j.chb.2012.03.013

23.

Duggan

(2013). Cell phone activities 2013. Pew Internet & American Life Project. Retrieved from http://pewinternet.org/Reports/2013/Cell-Activities.aspx

24.

Duggan

Smith

(2013). Cell Internet use 2013. Pew Internet & American Life Project. Retrieved from http://pewinternet.org/Reports/2013/Cell-Internet.aspx

25.

Ehrenberg

Juckes

White

K. M.

Walsh

S. P.

(2008). Personality and self-esteem as predictors of young people’s technology use. Cyber Psychology & Behavior, 11, 739–741. doi:10.1089/cpb.2008.0030

26.

Fabrigar

L. R.

Wegener

D. T.

MacCallum

R. C.

Strahan

E. J.

(1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299. doi:10.1037/1082–989X.4.3.272

27.

Finn

(1997). Origins of media exposure: Linking personality traits to TV, radio, print, and film use. Communication Research, 24, 507–528. doi:10.1177/009365097024005003.

28.

Fleeson

(2004). Moving personality beyond the person-situation debate: The challenge and the opportunity of within-person variability. Current Directions in Psychological Science, 13, 83–87. doi:10.1111/j.0963–7214.2004.00280.x

29.

Friedman

S. A.

Hancock

(2013). Phones, friends, and flu shots: How phone attachment can affect pain perceptions (Honors thesis). Cornell University. Retrieved from http://www.commitment.cornell.edu/cprs/pdf/Friedman%20S.pdf

30.

Geser

(2006). Are girls (even) more addicted? Some gender patterns of cell phone usage. Retrieved from http://socio.ch/mobile/t_geser3.pdf

31.

Haupt

(2007, June 12). Good vibrations? Bad? None at all? USA Today. Retrieved from http://usatoday30.usatoday.com/news/health/2007-06-12-cellphones_N.htm

32.

Horn

J. L.

(1965). A rationale and a test for the number of factors in factor analysis. Psychometrika, 30, 179–185. doi:10.1007/BF02289447

33.

Hughes

D. J.

Rowe

Batey

Lee

(2012). A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage. Computers in Human Behavior, 28, 561–569. doi:10.1016/j.chb.2011.11.001

34.

IDC International Data Corporation. (2013). Worldwide mobile phone market forecast to grow 7.3% in 2013 driven by 1 billion smartphone shipments, according to IDC. Retrieved from http://www.idc.com/getdoc.jsp?containerId=prUS24302813

35.

Igarashi

Motoyoshi

Takai

Yoshida

(2008). No mobile, no life: Self-perception and text-message dependency among Japanese high school students. Computers in Human Behavior, 24, 2311–2324. doi:10.1016/j.chb.2007.12.001

36.

Irvine

(2007, July). Cell phone phantom vibration. Vibrationdata. Retrieved from http://www.vibrationdata.com/Newsletters/July2007_NL.pdf

37.

ITU World Telecommunication Indicators Database. (2013). ICT facts and figures. Retrieved from http://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2013-e.pdf

38.

Jackson

L. A.

Zhao

Qiu

Kolenic

Fitzgerald

H. E.

Harold

von Eye

(2008). Culture, gender and information technology use: A comparison of Chinese and US children. Computers in Human Behavior, 24,2817–2829. doi:10.1016/j.chb.2008.04.007

39.

Jin

Park

(2010). In-person contact begets calling and texting: Interpersonal motives for cell phone use, face-to-face interaction, and loneliness. Cyberpsychology, Behavior, and Social Networking, 13, 611–618. doi:10.1089/cyber.2009.0314

40.

Kaiser

H. F.

(1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141–151. doi:10.1177/001316446002000116

41.

Kalmus

Realo

Siibak

(2011). Motives for Internet use and their relationships with personality traits and socio-demographic factors. Trames, 15, 385–403. doi:10.3176/tr.2011.4.04

42.

Lane

Manner

(2011). The impact of personality traits on smartphone ownership and use. International Journal of Business and Social Science, 2(17), 22–28.

43.

Lane

Manner

(2012). The influence of personality traits on mobile phone application preferences. Journal of Economics & Behavioral Studies, 4(5). 252–260.

44.

Watanabe

Liu

Uji

Shono

Kitamura

(2011). Internet and mobile phone text-messaging dependency: Factor structure and correlation with dysphoric mood among Japanese adults. Computers in Human Behavior, 27, 1702–1709. doi:10.1016/j.chb.2011.02.009

45.

McCrae

R. R.

(1996). Social consequences of experiential openness. Psychological Bulletin, 120(3), 323–337.

46.

McElroy

J. C.

Hendrickson

A. R.

Townsend

A. M.

DeMarie

S. M.

(2007). Dispositional factors in Internet use: Personality versus cognitive style. MIS Quarterly, 31(4), 809–820.

47.

Miller

(2012). The smartphone psychology manifesto. Perspectives on Psychological Science, 7, 221–237. doi:10.1177/1745691612441215

48.

Muck

(2003). Der Interpersonale Circumplex als Grundlage einer Eigenschaftstheorie der Interpersonalität im beruflichen Kontext [The interpersonal circumplex as a foundation of a trait-theory of interpersonality in professional contexts] Berlin, Germany: dissertation.de.

49.

Ostendorf

Angleitner

(2004). NEO-Persönlichkeitsinventar nach Costa und McCrae: NEO-PI-R[NEO-Personality Inventory – German version of the NEO-PI_R scale from Costa and McCrae]. Göttingen, Germany: Hogrefe.

50.

Park

W. K.

(2005). Mobile phone addiction. In Rich

Pedersen

P. E.

(Eds.), Mobile communications: Re-negotiation of the social sphere (pp. 253–272). London, UK: Springer.

51.

Pawlikowski

Altstötter-Gleich

Brand

(2013). Validation and psychometric properties of a short version of Young’s Internet Addiction Test. Computers in Human Behavior, 29, 1212–1223. doi:10.1016/j.chb.2012.10.014

52.

Phillips

J. G.

Butt

Blaszczynski

(2006). Personality and self-reported use of mobile phones for games. CyberPsychology & Behavior, 9, 753–758. doi:10.1089/cpb.2006.9.753

53.

Preacher

K. J.

Hayes

A. F.

(2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879–891.

54.

Rammstedt

John

O. P.

(2007). Measuring personality in one minute or less: A 10 items short version of the Big Five Inventory in English and German. Journal of Research in Personality, 41, 203–212. doi:10.1016/j.jrp.2006.02.001

55.

Rothberg

M. B.

Arora

Hermann

Kleppel

Marie

P. S.

Visintainer

(2010). Phantom vibrations syndrome among medical staff: A cross sectional survey. British Medical Journal. Retrieved from http://www.bmj.com/content/341/bmj.c6914.long

56.

Salehan

Negahban

(2013). Social networking on smartphones: When mobile phones become addictive. Computers in Human Behavior, 29, 2632–2639. doi:10.1016/j.chb.2013.07.003

57.

Santor

D. A.

Messervey

Kusumakar

(2000). Measuring peer pressure, popularity, and conformity in adolescent boys and girls: Predicting school performance, sexual attitudes, and substance abuse. Journal of Youth and Adolescence, 29, 163–182. doi:10.1023/A:1005152515264

58.

Smith

(2012). The best (and worst) of mobile connectivity. Pew Internet & American Life Project. Retrieved from http://pewinternet.org/Reports/2012/Best-Worst-Mobile.aspx

59.

Smith

G. T.

McCarthy

D. M.

(1995). Methodological considerations in the refinement of clinical assessment instruments. Psychological Assessment, 7, 300–308. doi:10.1037/1040–3590.7.3.300

60.

SPSS (Version 19) [Statistic software].Ehningen, Germany: IBM SPSS Statistics.

61.

Subba

S. H.

Mandelia

Pathak

Reddy

Goel

Tayal

… Nagaraj

(2013). Ringxiety and the mobile phone usage pattern among the students of a medical college in South India. Journal of Clinical and Diagnostic Research, 7, 205–209. doi:10.7860/JCDR/2013/4652.2729

62.

The mobile mindset study. (2012). Lookout. Retrieved from https://www.lookout.com/static/ee_images/lookout-mobile-mindset-2012.pdf

63.

Turkle

(2012). Always-on/always-on-you: The tethered self. In Katz

(Ed.), Handbook of mobile communication and social change (pp. 123–137). Cambridge, MA: MIT Press.

64.

Urban

Mayerl

(2006). Regressionsanalyse: Theorie, Technik und Anwendung. [Regression analysis: Theory, technique and use]. Wiesbaden, Germany: VS Verlag für Sozialwissenschaften.

65.

Utz

Tanis

Vermeulen

(2012). It is all about being popular: The effects of need for popularity on social network site use. Cyberpsychology, Behavior, and Social Networking, 15, 37–42. doi:10.1089/cyber.2010.0651

66.

Vincent

(2005). Emotional attachment to mobile phones: An extraordinary relationship. In Hamill

Lasen

(Eds.), Mobile world: Past, present and future (pp. 93–104). London, UK: Springer.

67.

Vincent

(2006). Emotional attachment and mobile phones. Knowledge, Technology & Policy, 19(1), 39–44.

68.

Von Pape

Karnowski

Wirth

(2008). Die Mobile-Phone-Appropriation-Skala (MPA-Skala): Konstruktion und Evaluation [The mobile-phone-appropriation-scale: Construction and evaluation]. In Matthes

Wirth

Daschmann

Fahr

(Eds.), Die Brücke zwischen Theorie und Empirie: Operationalisierung, Messung und Validierung in der Kommunikationswissenschaft (pp. 96–127). Köln, Germany: Halem.

69.

Walsh

S. P.

White

K. M.

Young

R. M.

(2008). Over-connected? A qualitative exploration of the relationship between Australian youth and their mobile phones. Journal of Adolescence, 31, 77–92. doi:10.1016/j.adolescence.2007.04.004

70.

Witt

E. A.

Massman

A. J.

Jackson

L. A.

(2011). Trends in youth’s videogame playing, overall computer use, and communication technology use: The impact of self-esteem and the Big Five personality factors. Computers in Human Behavior, 27, 763–769. doi:0.1016/j.chb.2010.10.025

71.

Zwick

W. R.

Velicer

W. F.

(1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, 432–442. doi:10.1037/0033–2909.99.3.432