Abstract
This study aimed to evaluate the impact of COVID-19 pandemic on mental well-being observed during the first quarantine implemented in France in 2020. This online survey included 1,876 French volunteer participants who completed data on lifestyle habits during the period of confinement and self-reported levels of resilience, optimism and psychological well-being. We observed that the score of participants’ psychological well-being was considerably lower among single participants, students, the unemployed and those facing risk of financial insecurity. The results of the multivariate analysis showed that low levels of psychological well-being were significantly associated with single status and male gender. Higher scores for general peer support, optimism, resilience and confidence in information shared within immediate circles of friends of family were also significantly positively associated with better mental health. Taken together, the results from this study showed that quarantine measures impacted the psychological well-being of the participants in our sample, that the degree of impact was strongly linked with individual levels of resilience and optimism, and that general support together with confidence in one's immediate circle of friends or family also played an important role in overall mental well-being.
Keywords: Well-being, COVID-19, Quarantine, Resilience, Optimism, General population
1. Introduction
The coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China in December 2019 and spread internationally to become a major public health concern within weeks (Phelan, Katz Gostin, 2020; Zhu, Zhang Wang, 2020). Although virus mortality rates outside of China were initially quite low, suggesting that the health impact of the disease in other countries could potentially be minor, coronavirus cases grew rapidly. On March 12, 2020, the World Health Organization (WHO) declared the emergence of COVID-19 a public health emergency of international concern, the highest level of alarm under international law, and announced a global pandemic. Beginning on March 15, 2020, unprecedented measures were adopted in France to control COVID-19 virus transmission by limiting contact between individuals. To this end, a national level stay-at-home order was implemented on March 17, 2020 that lasted for a total of 55 days and was lifted on May 11, 2020. The objectives were twofold: to isolate those who tested positive for the virus by providing a context for care in a protected environment, and to reduce transmission of the virus by isolating asymptomatic carriers during the incubation period when the virus is most contagious. The novelty of this approach in a historical context since the 19th century, notably compared to periods when quarantines were implemented during massive population flows, is that it combined citywide quarantine orders aimed at curbing the spread of the virus by restricting movement with additional response strategies such as isolating contagious persons receiving care in public or private designated healthcare facilities and, importantly, enforcing strict stay-at-home orders. The combined intiative that would eventually include regional travel restrictions and international border closures has affected entire populations across numerous countries.
A literature review conducted this year showed that extended stay-at-home quarantine measures could potentially have long-term consequences on psychological health (Brooks, Webster Smith, 2020). This review involved 24 studies conducted in ten countries on the psychological effects of quarantine during previous epidemics, and showed that extended periods of quarantine can trigger multiple psychological reactions including hyper-responsiveness to stress (Yoon, Kim, Ko Lee, 2016), irritability and insomnia (Reynolds et al., 2008). Three of the included studies showed a correlation between longer duration of quarantine and poorer mental health, specifically an increase of negative emotions (such as fear and anger), misuse of psychoactive substances and post-traumatic stress symptoms (Brooks et al., 2020; Hawryluck et al., 2004).
The primay objective of this article is to study the effect of variables most significantly associated with psychological well-being as measured during the first quarantine in France implemented in the spring and early summer of 2020. Indeed, the range of psychological repercussions of home confinement appear to be conditioned by the multiple ways home confinement is experienced: voluntary or imposed, brief or prolonged duration, confinement to the home environment or elsewhere, experienced alone or in a small group or family setting, and the presence of associated stress and/or traumatic factors, etc.(Auxéméry Tarquinio, 2020). Our intial hypothesis was that home confinement, its impact on financial security and inciting feelings of insecurity, would increase levels of stress experienced by the French population, perhaps more so than fear of the virus itself. We also theorized that individuals’ optimism and resilience would correlate with levels of psychological well-being.
The Great East (Grand Est) region in France was one of the first in France to be strongly impacted by the COVID-19 pandemic. Several indicators included in the National Public Health Agency's report showed that the epidemic reached a peak in this region during the week of March 23 to 29, 2020, and had passed by April 10, 2020 (GrandEst_PER_COVID19_20200409.Pdf, n.d.). We therefore decided it was worth investigating possible differences in subjective measurements as compared to other regions of France during the same period.
2. Method
2.1. Study design and population
This cross-sectional observational study relied principally on an online questionnaire made available from April 3, 2020 to the evening of May 10, 2020 by the project leader, the Pierre Janet Center of the University of Lorraine, who posted it on their website and relayed it to social networks. All participants received detailed information describing the purpose of the study prior to completing the questionnaire. The survey was purposefully designed to be anonymous to ensure confidentiality and reliability of the data. All procedures were carried out in accordance with the French General Data Protection Regulation (GDPR).
2.2. Data collection
The questionnaire consisted of five parts:
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Part 1 : Questions about socio-demographics to collect data on respondent age, gender, marital status, with or without children, number of dependents per household, type of occupation, and occupational status during quarantine.
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Part 2: Questions concerning activities and immediate surroundings related to the quarantine environment, region of residence, potential number of occupants during quarantine, means of communication used during quarantine (telephone, social networks, phone messaging, video conferencing, etc.).
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Part 3: Questions about specific areas of concern such as virus contamination and lack of protection (masks, hydro-alcoholic gels, social distancing) for both oneself and one's immediate circle of family and/or peers (relatives, spouse, parents, children, friends, neighbors, colleagues, caregivers or support staff), occurrence of COVID-19 contamination and/or death related to COVID-19 within the immediate family or peer environment, risk of insecurity induced by the quarantine situation, perceived levels of support measured on a 10-point visual analog scale (VAS), trust in information provided by the government related to advances in research against spread of the COVID-19 virus, trust in information transmitted by social networks, by the press or circulated within the immediate circle of family and peers. A final set of questions included in this part pertain to general feelings of stress levels before and during quarantine.
Several variables in this section were aggregated to obtain the following scores:
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-An insecurity score: this score is composed of 8 items. It was obtained by summing up the scores for general stress respondents felt before the quarantine was declared (a 10-point scale ranging from 0-none to 10-extreme), the 4 scores pertaining to levels of concern about lacking adequate protection, and the 10 scores related to general levels of concern (based on the general population). This provided us with a score ranging from 0 (not at all concerned) to 150 (extremely concerned).
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-A press confidence score which is the average of the 3 confidence scores (a 10-point scale ranging from 0-none to 10-extreme) related to information made available by printed press, television and radio.
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-A confidence score related to information from family and friends which is the average of the 2 confidence scores (a 10-point scale ranging from 0-none to 10-extreme) in information from family and friends.
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-Part 4: Three self-reported questionnaires validated in French measuring respondents’ levels of optimism, well-being and resilience were administered:
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1)
The Warwick-Edinburgh Mental Well-Being Scale (WEMWBS), developed by Tennant, Hiller and Fishwick (2007) and translated by Trousselart et al. (Trousselard et al., 2016). This self-administered questionnaire, first developed in the United Kingdom for assessing a population's mental well-being, is comprised of 14 positively worded items covering hedonic and eudaimonic aspects of mental health. It uses 5 response categories for measuring the frequency of different states (0=never, 5=all the time) that are summed to provide a single score. The theoretical range of scores for WEMWBS is 14–70, with higher scores indicating a higher level of mental well-being.
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The Life Orientation Test-Revised (LOT-R), validated in French, was used to measure optimism (Trottier, Mageau, Trudel Halliwell, 2008). Optimists approach life differently than pessimists in that they have positive expectations regarding the future (Scheier Carver, 1985; Scheier, Carver Bridges, 1994). Pessimists, on the other hand, will expect negative experiences in the future. The LOT-R was developed to assess individual differences in generalized optimism versus pessimism. It consists of 6 items, each scored on a 4-point Likert scale from “strongly disagree” to “strongly agree” and four filler items. Half of the coded items are phrased in an optimistic way to focus on an individual's expectations of postive outcomes, while the other half are phrased in a pessimistic way and focus on expectations of negative outcomes. Total scores can range from 0 to 24 indicating a maximum level of optimism.
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Finally, the Brief Resilience Scale (BRS), developed by Smith et al. (2008) is a 6-item questionnaire designed to assess resilience as the self-perceived ability to bounce back or recover quickly from stress. It was translated and validated in French by Jacobs and Horsch (2019). Each item is measured on a 5-point Likert scale (1=strongly disagree, 5=strongly agree). The three negatively worded items 2, 4 and 6 were recoded such that a high score indicates a high degree of resilience. Calculating the BRS score is therefore carried out by assigning the value (from 1 to 5) to the responses for the 6 items. This sum ranging from 6 to 30 and then divided by the total number of completed items provides the final score. This score ranges from 1 to 5 and is interpreted as follows: a score of 1.00 to 2.99 indicates resilience; a score of 3.00 to 4.30 indicates normal resilience and a score of 4.31 to 5.00 indicates high resilience.
2.3. Analyses
As a first step, we conducted a descriptive analysis of the collected data using means and standard deviation for numeric variables and percentages for categorical variables. The internal consistency of the insecurity score composed of 8 aggregated items was then verified by calculating Cronbach's Alpha coefficient.
A variable corresponding to the regional deparment of residence (regions outside of the Great East Region versus those within the Great East Region) and a comparison of the collected variables was made according to this new variable.
Our main objective was to give specific focus to studying psychological well-being of our respondents during this first quarantine period in France. To do this, we compared each mental well-being score against each variable and a bivariate, and perfomed multivariate regression to explain this score. Variables with p ≤ at 0.3 in bivariate analysis were integrated in to the multivariate model following a stepwise procedure. The scores were nevertheless presented in their raw format to interpret the strength of association of scores corresponding to optimism, resilience and insecurty, confidence and overall levels of mental well-being, for which the latter we linearized from 0 to 100 exclusively for results of the bivariate and multivariate linear regressions. Variables with p0.05 were considered significantly associated with mental well-being.
Statistical analyses were perfomed using R Statistical Software.
3. Results
3.1. Sample characteristics (Table 1)
Table 1.
Sociodemographic description of the sample (n = 1876) and comparison of these data by residential region relative to the Great East Region.
| Great East Region |
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|---|---|---|---|---|
| Total Respondents (N = 1876) N (%) | No (N = 694 ; 37%) N (%) | Yes (N = 1182 ; 63%) N (%) | p-value* | |
| Gender | 0.041 | |||
| Female | 1544 (82.3) | 588 (84.7) | 956 (80.9) | |
| Male | 332 (17.7) | 106 (15.3) | 226 (19.1) | |
| Age (average years, SD) | 40.1 (13.5) | 40.2 (13.6) | 40.0 (13.4) | 0.7 |
| Marital status | 0.2 | |||
| Married | 1217 (64.9) | 432 (62.2) | 785 (66.4) | |
| Single | 644 (34.3) | 251 (36.2) | 393 (33.2) | |
| Unknown | 15 (0.8) | 11 (1.6) | 4 (0.3) | |
| With children | 0.6 | |||
| No | 847 (45.1) | 318 (45.8) | 529 (44.8) | |
| Yes | 1013 (54.0) | 366 (52.7) | 647 (54.7) | |
| Unknown | 16 (0.9) | 10 (1.4) | 6 (0.5) | |
| If yes, are children dependent | 0.31 | |||
| No | 152 (22.4) | 75 (20.5) | 152 (23.5) | |
| Yes | 495 (77.6) | 291 (79.5) | 495 (76.5) | |
| Occupational status | 0.001 | |||
| Active, Independent | 174 (9.3) | 100 (14.4) | 74 (6.3) | |
| Active, Employee | 1228 (65.5) | 415 (59.8) | 813 (68.8) | |
| Student | 223 (11.9) | 73 (10.5) | 150 (12.7) | |
| Retired | 105 (5.6) | 38 (5.5) | 67 (5.7) | |
| No activity | 146 (7.8) | 68 (9.8) | 78 (6.6) | |
| Socio-professional category | 0.001 | |||
| Craftsman/Worker | 178 (9.5) | 70 (10.1) | 108 (9.1) | |
| Management | 562 (30.0) | 202 (29.1) | 360 (30.5) | |
| Intermediate Occupation/Employee | 575 (30.7) | 173 (24.9) | 402 (34.0) | |
| Medical or paramedical profession | 261 (13.9) | 135 (19.5) | 126 (10.7) | |
| No activity | 280 (14.9) | 102 (14.7) | 178 (15.1) | |
| Unknown | 20 (1.1) | 12 (1.7) | 8 (0.7) | |
| Occupational situation during the quarantine | 0.8 | |||
| Stopped | 323 (17.2) | 120 (17.3) | 203 (17.2) | |
| Remote work | 783 (41.7) | 283 (40.8) | 500 (42.3) | |
| Partial remote work | 121 (6.4) | 50 (7.2) | 71 (6.0) | |
| Work on site | 147 (7.8) | 52 (7.5) | 95 (8.0) | |
| Not Concerned | 502 (26.8) | 189 (27.2) | 313 (26.5) | |
| Quarantine situation | 0.4 | |||
| Home confinement with others | 1166 (62.2) | 416 (59.9) | 750 (63.5) | |
| Home confinement alone | 340 (18.1) | 135 (19.5) | 205 (17.3) | |
| Unknown | 370 (19.7) | 143 (20.6) | 227 (19.2) | |
| Quarantine environment | 0.10 | |||
| Home confinement with outdoor access | 1447 (77.1) | 506 (72.9) | 941 (79.6) | |
| Home confinement without outdoor access | 277 (14.8) | 112 (16.1) | 165 (14.0) | |
| Unknown | 152 (8.1) | 76 (11.0) | 76 (6.4) | |
| COVID-19 cases in immediate circle | 0.8 | |||
| Friends/Colleagues | 692 (36.9%) | 235 (33.9%) | 457 (38.7%) | |
| Family | 311 (16.6%) | 107 (15.4%) | 204 (17.3%) | |
| Self | 95 (5.1%) | 29 (4.2%) | 66 (5.6%) | |
| Unknown | 778 (41.5%) | 323 (46.5%) | 455 (38.5%) | |
| COVID-19 related deaths in immediate circle | 0.02 | |||
| No | 1493 (79.6%) | 555 (80.0%) | 938 (79.4%) | |
| Yes | 80 (4.3%) | 19 (2.7%) | 61 (5.2%) | |
| Unknown | 303 (16.2%) | 120 (17.3%) | 183 (15.5%) | |
| Risk of financial insecurity due to quarantine | 0.001 | |||
| No | 1297 (69.1%) | 447 (64.4%) | 850 (71.9%) | |
| Yes | 295 (15.7%) | 139 (20.0%) | 156 (13.2%) | |
| Unknown | 284 (15.1%) | 108 (15.6%) | 176 (14.9%) | |
*Statistical tests performed: Wilcoxon rank-sum test; chi-square test of independence.
A total of 1876 individuals responded to our online questionnaire. These respondents were mainly women (82.3%), the average age among participants was 40 years, 64.9% of the participants were in a relationship, and 54% were parents. Concerning professional occupation, 75% reported being actively employed, 41.7% worked remotely during the quarantine period and 63% lived in the Great East region. Also included in our sample were medical and paramedical professionals (14%). Concerning the conditions of quarantine measures, 18% of the participants experienced stay-at-home orders alone in their homes and 15% had to no access to an outside environment. While participants in our sample reported few COVID-19 related deaths among immediate friends and family (4.3%), cases of the COVID-19 virus among the immediate circle was relatively high (58.5%), of which 5% of participants described impacted them personally. Finally, 16% of the participants indicated that they felt the quarantine would very likely threaten their financial security. A comparison of these characteristics related to place of residence (Non-Great East region vs. Great East region) showed several significant differences such as higher number of COVID-19 related deaths in the Great East region (2.7% vs. 5.2%, p = 0.021) and a higher proportion of participants indicating a risk of financial insecurity related to the quarantine in the Non-Great East region (p0.001), but we also noted that a higher percentage of participants in the Non-Great East region were indepentently active professionals (p0.001).
Remote means of communication during the quarantine period were also used with greater frequency (see Table 2 ). We noted that face-to-face contact with others was completely suspended for 61% of the participants. Use of remote means of communication (telephone, sms messaging, communication via social networks and video conferencing) increased significantly during the quarantine for all types of communication with the most significant evolution observed for video conferencing, for which use went from 18% daily or weekly before the quarantine to 64% during the quarantine. People with no social contact or less than one contact per week, regardless of the means of communication, represented less than 2% of our sample (n = 23), 50 participants (2.7%) had only 1 contact per week and 78% of participants reported several contacts per week or even every day.
Table 2.
Means of communication used before and during quarantine and contact frequenc.
| Means of communication: |
Before quarantine |
During quarantine |
Test * | |||
|---|---|---|---|---|---|---|
| N | % | N | % | |||
| Face-to-face contact | Every day | 433 | 27 | 270 | 17 | 0.001 |
| Several times per week | 552 | 34 | 89 | 6 | ||
| Once per week | 340 | 21 | 86 | 5 | ||
| Less than once per week | 239 | 15 | 178 | 11 | ||
| Never | 37 | 2 | 966 | 61 | ||
| Telephone contact | Every day | 338 | 21 | 459 | 29 | 0.001 |
| Several times per week | 580 | 36 | 673 | 42 | ||
| Once per week | 404 | 25 | 297 | 19 | ||
| Less than once per week | 225 | 14 | 116 | 7 | ||
| Never | 45 | 3 | 46 | 3 | ||
| SMS messaging contact | Every day | 617 | 39 | 724 | 45 | 0.001 |
| Several times per week | 642 | 40 | 573 | 36 | ||
| Once per week | 167 | 10 | 128 | 8 | ||
| Less than once per week | 114 | 7 | 96 | 6 | ||
| Never | 54 | 3 | 72 | 5 | ||
| Contact via social networks | Every day | 554 | 35 | 714 | 46 | 0.001 |
| Several times per week | 458 | 29 | 405 | 26 | ||
| Once per week | 112 | 7 | 85 | 5 | ||
| Less than once per week | 185 | 12 | 113 | 7 | ||
| Never | 278 | 18 | 249 | 16 | ||
| Contact via video conferencing | Every day | 46 | 3 | 194 | 12 | 0.001 |
| Several time per week | 103 | 7 | 450 | 29 | ||
| Once per week | 129 | 8 | 361 | 23 | ||
| Less than once per week | 386 | 25 | 243 | 15 | ||
| Never | 909 | 58 | 320 | 20 | ||
*Statistical tests performed: Wilcoxon rank-sum test; chi-square test of independence.
3.2. Description of scores (Table 3)
Table 3.
Description of scores for mental health, insecurity and confidence and comparison by region.
| Total Respondents (N = 1876) |
Great East Region |
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|---|---|---|---|---|---|---|---|
| No (N = 694 ; 37%) |
Yes (N = 1182 ; 63%) |
p-value* | |||||
| n (%) | mean (SD) | n (%) | mean (SD) | n (%) | mean (SD) | ||
| Well-being score (WBS questionnaire: from 14 to 70) | 1540 (82.1) | 49.6 (7.8) | 562 (81.0) | 48.9 (8.34) | 978 (82.7) | 50.0 (7.41) | 0.06 |
| Optimism score (LOT-R quesiontionnaire: from 0 to 24) | 1571 (83.7) | 12.8 (4.5) | 572 (82.4) | 12.8 (4.68) | 999 (84.5) | 12.8 (4.41) | 0.5 |
| Resilience score (BRS questionnaire: from 1 to 5) | 1537 (81.2) | 3.1 (0.8) | 560 (80.7) | 3.09 (0.770) | 977 (82.7) | 3.16 (0.779) | 0.1 |
| Insecurity score (score range from 0 to 150) | 1594 (85.0) | 89.7 (29.2) | 581 (83.7) | 84.4 (30.6) | 1013 (85.7) | 92.7 (28.0) | 0.001 |
| VAS of support (from 0 to 10) (average, (SD)) | 1430 (73.2) | 5.4 (2.5) | 523 (75.4) | 5.36 (2.62) | 907 (76.7) | 5.40 (2.43) | 0.9 |
| Percentage of participants with confidence (%) : | |||||||
| 1) In information given by the government: | 1590 (84.7) | 54.5% | 588 (84.7) | 52.9% | 1002 (84.8) | 55.4% | 0.3 |
| 2) In researchers’ ability to combat the virus | 1593 (84.9) | 68.3% | 587 (84.6) | 67.1% | 1006 (85.1) | 69.0% | 0.4 |
| Level of confidence in (range from 0 to 10): | |||||||
| 1) Information shared on social media | 1597 (85.1) | 2.5 (2.2) | 587 (84.6) | 2.6 (2.2) | 1010 (85.4) | 2.5 (2.1) | 0.3 |
| 2) Information shared within immediate circle (family and friends) | 1594 (85.0) | 4.5 (2.2) | 584 (84.1) | 4.4 (2.2) | 1010 (85.4) | 4.5 (2.2) | 0.6 |
| 3) Information provided by the media (print, television, radio) | 1598 (85.2) | 5.0 (2.2) | 586 (84.4) | 5.0 (2.2) | 1012 (85.6) | 5.0 (2.2) | 0.7 |
*Statistical tests performed: Wilcoxon rank-sum test; chi-square test of independence.
SD: Standard Deviation.
The raw scores for psychological well-being, optimism, resilience, insecurity, and confidence are described in Table 3 , and our comparison of the raw psychological well-being scores for categorical variables is presented in Table 4 .
Table 4.
Description and comparison of raw scores for psychological well-being according to categorical variables and analyses of variables associated with the linearized psychological well-being score perceived during quarantine in bivariate and multivariate analysis (Linear regression).
| N | Raw Score Psychological Well-being | p | Bivariate analysis* |
Multivariate analysis** |
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|---|---|---|---|---|---|---|---|---|---|
| Mean (SD) | OR | 95% CI | p | OR | 95% CI | p | |||
| Gender | 0.3 | 0.3 | 0.02 | ||||||
| Female | 1276 | 49.7 (7.4) | Ref. | Ref. | |||||
| Male | 264 | 49.1 (9.5) | −1.0 | −2.8; 0.9 | −2.2 | −4.1; −0.3 | |||
| Age | 1540 | 0.14 | 0.09; 0.2 | 0.001 | |||||
| Marital status | 0.001 | 0.001 | 0.04 | ||||||
| Married | 997 | 50.4 (7.2) | Ref. | Ref. | |||||
| Single | 531 | 48.2 (8.6) | −3.9 | −5.3; −2.4 | −1.6 | −3.2; −0.1 | |||
| With children | 0.001 | 0.001 | |||||||
| No | 695 | 48.4 (8.1) | Ref. | ||||||
| Yes | 834 | 50.6 (7.3) | 3.9 | 2.5; 5.2 | |||||
| If yes, are children dependent | 0.8 | ||||||||
| Non | 189 | 50.7 (6.9) | |||||||
| Oui | 645 | 50.5 (7.4) | |||||||
| Medical healthcare professional | 0.02 | 0.02 | |||||||
| No | 1318 | 49.5 (7.8) | Ref. | ||||||
| Yes | 209 | 50.8 (6.6) | 2.4 | 0.4; 4.4 | |||||
| Occupational status | 0.001 | ||||||||
| Active, Employee | 1021 | 50.2 (7.2) | Ref. | ||||||
| Active, Independant | 139 | 51.8 (7) | 2.9 | 0.5; 5.3 | 0.02 | ||||
| Student | 183 | 46.3 (9.1) | −6.9 | −9.0; −4.7 | 0.001 | ||||
| Retired | 81 | 50.6 (6.5) | 0.86 | −2.2; 3.9 | 0.6 | ||||
| No activity | 116 | 46.4 (9.2) | −6.8 | −9.4;−4.2 | 0.001 | ||||
| Occupational situation during the quarantine | 0.001 | ||||||||
| Remote work | 653 | 50.5 (7.1) | Ref. | ||||||
| Stopped | 269 | 49.7 (7.8) | −1.5 | −3.3; 0.4 | 0.1 | ||||
| Partial remote work | 100 | 52 (7.3) | 2.7 | −0.03; 5.4 | 0.05 | ||||
| Work on site | 113 | 49.7 (6.8) | −1.5 | −4.1; 1.0 | 0.2 | ||||
| Great East Region | 0.01 | 0.01 | 0.05 | ||||||
| No | 564 | 48.9 (8.3) | Ref. | Ref. | |||||
| Yes | 976 | 50 (7.4) | 1.8 | 0.38; 3.3 | 1.5 | 0; 3.0 | |||
| Quarantine situation | 0.001 | 0.001 | |||||||
| Home confinement with others | 998 | 50 (7.7) | Ref. | ||||||
| Home confinement alone | 293 | 47.6 (8.4) | −4.3 | −6.1; −2.5 | |||||
| Quarantine environment | 0.001 | 0.001 | |||||||
| With outdoor acces | 1243 | 49.9 (7.6) | Ref. | ||||||
| Without outdoor access | 239 | 47.7 (8.6) | −3.9 | −5.9; −2.0 | |||||
| COVID-19 cases in immediate circle | 0.4 | ||||||||
| Friends, Colleagues | 664 | 50.1 (7.4) | |||||||
| Family | 303 | 50.3 (6.7) | |||||||
| Self | 92 | 49.2 (8.8) | |||||||
| COVID-19 related deaths in immediate circle | 0.1 | 0.12 | |||||||
| No | 1433 | 49.5 (7.8) | Ref. | ||||||
| Yes | 77 | 50.9 (6.9) | 2.5 | −0.6; 5.7 | |||||
| Risk of financial insecurity due to quarantine | 0.001 | 0.001 | |||||||
| No | 1248 | 50 (7.5) | Ref. | ||||||
| Yes | 281 | 47.9 (8.9) | −3.6 | −5.4; −1.8 | |||||
| Confidence in the government | 0.001 | 0.001 | |||||||
| No | 986 | 49.1 (8.1) | Ref. | ||||||
| Yes | 541 | 50.6 (7) | 2.7 | 1.2; 4.1 | |||||
| Confidence in research | 0.001 | 0.001 | |||||||
| No | 293 | 47.8 (9.1) | Ref. | ||||||
| Yes | 1238 | 50 (7.4) | 3.9 | 2.2; 5.7 | |||||
| Support score | 0.16 | 0.1 ; 0.2 | 0.001 | 0.6 | 0.03; 0.09 | 0.001 | |||
| Optimism score | 0.45 | 0.42. 0.48 | 0.001 | 0.27 | 0.23; 0.32 | 0.001 | |||
| Resilience score | 0.38 | 0.35. 0.41 | 0.001 | 0.21 | 0.16; 0.25 | 0.001 | |||
| Insecurity score | −0.06 | −0.09. −0.02 | 0.002 | ||||||
| Trust in social networks | 0.02 | −0.02. 0.05 | 0.4 | ||||||
| Trust in the press | 0.05 | 0.01. 0.08 | 0.005 | ||||||
| Trust in immediate circle | 0.08 | 0.04. 0.11 | 0.001 | 0.05 | 0.02; 0.09 | 0.004 | |||
Abbreviations: OR, odds ratio:.
*: only variable with p0.30 values are presented in bivariate analysis.
**: variables with p0.05 values are considered significantly associated with variables of well-being in multivariate analysis.
We observed that the mean psychological well-being score across the sample was 49.6 (SD=7.8). As shown in Table 4, this score was lower among single participants (48.2; p1.001), those confined to their homes alone (47.6; p1.001), without access to the outdoors (47.7; p0.0001), and among students and those with no professional activity (46.3 and 46.4 respectively; p0.001) and people who indicated a risk of financial insecurity (47.9; p0.001).
The level of psychological well-being was also significantly different (p0.0001) according to the frequency of social contact, for all means of communication combined (telephone, sms messaging, video conferencing, social media, etc.): the mean score for those with no social contact or less than one time per week was 35.9 (SD=12), the mean score for those with one social contact per week was 47.0 (SD=7) and the average score for psychological well-being for those with several social contacts per week or every day was 49.9 (SD=7.5).
For the other scores, the average level for optimism across our sample was 12.8 (SD=4.5), the average score for resilience was 3.1 (SD=0.8), indicating normal resilience, and the average VAS score for overall perceived support was 5.4 (SD=2.4). The score for insecurity showed good internal consistency (Cronbach's alpha=0.077). The mean insecurity score across our sample was 89.7 (SD=29.2). Finally, regarding confidence levels and corresponding scores, 54.5% of the participants expressed confidence in information provided by the governement and 68.3% expressed confidence in scientific research and researchers working towards understanding the COVID-19 virus and finding a vaccine. With regard to confidence levels measured on a scale of 0 to 10, the average confidence score for among participants was 2.5 (SD=2.2) for information found on social networks, the average score for confidence in information provided by the immediate circle of friends/relatives was 4.5 (SD=2.2), and the average score for confidence in the press was 5.0 (SD=2.2). A comparison of all scores by region of residence showed that only the security score was significantly different. Indeed, this score was significantly higher among people living in the Great East region (8.4 vs. 92.7; p1.001).
3.3. Variables associated with levels of pscyhological well-being during quarantine (Table 4)
The results of the multivariate analysis showed that low psychological well-being during the quarantine period was significantly associated with single marital status (OR=−1.6; p = 0.04) and male gender (OR=−2.2; p0.02). High scores for perceived general support (=0.6; p0.001), optimism (=0.27; p0.001), resilience (=0.21; p0.001), and confidence in information from the immediate circle (=0.04; p = 0.004) were also positively associated with better mental well-being. Other variables for which we observed strong bivariate correlation with improved mental well-being (see Table 3) such as older age (=0.14; p0.001), having children (OR=3.9; p0.001) and trust in government and research (OR=2.7; p0.001 and OR=3.9; p0.001 respectively) no longer appeared as multivariate model. Similarly, several variables that were strongly associated with lower levels of psychological well-being during bivariate quarantine also stopped being multivariate model, such as student status (OR=−6.9; p0.001) and retired status (OR=−6.8; p0.001) compared to actively employed status, experiencing quarantine alone at home (OR=−3.9; p0.001) or expressing an expected risk of financial insecurity due to the quarantine measures (OR=−3.0; p0.001).
4. Discussion
This cross-sectional study, launched 15 days after the first nationwide quarantine measures were implemented in France and completed at the end of the quarantine period, is based on data collected from 1148 individuals to ascertain how the experience of this unprecented quarantine situation impacted psychological well-being. Concerning specific conditions of this initial phase of home confinement, 42% of participants in our study remained gainfully employed and worked remotely, 18% experienced home confinement alone at home, 15% had no outdoor access during the quarantine, and 63% lived in the Great East region, which compared to other regions in France showed the highest scores for insecurity. At the time of this study, the Great East region was one of the most severely impacted by the epidemic in terms of active COVID-19 cases, which strained public health services. Protection of health care workers, paramedics and first responders, both in circulation and in hospitals, was rapidly recognized as the higest priority. Hospital teams and practitioners working in more isolated clinical settings played an integral part in the response effort, often working beyond normal working conditions to uphold values of protecting human health and dignity; they exhibited unfailing courage and dedication to the community as a whole, oftentimes to the detriment of their own well-being. An added dynamic for many of these workers was the necessity to stay employed during this period, despite the risks involved with continuing to work in potentially unsafe environments. The stress factors for many health workers were significant and centered essentially on three major dynamics: societal pressure surrounding the increasing anxiety-provoking nature of events unfolding worldwide coupled with an intense focus on recovery from the crisis through a commitment to providing critical patients with quality care, professional pressure marked by unprecedented workload and other predictable coping mechanisms, and pressure associated with personal life through either fear of contaminating one's family or returning to solitary conditions during confinement after a full day or night of work. Available data on the pscyhological consequences on health workers during this global health situation show, for example, a prevalence of 14.5% anxiety, 8.9% depression and 7.7% posttraumatic stress disorder (Tan, Chew Lee, 2020). Similar data were observed in the population of nearly 1000 frontline health professionals in Wuhan, China (initial focus of the pandemic).
In France, on average and excluding specific events, the score for psychological well-being of individuals measured by the same questionnaire we used in this study has previously been reported as 53 (Franck, 2020), whereas we observed in our own study a lower average score of 3.4 points. This score was found to be even lower for single individuals, those who experienced quarantine home alone, those without access to the outdoors during quarantine, students, the unemployed and participants who indicated potential risk of financial insecurity. A large survey conducted in France in the spring of 2020 that involved 20,000 people reported similar results using the same questionnaire on psychological well-being (Franck, 2020). Social support was perceived to be strongly associated with mental well-being, where our own sample showed that 78% of the participants had some form of daily social contact, mainly by telephone, social networks and sms messaging.
Similarly, our results show lower optimism levels than other studies conducted on the general population (Schou-Bredal, Heir Skogstad, 2017). Finally, the resilience score considered as the ability to “cope” with a difficult or stressful situation, often traumatic, indicated that participants in our study exhibited adequate resilience capacity. These two scores, optimism and resilience, were found to be strongly associated with levels of psychological well-being across our sample. Individuals with higher levels of optimism are more inclined to believe that the goals they set are achievable and, as a result, they invest more effort in achieving their goals than pessimists, and most of them succeed (Chang, Maydeu-Olivares D'Zurilla, 1997; Grover, Hyde, Lux, O'Kane Walton, 2019). Individuals with higher levels of optimism appear more inclinded to use effective coping mechanisms when faced with difficulties. They seek operational solutions and engage themselves both cognitively and emotionally in finding solutions, whereas pessimists are more inclined to use coping strategies that involve withdrawl, either mentally or behaviorally, from the given situation. It is therefore not surprising that in the context of the present global health situation, individuals with higher levels of optimism are better able to take care of themselves and implement more appropriate preservation and prevention strategies. This would also suggest that they are less inclined let themselves become overwhelmed by the situation for the fact that they take a proactive approach and responsbility for their own self care without waiting for outside help. Conversely, people with higher levels of pessimism can quickly become overwhelmed with feelings of powerlessness faced with persistent and omnipresnet bad news in the media as the pandemic unfolds. Resilience can be defined as the ability to adapt in the face of adversity and trauma or other significant stressors (Norris, Tracy Galea, 2009). It is the ability to succeed, to live and develop positively and in a socially acceptable way despite stress or adversity normally associated with risk of negative outcome. Numerous studies have shown that psychological resilience can be seen as an intermediary between environmental stress and an individual's psychological state (Hao, Hong, Xu, Zhou Xie, 2015; Howell, Miller-Graff, Schaefer Scrafford, 2020) that can mitigate the negative effects of the former (Poole, Dobson Pusch, 2017; Sheerin et al., 2018). Thus, resilience acts as an interface that allows people to protect themselves, including against psychological distress. In the limited number of studies that have examined the effect of resilience on mental health in the context of a global health crisis, resilience was found to be negatively correlated with both depression and anxiety in exposed individuals (Osofsky, Osofsky Hansel, 2011). Based on our own results, it appears that the combination of optimism and good resilience facilitates maintaining a certain level of well-being among the general population, which to our knowledge is rarely pointed out in studies on the effects of health crises on psychological health at the population level.
Although 80% of our sample was female, our multivariate analysis showed that the men's psychological well-being was significantly impacted. This result may be related to two contingent phenomena. The first being that it has been suggested that men are more at risk for contracting the virus than women, which may have contributed to levels of reported concern (Rozenberg, Vandromme Martin, 2020). Secondly, an important aspect is that the quarantine measures imposed a situation men may, to some degree, experience differently than women; it consisted of staying at home and no longer working in a professional setting that is often linked to identity. It is worth noting here that our study was conducted during the first quarantine period in France when working remotely was a relatively new concept. Many found themselves in situations of temporary unemployment due to a total loss of professional activity. Interestingly, we also noted a protective effect in the context of couples and, in a bivariate way, age. Indeed, young people and particularly students, often living away from their families and with limited financial means, experienced the most pronounced impacts in terms of psychological well-being, as shown in both our study and the literature (Bourion-Bédès, Tarquinio Batt, 2021). This study showed that the global health situation during the first quarantine in France led 15.2% to perceive themselves as moderatly anxious and 9.8% as strongly anxious. Another study carried out among Chinese students revealed that 24.9% experienced anxiety as a results of the COVID-19 pandemic (Cao et al., 2020). Similarly, a study involving Greek students during periods of quarantine reported an increase in anxiety scores, depression and suicidal thoughts, a general deterioration in quality of life and poorer sleep quality (Kaparounaki et al., 2020).
It was generally noted that the elderly felt well protected by the health measures put in place and experienced the first quarantine in relative comfort. Age did not emerge as signifiantly associated in multivariate analyses: the average age of our sample was 40 years. In addition, retirees, who represented only 6% of our sample, reported psychological well-being scores similar to younger, working people.
During the first quarantine, 68% of participants reported feeling reassured by scientific knowledge and expressed that they felt confident that research would lead to solutions for overcoming the pandemic. This confidence was significantly associated with improved mental well-being but only in bivariate analyses. We noted that trust in information from immediate family and friends played a greater protective role in terms of psychological well-being, while this score remained average.
The main strength of this study is the sample size. Additionally, tools that were validated in French with good psychometric properties were used for describing individuals’ mental health status. Clearly, it would have been informative to recontact the participants during the second quarantine which was experienced differently by the population, and indeed, a useful line of questioning would have been what these differences were exactly. Were the individuals able to benefit from their first quarantine experience, or conversely, did the negative phenomena observed in terms of malaise, depressive or anxiety disorders increase? The question is equally pertient for those subjects with higher scores related to pscyhological well-being. There is nothing to suggest that such parameters would persist over the long term. Importantly, it was widely understood by everyone that the first quarantine period would eventually end and that the total duration would be a matter or weeks, possibly months. Virtually no one expected the possibility of being faced with a second or third quarantine or prolonged enforced stay-at-home orders. The consequences in terms of psychological health, family, social and professional life combined with economic impacts associated with such an abrupt shut-down of society for the greater good of public health come with a host of secondary effects, the dimension and scope of which no one could have anticipated; the challenge is that we cannot fully understand how the different parameters evalutated in this study will or could evolve in the medium, long or even very long term and what the impacts will be on the general public. The fact that our study was transversal but also completely anonymous prevents us from being able to contact participants for follow up evaluations; indeed, we felt anonymity of participants would serve the overall integrity of the data but we also did not anticipate a second quarantine. However, a cluster analysis would make it possible to identify risk profiles and rather protective profiles. This analysis will be carried out soon by our team. A second limitation is the mode in which the questionnaire in our study was diffused to potential respondents, which was primarily through social networks and direct online responses. Despite advantages that come with using these methods (lower cost, speed of data collection, reduced data entry errors, greater freedom for the resondent) (Ganassali, 2008; Stephenson Crête, 2011), certain drawbacks nonetheless emerged from this approach. First and foremost, this type of data collection requires a certain familiarity with computers and the Internet, as well as access to social networks from which we disseminated the survey. Several authors mention that respondents to online surveys are generally regular, even expert, Internet users, a factor that can potentially impact the type of sample (generally more affluent, more educated and younger, for example) (Bosnjak et al., 2013). Importantly, this aspect of our study design could call into question the representativeness of our sample.
5. Conclusion
This study allowed us to observe that the psychological well-being of participants was impacted during this quarantine period, that it was strongly associated with levels of both optimism and resilience, and that support in general together with trust in the environment also played an important role in levels of mental well-being. Our results are farily consistent with what has been reported in the literature in recent months, notably that quarantine measures have long-term consequences on the population's psychological well-being (Brooks et al., 2020). This presents a constraint that governments and policy-makers have not fully acknowledged, despite the fact that a deeper understanding of this key dimension being the mental health of the general population could potentially act as a lever to helping or hindering society in efforts to forge paths to recovery and envision new ways of functioning to overcome this current global health crisis. If the emotional state of the population remains negatively affected and the health situation persists over longer periods, potentially several months as we are currently experiencing, it will be imperative to question the long-term effects of psychological health on physical health. It is indeed essential that we build on what has thus far been revealed by the current pandemic situation and its emotional impacts to establish a link between mental and physical states, particularly given that we now know that the negative emotional state is associated with chronic stress and chronic anxiety, both known to weaken the immune system, the body's primary defense against infection and disease (Powell, Sloan Bailey, 2013).
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Footnotes
This research did not receive any specific grant from funding agencies in the public, commercial, ornot-for-profit sectors
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