Predictors of Cyberchondria During the COVID-19 Pandemic: Cross-sectional Study Using Supervised Machine Learning.

[en] [en] BACKGROUND: Cyberchondria is characterized by repeated and compulsive online searches for health information, resulting in increased health anxiety and distress. It has been conceptualized as a multidimensional construct fueled by both anxiety and compulsivity-related factors and described as a "transdiagnostic compulsive behavioral syndrome," which is associated with health anxiety, problematic internet use, and obsessive-compulsive symptoms. Cyberchondria is not included in the International Classification of Diseases 11th Revision or the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and its defining features, etiological mechanisms, and assessment continue to be debated. OBJECTIVE: This study aims to investigate changes in the severity of cyberchondria during the COVID-19 pandemic and identify the predictors of cyberchondria at this time. METHODS: Data collection started on May 4, 2020, and ended on June 10, 2020, which corresponds to the first wave of the COVID-19 pandemic in Europe. At the time the study took place, French-speaking countries in Europe (France, Switzerland, Belgium, and Luxembourg) all implemented lockdown or semilockdown measures. The survey consisted of a questionnaire collecting demographic information (sex, age, education level, and country of residence) and information about socioeconomic circumstances during the first lockdown (eg, economic situation, housing, and employment status) and was followed by several instruments assessing various psychological and health-related constructs. Inclusion criteria for the study were being at least 18 years of age and having a good understanding of French. Self-report data were collected from 725 participants aged 18-77 (mean 33.29, SD 12.88) years, with females constituting the majority (416/725, 57.4%). RESULTS: The results showed that the COVID-19 pandemic affected various facets of cyberchondria: cyberchondria-related distress and compulsion increased (distress z=-3.651, P<.001; compulsion z=-5.697, P<.001), whereas the reassurance facet of cyberchondria decreased (z=-6.680, P<.001). In addition, COVID-19-related fears and health anxiety emerged as the strongest predictors of cyberchondria-related distress and interference with functioning during the pandemic. CONCLUSIONS: These findings provide evidence of the impact of the COVID-19 pandemic on cyberchondria and identify factors that should be considered in efforts to prevent and manage cyberchondria at times of public health crises. In addition, they are consistent with a theoretical model of cyberchondria during the COVID-19 pandemic proposed in 2020. These findings have implications for the conceptualization and future assessment of cyberchondria.

Precision for document type :

Review article

Disciplines :

Social & behavioral sciences, psychology: Multidisciplinary, general & others

Author, co-author :

INFANTI, Alexandre ; University of Luxembourg

Starcevic, Vladan ; Department of Psychiatry, Nepean Hospital, Penrith, Australia ; Discipline of Psychiatry, Faculty of Medicine and Health, Sydney Medical School Nepean Clinical School, University of Sydney, Sydney, Australia

Schimmenti, Adriano ; Faculty of Human and Social Sciences, Kore University of Enna, Enna, Italy

Khazaal, Yasser ; Addiction Medicine, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland ; Department of Psychiatry and Addictology, University of Montreal, Montreal, QC, Canada ; Department of Psychiatry, Lausanne University, Lausanne, Switzerland

Karila, Laurent ; Centre d'Enseignement, de Recherche et de Traitement des Addictions, Hôpital Universitaire Paul Brousse, Université Paris-Saclay, Villejuif, France

GIARDINA, Alessandro

Flayelle, Maèva ; Institute of Psychology, University of Lausanne, Lausanne, Switzerland

Hedayatzadeh Razavi, Seyedeh Boshra ; Institute of Psychology, University of Lausanne, Lausanne, Switzerland

Baggio, Stéphanie ; Division of Prison Health, Geneva University Hospitals and University of Geneva, Thônex, Switzerland ; Institute of Primary Health Care, University of Bern, Bern, Switzerland

Vögele, Claus ; Department of Behavioural and Cognitive Sciences, University of Luxembourg, Esch-sur-Alzette, Luxembourg

Billieux, Joël ; Addiction Medicine, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland ; Institute of Psychology, University of Lausanne, Lausanne, Switzerland

External co-authors :

yes

Language :

English

Title :

Predictors of Cyberchondria During the COVID-19 Pandemic: Cross-sectional Study Using Supervised Machine Learning.

Publication date :

25 April 2023

Journal title :

JMIR Formative Research

eISSN :

2561-326X

Publisher :

JMIR Publications Inc., Canada

Volume :

Pages :

e42206

Peer reviewed :

Peer Reviewed verified by ORBi

Funding text :

This work is part of the DRIVEN project funded by the Luxembourg National Research Fund under the PRIDE program (PRIDE17/12252781).

Available on ORBilu :

since 28 November 2023

Statistics

Number of views

46 (1 by Unilu)

Number of downloads

26 (0 by Unilu)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenAlex citations

WoS citations^™

Bibliography

Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 2020 Mar 14;395(10227):912-920 [FREE Full_text] [doi: 10.1016/S0140-6736(20)30460-8] [Medline: 32112714]
Holmes EA, O'Connor RC, Perry VH, Tracey I, Wessely S, Arseneault L, et al. Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry 2020 Jun 15;7(6):547-560 [FREE Full_text] [doi: 10.1016/S2215-0366(20)30168-1] [Medline: 32304649]
Pfefferbaum B, North CS. Mental health and the COVID-19 pandemic. N Engl J Med 2020 Aug 06;383(6):510-512. [doi: 10.1056/NEJMp2008017] [Medline: 32283003]
Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health 2020 Mar 06;17(5):E1729 [FREE Full_text] [doi: 10.3390/ijerph17051729] [Medline: 32155789]
Fiorillo A, Gorwood P. The consequences of the COVID-19 pandemic on mental health and implications for clinical practice. Eur Psychiatry 2020 Apr 01;63(1):e32 [FREE Full_text] [doi: 10.1192/j.eurpsy.2020.35] [Medline: 32234102]
Pierce M, Hope H, Ford T, Hatch S, Hotopf M, John A, et al. Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. Lancet Psychiatry 2020 Oct;7(10):883-892. [doi: 10.1016/s2215-0366(20)30308-4]
Taquet M, Luciano S, Geddes JR, Harrison PJ. Bidirectional associations between COVID-19 and psychiatric disorder: retrospective cohort studies of 62 354 COVID-19 cases in the USA. Lancet Psychiatry 2021 Feb 09;8(2):130-140 [FREE Full_text] [doi: 10.1016/S2215-0366(20)30462-4] [Medline: 33181098]
Albery IP, Spada MM, Nikčević AV. The COVID-19 anxiety syndrome and selective attentional bias towards COVID-19-related stimuli in UK residents during the 2020-2021 pandemic. Clin Psychol Psychother 2021 Nov;28(6):1367-1378 [FREE Full_text] [doi: 10.1002/cpp.2639] [Medline: 34169609]
Hoffart A, Johnson SU, Ebrahimi OV. The network of stress-related states and depression and anxiety symptoms during the COVID-19 lockdown. J Affect Disord 2021 Nov 01;294:671-678 [FREE Full_text] [doi: 10.1016/j.jad.2021.07.019] [Medline: 34333175]
Schimmenti A, Starcevic V, Giardina A, Khazaal Y, Billieux J. Multidimensional assessment of COVID-19-related fears (MAC-RF): a theory-based instrument for the assessment of clinically relevant fears during pandemics. Front Psychiatry 2020 Jul 31;11:748 [FREE Full_text] [doi: 10.3389/fpsyt.2020.00748] [Medline: 32848926]
Taylor S, Landry CA, Paluszek MM, Fergus TA, McKay D, Asmundson GJ. Development and initial validation of the COVID stress scales. J Anxiety Disord 2020 May;72:102232. [doi: 10.1016/j.janxdis.2020.102232]
Schimmenti A, Billieux J, Starcevic V. The four horsemen of fear: an integrated model of understanding fear experiences during the COVID-19 pandemic. Clin Neuropsychiatry 2020 Apr;17(2):41-45 [FREE Full_text] [doi: 10.36131/CN20200202] [Medline: 34908966]
Starcevic V, Schimmenti A, Billieux J. A model of multifaceted fear during the COVID-19 pandemic and balancing between overemphasising and neglecting the distinction between fear and anxiety: a reply to Heeren (2020). Clin Neuropsychiatry 2020 Aug;17(4):255-259 [FREE Full_text] [doi: 10.36131/cnfioritieditore20200407] [Medline: 34909001]
Starcevic V, Schimmenti A, Billieux J, Berle D. Cyberchondria in the time of the COVID-19 pandemic. Hum Behav Emerg Technol 2021 Jan 23;3(1):53-62 [FREE Full_text] [doi: 10.1002/hbe2.233] [Medline: 33363277]
Varma R, Das S, Singh T. Cyberchondria amidst COVID-19 pandemic: challenges and management strategies. Front Psychiatry 2021 Apr 30;12:618508 [FREE Full_text] [doi: 10.3389/fpsyt.2021.618508] [Medline: 33995143]
Starcevic V. Cyberchondria: challenges of problematic online searches for health-related information. Psychother Psychosom 2017 May 11;86(3):129-133 [FREE Full_text] [doi: 10.1159/000465525] [Medline: 28490037]
Starcevic V, Berle D, Arnáez S. Recent insights into cyberchondria. Curr Psychiatry Rep 2020 Aug 27;22(11):56 [FREE Full_text] [doi: 10.1007/s11920-020-01179-8] [Medline: 32852626]
McElroy E, Shevlin M. The development and initial validation of the cyberchondria severity scale (CSS). J Anxiety Disord 2014 Mar;28(2):259-265. [doi: 10.1016/j.janxdis.2013.12.007] [Medline: 24508033]
Vismara M, Caricasole V, Starcevic V, Cinosi E, Dell'Osso B, Martinotti G, et al. Is cyberchondria a new transdiagnostic digital compulsive syndrome? A systematic review of the evidence. Compr Psychiatry 2020 May;99:152167 [FREE Full text] [doi: 10.1016/j.comppsych.2020.152167] [Medline: 32146315]
Arsenakis S, Chatton A, Penzenstadler L, Billieux J, Berle D, Starcevic V, et al. Unveiling the relationships between cyberchondria and psychopathological symptoms. J Psychiatr Res 2021 Nov;143:254-261 [FREE Full_text] [doi: 10.1016/j.jpsychires.2021.09.014] [Medline: 34509786]
Starcevic V, Baggio S, Berle D, Khazaal Y, Viswasam K. Cyberchondria and its related constructs: a network analysis. Psychiatr Q 2019 Sep 16;90(3):491-505. [doi: 10.1007/s11126-019-09640-5] [Medline: 31098922]
Mestre-Bach G, Potenza MN. Cyberchondria: a growing concern during the COVID-19 pandemic and a possible addictive disorder? Curr Addict Rep 2023 Feb 09;10(1):77-96 [FREE Full_text] [doi: 10.1007/s40429-022-00462-3] [Medline: 36785757]
Akhtar M, Fatima T. Exploring cyberchondria and worry about health among individuals with no diagnosed medical condition. J Pak Med Assoc 2020 Jan;70(1):90-95 [FREE Full_text] [doi: 10.5455/JPMA.8682] [Medline: 31954030]
White RW, Horvitz E. Cyberchondria: studies of the escalation of medical concerns in web search. ACM Trans Inf Syst 2009 Nov 30;27(4):1-37. [doi: 10.1145/1629096.1629101]
Blackburn J, Fischerauer SF, Talaei-Khoei M, Chen NC, Oh LS, Vranceanu A. What are the implications of excessive internet searches for medical information by orthopaedic patients? Clin Orthop Relat Res 2019 Dec;477(12):2665-2673 [FREE Full_text] [doi: 10.1097/CORR.0000000000000888] [Medline: 31764332]
Wijesinghe CA, Liyanage ULNS, Kapugama KGCL, Warsapperuma WANP, Williams SS, Kuruppuarachchi KALA, et al. “Muddling by googling” – cyberchondria among outpatient attendees of two hospitals in Sri Lanka. Sri Lanka J Psychiatry 2019 Jun 18;10(1):11. [doi: 10.4038/sljpsyc.v10i1.8202]
Jungmann SM, Witthöft M. Health anxiety, cyberchondria, and coping in the current COVID-19 pandemic: which factors are related to coronavirus anxiety? J Anxiety Disord 2020 Jun;73:102239 [FREE Full_text] [doi: 10.1016/j.janxdis.2020.102239] [Medline: 32502806]
Oniszczenko W. Anxious temperament and cyberchondria as mediated by fear of COVID-19 infection: a cross-sectional study. PLoS One 2021 Aug 5;16(8):e0255750 [FREE Full_text] [doi: 10.1371/journal.pone.0255750] [Medline: 34352033]
Seyed Hashemi SG, Hosseinnezhad S, Dini S, Griffiths MD, Lin C, Pakpour AH. The mediating effect of the cyberchondria and anxiety sensitivity in the association between problematic internet use, metacognition beliefs, and fear of COVID-19 among Iranian online population. Heliyon 2020 Oct;6(10):e05135 [FREE Full_text] [doi: 10.1016/j.heliyon.2020.e05135] [Medline: 33072911]
Wu X, Nazari N, Griffiths MD. Using fear and anxiety related to COVID-19 to predict cyberchondria: cross-sectional survey study. J Med Internet Res 2021 Jun 09;23(6):e26285 [FREE Full_text] [doi: 10.2196/26285] [Medline: 34014833]
AlDameery K, Quteshat M, Al HI, Khalaf A. Cyberchondria, uncertainty, and psychological distress among Omanis during COVID-19: an online cross-sectional survey. J Hunan Univ 2021;48(11):141-146. [doi: 10.21203/rs.3.rs-84556/v1]
Bottesi G, Marino C, Vieno A, Ghisi M, Spada MM. Psychological distress in the context of the COVID-19 pandemic: the joint contribution of intolerance of uncertainty and cyberchondria. Psychol Health 2022 Nov 19;37(11):1396-1413. [doi: 10.1080/08870446.2021.1952584] [Medline: 34279150]
Laato S, Islam AN, Farooq A, Dhir A. Unusual purchasing behavior during the early stages of the COVID-19 pandemic: the stimulus-organism-response approach. J Retail Consum Serv 2020 Nov;57:102224. [doi: 10.1016/j.jretconser.2020.102224]
Bala R, Srivastava A, Ningthoujam GD, Potsangbam T, Oinam A, Anal CL. An observational study in Manipur State, India on preventive behavior influenced by social media during the COVID-19 pandemic mediated by cyberchondria and information overload. J Prev Med Public Health 2021 Jan;54(1):22-30 [FREE Full_text] [doi: 10.3961/jpmph.20.465] [Medline: 33618496]
Jokic-Begic N, Lauri Korajlija A, Mikac U. Cyberchondria in the age of COVID-19. PLoS One 2020;15(12):e0243704 [FREE Full_text] [doi: 10.1371/journal.pone.0243704] [Medline: 33332400]
Infanti A, Billieux J, Starčević V, Schimmenti A, Khazaal Y, Giardina A, et al. Cyberchondria and Covid-19 fear – an online survey in a sample of French-speaking European participants. Open Science Framework. 2021 Aug 27. URL: https://osf.io/swfmd [accessed 2023-03-27]
McElroy E, Kearney M, Touhey J, Evans J, Cooke Y, Shevlin M. The CSS-12: development and validation of a short-form version of the cyberchondria severity scale. Cyberpsychol Behav Soc Netw 2019 May;22(5):330-335. [doi: 10.1089/cyber.2018.0624] [Medline: 31013440]
Starcevic V, Berle D, Arnáez S, Vismara M, Fineberg NA. The assessment of cyberchondria: instruments for assessing problematic online health-related research. Curr Addict Rep 2020 Jun 01;7(2):149-165. [doi: 10.1007/s40429-020-00308-w]
Carleton RN, Norton MPJ, Asmundson GJ. Fearing the unknown: a short version of the Intolerance of Uncertainty Scale. J Anxiety Disord 2007 Jan;21(1):105-117. [doi: 10.1016/j.janxdis.2006.03.014] [Medline: 16647833]
Freeston MH, Rhéaume J, Letarte H, Dugas MJ, Ladouceur R. Why do people worry? Pers Individ Differ 1994 Dec;17(6):791-802. [doi: 10.1016/0191-8869(94)90048-5]
Khazaal Y, Chatton A, Rochat L, Hede V, Viswasam K, Penzenstadler L, et al. Compulsive health-related internet use and cyberchondria. Eur Addict Res 2021 Oct 29;27(1):58-66 [FREE Full_text] [doi: 10.1159/000510922] [Medline: 33120393]
Kroenke K, Spitzer RL, Williams JBW. The PHQ-15: validity of a new measure for evaluating the severity of somatic symptoms. Psychosom Med 2002;64(2):258-266. [doi: 10.1097/00006842-200203000-00008] [Medline: 11914441]
Heshmati R, Azmoodeh S, Caltabiano ML. Pathway linking different types of childhood trauma to somatic symptoms in a subclinical sample of female college students: the mediating role of experiential avoidance. J Nerv Ment Dis 2021 Apr 7;209(7):497-504. [doi: 10.1097/nmd.0000000000001323]
Toussaint A, Hüsing P, Kohlmann S, Löwe B. Detecting DSM-5 somatic symptom disorder: criterion validity of the Patient Health Questionnaire-15 (PHQ-15) and the Somatic Symptom Scale-8 (SSS-8) in combination with the Somatic Symptom Disorder – B Criteria Scale (SSD-12). Psychol Med 2019 Feb 07;50(2):324-333. [doi: 10.1017/s003329171900014x]
Abramowitz JS, Deacon BJ, Valentiner DP. The Short Health Anxiety Inventory: psychometric properties and construct validity in a non-clinical sample. Cognit Ther Res 2007 Feb 15;31(6):871-883 [FREE Full_text] [doi: 10.1007/s10608-006-9058-1] [Medline: 32214558]
Salkovskis PM, Rimes KA, Warwick HMC, Clark DM. The Health Anxiety Inventory: development and validation of scales for the measurement of health anxiety and hypochondriasis. Psychol Med 2002 Jul 15;32(5):843-853. [doi: 10.1017/s0033291702005822] [Medline: 12171378]
Bartholomew K, Horowitz LM. Attachment styles among young adults: a test of a four-category model. J Pers Soc Psychol 1991;61(2):226-244. [doi: 10.1037/0022-3514.61.2.226]
Griffin DW, Bartholomew K. Models of the self and other: fundamental dimensions underlying measures of adult attachment. J Pers Soc Psychol 1994 Sep;67(3):430-445. [doi: 10.1037/0022-3514.67.3.430]
Scharfe E, Bartholomew K. Reliability and stability of adult attachment patterns. Pers Relationsh 1994 Mar;1(1):23-43. [doi: 10.1111/j.1475-6811.1994.tb00053.x]
Costanzo A, Santoro G, Russo S, Cassarà MS, Midolo LR, Billieux J, et al. Attached to virtual dreams: the mediating role of maladaptive daydreaming in the relationship between attachment styles and problematic social media use. J Nerv Ment Dis 2021 May 4;209(9):656-664. [doi: 10.1097/nmd.0000000000001356]
Billieux J, Rochat L, Ceschi G, Carré A, Offerlin-Meyer I, Defeldre A, et al. Validation of a short French version of the UPPS-P Impulsive Behavior Scale. Compr Psychiatry 2012 Jul;53(5):609-615. [doi: 10.1016/j.comppsych.2011.09.001] [Medline: 22036009]
Cyders MA, Smith GT, Spillane NS, Fischer S, Annus AM, Peterson C. Integration of impulsivity and positive mood to predict risky behavior: development and validation of a measure of positive urgency. Psychol Assess 2007 Mar;19(1):107-118. [doi: 10.1037/1040-3590.19.1.107] [Medline: 17371126]
Whiteside SP, Lynam DR. The Five Factor Model and impulsivity: using a structural model of personality to understand impulsivity. Pers Individ Differ 2001 Mar;30(4):669-689. [doi: 10.1016/S0191-8869(00)00064-7]
Billieux J, Heeren A, Rochat L, Maurage P, Bayard S, Bet R, et al. Positive and negative urgency as a single coherent construct: evidence from a large-scale network analysis in clinical and non-clinical samples. J Pers 2021 Dec;89(6):1252-1262 [FREE Full_text] [doi: 10.1111/jopy.12655] [Medline: 34114654]
Cohen J. Statistical Power Analysis for the Behavioral Sciences. Mahwah, NJ: Lawrence Erlbaum Associates; 1988. [doi: 10.4324/9780203771587]
Maher JM, Markey JC, Ebert-May D. The other half of the story: effect size analysis in quantitative research. CBE Life Sci Educ 2013 Sep;12(3):345-351 [FREE Full_text] [doi: 10.1187/cbe.13-04-0082] [Medline: 24006382]
Murphy K. Machine Learning: A Probabilistic Perspective. Cambridge, MA: MIT Press; 2012.
Rosenbusch H, Soldner F, Evans A, Zeelenberg M. Supervised machine learning methods in psychology: a practical introduction with annotated R code. Soc Personal Psychol Compass 2021 Jan 15:e12579. [doi: 10.1111/spc3.12579]
Vabalas A, Gowen E, Poliakoff E, Casson AJ. Machine learning algorithm validation with a limited sample size. PLoS One 2019 Nov 7;14(11):e0224365 [FREE Full_text] [doi: 10.1371/journal.pone.0224365] [Medline: 31697686]
Berrar D. Cross-validation. In: Encyclopedia of Bioinformatics and Computational Biology. Amsterdam, the Netherlands: Elsevier; 2019:542-545. [doi: 10.1016/B978-0-12-809633-8.20349-X%5D%E2%80%9D]
Krstajic D, Buturovic LJ, Leahy DE, Thomas S. Cross-validation pitfalls when selecting and assessing regression and classification models. J Cheminform 2014 Mar 29;6(1):10 [FREE Full_text] [doi: 10.1186/1758-2946-6-10] [Medline: 24678909]
Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Ser B Stat Methodol 2005 Apr;67(2):301-320. [doi: 10.1111/j.1467-9868.2005.00503.x]
Yin P, Fan X. Estimating R 2 shrinkage in multiple regression: a comparison of different analytical methods. J Exp Educ 2001 Jan;69(2):203-224. [doi: 10.1080/00220970109600656]
Varoquaux G, Buitinck L, Louppe G, Grisel O, Pedregosa F, Mueller A. Scikit-learn: machine learning without learning the machinery. GetMobile Mob Comput Commun 2015 Jun;19(1):29-33. [doi: 10.1145/2786984.2786995]
Akgül G, Atalan Ergin D. Adolescents' and parents' anxiety during COVID-19: is there a role of cyberchondriasis and emotion regulation through the internet? Curr Psychol 2021 Jan 03;40(10):4750-4759 [FREE Full_text] [doi: 10.1007/s12144-020-01229-7] [Medline: 33424198]
Maftei A, Holman AC. Cyberchondria during the coronavirus pandemic: the effects of neuroticism and optimism. Front Psychol 2020 Oct 30;11:567345 [FREE Full_text] [doi: 10.3389/fpsyg.2020.567345] [Medline: 33192848]
Fergus TA, Spada MM. Moving toward a metacognitive conceptualization of cyberchondria: examining the contribution of metacognitive beliefs, beliefs about rituals, and stop signals. J Anxiety Disord 2018 Dec;60:11-19. [doi: 10.1016/j.janxdis.2018.09.003] [Medline: 30317062]
McMullan RD, Berle D, Arnáez S, Starcevic V. The relationships between health anxiety, online health information seeking, and cyberchondria: systematic review and meta-analysis. J Affect Disord 2019 Feb 15;245:270-278. [doi: 10.1016/j.jad.2018.11.037] [Medline: 30419526]
Fergus TA. Cyberchondria and intolerance of uncertainty: examining when individuals experience health anxiety in response to internet searches for medical information. Cyberpsychol Behav Soc Netw 2013 Oct;16(10):735-739. [doi: 10.1089/cyber.2012.0671] [Medline: 23992476]