Development of information overload severity scale in the situation of coronavirus disease 2019 epidemic_West China Medical Journal

Authors：

YANG Zi ¹ , CHEN Xiachan ² , KANG Yukun ¹ ,  XU Jiajun ^1,3

1. Mental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Institute of Forensic Medicine, West China School of Basic and Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
3. Mental Health Rehabilitation Center, the People’s Hospital (Traditional Chinese Medicine Hospital) of Karamay City, Karamay, Xinjiang 834000, P. R. China;

Corresponding author：

XU Jiajun, Email: xujiajun120@126.com

Keywords：

Information overload; Coronavirus disease 2019; Stress reaction

DOI：

10.7507/1002-0179.202003280

Video：

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Objective To compile the information overload severity scale in the situation of coronavirus disease 2019 epidemic, and evaluate the reliability and validity.Methods From February to March 2020, according to the procedures of literature analysis, semi-structured interview, and expert consultation, an initial scale was formed; and then the online scale was measured, and the scale items were screened based on the measured results of the scale. The reliability was evaluated by Cronbach’s α coefficient, and the validity was tested by exploratory factor analysis.Results There were 8 items in the initial scale. The scale items were screened based on the degree of dispersion, the correlation coefficient with the total score, and the factor-load-related indicators, and finally a 7-item scale was formed. The factor analysis results of the scale showed that one component could be extracted from the scale, and the reliability analysis showed that the total Cronbach’s α coefficient of the scale was 0.863.Conclusion The information overload severity scale has good reliability and validity, which can provide strong support for related research after the outbreak of coronavirus disease 2019 and other major public events.

Citation： YANG Zi, CHEN Xiachan, KANG Yukun, XU Jiajun. Development of information overload severity scale in the situation of coronavirus disease 2019 epidemic. West China Medical Journal, 2021, 36(4): 449-452. doi: 10.7507/1002-0179.202003280 Copy

1.	Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med, 2020, 382(13): 1199-1207.
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4.	Qiu J, Shen B, Zhao M, et al. A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: implications and policy recommendations. Gen Psychiatr, 2020, 33(2): e100213.
5.	Pollet TV, Roberts SG, Dunbar RI. Use of social network sites and instant messaging does not lead to increased offline social network size, or to emotionally closer relationships with offline network members. Cyberpsychol Behav Soc Netw, 2011, 14(4): 253-238.
6.	Misra S, Stokols D. Psychological and health outcomes of perceived information overload. Environm Behav, 2012, 44(6): 737-759.
7.	Swar B, Hameed T, Reychav I. Information overload, psychological ill-being, and behavioral intention to continue online healthcare information search. Comput Human Behav, 2017, 70(70): 416-425.
8.	Jiang S, Beaudoin CE. Health literacy and the internet: an exploratory study on the 2013 HINTS survey. Comput Hum Behav, 2016, 58: 240-248.
9.	Cain MS, Vul E, Clark K, et al. A Bayesian optimal foraging model of human visual search. Psychol Sci, 2012, 23(9): 1047-1054.
10.	Chen W, Lee KH. Sharing, liking, commenting, and distressed? The pathway between Facebook interaction and psychological distress. Cyberpsychol Behav Soc Netw, 2013, 16(10): 728-734.
11.	Cowan N. What are the differences between long-term, short-term, and working memory?. Prog Brain Res, 2008, 169: 323-338.
12.	Flavián C, Gurrea R, Orús C. An integrative perspective of online foraging behavior with search engines. Psychol Market, 2012, 29(11): 836-849.
13.	Franconeri SL, Alvarez GA, Cavanagh P. Flexible cognitive resources: competitive content maps for attention and memory. TrendsCogn Sci, 2013, 17(3): 134-141.
14.	Gaspelin N, Luck SJ. The role of inhibition in avoiding distraction by salient stimuli. Trends Cogn Sci, 2018, 22(1): 79-92.
15.	Golman R, Hagmann D, Loewenstein G. Information avoidance. J Econ Literat, 2017, 55(1): 96-135.
16.	Grant AM, Schwartz B. Too much of a good thing: the challenge and opportunity of the Inverted U. Perspect Psychol Sci, 2011, 6(1): 61-76.
17.	Greifeneder R, Scheibehenne B, Kleber N. Less may be more when choosing is difficult: choice complexity and too much choice. Acta Psychol (Amst), 2010, 133(1): 45-50.
18.	Leroy S, Glomb TM. Tasks interrupted: how anticipating time pressure on resumption of an interrupted task causes attention residue and low performance on interrupting tasks and how a “ready-to-resume” plan mitigates the effects. Organ Sci, 2018, 29(3): 380-397.
19.	Leroy S, Schmidt AM. The effect of regulatory focus on attention residue and performance during interruptions. Organ Behav Hum Decis Process, 2016, 137: 218-235.
20.	Li CY. Why do online consumers experience information overload? An extension of communication theory. J Inf Sci, 2017, 43(6): 835-851.

1. Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med, 2020, 382(13): 1199-1207.
2. Duan L, Zhu G. Psychological interventions for people affected by the COVID-19 epidemic. Lancet Psychiatry, 2020, 7(4): 300-302.
3. Xiang YT, Yang Y, Li W, et al. Timely mental health care for the 2019 novel coronavirus outbreak is urgently needed. Lancet Psychiatry, 2020, 7(3): 228-229.
4. Qiu J, Shen B, Zhao M, et al. A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: implications and policy recommendations. Gen Psychiatr, 2020, 33(2): e100213.
5. Pollet TV, Roberts SG, Dunbar RI. Use of social network sites and instant messaging does not lead to increased offline social network size, or to emotionally closer relationships with offline network members. Cyberpsychol Behav Soc Netw, 2011, 14(4): 253-238.
6. Misra S, Stokols D. Psychological and health outcomes of perceived information overload. Environm Behav, 2012, 44(6): 737-759.
7. Swar B, Hameed T, Reychav I. Information overload, psychological ill-being, and behavioral intention to continue online healthcare information search. Comput Human Behav, 2017, 70(70): 416-425.
8. Jiang S, Beaudoin CE. Health literacy and the internet: an exploratory study on the 2013 HINTS survey. Comput Hum Behav, 2016, 58: 240-248.
9. Cain MS, Vul E, Clark K, et al. A Bayesian optimal foraging model of human visual search. Psychol Sci, 2012, 23(9): 1047-1054.
10. Chen W, Lee KH. Sharing, liking, commenting, and distressed? The pathway between Facebook interaction and psychological distress. Cyberpsychol Behav Soc Netw, 2013, 16(10): 728-734.
11. Cowan N. What are the differences between long-term, short-term, and working memory?. Prog Brain Res, 2008, 169: 323-338.
12. Flavián C, Gurrea R, Orús C. An integrative perspective of online foraging behavior with search engines. Psychol Market, 2012, 29(11): 836-849.
13. Franconeri SL, Alvarez GA, Cavanagh P. Flexible cognitive resources: competitive content maps for attention and memory. TrendsCogn Sci, 2013, 17(3): 134-141.
14. Gaspelin N, Luck SJ. The role of inhibition in avoiding distraction by salient stimuli. Trends Cogn Sci, 2018, 22(1): 79-92.
15. Golman R, Hagmann D, Loewenstein G. Information avoidance. J Econ Literat, 2017, 55(1): 96-135.
16. Grant AM, Schwartz B. Too much of a good thing: the challenge and opportunity of the Inverted U. Perspect Psychol Sci, 2011, 6(1): 61-76.
17. Greifeneder R, Scheibehenne B, Kleber N. Less may be more when choosing is difficult: choice complexity and too much choice. Acta Psychol (Amst), 2010, 133(1): 45-50.
18. Leroy S, Glomb TM. Tasks interrupted: how anticipating time pressure on resumption of an interrupted task causes attention residue and low performance on interrupting tasks and how a “ready-to-resume” plan mitigates the effects. Organ Sci, 2018, 29(3): 380-397.
19. Leroy S, Schmidt AM. The effect of regulatory focus on attention residue and performance during interruptions. Organ Behav Hum Decis Process, 2016, 137: 218-235.
20. Li CY. Why do online consumers experience information overload? An extension of communication theory. J Inf Sci, 2017, 43(6): 835-851.

West China Medical Journal

Development of information overload severity scale in the situation of coronavirus disease 2019 epidemic

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