“Psychological Typhoon Eye Effect” and “Ripple Effect”: Double perspective test of risk perception and anxiety characteristics of people in different COVID-19 severity regions

doi:10.3724/SP.J.1041.2020.01087

Abstract

Abstract:

COVID-19 has greatly affected the psychological state of Chinese people. This study carried out a dynamic follow-up survey of the psychological state of Chinese people and their evaluation of Wuhan residents during the epidemic period since the day of Wuhan’s citywide lockdown. The purpose of this work was to explore differences in degree of concern, risk perception, and anxiety response among regions affected by COVID-19 to different degrees. Our findings have important practical value for future crisis emergency management.
This work included a large-scale survey covering 4833 Chinese residents, and it was conducted after Wuhan was closed. Its purpose was to assess whether COVID-19 had invoked the psychological typhoon eye effect of a disaster event. The survey involved two angles, the “actor” angle, in which participants evaluated their own psychological states, and the “bystander” angle, in which participants evaluated Wuhan citizens’ psychological states. We called these Study 1 and Study 2. Study 1 explored the psychological state of residents themselves and the results were consistent with the ripple effect to some extent within the epidemic period, which is the opposite pattern of the psychological typhoon eye. The residents who lived near the hardest-hit areas showed significantly higher risk perception and anxiety. Study 2 explored how people from different areas evaluated Wuhan residents’ psychological state. The results of Study 2 did show a replicated psychological typhoon eye effect in terms of anxiety, and the number of psychological workers and doctors residents needed. However, when it came to risk cognition, residents in low-risk areas rated Wuhan citizens’ risk cognition as significantly lower than people in high-risk areas did, which generally manifested as a ripple effect.
This study also showed a marginal zone effect and a psychological controllable threshold. The marginal zone effect means there was a phenomenon in which risk perception was lower in the middle zone or middle-risk area than at either end. The psychological controllable threshold is one of the sub-scales of risk cognition. That is, uncontrollability did not show the psychological typhoon eye effect in the bystander portion of our study.
This paper further expands and enriches the boundary conditions of the psychological typhoon eye effect of public risk events, provides more abundant and direct research evidence for the perception difference between actor and bystander angle in the study of psychological typhoon eye effect, and has important implications for a deeper understanding of the psychological evolution of public health emergencies and public crisis management.

Key words: COVID-19, Psychological Typhoon Eye Effect, Ripple Effect, risk perception, anxiety, marginal zone effect

WEN Fangfang, MA Shuhan, YE Hanxue, QI Yue, ZUO Bin. (2020). “Psychological Typhoon Eye Effect” and “Ripple Effect”: Double perspective test of risk perception and anxiety characteristics of people in different COVID-19 severity regions. Acta Psychologica Sinica, 52(9), 1087-1104.

Figures/Tables 11

References 46

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Author/year	Nature of the emergency	Specific measurement time	Measurement Index	Evaluation perspective	Psychological typhoo eye effect
Guedeney & Mandel (1973)	Neighborhood	Potential risk	Anxiety level	Actor	√
Maderthaner et al. (1978)	Neighborhood	Potential risk	Risk perception	Actor	Part √
Okeke & Armour (2000)	Neighborhood	Potential risk	Anxiety level	Actor	×
Shi et al. (2003)	SARS	During and after the disaster	Epidemic risk perception, psychological stress, epidemic development expectation, coping behavior, mental health, and economic development expectation	Bystander	√
Xie et al. (2005)	SARS	After the disaster	Levels of anxiety, and life disruption	Actor	√
Li et al. (2009a)	Earthquake	After the disaster	Recovery time and funding needed	Bystander	√
Li et al. (2009b)	Earthquake	After the disaster	The probability of post-disaster epidemic situation, the amount of first-aid measures needed in disaster areas, the number of (psychological) doctors needed per thousand residents in disaster areas, and the amount of drugs needed by residents in disaster areas	Actor (or imagining oneself as an ator)	√
Li et al. (2010)	Earthquake	After the disaster	Same as Ii et al. (2009b)	Actor (or imagining oneself as an ator)	√
Xie et al. (2011)	Earthquake	After the disaster	A willingness to buy insurance, and to vacate one’s place of residence	Actor (or imagining oneself as an ator)	√
			Risk perception of aftershocks	Actor (or imagining oneself as an ator)	√
			Anxiety level (Chinese version of state trait anxiety inventory)	Actor (or imagining oneself as an ator)	×
Xie et al. (2011)	SARS	After the disaster	Anxiety level (Chinese version of state trait anxiety inventory)	Actor	√
Zheng et al. (2015)	Adjacent shelter facilities	Potential risk	Risk perception, perceived benefits and harm	Actor	√
Xu et al. (2020)	COVID-19	In a disaster	Two psychological indicators of subjective fear (estimation of the highest price people in Wuhan are willing to pay for masks and number of days of delay in starting school in Wuhan in 2020)	Bystander	√

Author/year	Nature of the emergency	Specific measurement time	Measurement Index	Evaluation perspective	Psychological typhoo eye effect
Guedeney & Mandel (1973)	Neighborhood	Potential risk	Anxiety level	Actor	√
Maderthaner et al. (1978)	Neighborhood	Potential risk	Risk perception	Actor	Part √
Okeke & Armour (2000)	Neighborhood	Potential risk	Anxiety level	Actor	×
Shi et al. (2003)	SARS	During and after the disaster	Epidemic risk perception, psychological stress, epidemic development expectation, coping behavior, mental health, and economic development expectation	Bystander	√
Xie et al. (2005)	SARS	After the disaster	Levels of anxiety, and life disruption	Actor	√
Li et al. (2009a)	Earthquake	After the disaster	Recovery time and funding needed	Bystander	√
Li et al. (2009b)	Earthquake	After the disaster	The probability of post-disaster epidemic situation, the amount of first-aid measures needed in disaster areas, the number of (psychological) doctors needed per thousand residents in disaster areas, and the amount of drugs needed by residents in disaster areas	Actor (or imagining oneself as an ator)	√
Li et al. (2010)	Earthquake	After the disaster	Same as Ii et al. (2009b)	Actor (or imagining oneself as an ator)	√
Xie et al. (2011)	Earthquake	After the disaster	A willingness to buy insurance, and to vacate one’s place of residence	Actor (or imagining oneself as an ator)	√
			Risk perception of aftershocks	Actor (or imagining oneself as an ator)	√
			Anxiety level (Chinese version of state trait anxiety inventory)	Actor (or imagining oneself as an ator)	×
Xie et al. (2011)	SARS	After the disaster	Anxiety level (Chinese version of state trait anxiety inventory)	Actor	√
Zheng et al. (2015)	Adjacent shelter facilities	Potential risk	Risk perception, perceived benefits and harm	Actor	√
Xu et al. (2020)	COVID-19	In a disaster	Two psychological indicators of subjective fear (estimation of the highest price people in Wuhan are willing to pay for masks and number of days of delay in starting school in Wuhan in 2020)	Bystander	√

Classification of epidemic situation of different degree	Regions	N	Sex (male/female)	Age (M ± SD)
Regions with different risk levels (geographical distance from hard-hit areas)	Wuhan	468	134/334	35.74 ± 12.28
	Other parts of Hubei	867	317/550	33.13 ± 11.78
	Hubei Province bordering on the city	327	110/217	28.82 ± 10.33
	Other provinces and cities in the country	1019	278/741	31.46 ± 10.89
Areas with different risk levels (daily cumulative confirmed cases)	High risk regions	231	97/134	33.17 ± 12.14
	Medium to high risk regions	1145	372/773	34.00 ± 11.95
	Medium risk regions	251	72/179	29.68 ± 10.57
	Low risk regions	1054	298/756	31.20 ± 10.91

Classification of epidemic situation of different degree	Regions	N	Sex (male/female)	Age (M ± SD)
Regions with different risk levels (geographical distance from hard-hit areas)	Wuhan	468	134/334	35.74 ± 12.28
	Other parts of Hubei	867	317/550	33.13 ± 11.78
	Hubei Province bordering on the city	327	110/217	28.82 ± 10.33
	Other provinces and cities in the country	1019	278/741	31.46 ± 10.89
Areas with different risk levels (daily cumulative confirmed cases)	High risk regions	231	97/134	33.17 ± 12.14
	Medium to high risk regions	1145	372/773	34.00 ± 11.95
	Medium risk regions	251	72/179	29.68 ± 10.57
	Low risk regions	1054	298/756	31.20 ± 10.91

Classification of epidemic severity	Region	Risk perception	Possibility	Severity	Unpredictability	Uncontrollability	Anxiety
Regions with different risk levels (geographical distance from hard- hit areas)	Wuhan	30.20 ± 5.32	2.29 ± 1.04	12.22 ± 2.26	8.78 ± 1.58	6.91 ± 2.04	20.37 ± 5.40
	Other parts of Hubei	29.05 ± 5.76	1.91 ± 0.88	11.84 ± 2.63	8.64 ± 1.78	6.66 ± 2.24	19.27 ± 4.87
	Hubei Province bordering on the city	28.59 ± 5.35	1.99 ± 0.78	11.61 ± 2.35	8.28 ± 1.70	6.71 ± 2.03	19.30 ± 4.94
	Other provinces and cities in the country	28.79 ± 5.45	1.92 ± 0.78	11.62 ± 2.47	8.38 ± 1.74	6.86 ± 2.00	19.07 ± 5.12
Areas with different risk levels (daily cumulative confirmed cases)	High risk regions	29.73 ± 5.32	2.01 ± 0.94	11.92 ± 2.42	8.75 ± 1.56	7.04 ± 2.19	19.06 ± 5.25
	Medium to high risk regions	29.32 ± 5.67	2.03 ± 0.95	11.95 ± 2.52	8.65 ± 1.74	6.69 ± 2.15	19.72 ± 5.02
	Medium risk regions	28.28 ± 5.53	1.90 ± 0.76	11.42 ± 2.60	8.31 ± 1.80	6.64 ± 1.98	18.29 ± 4.87
	Low risk regions	28.91 ± 5.42	1.96 ± 0.79	11.70 ± 2.41	8.38 ± 1.72	6.87 ± 2.02	19.37 ± 5.14