Risk and Protective Factors for Poorer Overall Health, Increased Psychological Distress, and Suicidal Ideation Due to SARS-CoV-2 outbreak in the General Japanese Population

Kanto Araki ¹, Keita Kiuchi ^2,*, Katsumasa Kishi ³

1. Center for Asian and Pacific Studies, Seikei University, Musashino, Japan

2. Research Center for Overwork-Related Disorders, National Institute of Occupational Safety and Health, Kawasaki, Japan

3. Practical Psychology Institute, LLC, Kawasaki, Japan

* Correspondence: Keita Kiuchi

Academic Editor: Gerhard Litscher

Received: December 28, 2020 | Accepted: February 28, 2021 | Published: March 12, 2021

OBM Integrative and Complementary Medicine 2021, Volume 6, Issue 1, doi:10.21926/obm.icm.2101008

Recommended citation: Araki K, Kiuchi K, Kishi K. Risk and Protective Factors for Poorer Overall Health, Increased Psychological Distress, and Suicidal Ideation Due to SARS-CoV-2 outbreak in the General Japanese Population. OBM Integrative and Complementary Medicine 2021; 6(1): 008; doi:10.21926/obm.icm.2101008.

© 2021 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

1. Introduction

As of June 1, 2020, the number of people infected with COVID-19 (SARS-CoV-2 virus) globally has surpassed 6 million [1]. In Japan, the weekly increases in the daily numbers of new cases of infection peaked at a figure of 560.1 on April 14, 2020, after which it has decreased to 73.1 on May 15. Consequently, on May 25, 2020, the Government of Japan lifted the state of emergency, and the restrictions imposed on outside visit, travel, and commercial activity were also expected to be lifted. It appears that the first wave of SARS-CoV-2 infections in Japan is currently under control. However, the prevalence of outbreak-related mental health problems in the Japanese population and whether these problems would require psychiatric treatment remain unclear. An early-stage review of the impact of COVID-19 on human mental health suggested that the outbreak may have caused a general increase in the prevalence of anxiety, depression, and stress [2]. In addition, a large-scale Chinese survey study reported psychological distress in almost 35% of the respondents and that this distress was associated with age, being female, being more educated, certain occupations, and the area of residence [3]. Other studies have reported associations among the psychological health of the general population, social support, and coping mechanisms [4,5]. Conversely, to the author’s knowledge, although personality traits are usually reported to predict the wellbeing of an individual [6], no studies assessing this association in relation to the SARS-CoV-2 outbreak are reported so far. However, in certain outbreak-related situations, such as when socializing is restricted, people who score high in extraversion are expected to experience greater psychological stress. Moreover, there are limited reports on the increase in suicidal risk, which is regarded as the worst outcome of outbreak-related mental health problems in general populations. A study conducted in Colombia reported 7.6% of the participants having high scores (>9) on the Depression Scale of the Center for Epidemiological Studies, which indicates a high suicidal risk [7].

The present study was conducted in the Japanese resident population immediately after the Government of Japan lifted the state of emergency. The study explored the effects of demographic factors, COVID-19-related factors, personality traits, coping measures, social support, and life event stressors on the overall mental health, psychological distress, and suicidal ideation in the general population of Japan. An assessment of the factors that could influence the psychosomatic responses of people from a comprehensive perspective, encompassing everything from residential situations to coping behaviors (as in the present study), may provide useful information for developing an integrative and complementary treatment approach that would consider individuals as whole beings and utilize their self-healing abilities.

2. Materials and Methods

2.1 Procedure

The present study was designed as a retrospective study for analyzing the impact of the lockdown implemented in Japan for the prevention of the spread of COVID-19 infection from April 7, 2020 to May 21, 2020. The study was conducted at the end of May, 2020 through an online survey. The data collected from the survey was used for examining the impact of the characteristics of the participants (demographic information, employment status, living environment, and COVID-19-related factors), the life event-related stressors, coping behaviors, personality traits, and social support on four outcome measures (physical fitness, mental health, psychological distress, and suicide ideation). The physical and mental states at the time of the survey were measured for the outcome measures, and reflections on the information during the lockdown were sought and collected for the explanatory variables. The present study is a hypothesis-testing study based on the hypothesis that the characteristics of the participants, the life event-related stressors, coping behaviors, personality traits, and social support could predict the mental and physical responses of the residents to the COVID-19 outbreak. Participation in the online survey was voluntary, and written informed consent was obtained from all participants. The study design was approved by the Research Ethics Review Committee of the Practical Psychology Institute, LLC (No. 2020001).

2.2 Sample Selection

The online survey was conducted from May 26, 2020 to May 27, 2020 for a sample population of Japanese residents aged 18 years or above who were members of the survey panel of the online survey service company named Crowd Works, Inc. A total of 2,594 panel members viewed the survey, among which 1,500 individuals responded, resulting in an acceptance rate of 57.8%. The possibility of a portion of respondents lacking the requisite cognitive functioning or literacy skills to complete an online survey was considered and, therefore, screening for such respondents was performed based on the exclusion criteria of evidently random and/or consistently contradictory responses. Since no responses met the exclusion criteria, the data from all responses were included in the analysis. Further information regarding the basic characteristics of the participants may be obtained by referring to a previously reported short study [8].

2.3 Survey Items

2.3.1 Participant Characteristics

In order to obtain the demographic information, the respondents were inquired regarding their age group, gender (male, female, other), the highest level of education (middle school, high school, junior college/vocational school, university, post-graduate diploma), marital status (never married, divorced or widowed, married and living with a partner, married and living separately), ethnicity (non-Chinese Asian, African/Black, mixed, Caucasian/White, Chinese, Middle Eastern/Arab, other), pre-COVID-19 employment status (student, self-employed, management, full-time employee (including agency hires with open-ended contracts), part-time employee, contract worker, housewife/househusband, on leave (educational leave, sick leave, etc.), unemployed), and health status (pregnancy, psychiatric treatment, underlying conditions).

In regard to the employment factors related to the SARS-CoV-2 outbreak, the respondents were inquired regarding their frequency of going to work during the state of emergency (almost never, half-a-week or less, more than half-a-week, every day), whether they worked remotely, the kind of work (went to their workplace every day, worked remotely during the emergency, had always worked remotely, business temporarily closed, lost job/business permanently, were already unemployed); and their household income prior to and after the state of emergency (<18600 USD, 18600 USD to 37200 USD, 37300 USD to 74500 USD, 74600 USD to 111800 USD, 111900 USD to 149000 USD, and ≥149000 USD).

The living environment-related factors inquired were the type of residence (house, apartment, student dormitory/shared housing/group facility, other), the number of rooms in residence (excluding spaces such as bathrooms, toilets, or kitchen), amenities, and surrounding environment (garden or balcony, park or botanical garden, convenience stores, supermarkets, and other food stores, restaurants, other stores to purchase the daily necessities and goods for the household), and the number of adults and children under 18, under 12, and in the pre-school age within the household.

The COVID-19-related factors inquired were the COVID-19 infection status of the participants (cured, under treatment, suspected, none), if they had come in contact with an infected person in the previous week (yes, possibly, no), the degree of voluntary isolation (did not leave the home at all, only went out when necessary such as for exercise, grocery shopping, or work, did not self-isolate although practiced social distancing (2 meters) when outside, did not self-isolate or practice social distancing).

2.3.2 Life Event-Related Stressors and Coping Measures Practiced During the State of Emergency

The respondents were asked if they had experienced any of the potential life events (E1‒E30) listed in Table 1 during the state of emergency, and, if so, to rate that experience as “not stressful/distressing”, “a little stressful/distressing”, or “extremely stressful/distressing”. In addition, the respondents were asked to select from a list (C1‒C17), which of the possible coping measures, i.e., the diversions and mental health maintenance measures listed in Table 2 (multiple responses allowed), had they practiced intentionally during the state of emergency.

Table 1 Correlations between life events and each of the variables.

Table 2 Correlations between coping measures and each of the variables.

2.3.3 Psychological Measures

The personality trait indicator was assessed using the Ten Item Personality Inventory [9], which assesses an individual’s personality based on a five-factor model named “the Big Five personality traits”. Each of the five factors, namely, extraversion (EXT), agreeableness (AGR), conscientiousness (CON), neuroticism (NEU), and openness (OPE), was measured based on two items rated on a 7-point scale, and accordingly, the scores for each of the five factors ranged from 0 to 14. The Japanese version (TIPI-J) of this tool was developed and validated by Oshio et al. [10].

The social support indicator was measured using a brief form of the Japanese version of the Multidimensional Scale Of Perceived Social Support [11], which comprised 7 items with the highest factor loadings [12] rated on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree). The total scores for the scale, therefore, ranged from 7 to 49.

The SF-8TM Health Survey was used for assessing the overall health of the participants [13]. The Japanese version of this tool was developed by Fukuhara and Suzukamo [14]. The survey comprised 8 items rated on a 5-point or 6-point scale. Two component health indicators, a physical component summary (PCS), and a mental component summary (MCS) were calculated to generate a mean score of 50 and a standard deviation of 10. Higher scores indicated better physical and mental health.

The psychological distress indicator was assessed using the K-6 Distress Scale developed by Kessler et al. [15]. This scale measures psychological distress based on the symptoms of both depression and anxiety. The Japanese version of the scale was developed by Furukawa et al. [16]. The items are rated on a 5-point scale ranging from “not at all” to “always”, generating total scores ranging from 0 to 24, with higher scores indicating greater psychological distress. The mean ±SD score for the study sample comprising a total of 85,154,382 Japanese individuals aged 15 years or above was determined to be 3.34 ±3.39 [17]. In the case of Japanese people, a score ranging between 5 and 12 is considered to indicate moderate distress, while a score of 13 or above indicates severe distress [18].

Suicidal ideation was assessed using the Suicidal Behaviors Questionnaire-Revised (SBQ-R) [19], which comprised 4 items rated on 5-point to 7-point scales unique to each item. The total scores ranged from 3 to 18. A study on the Spanish version of this questionnaire estimated a positive predictive value (PPV) of 98.3% and a negative predictive value (NPV) of 8.7% for a suicide attempt within one month for the psychiatric outpatients when a threshold score of 11 was used [20]. The scale was translated into Japanese in the present study, and its accuracy was verified through back-translation.

2.4 Statistical Analysis

IBM SPSS 26 was employed for the statistical analyses. The categorical variables were converted to binary variables for analysis, while a few continuous variables were treated as both continuous and binary when certain response levels, such as junior college graduate, university graduate, living with one other adult, living with 5 other adults, living with 3 pre-school children, self-isolation, and no preventative measures, had demonstrated the characteristics of an independent category in a previous analysis [8]. Significant associations among the variables were assessed by determining the Spearman’s rank correlation coefficient (ρ) to obtain the basic information for developing multiple regression models, such as the risk of multicollinearity and the strength of the one-to-one correlation. Next, a multiple regression was performed using the scores from the PCS, MCS, K6, and SBQ-R as the response variables, while the personality traits, social support, demographic variables, factors related to employment during the state of emergency, and COVID-19-related factors were used as explanatory variables. The significance threshold was set at p < 0.0001.

3. Results

The sample’s characteristics are listed in Table 3 and the descriptive statistics for the psychological measures are presented in Table 4. Over 60% of the participants were female, and almost all were non-Chinese Asians. There was a certain diversity in age, the highest level of education, employment status, and income level. In the K-6 Distress Scale assessment, 867 (58.1%) participants obtained scores of 5 or above, indicating moderate distress, while 208 (14%) obtained scores of 13 or above, indicating severe distress. In the suicidal ideation assessment, where a score of 11 was the threshold for predicting a suicide attempt, 409 (27.3%) participants obtained a score of 3 (no suicidal ideation), and 134 (8.9%) obtained a score of 11 or above (indicating suicidal ideation).

Table 3 Participant characteristics.

Table 4 Psychological measures - Descriptive statistics.

Table 1, Table 2 and Table 5 present the correlation matrices. Although multiple significant one-to-one correlations were observed between the variables, the sizes of these correlations varied widely. Table 6, Table 7, Table 8 and Table 9 present the results of the multiple regression analysis. E28 “insufficient exercise” was determined as the only significant predictor for PCS (β = -0.23, SE = 0.03), while neuroticism (β = -0.16, SE = 0.03), E17 “outbreak-related mental health problems” (β = -0.22, SE = 0.03), and E25 “uncertainty regarding the future” (β = -0.12, SE = 0.03) were identified as the significant predictors for MCS. The predictive factors for K6 were agreeableness (β = -0.08, SE = 0.02), neuroticism (β = 0.22, SE = 0.02), social support (β = -0.12, SE = 0.02), E17 “outbreak-related mental health problems” (β = 0.21, SE = 0.02), E25 “uncertainty regarding the future” (β = 0.14, SE = 0.02), and E26 “decline in the duration and quality of sleep” (β = 0.10, SE = 0.02), while the predictive factors for SBQ-R were neuroticism (β = 0.11, SE = 0.03), social support (β = -0.27, SE = 0.03), and having a psychiatric disorder (β = 0.18, SE = 0.03).

Table 5 Correlations between the variables (one-to-one).