Ellen et al. BMC Public Health (2021) 21:622 https://doi.org/10.1186/s12889-021-10673-4 RESEARCH ARTICLE Open Access Meaningful activities during COVID-19 lockdown and association with mental health in Belgian adults Cruyt Ellen1 , De Vriendt Patricia1,2,3 , De Letter Miet1 , Vlerick Peter4 , Calders Patrick1 , De Pauw Robby1 , Oostra Kristine1 , Rodriguez-Bailón Maria5 , Szmalec Arnaud6,7, Merchán-Baeza Jose Antonio8 , Fernández-Solano Ana Judit9 , Vidaña-Moya Laura10 and Van de Velde Dominique1* Abstract Background: The spread of COVID-19 has affected people’s daily lives, and the lockdown may have led to a disruption of daily activities and a decrease of people’s mental health. Aim: To identify correlates of adults’ mental health during the COVID-19 lockdown in Belgium and to assess the role of meaningful activities in particular. Methods: A cross-sectional web survey for assessing mental health (General Health Questionnaire), resilience (Connor-Davidson Resilience Scale), meaning in activities (Engagement in Meaningful Activities Survey), and demographics was conducted during the first Belgian lockdown between April 24 and May 4, 2020. The lockdown consisted of closing schools, non-essential shops, and recreational settings, employees worked from home or were technically unemployed, and it was forbidden to undertake social activities. Every adult who had access to the internet and lived in Belgium could participate in the survey; respondents were recruited online through social media and e-mails. Hierarchical linear regression was used to identify key correlates. Results: Participants (N = 1781) reported low mental health (M = 14.85/36). In total, 42.4% of the variance in mental health could be explained by variables such as gender, having children, living space, marital status, health condition, and resilience (β = −.33). Loss of meaningful activities was strongly related to mental health (β = −.36) and explained 9% incremental variance (R2 change = .092, p < .001) above control variables. Conclusions: The extent of performing meaningful activities during the COVID-19 lockdown in Belgium was positively related to adults’ mental health. Insights from this study can be taken into account during future lockdown measures in case of pandemics. Keywords: Corona, General health, Meaningful activities, Occupations, Resilience, Well-being * Correspondence: Dominique.vandevelde@ugent.be 1 Faculty of Medicine and Health Sciences, Department of Rehabilitation Sciences, Occupational Therapy, Physiotherapy and Speech-language Pathology/Audiology, Ghent University, Corneel Heymanslaan 10, B3, entrance 46, 9000 Ghent, Belgium Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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BMC Public Health (2021) 21:622 Page 2 of 15 Background [9]; and those living alone [23] have the highest risk to Coronavirus disease 19 (COVID-19) is a novel infectious develop mental health problems such as anxiety or de- disease with an onset in Wuhan City, China, in pression during the COVID-19 crisis. December 2019 [1]. Since then, COVID-19 has become So far none of these studies on mental health during a pandemic and can cause a severe acute respiratory COVID-19 took the role or potential influence of one’s syndrome that can lead to death [2]. The World Health daily meaningful activities on adult mental health into Organization (WHO) declared the COVID-19 outbreak account, although the lockdown has had a major impact as a public health emergency of international concern on daily activities [30] and previous research has shown [3]. Governments around the globe implemented highly that daily activities can have a huge impact on one’s restrictive, sometimes intrusive measures under rapidly mental health [31–36]. changing epidemiological situations [4]. Activity engagement has also been associated with Epidemic diseases are a permanent threat to global lower levels of mental health symptoms due to the health. Nowadays, many infections such as smallpox and meaning people attribute to their daily activities [37–41]. influenza can be prevented by vaccinations, and COVID- Indeed, activity engagement contributes strongly to 19 is not the first epidemic to affect Belgium. In the past, humans’ sense of purpose in life and fulfilment of psy- Europe, including Belgium had to deal with (Mexican) chological basic needs (e.g. need for autonomy, need to influenza, smallpox, and the Black Plague. In recent de- belong, and need for competence) leading to better cades, Belgium was spared life-threatening epidemics health [42], well-being [43, 44], and successful aging such as Severe Acute Respiratory Syndrome (SARS) in [45–47]. This suggests that the COVID-19 lockdown 2003, which had very similar symptoms of COVID-19 and the implied immediate and unprecedented impact [5]. This is therefore the first time the majority of the on multiple facets of life might influence one’s mental Belgian population has experienced something so mani- health due to a diminished sense of purpose and/or frus- fest and profound. tration of these psychological needs. This may be espe- On March 13, 2020, a lockdown in Belgium was a ne- cially true for adults who are undergoing a critical time cessary preventive action to avert the threat of a health of interpersonal development, education, family devel- crisis [6]. Despite this lockdown in the month of June, opment, and career building. For instance, young 2020, more than 15,000 COVID-19 related deaths were adults are at high risk for mental health problems as reported for Belgium’s population of about 11 million they reported elevated loneliness and depression even people, that is, 174 deaths per day per million inhabi- after the first 5 months of exposure to the COVID-19 tants (data retrieved on the first of August, 2020) [7]. pandemic [22]. Research has shown that epidemics can cause severe Considering the relevance of meaningful activities for and variable psychological effects on people [8, 9]. The mental health, it can be concluded that there is a gap in growing literature on COVID-19 has already shown that the COVID-19 literature about the relationship between the pandemic and accompanying measures have had a mental health and meaningful activities during lock- profound effect on–besides health issues–all aspects of so- down. This study therefore examined whether meaning ciety, including mental health [10, 11]. Because mental in activities was associated with mental health, regardless health under COVID-19 is now among the foremost pub- of demographic and personal characteristics (e.g., lic health concerns throughout the world, it is also one of resilience). the most researched topics [12]. Most of the mental The hypothesis (H) of this study was that the inability health-related studies during COVID-19 focused on care- to engage in meaningful activities during COVID-19 givers, such as nurses and physicians, who are on the lockdown would be a contributing factor for low mental frontlines of the pandemic responses [13–17] or consid- health. Specifically, we expected a positive association ered the mental health of COVID-19 patients [18]. between engaging in meaningful activities and mental COVID-19 and mental health is, to date, a rapidly health in adults, even after taking control variables into growing field of research. The results are fragmented account. and a clear picture is still missing. Several mental health studies on COVID-19 found associations between demo- graphic characteristics and mental health. It seems that Materials and methods younger people (< 30 years, inclusive of students [19, Study design 20]) [13, 21–25]; women [9, 13, 19, 20, 22, 26]; health- A cross-sectional online survey was conducted among a care workers [13, 21]; unemployed people [19]; adults sample of adults in Belgium, via the online platform who have children [27, 28]; people living in rural areas Limesurvey©. The study adhered to the strengthening of [29]; those having cancer or chronic diseases [23]; those the reporting of observational studies in epidemiology living with family member at high risk for COVID-19 (STROBE) statement [48]. Ellen et al. BMC Public Health (2021) 21:622 Page 3 of 15 Procedure and participants Classification of Functioning and Disability and Health The first lockdown measures in Belgium began on (ICF) [49]. March 13, 2020, comprising the following restrictions: Participants were asked to indicate whether or not (1) primary schools, Universities of Applied Sciences, they performed each of these daily activities before the and Universities had to close and turned digital; (2) all COVID-19 crisis. If so, they had to indicate whether they not-essential shops had to close, and only food-related adapted the activity during COVID-19. Four category shops were permitted to be open; (3) businesses had to options were provided: (1) as usual (in the same manner close and employees became technically unemployed or compared to before the COVID-19 crisis); (2) in another had to work from home; (4) planned activities such as environment (e.g., at home instead of the office); (3) in concerts and, sports events were cancelled; (5) recre- another way (e.g., online shopping instead of shopping ational settings such as cinemas and, fitness centers, had in the street); and (4) another activity evoking the same to close; and (6) it was forbidden to see family and purpose or meaning (e.g., going for a walk instead of go- friends outside one’s own house and to undertake social ing to the gym). Selecting one or more categories was activities. These measures lasted until May 4, 2020, possible. when the number of COVID-19 infections stabilized. The web-based self-reported questionnaire was distrib- uted online in Belgium (Flanders and Wallonia) between Part 2: instruments April 24 (6 weeks after elapsing the total lockdown) and May 4, 2020. The data collection stopped after the gov- The general health questionnaire (GHQ) Participants’ ernment introduced a reduction in the measures with a mental health was assessed using the 12-item version of gradual start-up of work, shops, and schools. the GHQ, which is a valid and reliable instrument for Participants were recruited through online communi- assessing psychological morbidity and distress [50]. This cations on social media (Facebook, e-mails, Twitter, and widespread validated instrument is used by the govern- LinkedIn) and through e-mails (sent to the authors’ net- ment in (epidemiological) studies in Belgium [51–53]. It works, patient associations, colleges, and universities). had a sensitivity of 83.4% and specificity of 76.3% [54]. To capture the entire lifespan of adulthood, every Internal consistency of the GHQ in this study sample adult, aged 18 years or older, who had access to the was calculated with the Cronbach’s Alpha. Every item internet and lived in Belgium, could voluntarily and an- (e.g., Lately, have you lose much sleep over worry?) has onymously participate in the study. Participants under four answer options using a Likert scale (0= ‘not at all’; the age of 18 were excluded because they are too young 1= ‘no more than usual’; 2= ‘rather more than usual’; or to answer the survey questions properly and are still de- 3= ‘much more than usual’). The total sum scores can pendents on their parents. range from 0 to 36, with higher total scores reflecting higher levels of psychological morbidity or distress. A Measures score of 12 or lower in adults indicates psychological Three standardized and validated measurement instru- well-being [54]. ments were integrated into the online questionnaire and supplemented by additional questions to describe the study sample. The Connor-Davidson resilience scale (CD-RISC) The CD-RISC measures the personal characteristic of Part 1: Sociodemographic and activity related data resilience, broadly conceptualized as healthy and adap- The first part of the online questionnaire included oper- tive functioning in the aftermath of adversity [55, 56]. ationalizations of the following descriptive variables: age, The 10-item CD-RISC (e.g., ‘I am able to adapt when gender, educational level, marital status, having children, changes occur’) is scored on a 5-point Likert scale ran- employment status (with working situation), living situ- ging from 0= ‘not true at all’ to 4 = ‘true nearly all of the ation, living region, living area, living space, health con- time’. The total sum score ranges from 0 to 40. A higher dition, and whether the participants were informal score indicates higher resilience [57]. The CD-RISC is a caregivers or receiving informal care. widely recognized and well-validated measurement of re- Next, participants were presented a fixed list of 18 silience in different cultures [58] and populations [59]. daily activities. These activities were relevant across all In adults, the threshold score is 29 [60]. It showed a stages of adulthood and were identified through a litera- good convergent validity, accounted for high explained ture study including basal, instrumental, and advanced variance (81.5%), and overall correlation values on diver- activities of daily living. A consensus was made based on gent validity were close to zero [61]. Internal consistency the expertise of the research team, and the activities of the CD-RISC in this study sample was calculated with were linked to the nine domains of the International Cronbach’s Alpha. Ellen et al. BMC Public Health (2021) 21:622 Page 4 of 15 The engagement in meaningful activities survey were transformed into ‘dummy variables’. In Model 1, (EMAS) The 12-item EMAS with 4-point Likert scale regression coefficients were calculated for the control according to Eakman [62] was used. This measure was variables retrieved from bivariate analysis. The factor developed to assess aspects of activity meaning and em- ‘meaningful activities’ was added in Model 2 to examine phasizes activity’s congruity with one’s value system and whether meaningful activities are statistically signifi- its ability to fulfill basic needs and mastery. The EMAS cantly related to mental health, while adjusting for key uses the broad term ‘activities’ to represent typical confounding variables (demographic and personal char- activities within self-care, leisure, and productivity. Par- acteristics). Models were screened for multicollinearity ticipants were asked to rate each statement (e.g. ‘The ac- according to the calculations of the Variance Inflation tivities I do reflect the kind of person I am’) on a 4-point Factor (VIF). F-values below 0.10 were automatically re- Likert scale, ranging from 1 = ‘seldom’ to 4 = ‘always’. A moved because can be considered insignificant. total sum score ranges from 12 to 48. The meaningful- ness of a person’s activities can be either low (EMAS Results < 29), moderate (EMAS 29–41), or high (EMAS > 41). Descriptive results The EMAS was found to have adequate test-retest reliabil- Sociodemographic variables ity (r = .71) and significant positive correlations and nega- In total, a convenience sample of 1781 participants com- tive zero-order correlations with measures of meaning pleted the questionnaire. Descriptive data for the inde- and purpose in life, depressive symptomology, life satisfac- pendent variables are displayed in Table 1. tion, and health-related quality of life [50, 63]. Internal consistency of the EMAS in this study sample was calcu- Activities during the COVID-19 lockdown lated with Cronbach’s Alpha. An overview of the activities that the participants per- formed before and during the COVID-19 crisis can be Data analysis found in Table 2. Thirty-seven percent of the respon- Only full completed questionnaires were used for statis- dents who indicated that they did social activities outside tical analyses. All statistics were performed using SPSS the home before COVID-19 stopped these activities dur- 26 (SPSS Inc., Chicago, IL) and a p < .05 was considered ing COVID-19 lockdown. Approximately, two-third of significant in all analyses. A descriptive analysis (fre- the students who did a student job and nearly 50 % of quencies and means) of the sample (demographics and the adults who volunteered before the COVID-19 crisis activities during COVID-19) was conducted. had to quit these activities. Activities that continued in- doors, alone, or in a ‘bubble’ with closest family, such as Step 1: bivariate analysis leisure time (97.3%), caring for family (99.4%), household In preparation for the multivariate analysis and to iden- (99.3%), doing chores in the house (98%), and self-care tify significant correlates of mental health, all potential (99.8%), were largely retained. relevant variables retrieved from the survey were associ- Table 3 shows whether or not participants adapted ated with mental health. Bivariate analysis through their activities during the lockdown according to the between-group differences in mental health (GHQ) re- four described categories. The activities that were per- garding nominal and ordinal independent variables was formed in-house during the COVID-19 lockdown were evaluated by Mann–Whitney U tests for questions with hardly modified. In particular, taking care of themselves two answer categories (gender, having children, living (61%) and the family (56%), cooking healthy foods (68%), area, informal caregiver, receiving care, living space) and sexual activity (83%), doing household-related activities Kruskal–Wallis tests for questions with more than two (79%), doing chores in the house (61%) and performing answer categories (marital status, educational level, em- student jobs (82%) did not happen any differently than ployment status, living condition, region, working situ- prior to the COVID-19 outbreak. ation, health condition). Mann–Whitney U tests were However, other daily activities such as sports (48%), conducted after the Kruskal–Wallis tests to find which religion (56%), attending trainings (66%), and going to groups significantly differed from each other based on work (65%) were still performed but largely in a different GHQ scores. Spearman’s correlation coefficients were environment. Adults social outside activities (70%), at- obtained for the continuous independent variables (age, tending trainings (84%), and caring for others outside EMAS, and CD-RISC). the family (55%) were performed in a different manner during COVID-19 lockdown. Step 2: multivariate analysis Finally, 35% of the participants regularly cared for To test the hypothesis, multivariate analysis with hier- their health through sports, and 36% of the participants archical multiple linear regression was used. All categor- performed social activities prior to the COVID-19 out- ical variables with more than two answer categories break reported that they replaced these daily activities Ellen et al. BMC Public Health (2021) 21:622 Page 5 of 15 Table 1 Overview of sociodemographic characteristics of the study sample (N = 1781) Mean age (SD) 34.79 (16.8) % N Gender Woman 75.3 1341 Men 24.7 440 Marital status Married 27.4 489 Divorced 2.8 50 Single 37.4 667 Widow 1.3 23 Living together 18.8 335 Other 12.2 217 Educational level Elementary school 0.6 10 Middle school 22.8 406 University of Applied Sciences and University 76.6 1365 Health condition Healthy 78 1389 Acutely ill 2.9 52 Chronically ill 17.9 318 Mentally ill 1.2 22 Employment status Student 45 801 Employed 37.3 664 Unemployed 17.7 316 Working situation (if employed) I work from home 26.1 465 I work as usual 10.9 195 Technically unemployed 2.6 47 Other 4.4 79 Having children Yes 33.7 601 No 66.2 1180 Living situation Living alone 9 160 Living alone with children 2 35 Living together without children 23.9 425 Living together with children 18.5 330 Living with parents, family 41.7 742 In a student room alone 0.8 15 In a dorm with another student 2.3 41 Living region Flanders (Dutch-speaking part) 94.7 1687 Wallonia (French-speaking part) 3.2 57 Brussels 2.1 37 Living area Urban 42.5 757 Rural 57.5 1024 Living space House, apartment with garden or balcony 92.1 1640 Studio, apartment without balcony 7.9 141 Giving informal care Yes 9.3 166 No 90.7 1615 Receiving informal care Yes 6.1 108 No 93.9 1673 SD Standard deviation Ellen et al. BMC Public Health (2021) 21:622 Page 6 of 15 Table 2 Percentages of participants who discontinued or maintained the selected activities during COVID-19 lockdown ‘Don’t do anymore’Participants who discontinued ‘Still do’Participants who maintained the activities activities Self-care (n = 1754) 0.2% 99.8% Free time activities indoors (n = 1697) 2.7% 97.3% Social activities outdoors (n = 1619) 37.4% 62.6% Household (n = 1616) 0.7% 99.3% Free time activities outdoors (n = 1473) 17% 83% Caring for my health through sports (n = 1436) 3.7% 96.3% Caring for my health through cooking (n = 2.7% 97.3% 1351) Sexuality (n = 1255) 13.1% 86.9% Attending a training (n = 945) 4.6% 95.4% Doing chores in and around the house (n = 2% 98% 841) Going to work (n = 792) 6.4% 93.6% Caring for family (n = 515) 0.6% 99.4% Caring for others outside the family (n = 465) 18.5% 81.5% Volunteering work (n = 401) 48.9% 51.1% Caring for my health through mental activities 7% 93% (n = 385) Student job (n = 326) 68.4% 31.6% Doing chores for other people (n = 169) 39.6% 60.4% Religious activities (n = 92) 12% 88% n = number of participants who performed the activity before the COVID-19 crisis Table 3 Percentages of participants who (did not) change(d) their activities during COVID-19 Not different In another environment In another way Comparable activity Self-care (n = 1750) 61% 15% 22% 16% Free time activities indoors (n = 1651) 44% 29% 22% 29% Social activities outdoors (n = 1015) 11% 40% 70% 36% Household (n = 1603) 79% 7% 13% 7% Free time activities outdoors (n = 1226) 16% 69% 56% 10% Caring for my health through sports (n = 1383) 32% 48% 34% 35% Caring for my health through cooking (n = 1317) 68% 20% 15% 7% Sexuality (n = 1085) 83% 4% 10% 5% Attending trainings (n = 902) 6% 66% 84% 4% Doing chores in and around the house (n = 824) 61% 17% 27% 8% Going to work (n = 741) 23% 65% 31% 2% Caring for family (n = 513) 56% 15% 23% 23% Caring for others outside the family (n = 382) 25% 32% 55% 4% Volunteering work (n = 205) 27% 39% 48% 12% Caring for my health through mental activities (n = 358) 46% 23% 26% 29% Student job (n = 106) 82% 6% 8% 4% Doing chores for other people (n = 102) 37% 24% 40% 18% Religious activities (n = 81) 37% 56% 26% 7% Ellen et al. BMC Public Health (2021) 21:622 Page 7 of 15 with other still comparable activities evoking the same than men (p < .001), which indicates lower mental purpose or meaning. health. Participants who had children scored significantly lower in the GHQ than adults without children, which indicates better mental health (p < .001). People living in Mental health, resilience and meaning in activities an urban living area had lower mental health than par- Internal consistency of the measurement instruments ticipants who lived in a rural area (p = .004). Participants was calculated for GHQ (Cronbach’s Alpha = .888), whose living space included a garden or balcony had a EMAS (Cronbach’s Alpha = .907), and CD-RISC (Cron- lower score in the GHQ which reflects better mental bach’s alpha = .883), and showed a good to excellent in- health (p < .001). ternal consistency for every instrument. The significant independent variables associated with The mean GHQ score for the overall sample was mental health and retrieved from the Kruskal-Wallis test 14.85. Based on the threshold score of 12 for adults, the were marital status, employment status, living condition, mean score lies above the threshold score which reflects health condition. The results are displayed in Table 5. higher levels of psychological morbidity or distress. Married respondents scored significantly lower in the Participants scored on average 24.85 on the CD-RISC, GHQ than being divorced (p = .033), being alone which indicates a lower resilience than the cut-off score (p < .001), and living together (p < .001), which indicates of 29 for adults. better mental health. Based on the EMAS categories, 655 participants expe- Being alone scored significantly lower in the GHQ rienced low meaning in activities, 1013 participants than being a widow (p = .019) or living together experienced a moderate sense of meaning in their activ- (p < .001), meaning better mental health. ities, and 83 experienced high meaning in their activities. Students scored significantly higher in the GHQ than employed (p < .001) and unemployed adults (p < .001), Bivariate analysis indicating worse mental health. The independent variables that were statistically signifi- Living alone scored significantly higher in the GHQ cantly associated with mental health (GHQ) in the than living together with (p = .001) and without children Mann–Whitney U test were gender, having children, liv- (p = .002), meaning lower mental health. ing area, and living space. The results are displayed in Participants who lived with parent(s) or family scored Table 4. Woman scored significantly higher in the GHQ higher in the GHQ than those living alone (p = .025), Table 4 Overview bivariate analysis results (1): Mann-Whitney U test: differences between (dichotomous) groups for the General Health Questionnaire (N = 1781) GHQ Mean (SD) Mann-Whitney U Z P Gender 230,410 −6.909 <.001 Woman 15.44 (6.80) Men 13.04 (6.55) Having children 258,587 −9.364 <.001 Yes 12.89 (6.58) No 15.84 (6.72) Living area 356,404 −2.909 <.05 Rural 14.44 (6.71) Urban 15.41 (6.92) Informal caregiver 123,306 −1.704 .088 Yes 15.65 (6.90) No 14.77 (6.80) Receiving care 81,136 −1.779 .075 Yes 16.14 (7.40) No 14.77 (6.77) Living space 91,852.5 −4.06 <.001 Balcony/garden 14.62 (6.67) No balcony/garden 17.50 (7.9) Higher scores in GHQ means lower mental health Ellen et al. BMC Public Health (2021) 21:622 Page 8 of 15 Table 5 Overview bivariate analysis results (2): Kruskal–Wallis test: differences between (categorical) groups for the General Health Questionnaire followed by Mann–Whitney U (N = 1781) GHQ Mean GHQ Median P-value Kruskal– P-value Mann-Whitney Ua (Range; SD) (inter quartile) Wallis Marital status <.001 1.Married 12.54 (0–36; 6.18) 11 (9) .033 between 1 and 2 2.Divorced 14.74 (3–32; 7.08) 15 (11) <.001 between 1 and 3 3.Alone 16.56 (1–36; 6.79) 16 (10) <.001 between 1 and 5 4.Widow 12.91 (1–23; 5.61) 13 (7) <.001 between 1 and 6 5.Living together 14.17 (0–36; 6.73) 13 (10) .019 between 3 and 4 6.Other 16.07 (2–35; 6.81) 16 (10) <.001 between 3 and 5 .001 between 5 and 6 Educational level .156 Primary education 12.3 (4–20; 5.74) 10.50 (11) Secondary education 15.44 (1–35; 7.17) 14.50 (11) Higher education 14.69 (0–36; 6.71) 14 (10) Employment status <.001 1.Student 16.67 (1–36; 6.80) 16 (9) <.001 between 1 and 2 2.Employed 13.16 (0–34; 6.25) 12 (9) <.001 between 1 and 3 3.Not employed 13.78 (1–36; 6.90) 12 (9) Living condition <.001 1.Alone 15.19 (2–35; 7.30) 14 (11) .002 between 1 and 3 2.Alone with children 14.29 (1–29; 6.97) 15 (10) .001 between 1 and 4 3.Living together without children 13.09 (0–36; 6.23) 12 (9) .025 between 1 and 5 4.Living together with children 12.83 (0–36; 6.47) 11.5 (9) .001 between 1 and 7 5.Living in with parent(s),family 16.36 (1–36; 6.50) 16 (10) .004 between 2 and 7 6.Room alone 19.27 (5–36; 8.37) 21 (12) <.001 between 3 and 5 7.Room together 19.34 (3–35; 8.01) 22 (13) .003 between 3 and 6 8.Other 14.88 (3–34; 7.96) 13 (11) <.001 between 3 and 7 <.001 between 4 and 5 .002 between 4 and 6 <.001 between 4 and 7 .005 between 5 and 7 .025 between 7 and 8 Region .545 Flanders 14.88 (0–36; 6.80) 14 (11) Wallonia 14.81 (3–34; 7.53) 14 (11) Brussels 13.68 (2–32; 6.95) 12 (10) Working situation .504 Working from home 13.36 (0–33; 6.44) 13 (10) Work as usual 12.92 (4–30; 5.46) 11 (8) Technically unemployed 14.74 (4–34; 7.54) 13 (10) Other 14.28 (0–36; 7.58) 13 (8) Health condition <.001 1.Healthy 14.63 (0–36; 6.66) 14 (10) .011 between 1 and 2 2.Acute ill 17.02 (2–31; 6.99) 16 (11) .001 between 1 and 4 3.Chronically ill 15.06 (3–36; 7.09) 14 (10) .042 between 2 and 3 4.Mentally ill 20.23 (2–36; 9.17) 20.50 (11) .003 between 3 and 4 To increase the interpretability, means as well as medians were displayed in this table. Higher scores in GHQ indicate lower mental health. aThe numbers in the last column correspond with the groups described in column 1 Ellen et al. BMC Public Health (2021) 21:622 Page 9 of 15 living together (with children (p < .001) or without chil- Table 7 Hierarchical regression analysis of demographic dren (p < .001)), meaning lower mental health. characteristics, personal factors and meaning in activities Participants who lived in a room together with other associated with mental health people (e.g., student accommodation) scored higher in Mental health the GHQ than participants who lived alone (p = .001), Model 1 Model 2 alone with children (p = .004), or those living together B SE B β B SE B β (with children (p < .001) or without children (p < .001)) Control variables or living in with parent(s) or family (p = .005), meaning Gender −.793 .317 −.050* −.596 .294 −.038* lower mental health. Having children −.968 .353 −.067* −.798 .328 −.055* Participants who lived in a room alone scored higher in the GHQ than participants who lived together, with Living area .391 .279 .028 .254 .259 .018 children (p = .002), meaning lower mental health. Living space −1.164 .512 −.046* − 1.002 .476 −.040* Healthy participants scored lower in the GHQ than Employment status −.297 .314 −.021 −.083 .292 −.006 acutely ill participants (p = .011) or mentally ill partici- Marital status −1.536 .331 −.112** −1.037 .309 −.076* pants (p < .001), which indicates better mental health. Health condition −.975 .344 −.059* −.884 .319 −.054* Chronically ill persons scored lower in the GHQ than Resilience (CD-RISC) −.530 .021 −.501** −.351 .022 −.332** mentally ill participants (p = .003) and acutely ill partici- pants (p = .042), meaning better mental health. Main effect As shown in Table 6, Spearman’s Rho test showed a EMAS −.363* .022 −.358** significant moderate relationship between EMAS-GHQ R2 .335** .427** (Rs = −.547, p < .001) and CD-RISC-GHQ (Rs = −.524, Adjusted R2 .332** .424** p < .001). Age was also significantly related to mental R2 change .335** .092** health (Rs = −.254, p < .001). **significant result (p < .001), *significant result (p < .05) VIF factors showed no problems in terms of multicol- linearity, except for ‘living condition’ and ‘marital status’, which reflect both whether or not respondents live alone and together accounted significantly for 33.2% of the or share their life with someone. The decision based on variance in mental health (p < .001). In Model 2, the a VIF factor of 1 was to exclude living condition. A variable meaning in activity (EMAS) was added to the closer look at the variables ‘age’, ‘employment status’ regression equation, which explained 9.2% incremental and ‘having children’ showed that they intrinsically indi- variance, augmenting the total explained variance in cate the same thing, namely the stage of life. The corre- mental health to 42.4% (p < .001). Six of the eight control lations between age and employment status (r = .792), variables were significantly associated with mental age and having children (r = .753) were strong. Accord- health, including gender (β = −.038; p = .043), having ingly, the decision was made to exclude ‘age’ in the fol- children (β = −.055; p = .015), living space (β = −.040; p = lowing analysis. .035), marital status (β = −.076; p = .001), health condition (β = −.054; p = .006), and resilience (β = −.332; Multivariate analysis p < .001). In the next step, mental health was regressed using all at once predictors that were statistically significantly re- lated to mental health in the bivariate analysis. Discussion Results from the hierarchical regression analysis are To gain insight into the mental health of Belgian adults provided in Table 7. The eight control variables (gender, during the COVID-19 lockdown, this study investigated having children, living area, living space, employment some potential predictors of mental health and focused status, marital status, health condition, and resilience on the role of meaning in activities in particular. Based (CD-RISC)) were entered simultaneously into Model 1 on our results, we could confirm our hypothesis that meaningful activities do contribute to general mental Table 6 Overview bivariate analysis (3): Spearman correlation health in adults during COVID-19 lockdown. test: associations between mental health and continuous The COVID-19 pandemic caused significant changes independent variables in study sample (N = 1781) to peoples’ daily lives as their movements were restricted Spearman’s Rho P in an effort to slow down the spread of the virus. Faced EMAS −.547 <.001 with new realities of working from home, online meet- ings, temporary unemployment, home-schooling (of CD-RISC −.524 <.001 children), and lack of social contact with friends and Age −.254 <.001 family, the mental health of people was affected [64]. Ellen et al. BMC Public Health (2021) 21:622 Page 10 of 15 Based on the discussion of Allsop and colleagues [65], disruption turned into experiences of deprivation in the number of people suffering from mental health which the people were restricted from participation in problems during a major event is often greater than the necessary meaningful activities due to circumstances number of people suffering from physical problems. The outside their control [74]. results of our study showed low mental health among It can be presumed that the longer the COVID-19 Belgian adults, which is not unexpected as current pandemic lasted, the more difficult it was to remain sat- COVID-19 research showed similar results elsewhere. isfied with curtailed activities, and the more people lost Using the same instrument, GHQ, researchers from the meaning in these activities. Due to the imposed mea- United Kingdom Household Longitudinal Study sures, the form in which people were forced to perform (UKHLS) [66] did a comparison between mental health their activities was reduced to basic functions (e.g. the pre-COVID-19 and during COVID-19, they found that function of shopping is to ensure oneself of the adults had worse mental health during COVID-19 than necessary ingredients to stay alive) [73]. People became pre-COVID-19. A follow-up study found that, in the first task-oriented, yet were less likely to engage in creative COVID-19 wave 29.2% of their respondents scored thinking which is primarily driven primarily by enjoy- above the threshold on the GHQ, which indicates cases ment and a sense of meaning in activities [75, 76]. Con- of psychiatric disorder [67]. Furthermore, from April sequently, the form of the activities did not leave enough 2020 until June 2020, all sociodemographic groups room for aspects of meaning, such as shopping together showed significant increases in mental health problems for fun. This could thus be an explanation of why most in the UK [68]. of the participants experienced moderate meaning in ac- The loss of mental health can, according to our study tivities. Comparing this result with a normative adult results, be partly explained by the loss of meaning in ac- group that scored high in meaning in activities under tivities. Hierarchical regression showed that meaning in normal circumstances (M = 45,3), we can state that the activities (EMAS) accounted incrementally for 9.2% of COVID-19 lockdown caused a serious loss in meaning the variance in mental health (GHQ), beyond the effects in activities for Belgian adults [51]. Resilience was the of demographic and personal variables. The subjective second strongest contributor to mental health after experience of meaning associated with engagement in meaning in activity. These results are in line with other activity may be a key mechanism through which daily recent studies. In the face of COVID-19, people need to activities influence personal well-being and, according to cope with these ongoing stressors and minimize psycho- the study results, mental health [69–71]. As stated, logical distress [77]. Being resilient can protect against meaning in activities is a key outcome of human health these events and make it possible to thrive from adver- and well-being and our study demonstrated that this also sity [78–80]. In a COVID-19 study across healthcare and holds true during a pandemic, when anxiety and stress non-healthcare professionals, higher resilience scores prevail [42, 44]. were associated with lower COVID-19 related worries, As the forced adaptation to the lockdown measures as well as a reduced rate of anxiety and depression [14]. likely caused an unintended disruption or even (tempor- The demographic factors gender, having children, ary) loss of daily activities (e.g., work, hobbies) for most marital status, living space, and current health condition people (e.g., children, adults, and elderly), one might ex- contributed statistically significantly to lower mental pect that day-to-day living, behavior, and well-being health in our study sample. Women had lower mental might be blurred [4, 66]. People were forced to adapt health than men in this study, which is in line with other their daily activities, and activities that could not easily COVID-19 studies of mental health in women [13, 19, be adapted — such as volunteering work, student jobs, 20, 22]. Females’ sense of identity in activities is more af- and most affected of all, social activities outdoors — had fected by the social connections formed, rather than by to be discontinued [72]. At the start of the lockdown, other aspects in the activity setting [81]. Women seem people experienced the measures as a temporary disrup- to attach more meaning to social activities, which could tion of the situation and adapted by trying to find new hardly or no longer be carried out during COVID-19 ways to experience meaning in the performed activities lockdown, while men attach more meaning to physical by changing the form of the activity, searching for other activities that could still be performed during lockdown. activities, or changing their time investment in these ac- The care and household tasks, in which women are usu- tivities [73]. As the lockdown persisted, people struggled ally more active, interfered much more with other activ- to find meaning and started to attribute the negative ities than usual during lockdown. In Belgium, parenting effects of the measures to features beyond their control adults could request corona leave to manage the care of (e.g., people started blaming the government that the (home-schooled) children. Seventy-five percent of the measures were too hard). We thus assume, based on an parents who claimed the leave appeared to be women occupational therapy model, that the temporary [82]. In general, women were found to be more Ellen et al. BMC Public Health (2021) 21:622 Page 11 of 15 susceptible to mental health related symptoms than men mental health in our study sample of adults, it was not a because they show greater emotional response [27]. It can significant contributor for mental health in the multi- thus be concluded that women were found to be slightly variate analysis. This suggests that its explanatory power more vulnerable in terms of mental health than men. is limited compared to the other included predictors. It seems that being married during the COVID-19 Living in a rural area was associated with better mental lockdown helped respondents to have better mental health during the COVID-19 lockdown than living in an health. There is a considerable amount of evidence urban area, perhaps because it provides opportunities to showing that married people have better mental health take long walks outdoors and, be in nature, which posi- than never-married and divorced people [83, 84], which tively promotes mental health [88–96]. However, this is can be explained by the importance of the satisfaction contradicted in the study of Summer-Gabr [99] in the and support associated with such a dedicated relation- United States, where living in urban areas appeared to ship [85]. Our study results suggest that living alone show better mental health than people living in rural may be related to lower mental health during lockdown areas due to better access to health care and mental compared to adults who are widows or living together. health services. We speculate that the meaning and po- Previous research has also confirmed that living with a tential impact of a variable such as living area on mental partner is a protective factor for general psychiatric dis- health might be weakened in our study as Belgium is a orders during the COVID-19 crisis [67]. very small country in which the difference between rural Next, our study results demonstrated that chronically and urban areas is less manifest. This implies that other ill adults need to have specific attention. They are less factors, such as resilience and one’s engagement in affected in terms of mental health during the COVID-19 meaningful activities, might have a greater influence on lockdown compared to mentally and acutely ill adults. mental health. Moreover, it is remarkable that chronically ill persons Finally, participants without children had lower mental did not statistically significantly differ from healthy health than adults with children. This is contrary to the people. They may have been better able to adapt to the common findings in the current literature. A national changing situation in COVID-19 lockdown because they COVID-19 study in the US explained the low mental already experienced a loss of activity and prolonged iso- health in parents by the fact that parents reported wors- lation due to their illness, thus preparing them to be bet- ening behavioral health for their children [28] and un- ter able to cope with this crisis [86, 87]. stable financial circumstances, school closure, suspended To our knowledge, living space has not yet been de- educational services for children may underlie low men- scribed in the COVID-19 literature as a contributor to tal health in parents [100]. Our contrary results could be mental health. During the COVID-19 lockdown, the due to the fact that most of the participants who did not strict measures prohibited outdoor activities: people only have children in our study, were students who do not could leave the house to provide for the necessities of belong to the working adults group. life or to work if telecommuting was not possible. People An unexpected result is that work status was not sig- who lived with access to a garden or balcony, could go nificantly associated with mental health in the multivari- outside and do physical or psychological activities there. ate analysis, despite a bivariate association. COVID-19 It is already proven that (physical) activities in an out- studies have already shown that unemployed adults and door space can protect against mental health problems, students have a greater chance of being exposed to men- and restricted access is likely to have negative implica- tal health problems [19, 67]. Similarly, in our study, stu- tions for mental health [88–96]. People without the dents reported lower mental health compared to opportunity to go outside their house (e.g. no garden or employed and non-employed adults, and the latter two balcony) might have experienced deprivation, which groups did not differ substantially in terms of mental could cause the lower mental health we found in this health. These results might reflect that students were a study. Similar results were found in an epidemiological vulnerable subgroup during COVID-19 lockdown. Alter- study where the type of housing children inhabited al- natively, employment, as measured in our study, might tered mental health correlates [97]. High-rise multiple be too generic a variable, which neglects the type of job dwelling units are inimical to the mental health of one performs or its characteristics. It might be that men- mothers with young children because of the social isola- tal health is more influenced by the extent of remote tion and restricted play opportunities for children [97]. working and its interference with daily functioning at A study in low-income housing areas in London showed home. that having less access to private gardens was associated Remarkably, educational level was not significantly re- with a higher prevalence of depression [98]. lated to mental health in our study. This contradicts pre- Although we found a statistically significant bivariate vious studies that have shown people with higher association between living area (rural versus urban) and degrees (above bachelor’s level) experienced an increase Ellen et al. BMC Public Health (2021) 21:622 Page 12 of 15 in mental health problems at the time of the pandemic into account throughout lockdown decision-making pro- [26, 68]. Our result might be due to range restriction, as cesses and measures. the majority (76.6%) of our participants held a higher educational degree (University of Applied Sciences or Methodological considerations / limitations University). The presented results need to be interpreted with cau- Nevertheless, our study demonstrated that maintaining tion owing to some study limitations. First, because this or reconstructing meaningful activities during the study was initiated during the COVID-19 pandemic, we COVID-19 pandemic seemed to be an important path- could not rely on data from the Belgian population re- way to build a meaningful life in the context of profound garding resilience, mental health, and meaningful activ- disruption [101]. Increasing awareness of the importance ities from the period before the pandemic. As a of meaningful activities in daily life might lead to more consequence, comparisons were not possible and we widespread recognition of the potentially detrimental ef- were unable to capture changes or trajectories in mental fects of disruption and deprivation of such activities health or any of the identified predictors. when these occur [102]. Second, the GHQ-12 failed to be a clinical assessment The impact that isolation due to COVID-19 lockdown in this study. Results should be interpreted with caution has on people’s ability to achieve a sense of occupational and do not mean that people with low mental health balance, defined as a balance of engagement in occupa- have a mental illness [66]. tions that leads to well-being [103], is alarming. Occupa- Third, as our findings are based on a cross-sectional tional therapists thus have a critical role to play in research design, no causal statements can be inferred. helping people respond to this type of crisis [104], and Although the present study has shown that there is a leaders in the profession have articulated its relevance in strong positive relationship between meaningful activ- supporting mental health and wellbeing in populations ities and mental health in Belgian adults, further longitu- worldwide [101, 105, 106]. Occupational therapists have dinal studies are needed to investigate potential causal already learned a lot from their clients about how every- effects. day life might be rebuilt within constraining parameters Fourth, as the participants in our sample are not com- that are out of the client’s control. Our unique occupa- pletely representative of the whole Belgium population, tional focus can be central in identifying new and cre- future researchers might investigate the generalizability ative solutions in response to the unprecedented and of the study findings to other target groups and coun- challenging COVID-19 crisis, as we have the right know- tries as well. ledge and the creativity to respond to the massive impact Fifth, exclusively self-reported measures were used in of the COVID-19 pandemic on our clients and the gen- this study. These measures can cause common method eral population [104]. Providing meaningful activities variance, which can influence results [107]. The authors during social lockdown is an important point of atten- of this study did, however, take precautions to reduce tion that, in addition to health and economic aspects, this possible effect by indicating that there were no right should be taken into account when deciding on mea- or wrong answers, by guaranteeing anonymity, and by sures concerning COVID-19. using existing valid scales with sufficient internal To our knowledge, this is one of the first national consistency. Future research might incorporate ratings sample studies to consider a comprehensive set of fac- from multiple sources (e.g., peer ratings) or assess more tors that might contribute to adults’ mental health, and objective indicators and measures, in addition to subject- in particular, identified meaningful activities as a plaus- ive measures. Finally, another drawback of a self- ible key predictor of mental health during times of glo- reported online survey is that participants who have bal crisis. questions cannot address them directly to the re- searcher. To give participants the opportunity to raise Conclusion questions we did include, however, an open field ques- The findings suggest that sociodemographic factors, re- tion at the end of the survey (last question), for this pur- silience, and meaning in activities were associated with pose, and the contact details of the first author of this reduced mental health. Each of the seven identified fac- study were given at the start of the survey and partici- tors has to be taken into account to emerge from lock- pants were encouraged to e-mail with questions and down in a sustainable way and from a social perspective, comments regarding the survey as well. to maintain mental health. This study stressed the im- portance of activities during COVID-19 and raises a new Abbreviations idea that could be interesting for health policymakers COVID-19: Coronavirus Disease; WHO: World Health Organization; SARS: Severe Acute Respiratory Syndrome; H: Hypothesis; during and beyond COVID-19: besides economical and STROBE: Strengthening the Reporting of Observational Studies in health aspects, meaning in activities must also be taken Epidemiology; ICF: International Classification of Functioning, Disability and Ellen et al. BMC Public Health (2021) 21:622 Page 13 of 15 Health; GHQ: General Health Questionnaire; CD-RISC: Connor-Davidson Received: 17 December 2020 Accepted: 22 March 2021 Resilience Scale; EMAS: Engagement in Meaningful Activities Survey; VIF: Variance Inflation Factor; UKHLS: United Kingdom Household Longitudinal Study References 1. Nishiura H, Jung SM, Linton NM, Kinoshita R, Yang Y, Hayashi K, et al. 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