Associations between the lockdown group, free memory recall, and emotional responses during the COVID-19 lockdown: A global survey of 49 countries

Associations between the lockdown group, free memory recall, and emotional responses during the COVID-19 lockdown: A global survey of 49 countries | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Associations between the lockdown group, free memory recall, and emotional responses during the COVID-19 lockdown: A global survey of 49 countries Oyejide, AO, Besharati, SN, Alcock, S, Schioth, HB, Brooks, SJ This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5083107/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The unprecedented outbreak of the COVID-19 pandemic has altered the course of many lives, resulting in multiple health and social challenges. Due to the speed at which this pandemic spread, various public health ‘lockdown’ measures were introduced to mitigate its spread. The outcome of adherence to these measures has revealed the possible influence on individuals’ varying cognitive abilities. Accordingly, this study aimed to explore the predictive relationships between lockdown responses and COVID-19 restrictions, memory recall performance, and associated emotional responses while examining the sociodemographic influences of age and sex. Participants were drawn from a secondary dataset of an international online survey study of 1634 individuals aged 18–75 years across 49 countries. Participants’ demographic questionnaires, free memory recall, and hospital anxiety and depression scale scores were used to collect the data for analysis. Four-way MANOVA and hierarchical multiple regression were utilised to explore the mean differences and predict relationships between the study variables. Significant differences were found in memory recall performance and anxiety and depression scores across lockdown groups (the comply, sufferer, and defiant). Regression analysis indicated that age and gender were predictive markers of lockdown responses and anxiety (R2 = .14, F4,1625 = 66.15, p < .001, f2 = 0.17), while age was the only predictor of lockdown responses and depression association (b = -0.78, t(1625) = -4.35, p < .001). Lockdown compliance was associated with better free recall (M = 8.51, SD = 6.38, p < .001; 𝜂2 = .01), lockdown suffering was associated with greater anxiety (M = 9.97, SD = 4.36, p < .001; 𝜂2 = .06), and lockdown deviance was associated with greater depression (M = 7.90, SD = 3.12, p < .001; 𝜂2 = .05). The current study provides valuable information on the mechanisms of cognitive interpretations and emotional arousal in individuals’ social isolation responses to recent life stress and potential severe pandemics. This may support the need for robust interventions aimed at improving people’s psychological appraisals associated with anxiety in preparation for any new potential waves or future pandemics. Cognitive Neuroscience Psychology COVID-19 lockdown free memory recall anxiety depression public health measures Figures Figure 1 1. Introduction The growing threat of global pandemics has set the stage to further explore the role of sociobehavioural responses to public health compliances that are put in place to reduce the spread and contain such adverse and uncertain events 1 . The novel approach of collective social adherence to various social rules (e.g., country-level lockdown) has been identified as the most effective approach for mitigating the social problems associated with uncertain and threat-imposed global pandemics 2 , 3 . The outbreak of COVID-19 and its spread at an unprecedented speed necessitated imposed health measures to reduce the high morbidity and mortality rates. Different social adherence and preventative measures, such as social distancing, wearing masks, and hand washing, were geared toward reducing person-to-person transmission, with estimated higher compliance required to control the outbreak and reduce viral spread 4 . However, the effectiveness of these measures, which were initiated before widespread vaccine rollout, largely depended on individual responses and societal adherence to the imposed COVID-19 lockdown restrictions 5 , 6 . While the dynamics surrounding social adherence to pandemic rules are yet unknown, understanding social isolation measures has proven to be a valuable tool for mitigating disease spread and promoting sociobehavioural attitudes consistent with public health measures. During any viral infection, such as during the COVID-19 pandemic, the psychological reactions of the population, including social disorders and the prevalence of psychosocial diseases such as anxiety and depression, play an important role in disease spread 7 . The mental health outcomes of viral infections, such as the COVID-19 pandemic and the resulting strict lockdown measures, have resulted in negative impacts on the emotional and psychological health and well-being of individuals and communities that were directly and indirectly affected by the pandemic 8 . Consequently, because of limited access to mental and medical health resources, as well as inefficient primary healthcare infrastructure, especially in sub-Saharan Africa, there has been a high prevalence of anxiety and depressive symptoms. This spread was exacerbated by the COVID-19 pandemic and by prolonged stringent measures applied by public health institutions to mitigate this highly contagious pandemic 8 , 9 . Studies have shown the prevalence of psychological distress, specifically anxiety and depression 10 , 11 , during prolonged COVID-19 lockdowns. These restrictions were associated with social adherence measures such as reduced social interaction, specifically stringent social distancing and systematic quarantine. The consequence of such social adherence to lockdown rules has led to devastating mental health outcomes, including emotional distress, thereby exposing people to psychological risks and heightened levels of anxiety and depressive symptoms 12 . These outcomes have influenced individual and group social engagement and behavioural responses to the pandemic and its strict containment measures 13 , 14 . In addition, peoples’ behavioural responses to lockdown measures clearly suggest the possibility of stratifying them according to the classification of their behaviours 15 Furthermore, studies have suggested that the association between increased mental health symptoms (e.g., anxiety and stress) tends to modulate the encoding, consolidation, and retrieval of episodic memory processes 16 , 17 . The consensus that emotional episodic events are better remembered than neutral events further reinforces the significant influence of emotion in improving the encoding and consolidation of memory processes 18 , 19 . Previous studies have shown that emotional memory recall is better than neutral recall, especially for emotional memories with negative valences 20 , 21 . In light of this, research has shown that threatening events such as the COVID-19 pandemic and resulting lockdown measures may significantly modify memory recall in individual and group lockdown responses 1 . Additionally, widespread COVID-19 and extended quarantine days have been shown to influence populations’ emotional responses, such as fear of contagion and mortality, resulting in heightened stress, anxiety and depression 22 . As such, the relationship between emotional responses and episodic memory recall could be a contributor to anxiety and depressive symptoms among individuals of varying age groups and with different gender structures during the COVID-19 pandemic restrictions 23 . Episodic memory is a system involved in conscious awareness and recollection of events and personal experiences 24 . Literature has posited that varying behavioural outcomes and responses to COVID-19 lockdown measures may potentially influence an individual or group’s cognitive abilities, such as episodic memory recall 1 , 25 . Despite this, there is still a dearth of research on how pre-existing memory processes and profiles are influenced by individual and group responses to uncertain pandemics such as COVID-19 and its various social isolation measures. This phenomenon is especially prevalent globally, where limited studies have investigated how cognitive abilities, such as episodic memory recall, anxiety, and depression, are associated with varying responses to COVID-19 lockdown measures. The outcomes of recently recognised psychological responses to COVID-19 lockdown measures have shown that behavioural changes in individuals’ compliance levels to pandemic social restrictions are influenced by prevailing social stereotypes and cultural norms 15 , 26 . For example, a UK study showed that people commonly accepted lockdown rules (48%), followed by experiencing suffering (44%), and the least common group resisted the UK lockdown rules (9%). However, these responses could also influence people’s ability to correctly appraise their self-regulation strategies. These strategies could be linked to decision-making processes within the cognitive structures of individuals’ executive functioning capacity in terms of levels of cognitive flexibility and working memory capacity 25 , 27 . As elucidated by Del Missier et al . 24 , associations between memory and decision-making are evident when emotion-based judgments are executed under higher or lower cognitive loads. The operationalisation of this association highlighted the assumption that semantic response (a type of memory response that consists of factual information and meaningful knowledge properties) plays a fundamental role in background knowledge decision-making processes, while past experiences involve influences of episodic memory (a memory system involved in conscious awareness and recollection of events and personal experiences) 24 . This means that an association between memory and decision-making processes may influence the outcome of individual psychological or behavioural responses arising from new semantic frameworks and episodic content retrieval that are linked to social isolation during COVID-19 lockdown measures 28 , 29 . While various cross-sectional and reviewed studies 25 , 30 have focused on the psychological well-being and cognitive performance of individuals during the COVID-19 pandemic, we could not locate any study that specifically investigated the association between memory recall processes and social adherence during the lockdown period, especially within the broader global survey study. Our study aimed to investigate the associations between lockdown group responses to COVID-19 restrictions and free memory recall and between associated anxiety and depression levels in participants drawn from 49 different countries across the globe. Additionally, the study further explored the predictive effect of age and gender on the relationships between these constructs. Research has shown the effects of age and gender differences on auditory and visual episodic memory performance among younger and older adults 31 , 32 . While contributing to the body of knowledge, our study predicted that there would be significant differences across lockdown group responses (comply, sufferer, defiant) on free memory recall and associated emotional responses related to anxiety and depression. Furthermore, we hypothesised that age and gender would predict the associations between COVID-19 lockdown group responses and free memory recall, and between anxiety and depression. 2 Results 2.1 Effect of lockdown group response on memory recall and associated emotional profiles As hypothesised, we found significant differences (ranging from small to medium effect sizes) in the lockdown group responses on free memory recall ( F 2,1594 = 6.67, p < .001, 𝜂 2 = .01), anxiety ( F 2,1594 = 53.27, p < .001, 𝜂 2 = .06), and depression ( F 2,1594 = 41.64, p < .001, 𝜂 2 = .05). The significant associations were weak across the results, particularly in the case of free memory recall, which had the weakest effect size. As shown in Table 2 , in particular, our sample perceived significantly better memory recall in the comply group ( M = 8.51, SD = 6.38) than in the sufferer ( M = 7.83, SD = 6.11) and defiant ( M = 5.69, SD = 6.69) groups. Examining the changes in the emotional profiles of the participants in the lockdown group, we found significantly greater anxiety levels in the sufferer group ( M = 9.97, SD = 4.36) than in the defiant ( M = 9.78, SD = 3.22) and comply ( M = 7.29, SD = 4.02) groups. Furthermore, a significantly greater level of depression was recorded in the defiant group ( M = 7.90, SD = 3.12) than in the sufferer ( M = 7.41, SD = 3.80) and comply ( M = 5.62, SD = 3.61) groups. Table 1 Differences in memory recall and emotional profiles between lockdown groups Dependent variable Lockdown group comparison Mean difference Sig. 95% Confidence Interval I J LB UB Free memory recall comply sufferer 0.59 .127 − .168 1.347 comply defiant 2.652** .000 1.203 4.101 sufferer defiant 2.062* .006 .598 3.527 Anxiety sufferer comply 2.434** .000 1.959 2.909 defiant comply 2.184** .000 1.276 3.093 sufferer defiant .249 .594 − .669 1.167 Depression sufferer comply 1.872** .000 1.436 2.308 defiant comply 2.314** .000 1.480 3.147 defiant sufferer .442 .304 − .401 1.284 Note. N = 1630. Sig. = significance. ** = p < .001. * = p < .05 2.2 Relationships between sociodemographic factors, free memory recall, anxiety, and depression The full regression model of lockdown group responses and the sociodemographic variables age and gender significantly predicted free memory recall ( F 4,1625 = 9.15, p < .001). When sociodemographic variables were introduced into the model (adjusted R 2 = .020, F (4, 1623) = 0.99, p = .371), the adjusted R 2 values were minimal, indicating that only 2% of the variance in memory recall was explained by the predictors. The associated F -statistic for the predictors added was non-significant, suggesting that including age and gender did not improve the model’s ability to explain variance in memory recall over what was accounted for by the lockdown group alone. Furthermore, only the lockdown group variables, sufferer group ( \(\:b\) = -0.75, t (1623) = -2.18, p = .030) and defiant group ( \(\:b\) = -2.71, t (1623) = -5.69, p < .001), were significantly different, as shown in Table 3. These results suggest that although the full model was significant, sociodemographic variables were not significant predictors of the relationship between lockdown group response and free memory recall in this study. Furthermore, as reported in Table 3, age and gender were shown to predict the relationship between the lockdown group and anxiety. The hierarchical regression showed a statistically significant model at both steps of the model analysis. The results showed a total variance of 13.8%, explained by the full model ( R 2 = .14, F 4,1625 = 66.15, p < .001, f 2 = 0.17). When controlling for lockdown group response in the full model, both age ( \(\:b\) = -1.25, t (1625) = -6.36, p < .001) and gender ( \(\:b\) = -1.52, t (1625) = -7.55, p < .001) had statistically significant effects on anxiety. The results regarding the effect of age on the association between the lockdown group and anxiety, therefore, suggest that younger adults appear to be more anxious in their response levels during COVID-19 lockdown measures than older adults are. Similarly, the regression results further showed that females had greater anxiety in their lockdown response levels than males did. The full model of the lockdown group, age and gender in predicting depression also showed a statistically significant result ( R 2 = .080, F 4,1625 = 34.85, p < .001, f 2 = .09). These results suggested that sociodemographic factors predict the association between lockdown group response and depression. However, while investigating the variable(s) that contributed to this significant prediction when controlling for the lockdown group in the analysis, age was the only significant predictor ( \(\:b\) = -0.78, t (1625) = -4.35, p < .001), and gender was a nonsignificant predictor ( \(\:b\) = -0.13, t (1625) = -0.69, p = .490). This result, therefore, suggested that younger adults in this study were more likely to be depressed than older adults were, as shown in Table 3. Table 2 Results of the regression model predicting the lockdown group and emotional profiles Variable Free memory recall Anxiety Depression b 95% CI \(\:\varvec{\beta\:}\) b 95% CI \(\:\varvec{\beta\:}\) b 95% CI \(\:\varvec{\beta\:}\) Intercept 8.79** [8.13, 9.44] 8.78** [8.36, 9.19] 6.06** [5.68, 6.43] COVID-19 lockdown group (ref. comply group) Sufferer group 0.75* [-1.42, -0.07] -0.06 2.48** [2.06, 2.90] 0.28 1.82** [-1.43, 2.20] 0.24 Defiant group -2.71** [-3.64, -1.77] -0.15 2.72** [-3.64, -1.77] 0.22 2.31** [1.77, 2.84] 0.21 Sociodemographic variables Age -0.13 [-0.74, 0.49] -0.01 -1.25** [-1.64, -0.87] -0.15 -0.78** [-1.13, -0.43] -0.10 Gender -0.45 [-1.08, 0.18] -0.04 -1.52** [-1.92, -1.13] -0.18 -0.13 [-0.49, 0.23] -0.02 Regression statistically significant results F (4, 1625) 9.15** 66.15** 34.85** t value 26.20** 41.75** 31.54** Change in R 2 0.001 0.03 0.01 R 2 0.02 0.14 0.08 Note. N = 1630. b = unstandardised regression coefficient; \(\:\beta\:\) = standardised regression coefficient; CI = confidence interval. ** p < .001. * p < .05. 3 Discussion Our findings revealed significant associations between free memory recall, anxiety, and depression across lockdown group response levels. Individuals in the compliant group had better free recall, those in the sufferers group had significantly greater anxiety, and those in the defiant group had greater depression symptoms during the 2020 period of the global COVID-19 lockdown. Age and gender were also significant predictors of anxiety in the lockdown group. Another important finding was that none of the sociodemographic variables, specifically age and gender, were significant predictors of lockdown group responses and free memory recall relationship. The rationale of this study was to provide insight into the mechanisms of semantic coding associated with free recall memory and how these mechanisms influence varying individual and group compliance responses to pandemic lockdown restriction measures. Additionally, the study showed the intriguing influence of emotional content on the neural processes of individuals and the group’s psychological outlook on social isolation measures. The significant association between lockdown group responses and free memory recall showed that the comply group exhibited better memory recall than the sufferer and defiant groups. This means that the overall memory recall performance of the individuals in the comply group (those who easily adhered to group/social norms and COVID-19 lockdown rules) indicated a positive recency effect on their delayed recall tasks. This effect tapped into a more stable long-term storage mechanism component of the free recall performance, which is mainly affected by semantic coding 33 , 34 . The storage mechanism component is unaffected by the rehearsal-preventing task of delayed recall; as such, correctly recalling texts from the beginning of the passage was more prevalent in the long-term storage component than the short-term storage mechanism of single-trial free recall, which also reflects a recency effect but with immediate recall of the recently rehearsed texts from the end of the passage. It must be noted, however, that, based on the nature of the online survey used in this study, the assumption was that participants engaged the recency effect of delayed recall with distinctively long pauses (between 20 and 30 seconds) that preceded their recall response – a unique response time associated with free recall memory tasks 35 . In light of this, interpretation of this finding was considered in the context of this observation. The significant findings across the lockdown group could be attributed to cognitive interpretations of individual/group variations as an indication of significant free memory recall performance findings 36 . In light of these cognitive variations, it was not unexpected that free memory recall performance between the comply and sufferer groups indicated non-significant differences in memory recall. However, performance significantly differed between the comply and defiant groups and between the sufferer and defiant groups. Another possible reason for this can be attributed to the impact of recent life stress (such as the COVID-19 pandemic) on the cognitive process of the participants. The outcome of this stress, reflected as either acute or chronic, was assumed to impair the retrieval process within the memory recall capacity. As a result, the recall process impinges upon individual episodic memory content, which happens to be the seat of the long-term storage mechanism of the free memory recall task 37 . This finding indicates that recent life stress, which might be more pronounced in the suffering and defiant groups than in the compliant group in our study, has the potential to limit the capacity of long-term storage mechanisms, especially when individuals or groups are faced with life-threatening psychological and emotional challenges. The COVID-19 pandemic could presumably exert substantial effects on the memory retention and retrieval abilities of individuals with cognitive variations necessary for decision-making responses 38 . Age-related decreases in cognitive function could also be attributed to the significant effect of these outcomes. The participants’ sample distribution across different age cohorts showed a positively skewed distribution of their free memory recall scores. Therefore, it was not unusual to expect significant age differences to be associated with the memory recall performance of respondents across lockdown groups in this study. This was prevalent with reference to reduced inefficient recall and retrieval performance of the episodic content of the long-term memory store 39 . Although evidence-based results have lent support to this assumption 40 , 41 , the experimental studies of Craik 42 and Raymond 43 foreground the assumption that the effectiveness of memory recall from long-term storage of episodic memory is affected by successive age-related increases, including the length and stimulus size of the recalled vocabulary or text 44 . This finding suggested that there may be certain differential and ineffective cognitive functioning processing in older adults compared to younger adults. This was due to poor retrieval and selective decline in performance from the long-term storage mechanism of episodic memory 45 . This study also revealed important significant findings on anxiety and depression across lockdown groups. The results showed that the sufferer group experienced greater anxiety symptoms than the defiant and comply groups. In comparison, the defiant group displayed greater depressive symptoms compared to the sufferer and comply groups. These findings suggested that both anxiety and depressive symptoms were significantly associated across the lockdown group responses. These findings are consistent with previous literature and systematic reviews, especially on COVID-19 behavioural and cognitive responses to social isolation measures 10 , 25 , 26 . While depressive symptoms decreased across the lockdown response levels compared to heightened anxiety levels, the effect sizes of both anxiety (𝜂 2 = 0.63) and depression (𝜂 2 = 0.50) across group responses were relatively modest. Nevertheless, the significant differences in emotional responses across the lockdown groups could be due to several reasons. First, the global lockdown disrupted people’s personal, financial, and social lives, resulting in a negative psychological outlook. Moreover, the extended ‘sit-at-home’ lockdown restrictions might have elevated individual anxiety and depressive responses. This might have been more prevalent in the sufferer group because of their assumed financial difficulty and low optimism during the pandemic lockdown. This might further aggravate their anxiety levels because of agitation and lower optimism in the government’s response to controlling disease spread. This explanation is consistent with recent literature on the exacerbated emotional levels of anxiety, stress, and depressive symptoms in people during the COVID-19 pandemic, which has resulted in maladaptive coping responses across individuals and group outcomes 36 , 46 . Additionally, the role of misinformation due to high social media exposure and usage, including emerging conspiracy theories on COVID-19 infections and treatments 47 , 48 , could also be attributed to significant differences in emotional content across lockdown groups. Frequent social media usage and lack of government plans to respond adequately to changing scientific information (leading to misinformation) might have negatively influenced people’s emotional state toward inappropriate responses to pandemic lockdown measures. For instance, the defiant group, which was susceptible to high social media exposure and usage, was linked to greater depressive symptoms in our study. This finding is consistent with recent studies that postulated the significant association of increasing misinformation, conspiracy theories, and fake news on COVID-19 infections and outcomes with heightened emotional and psychological responses 49 , 50 . In light of the reviewed literature and hypothesis that stated that significant differences exist between lockdown group responses to COVID-19 social restriction measures on participants’ emotional content of anxiety and depression, the findings of this study therefore offer consistent support for the body of knowledge in favour of the significant effects of these measures on emotional responses to COVID-19 lockdown measures. Consistent with the findings of recent studies 27 , 51 , our regression analyses showed that age significantly predicted the associations between lockdown group responses and emotional responses to anxiety and depression. The negative prediction of the result suggested that younger adults were more exposed to heightened levels of anxiety and depression than older adults were. An explanation for this could be that older individuals have the emotional capacity or greater memories of overcoming past difficulties, to contextualise a stressor, such as the outcome of the COVID-19 lockdown measures, which helps them maintain a more stable emotional balance than younger individuals 52 . Additionally, older adults tend to have a more mature social disposition and better financial support base, such as better-paying jobs, which might reduce the context of emotional imbalance than younger adults. Furthermore, gender significantly predicted group responses and anxiety relationship. Compared to males, females showed higher anxiety symptoms, which was consistent with the findings of previous studies indicating a significant increase in anxiety observed in females 53 , 54 . A potential explanation for this could be because of the assumptions that females bear more disproportionate domestic and caregiving responsibilities than men, especially during the pandemic period, such as during the COVID-19 social isolation, which results in contextually skewed gender divisions of labour in society, including household settings 55 , 56 . As a result, females could be considered more susceptible to increased anxiety and depressive symptoms. Social isolation measures such as restricted physical mobility during the pandemic could also increase females’ exposure to domestic violence and hostile experiences. This could exacerbate their emotional disturbance levels, especially in areas where gender violence practices and narratives are prevalent, such as sub-Saharan Africa, including Southern Africa 57 – 59 . 4. Materials and Methods 4.1 Participants This study was nested within an existing dataset of a larger international online survey study conducted between July and September 2020 on Prolific and Qualtrics online survey platforms. The sample consisted of participants from 49 countries in Africa, Asia, Europe, North America, and South America. A larger study utilised non-probability, convenience, and snowball sampling methods. No restrictions were imposed on referring friends or family members, as participation was voluntary. Brief information about the aims of this study was provided online to all participants. Informed consent was obtained online from all participants before data collection. Furthermore, participants were eligible if they were adults aged 18–75 years, had no psychological conditions as declared by each participant, and could speak and write in English. Among the total valid sample size of 2309 participants, 1634 respondents were classified as eligible. Participants were excluded due to incomplete online surveys (n = 613), missing data on age (n = 29), insufficient data on non-binary sex (n = 18), or missing education (n = 15). 4.1.1 Sociodemographic and lockdown response characteristics The demographic characteristics of the sample (N = 1634) are summarised in Table 1 . The participants’ ages ranged from 18 to 74 years ( M = 28.60, SD = 10.92). There were slightly more younger adult participants (50.6%) than older adults (49.4%). Most participants self-identified as male (54.30%), were from Europe (80.20%), and fell within the comply lockdown grouping (48.96%). The comply group had the most participants (n = 800), followed by the sufferer group (n = 600), while the defiant group (n = 227) had the lowest participant grouping. Table 2 Sociodemographic characteristics and COVID-19 lockdown group distribution Demographic variables Group n % Age M(SD) : 28.60(10.92) Range: 18–25 Younger adults 827 50.60 Range: 26–74 Older adults 807 49.40 Gender Female 747 45.70 Male 887 54.30 Continental grouping Europe 1308 80.20 North America 155 9.50 South America & the Caribbean 109 6.68 Africa & Middle East 46 2.82 Asia & Australasia 13 0.80 Lockdown group Comply group 800 48.96 Sufferer group 607 37.15 Defiant group 227 13.89 Note. Total N = 1634 for all variables except for continental grouping ( N = 1631); M = mean; SD = standard deviation. 4.2 Instruments 4.2.1 Demographic and COVID-19 Experience Questionnaire The survey used self-reporting questionnaires consisting of two sections. In the first section, participants' sociodemographic data, specifically age range and sex (binary classification), were collected. Participants’ sex classification was self-reported by each of the participants. The second section utilised the 54-item COVID-19 experience questionnaire created by the authors, which was based on a previous study that identified 3 lockdown response groups in the UK from King’s College, London 15 . The questionnaire (available on request) was used to assess lockdown responses in this cohort. The questionnaire was answered on a 5-point Likert scale, and assessed participants’ beliefs, attitudes, and behaviours around COVID-19 pandemic characteristics and government-imposed lockdown measures 36 . Accordingly, three lockdown groups were categorised based on the K-means cluster analysis of the questionnaire scores (see below), namely: (1) the Comply group (CG): people with higher adherence to group/society norms and stereotypes; (2) the Sufferer Group (SG): those who adhered to lockdown rules with some deviations and were known to possess conflicting outlooks on social norms; and (3) the Defiant Group (DG): those with a negative outlook on COVID-19 lockdown restrictions and low adherence. This classification aligned with the three groups identified by another study 15 . 4.2.2 Memory Recall. An online self-administered memory test was measured by a free memory recall test (FMRT), which is adapted for online administration. The adapted FMRT assessed memory recall of previously memorised statements of unrelated or coupled textual words that contained concreteness, emotionality, and neutrality 60 , 61 . The FMRT consists of 30 bold selected words (e.g., viral, swarming, quack) within the passage; these words are made available to participants to recall by writing as many bold letters as they remember after an overt rehearsal of the passage after 20–30 seconds. The bold text to be recalled represents categories of concrete (e.g., door), abstract (e.g., silence), neutral (e.g., ordinary), and emotional (e.g., viral) words to test participants’ memory recall performance. The bold text recall did not have to follow the sequence as it appeared in the passage. Since it was an online assessment, the bold text recalled was to be written down in the provided online space. Additionally, spelling errors were not accounted for, but synonyms were not recorded as the correct answer to the bold text. Participants were not given specific time to recall the bold text, but it was assumed that the recall would be quicker since it was part of an online data collection activity. The FRMT scores ranged from 0 to 30, with each correctly recalled word given one point. The FRMT has a strong internal consistency reliability of .71 61 . 4.2.3 Anxiety and Depression. The presence of anxiety and depression was measured by the Hospital Anxiety and Depression Scale (HADS) 62 . It is a brief self-assessment emotion questionnaire designed to assess symptoms of anxiety and depression within non-psychiatric hospital settings 63 . It comprises two subscales for anxiety and depression, each having seven items (closed format) of a 4-point Likert scale (0–3), with a range of 0–21 for each subscale 64 . A higher total score indicates a greater severity of anxiety and/or depression. Scores ranging from 0–7 are in the normal range; 8–10 as mild or borderline; 11–14 as moderate; and 15–21 as severe self-reports of anxiety and/or depression 65 . The HADS subscales are considered a justifiable measure of severity, with reliability measures ranging from .83 to .93 for anxiety and from .74 to .90 for depression 63 , 66 . The Cronbach’s reliability coefficient for the HADS in this study was .80 for anxiety and .74 for depression. 4.3 Data analyses 4.3.1 K -means cluster analysis The creation of a lockdown response variable in this study was adopted in line with the online survey study through a k -means cluster analysis. The larger international online study performed an exploratory factor analysis on the 54 lockdown items that assessed participants’ beliefs, attitudes, and behaviours related to COVID-19 pandemic characteristics and government-imposed lockdown measures 36 . Principal component analysis (PCA) was also performed on the lockdown-related questionnaires, which were answered on a 5-point Likert scale covering statements such as adherence to lockdown instructions, self-medication approach, beliefs around COVID-19, participants’ well-being during the pandemic lockdown, individual’s non-pandemic health behaviours, belief and perception about the future, level of trust in government, and use of social media during the lockdown. Cluster analysis was further performed using varimax rotation and Kaiser’s criterion normalisation and extraction, with analysis of eigenvalues greater than 1 67 . The outcome of the analysis was plotted “k” within 30 iterations for 2, 3, and 6 factors, whereby the cluster analysis of k = 3 was chosen as the optimal cluster division for maintaining meaningful population size, as well as in alignment with the previous online survey study 15 , 36 . The identification of the COVID-19 lockdown group in this study (slightly modified to include the ‘comply group’, ‘sufferer group’ and ‘defiant group’) therefore showed how each grouping characteristic informed the cognitive (specifically, free memory recall), emotional, and neural processes underlying psychological responses to the COVID-19 lockdown rules. 4.3.2 Statistical analyses Multivariate analysis of variance (MANOVA) was also conducted to analyse the significant differences in the means and effect sizes of COVID-19 lockdown groups, age, and gender on the outcome variables of free memory recall, anxiety, and depression. Furthermore, the associations between lockdown group responses and free memory recall, anxiety, and depression were determined through hierarchical multiple linear regression analysis. Parametric assumptions for all the statistical analyses above were considered and met or adjusted using inferred random sampling, and a sample size normality distribution 68 , 69 was used before the analyses were conducted. Additionally, running a 4-way MANOVA test comes with added assumptions such as the absence of multicollinearity, no univariate or multivariate outliers, equal population covariance matrices, homogeneity of variance, and multivariate normality residuals for all dependent variables. Although the homogeneity of variance covariance and part of Levene’s test were violated, research has shown that Box’s M can be stricter and sensitive to the equality of covariance when the sample size is large; as such, violation of assumptions is not unusual within social science research 70 . Since these two assumptions were thus violated and because of the robust method of MANOVA tests, the interpretation of the statistical tests was derived from Pillai’s Trace results rather than from Wilk’s Lambda 70 , 71 . Outliers were statistically analysed using Cook’s and Mahalanobis distances of 18.47 for the 4 independent variables. All the assumptions for conducting multiple regression were checked, and all the assumptions were met. The residual errors were further normally distributed and fulfilled for each dependent variable. A stepwise hierarchical multiple linear regression analysis was utilised to depict the stepwise changes in the effect of the prediction between the focal independent variable and demographic variables on the dependent variables 72 . The data analysis was performed using IBM SPSS statistics version 27 73 , and the value of alpha (α) was set at .05 as a threshold for all the statistical tests, with Bonferroni corrections applied when necessary to account for multiple comparisons. The adjusted alpha level for the Bonferroni comparison was .0125, which was further used to assess the level of statistical significance between the dependent variables. A Bonferroni post hoc analysis was performed on all the significant findings to determine the significance of the effects of the independent variables on the dependent variables. 5. Strengths and Limitations A major strength of this study is that it provides informative data linking COVID-19 lockdown responses and cognitive-emotional performance. This may improve our understanding of public perceptions that consequently inform responses to social isolation measures in the face of a severe viral pandemic. As such, this study was able to add to our understanding of cognitive-emotional processes that are involved in people’s behavioural and decision-making responses in the course of prolonged lockdown restriction measures during the pandemic. These data could inform strategies for improving and maintaining individual and group behavioural responses to future pandemics or other global crises. In terms of methodological rigour, the strength of this study was its use of k -means cluster analysis to classify the lockdown groups based on similar responses on compliance to lockdown rules 15,36 . The use of k -means also assisted in grouping individuals with similar traits to allow for correct analyses and to describe information and patterns that are specific and representative of the group traits within the cluster analysis 74 . However, our study has a few limitations. First, the primary goal of this study was exploratory, where statistical analyses were designed to explore the relationships between variables of interest. The context of the study was also cross-sectional. Hence, its exploratory nature did not allow us to ascertain precisely defined hypotheses, while its cross-sectional outlook limited the ability to draw causal conclusions from the findings of the study. Future studies should use a longitudinally designed approach to enhance the precise evaluation of cognitive-emotional performance and responses of the sample in relation to COVID-19 lockdown measures. Another limitation was that despite the large sample size, the total sample could not be determined to be representative of all the nationalities represented. Specifically, there were significant variations in sample representation across the continental regions, with Europe having the dominant sample size, while Africa, Asia, and Australasia were sparsely represented. With respect to this, caution should be exercised, as the generalisability of the findings to other cultures is limited. In conclusion, this study revealed that common global behavioural responses to COVID-19 lockdown measures during 2020 were compliance, suffering, and defiant, and that complying with these rules was associated with better cognitive performance on a recall test. Moreover, those who suffered during the pandemic had greater levels of anxiety, whereas those who were defiant and had greater engagement with social media reported higher levels of depression. Younger females were more susceptible to anxiety. In sum, these data may help to provide additional assistance to members of society who might face cognitive and emotional difficulties in response to threats and challenges in future global crises. Declarations Ethical clearance was obtained from the University of the Witwatersrand Human Research Ethics Committee (non-medical; protocol number: MASPR/21/08) and the Liverpool John Moores University Research Ethics Committee (approval code 20/NSP/035) to conduct this online survey research study. References Leon, C. S. et al. Impairment of aversive episodic memories during Covid-19 pandemic: The impact of emotional context on memory processes. Neurobiology of Learning and Memory 187 , 107575 (2022). https://doi.org/https://doi.org/10.1016/j.nlm.2021.107575 Esterwood, E. & Saeed, S. A. Past epidemics, natural disasters, COVID19, and mental health: Learning from history as we deal with the present and prepare for the future. Psychiatric Quarterly 91 , 1121-1133 (2020). https://doi.org/10.1007/s11126-020-09808-4 Sturman, D., Auton, J. C. & Thacker, J. Knowledge of social distancing measures and adherence to restrictions during the COVID-19 pandemic. 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Frontiers in Global Women's Health 1 (2020). https://doi.org/10.3389/fgwh.2020.00004 Gruenewald, P. J. & Lockhead, G. R. The free recall of category examples. Journal of Experimental Psychology: Human Learning and Memory 6 , 225-240 (1980). https://doi.org/10.1037/0278-7393.6.3.225 Rubin, D. C. & Friendly, M. Predicting which words get recalled: Measures of free recall, availability, goodness, emotionality, and pronunciability for 925 nouns. Memory & Cognition 14 , 79-94 (1986). https://doi.org/10.3758/BF03209231 Zigmond, A. S. & Snaith, R. P. The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica 67 , 361-370 (1983). https://doi.org/10.1111/j.1600-0447.1983.tb09716.x Bjelland, I., Dahl, A. A., Haug, T. T. & Neckelmann, D. The validity of the Hospital Anxiety and Depression Scale: An updated literature review. Journal of Psychosomatic Research 52 , 69-77 (2002). https://doi.org/10.1016/S0022-3999(01)00296-3 Snaith, R. P. The Hospital Anxiety And Depression Scale. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5083107","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":353580695,"identity":"f1ec4a25-fe6b-414e-93d5-0b94fa3c8707","order_by":0,"name":"Oyejide, AO","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABGElEQVRIie2PP0vDQBiH3/BCXCLn+GZJvsKFQHGQfJYLB+2SUqdOIk7tUu1qv0WnrJ4E2qU4ZywUMp8IooN/rlVKh5PgJnjPcNx78Nzv9wI4HH8SsT1od+XChwjwt0oK2OqIw8GH/Kotho3lQj8Wp8BIqvP18Kw3X7JKw0UG8VhZFVo1cjYrCcLbruDiodufV+gTLCR4E2FVoC5SPDYKrwvO81HVL41iGirTz67E9eAJ33bKQBvlo9epEDW8K/DZ2qqYzxG9rxQwihJGAfJGCgKypySrJvWuSwrCScPNLjK5q7BD+Y0MiOwp0VJu4LW8jNiRbJKXYRaH0/uN1s9ZFE9/WP+bAE6Ez/ej2L60whTaizgcDse/5xNMbliU8qd0SgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-4137-831X","institution":"Wits School of Education, University of the Witwatersrand, South Africa.","correspondingAuthor":true,"prefix":"","firstName":"AO","middleName":"","lastName":"Oyejide","suffix":""},{"id":353583839,"identity":"cdfb51c2-effe-4ec0-9131-8d515926156b","order_by":1,"name":"Besharati, SN","email":"","orcid":"https://orcid.org/0000-0003-2836-7982","institution":"Department of Psychology, University of the Witwatersrand, South Africa.","correspondingAuthor":false,"prefix":"","firstName":"SN","middleName":"","lastName":"Besharati","suffix":""},{"id":353583840,"identity":"9e6d8d1d-ca29-4118-bb11-7afda0011ff0","order_by":2,"name":"Alcock, S","email":"","orcid":"https://orcid.org/0000-0002-9655-0909","institution":"SAMRC Developmental Pathways for Health Research Unit, Department of Pediatrics, University of the Witwatersrand, South Africa.","correspondingAuthor":false,"prefix":"","firstName":"S","middleName":"","lastName":"Alcock","suffix":""},{"id":353583841,"identity":"59f75978-c079-4a65-bd21-83b41f7587f6","order_by":3,"name":"Schioth, HB","email":"","orcid":"https://orcid.org/0000-0001-7112-0921","institution":"Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Sweden","correspondingAuthor":false,"prefix":"","firstName":"HB","middleName":"","lastName":"Schioth","suffix":""},{"id":353583842,"identity":"220ae11c-182f-4405-9d4c-9283f4aa105f","order_by":4,"name":"Brooks, SJ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYDCCA1DagIEHRCUw8IOpAsJaJOBaJBtAlAEpWgwOQCzFCfhuH3/46UbNnTpz9rPHPnyoSLM3Pr868cMDAwZ5frEDWLVInssxls459kzCsicveeaMMzmJ22683SwBdJjhzNkJWLUYnOFhkM5hOyxhcCDHmJm3rSLB7MbZDSAtCQa3cWlhf/w75x9Qy/k3YC32xjPObv6BXwuDmXRuG1DLDbAtOYwb+Hu34bVF8gyPmXVu32HJDTfeJTPOOJOWOOMG7zaLBAMJnH7hAzrsds63w/wG53MPM3yoSLbn7z+7+eaPCht5fmnsWrAACbBKCWKVgwD/AVJUj4JRMApGwQgAAIC9ZOsoN2Q7AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-9146-6257","institution":"Liverpool John Moores University, School of Psychology, Faculty of Health, UK.","correspondingAuthor":true,"prefix":"","firstName":"SJ","middleName":"","lastName":"Brooks","suffix":""}],"badges":[],"createdAt":"2024-09-13 10:35:49","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5083107/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5083107/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65305751,"identity":"04d13381-02f2-408b-824d-d8d5f67de075","added_by":"auto","created_at":"2024-09-26 01:10:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75349,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMap of the 49 participating countries with total sample size. (N = 2273). We did not obtain samples from countries in grey.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5083107/v1/6cbeca76f3e943b3c753de09.png"},{"id":65306190,"identity":"67e77787-fea2-44ba-b366-5d4d7fcb3266","added_by":"auto","created_at":"2024-09-26 01:18:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":946786,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5083107/v1/5f421cfb-976d-40e2-adf4-b1b201b1132b.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssociations between the lockdown group, free memory recall, and emotional responses during the COVID-19 lockdown: A global survey of 49 countries\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe growing threat of global pandemics has set the stage to further explore the role of sociobehavioural responses to public health compliances that are put in place to reduce the spread and contain such adverse and uncertain events\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The novel approach of collective social adherence to various social rules (e.g., country-level lockdown) has been identified as the most effective approach for mitigating the social problems associated with uncertain and threat-imposed global pandemics\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The outbreak of COVID-19 and its spread at an unprecedented speed necessitated imposed health measures to reduce the high morbidity and mortality rates. Different social adherence and preventative measures, such as social distancing, wearing masks, and hand washing, were geared toward reducing person-to-person transmission, with estimated higher compliance required to control the outbreak and reduce viral spread\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, the effectiveness of these measures, which were initiated before widespread vaccine rollout, largely depended on individual responses and societal adherence to the imposed COVID-19 lockdown restrictions\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. While the dynamics surrounding social adherence to pandemic rules are yet unknown, understanding social isolation measures has proven to be a valuable tool for mitigating disease spread and promoting sociobehavioural attitudes consistent with public health measures. During any viral infection, such as during the COVID-19 pandemic, the psychological reactions of the population, including social disorders and the prevalence of psychosocial diseases such as anxiety and depression, play an important role in disease spread\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe mental health outcomes of viral infections, such as the COVID-19 pandemic and the resulting strict lockdown measures, have resulted in negative impacts on the emotional and psychological health and well-being of individuals and communities that were directly and indirectly affected by the pandemic\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Consequently, because of limited access to mental and medical health resources, as well as inefficient primary healthcare infrastructure, especially in sub-Saharan Africa, there has been a high prevalence of anxiety and depressive symptoms. This spread was exacerbated by the COVID-19 pandemic and by prolonged stringent measures applied by public health institutions to mitigate this highly contagious pandemic\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eStudies have shown the prevalence of psychological distress, specifically anxiety and depression\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, during prolonged COVID-19 lockdowns. These restrictions were associated with social adherence measures such as reduced social interaction, specifically stringent social distancing and systematic quarantine. The consequence of such social adherence to lockdown rules has led to devastating mental health outcomes, including emotional distress, thereby exposing people to psychological risks and heightened levels of anxiety and depressive symptoms\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. These outcomes have influenced individual and group social engagement and behavioural responses to the pandemic and its strict containment measures\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In addition, peoples\u0026rsquo; behavioural responses to lockdown measures clearly suggest the possibility of stratifying them according to the classification of their behaviours\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurthermore, studies have suggested that the association between increased mental health symptoms (e.g., anxiety and stress) tends to modulate the encoding, consolidation, and retrieval of episodic memory processes\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The consensus that emotional episodic events are better remembered than neutral events further reinforces the significant influence of emotion in improving the encoding and consolidation of memory processes\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Previous studies have shown that emotional memory recall is better than neutral recall, especially for emotional memories with negative valences\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In light of this, research has shown that threatening events such as the COVID-19 pandemic and resulting lockdown measures may significantly modify memory recall in individual and group lockdown responses\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Additionally, widespread COVID-19 and extended quarantine days have been shown to influence populations\u0026rsquo; emotional responses, such as fear of contagion and mortality, resulting in heightened stress, anxiety and depression\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. As such, the relationship between emotional responses and episodic memory recall could be a contributor to anxiety and depressive symptoms among individuals of varying age groups and with different gender structures during the COVID-19 pandemic restrictions\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEpisodic memory is a system involved in conscious awareness and recollection of events and personal experiences\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Literature has posited that varying behavioural outcomes and responses to COVID-19 lockdown measures may potentially influence an individual or group\u0026rsquo;s cognitive abilities, such as episodic memory recall\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Despite this, there is still a dearth of research on how pre-existing memory processes and profiles are influenced by individual and group responses to uncertain pandemics such as COVID-19 and its various social isolation measures. This phenomenon is especially prevalent globally, where limited studies have investigated how cognitive abilities, such as episodic memory recall, anxiety, and depression, are associated with varying responses to COVID-19 lockdown measures.\u003c/p\u003e \u003cp\u003eThe outcomes of recently recognised psychological responses to COVID-19 lockdown measures have shown that behavioural changes in individuals\u0026rsquo; compliance levels to pandemic social restrictions are influenced by prevailing social stereotypes and cultural norms\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. For example, a UK study showed that people commonly accepted lockdown rules (48%), followed by experiencing suffering (44%), and the least common group resisted the UK lockdown rules (9%). However, these responses could also influence people\u0026rsquo;s ability to correctly appraise their self-regulation strategies. These strategies could be linked to decision-making processes within the cognitive structures of individuals\u0026rsquo; executive functioning capacity in terms of levels of cognitive flexibility and working memory capacity\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. As elucidated by Del Missier \u003cem\u003eet al\u003c/em\u003e.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, associations between memory and decision-making are evident when emotion-based judgments are executed under higher or lower cognitive loads. The operationalisation of this association highlighted the assumption that semantic response (a type of memory response that consists of factual information and meaningful knowledge properties) plays a fundamental role in background knowledge decision-making processes, while past experiences involve influences of episodic memory (a memory system involved in conscious awareness and recollection of events and personal experiences)\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. This means that an association between memory and decision-making processes may influence the outcome of individual psychological or behavioural responses arising from new semantic frameworks and episodic content retrieval that are linked to social isolation during COVID-19 lockdown measures\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile various cross-sectional and reviewed studies\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e have focused on the psychological well-being and cognitive performance of individuals during the COVID-19 pandemic, we could not locate any study that specifically investigated the association between memory recall processes and social adherence during the lockdown period, especially within the broader global survey study. Our study aimed to investigate the associations between lockdown group responses to COVID-19 restrictions and free memory recall and between associated anxiety and depression levels in participants drawn from 49 different countries across the globe. Additionally, the study further explored the predictive effect of age and gender on the relationships between these constructs. Research has shown the effects of age and gender differences on auditory and visual episodic memory performance among younger and older adults\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. While contributing to the body of knowledge, our study predicted that there would be significant differences across lockdown group responses (comply, sufferer, defiant) on free memory recall and associated emotional responses related to anxiety and depression. Furthermore, we hypothesised that age and gender would predict the associations between COVID-19 lockdown group responses and free memory recall, and between anxiety and depression.\u003c/p\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Effect of lockdown group response on memory recall and associated emotional profiles\u003c/h2\u003e \u003cp\u003eAs hypothesised, we found significant differences (ranging from small to medium effect sizes) in the lockdown group responses on free memory recall (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,1594\u003c/sub\u003e = 6.67, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u0026#120578;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.01), anxiety (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,1594\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;53.27, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u0026#120578;\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.06), and depression (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,1594\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;41.64, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u0026#120578;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.05). The significant associations were weak across the results, particularly in the case of free memory recall, which had the weakest effect size. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, in particular, our sample perceived significantly better memory recall in the comply group (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.51, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.38) than in the sufferer (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.83, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.11) and defiant (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.69, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.69) groups. Examining the changes in the emotional profiles of the participants in the lockdown group, we found significantly greater anxiety levels in the sufferer group (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.97, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.36) than in the defiant (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.78, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.22) and comply (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.29, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.02) groups. Furthermore, a significantly greater level of depression was recorded in the defiant group (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.90, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.12) than in the sufferer (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.41, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.80) and comply (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.62, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.61) groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in memory recall and emotional profiles between lockdown groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLockdown group comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95% Confidence Interval\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFree memory recall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecomply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esufferer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecomply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edefiant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.652**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esufferer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edefiant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.062*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.527\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esufferer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecomply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.434**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edefiant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecomply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.184**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esufferer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edefiant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esufferer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecomply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.872**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edefiant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecomply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.314**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edefiant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esufferer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote. N\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1630. Sig. = significance. ** = \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. * = \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Relationships between sociodemographic factors, free memory recall, anxiety, and depression\u003c/h2\u003e \u003cp\u003eThe full regression model of lockdown group responses and the sociodemographic variables age and gender significantly predicted free memory recall (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e4,1625\u003c/sub\u003e = 9.15, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). When sociodemographic variables were introduced into the model (adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.020, \u003cem\u003eF\u003c/em\u003e(4, 1623)\u0026thinsp;=\u0026thinsp;0.99, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.371), the adjusted \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e values were minimal, indicating that only 2% of the variance in memory recall was explained by the predictors. The associated \u003cem\u003eF\u003c/em\u003e-statistic for the predictors added was non-significant, suggesting that including age and gender did not improve the model\u0026rsquo;s ability to explain variance in memory recall over what was accounted for by the lockdown group alone. Furthermore, only the lockdown group variables, sufferer group (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e = -0.75, \u003cem\u003et\u003c/em\u003e(1623) = -2.18, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.030) and defiant group (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e = -2.71, \u003cem\u003et\u003c/em\u003e(1623) = -5.69, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), were significantly different, as shown in Table\u0026nbsp;3. These results suggest that although the full model was significant, sociodemographic variables were not significant predictors of the relationship between lockdown group response and free memory recall in this study.\u003c/p\u003e \u003cp\u003eFurthermore, as reported in Table\u0026nbsp;3, age and gender were shown to predict the relationship between the lockdown group and anxiety. The hierarchical regression showed a statistically significant model at both steps of the model analysis. The results showed a total variance of 13.8%, explained by the full model (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u003c/b\u003e\u0026thinsp;.14, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e4,1625\u003c/sub\u003e = 66.15, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003ef\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.17). When controlling for lockdown group response in the full model, both age (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e = -1.25, \u003cem\u003et\u003c/em\u003e(1625) = -6.36, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and gender (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e = -1.52, \u003cem\u003et\u003c/em\u003e(1625) = -7.55, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) had statistically significant effects on anxiety. The results regarding the effect of age on the association between the lockdown group and anxiety, therefore, suggest that younger adults appear to be more anxious in their response levels during COVID-19 lockdown measures than older adults are. Similarly, the regression results further showed that females had greater anxiety in their lockdown response levels than males did.\u003c/p\u003e \u003cp\u003eThe full model of the lockdown group, age and gender in predicting depression also showed a statistically significant result (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cb\u003e=\u003c/b\u003e\u0026thinsp;.080, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e4,1625\u003c/sub\u003e = 34.85, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003ef\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.09). These results suggested that sociodemographic factors predict the association between lockdown group response and depression. However, while investigating the variable(s) that contributed to this significant prediction when controlling for the lockdown group in the analysis, age was the only significant predictor (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e = -0.78, \u003cem\u003et\u003c/em\u003e(1625) = -4.35, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and gender was a nonsignificant predictor (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e = -0.13, \u003cem\u003et\u003c/em\u003e(1625) = -0.69, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.490). This result, therefore, suggested that younger adults in this study were more likely to be depressed than older adults were, as shown in Table\u0026nbsp;3.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the regression model predicting the lockdown group and emotional profiles\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFree memory recall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.79**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[8.13, 9.44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.78**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[8.36, 9.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.06**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[5.68, 6.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOVID-19 lockdown group\u003c/b\u003e \u003cb\u003e(ref. comply group)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSufferer group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[-1.42, -0.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.48**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[2.06, 2.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.82**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[-1.43, 2.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDefiant group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.71**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[-3.64, -1.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.72**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-3.64, -1.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.31**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[1.77, 2.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSociodemographic variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[-0.74, 0.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.25**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-1.64, -0.87]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.78**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[-1.13, -0.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[-1.08, 0.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.52**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-1.92, -1.13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[-0.49, 0.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegression statistically significant results\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e(4, 1625)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.15**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.15**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.85**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003et value\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e26.20**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e41.75**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e31.54**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChange in R\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003eNote.\u003c/em\u003e N\u0026thinsp;=\u0026thinsp;1630. \u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;unstandardised regression coefficient; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\beta\\:\\)\u003c/span\u003e\u003c/span\u003e = standardised regression coefficient; CI\u0026thinsp;=\u0026thinsp;confidence interval. **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3 Discussion","content":"\u003cp\u003eOur findings revealed significant associations between free memory recall, anxiety, and depression across lockdown group response levels. Individuals in the compliant group had better free recall, those in the sufferers group had significantly greater anxiety, and those in the defiant group had greater depression symptoms during the 2020 period of the global COVID-19 lockdown. Age and gender were also significant predictors of anxiety in the lockdown group. Another important finding was that none of the sociodemographic variables, specifically age and gender, were significant predictors of lockdown group responses and free memory recall relationship. The rationale of this study was to provide insight into the mechanisms of semantic coding associated with free recall memory and how these mechanisms influence varying individual and group compliance responses to pandemic lockdown restriction measures. Additionally, the study showed the intriguing influence of emotional content on the neural processes of individuals and the group\u0026rsquo;s psychological outlook on social isolation measures.\u003c/p\u003e \u003cp\u003eThe significant association between lockdown group responses and free memory recall showed that the comply group exhibited better memory recall than the sufferer and defiant groups. This means that the overall memory recall performance of the individuals in the comply group (those who easily adhered to group/social norms and COVID-19 lockdown rules) indicated a positive recency effect on their delayed recall tasks. This effect tapped into a more stable long-term storage mechanism component of the free recall performance, which is mainly affected by semantic coding\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The storage mechanism component is unaffected by the rehearsal-preventing task of delayed recall; as such, correctly recalling texts from the beginning of the passage was more prevalent in the long-term storage component than the short-term storage mechanism of single-trial free recall, which also reflects a recency effect but with immediate recall of the recently rehearsed texts from the end of the passage. It must be noted, however, that, based on the nature of the online survey used in this study, the assumption was that participants engaged the recency effect of delayed recall with distinctively long pauses (between 20 and 30 seconds) that preceded their recall response \u0026ndash; a unique response time associated with free recall memory tasks\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In light of this, interpretation of this finding was considered in the context of this observation.\u003c/p\u003e \u003cp\u003eThe significant findings across the lockdown group could be attributed to cognitive interpretations of individual/group variations as an indication of significant free memory recall performance findings\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In light of these cognitive variations, it was not unexpected that free memory recall performance between the comply and sufferer groups indicated non-significant differences in memory recall. However, performance significantly differed between the comply and defiant groups and between the sufferer and defiant groups. Another possible reason for this can be attributed to the impact of recent life stress (such as the COVID-19 pandemic) on the cognitive process of the participants. The outcome of this stress, reflected as either acute or chronic, was assumed to impair the retrieval process within the memory recall capacity. As a result, the recall process impinges upon individual episodic memory content, which happens to be the seat of the long-term storage mechanism of the free memory recall task\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. This finding indicates that recent life stress, which might be more pronounced in the suffering and defiant groups than in the compliant group in our study, has the potential to limit the capacity of long-term storage mechanisms, especially when individuals or groups are faced with life-threatening psychological and emotional challenges. The COVID-19 pandemic could presumably exert substantial effects on the memory retention and retrieval abilities of individuals with cognitive variations necessary for decision-making responses\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAge-related decreases in cognitive function could also be attributed to the significant effect of these outcomes. The participants\u0026rsquo; sample distribution across different age cohorts showed a positively skewed distribution of their free memory recall scores. Therefore, it was not unusual to expect significant age differences to be associated with the memory recall performance of respondents across lockdown groups in this study. This was prevalent with reference to reduced inefficient recall and retrieval performance of the episodic content of the long-term memory store\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Although evidence-based results have lent support to this assumption\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, the experimental studies of Craik\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e and Raymond\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e foreground the assumption that the effectiveness of memory recall from long-term storage of episodic memory is affected by successive age-related increases, including the length and stimulus size of the recalled vocabulary or text\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. This finding suggested that there may be certain differential and ineffective cognitive functioning processing in older adults compared to younger adults. This was due to poor retrieval and selective decline in performance from the long-term storage mechanism of episodic memory\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study also revealed important significant findings on anxiety and depression across lockdown groups. The results showed that the sufferer group experienced greater anxiety symptoms than the defiant and comply groups. In comparison, the defiant group displayed greater depressive symptoms compared to the sufferer and comply groups. These findings suggested that both anxiety and depressive symptoms were significantly associated across the lockdown group responses. These findings are consistent with previous literature and systematic reviews, especially on COVID-19 behavioural and cognitive responses to social isolation measures\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. While depressive symptoms decreased across the lockdown response levels compared to heightened anxiety levels, the effect sizes of both anxiety (\u0026#120578;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.63) and depression (\u0026#120578;\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.50) across group responses were relatively modest. Nevertheless, the significant differences in emotional responses across the lockdown groups could be due to several reasons. First, the global lockdown disrupted people\u0026rsquo;s personal, financial, and social lives, resulting in a negative psychological outlook. Moreover, the extended \u0026lsquo;sit-at-home\u0026rsquo; lockdown restrictions might have elevated individual anxiety and depressive responses. This might have been more prevalent in the sufferer group because of their assumed financial difficulty and low optimism during the pandemic lockdown. This might further aggravate their anxiety levels because of agitation and lower optimism in the government\u0026rsquo;s response to controlling disease spread.\u003c/p\u003e \u003cp\u003eThis explanation is consistent with recent literature on the exacerbated emotional levels of anxiety, stress, and depressive symptoms in people during the COVID-19 pandemic, which has resulted in maladaptive coping responses across individuals and group outcomes\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Additionally, the role of misinformation due to high social media exposure and usage, including emerging conspiracy theories on COVID-19 infections and treatments\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, could also be attributed to significant differences in emotional content across lockdown groups. Frequent social media usage and lack of government plans to respond adequately to changing scientific information (leading to misinformation) might have negatively influenced people\u0026rsquo;s emotional state toward inappropriate responses to pandemic lockdown measures. For instance, the defiant group, which was susceptible to high social media exposure and usage, was linked to greater depressive symptoms in our study. This finding is consistent with recent studies that postulated the significant association of increasing misinformation, conspiracy theories, and fake news on COVID-19 infections and outcomes with heightened emotional and psychological responses\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. In light of the reviewed literature and hypothesis that stated that significant differences exist between lockdown group responses to COVID-19 social restriction measures on participants\u0026rsquo; emotional content of anxiety and depression, the findings of this study therefore offer consistent support for the body of knowledge in favour of the significant effects of these measures on emotional responses to COVID-19 lockdown measures.\u003c/p\u003e \u003cp\u003eConsistent with the findings of recent studies\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, our regression analyses showed that age significantly predicted the associations between lockdown group responses and emotional responses to anxiety and depression. The negative prediction of the result suggested that younger adults were more exposed to heightened levels of anxiety and depression than older adults were. An explanation for this could be that older individuals have the emotional capacity or greater memories of overcoming past difficulties, to contextualise a stressor, such as the outcome of the COVID-19 lockdown measures, which helps them maintain a more stable emotional balance than younger individuals\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Additionally, older adults tend to have a more mature social disposition and better financial support base, such as better-paying jobs, which might reduce the context of emotional imbalance than younger adults. Furthermore, gender significantly predicted group responses and anxiety relationship. Compared to males, females showed higher anxiety symptoms, which was consistent with the findings of previous studies indicating a significant increase in anxiety observed in females\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. A potential explanation for this could be because of the assumptions that females bear more disproportionate domestic and caregiving responsibilities than men, especially during the pandemic period, such as during the COVID-19 social isolation, which results in contextually skewed gender divisions of labour in society, including household settings\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. As a result, females could be considered more susceptible to increased anxiety and depressive symptoms. Social isolation measures such as restricted physical mobility during the pandemic could also increase females\u0026rsquo; exposure to domestic violence and hostile experiences. This could exacerbate their emotional disturbance levels, especially in areas where gender violence practices and narratives are prevalent, such as sub-Saharan Africa, including Southern Africa\u003csup\u003e\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"4. Materials and Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Participants\u003c/h2\u003e \u003cp\u003eThis study was nested within an existing dataset of a larger international online survey study conducted between July and September 2020 on Prolific and Qualtrics online survey platforms. The sample consisted of participants from 49 countries in Africa, Asia, Europe, North America, and South America. A larger study utilised non-probability, convenience, and snowball sampling methods. No restrictions were imposed on referring friends or family members, as participation was voluntary. Brief information about the aims of this study was provided online to all participants. Informed consent was obtained online from all participants before data collection. Furthermore, participants were eligible if they were adults aged 18\u0026ndash;75 years, had no psychological conditions as declared by each participant, and could speak and write in English. Among the total valid sample size of 2309 participants, 1634 respondents were classified as eligible. Participants were excluded due to incomplete online surveys (n\u0026thinsp;=\u0026thinsp;613), missing data on age (n\u0026thinsp;=\u0026thinsp;29), insufficient data on non-binary sex (n\u0026thinsp;=\u0026thinsp;18), or missing education (n\u0026thinsp;=\u0026thinsp;15).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e4.1.1 Sociodemographic and lockdown response characteristics\u003c/h2\u003e \u003cp\u003eThe demographic characteristics of the sample (N\u0026thinsp;=\u0026thinsp;1634) are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The participants\u0026rsquo; ages ranged from 18 to 74 years (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;28.60, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.92). There were slightly more younger adult participants (50.6%) than older adults (49.4%). Most participants self-identified as male (54.30%), were from Europe (80.20%), and fell within the comply lockdown grouping (48.96%). The comply group had the most participants (n\u0026thinsp;=\u0026thinsp;800), followed by the sufferer group (n\u0026thinsp;=\u0026thinsp;600), while the defiant group (n\u0026thinsp;=\u0026thinsp;227) had the lowest participant grouping.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic characteristics and COVID-19 lockdown group distribution\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographic variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM(SD)\u003c/em\u003e: 28.60(10.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange: 18\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYounger adults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange: 26\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOlder adults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"4\" nameend=\"c2\" namest=\"c1\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eContinental grouping\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEurope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorth America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSouth America \u0026amp; the Caribbean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAfrica \u0026amp; Middle East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAsia \u0026amp; Australasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eLockdown group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComply group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSufferer group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDefiant group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote.\u003c/em\u003e Total \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1634 for all variables except for continental grouping (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1631); \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;mean; \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Instruments\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1 Demographic and COVID-19 Experience Questionnaire\u003c/h2\u003e \u003cp\u003eThe survey used self-reporting questionnaires consisting of two sections. In the first section, participants' sociodemographic data, specifically age range and sex (binary classification), were collected. Participants\u0026rsquo; sex classification was self-reported by each of the participants. The second section utilised the 54-item COVID-19 experience questionnaire created by the authors, which was based on a previous study that identified 3 lockdown response groups in the UK from King\u0026rsquo;s College, London\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The questionnaire (available on request) was used to assess lockdown responses in this cohort. The questionnaire was answered on a 5-point Likert scale, and assessed participants\u0026rsquo; beliefs, attitudes, and behaviours around COVID-19 pandemic characteristics and government-imposed lockdown measures\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Accordingly, three lockdown groups were categorised based on the \u003cem\u003eK-means\u003c/em\u003e cluster analysis of the questionnaire scores (see below), namely: (1) the Comply group (CG): people with higher adherence to group/society norms and stereotypes; (2) the Sufferer Group (SG): those who adhered to lockdown rules with some deviations and were known to possess conflicting outlooks on social norms; and (3) the Defiant Group (DG): those with a negative outlook on COVID-19 lockdown restrictions and low adherence. This classification aligned with the three groups identified by another study\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2 Memory Recall.\u003c/h2\u003e \u003cp\u003eAn online self-administered memory test was measured by a free memory recall test (FMRT), which is adapted for online administration. The adapted FMRT assessed memory recall of previously memorised statements of unrelated or coupled textual words that contained concreteness, emotionality, and neutrality\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. The FMRT consists of 30 bold selected words (e.g., viral, swarming, quack) within the passage; these words are made available to participants to recall by writing as many bold letters as they remember after an overt rehearsal of the passage after 20\u0026ndash;30 seconds. The bold text to be recalled represents categories of concrete (e.g., door), abstract (e.g., silence), neutral (e.g., ordinary), and emotional (e.g., viral) words to test participants\u0026rsquo; memory recall performance. The bold text recall did not have to follow the sequence as it appeared in the passage. Since it was an online assessment, the bold text recalled was to be written down in the provided online space. Additionally, spelling errors were not accounted for, but synonyms were not recorded as the correct answer to the bold text. Participants were not given specific time to recall the bold text, but it was assumed that the recall would be quicker since it was part of an online data collection activity. The FRMT scores ranged from 0 to 30, with each correctly recalled word given one point. The FRMT has a strong internal consistency reliability of .71\u003csup\u003e61\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3 Anxiety and Depression.\u003c/h2\u003e \u003cp\u003eThe presence of anxiety and depression was measured by the Hospital Anxiety and Depression Scale (HADS)\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. It is a brief self-assessment emotion questionnaire designed to assess symptoms of anxiety and depression within non-psychiatric hospital settings\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. It comprises two subscales for anxiety and depression, each having seven items (closed format) of a 4-point Likert scale (0\u0026ndash;3), with a range of 0\u0026ndash;21 for each subscale\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. A higher total score indicates a greater severity of anxiety and/or depression. Scores ranging from 0\u0026ndash;7 are in the normal range; 8\u0026ndash;10 as mild or borderline; 11\u0026ndash;14 as moderate; and 15\u0026ndash;21 as severe self-reports of anxiety and/or depression\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. The HADS subscales are considered a justifiable measure of severity, with reliability measures ranging from .83 to .93 for anxiety and from .74 to .90 for depression\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. The Cronbach\u0026rsquo;s reliability coefficient for the HADS in this study was .80 for anxiety and .74 for depression.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Data analyses\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e4.3.1 \u003cem\u003eK\u003c/em\u003e-means cluster analysis\u003c/h2\u003e \u003cp\u003eThe creation of a lockdown response variable in this study was adopted in line with the online survey study through a \u003cem\u003ek\u003c/em\u003e-means cluster analysis. The larger international online study performed an exploratory factor analysis on the 54 lockdown items that assessed participants\u0026rsquo; beliefs, attitudes, and behaviours related to COVID-19 pandemic characteristics and government-imposed lockdown measures\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Principal component analysis (PCA) was also performed on the lockdown-related questionnaires, which were answered on a 5-point Likert scale covering statements such as adherence to lockdown instructions, self-medication approach, beliefs around COVID-19, participants\u0026rsquo; well-being during the pandemic lockdown, individual\u0026rsquo;s non-pandemic health behaviours, belief and perception about the future, level of trust in government, and use of social media during the lockdown.\u003c/p\u003e \u003cp\u003eCluster analysis was further performed using varimax rotation and Kaiser\u0026rsquo;s criterion normalisation and extraction, with analysis of eigenvalues greater than 1\u003csup\u003e67\u003c/sup\u003e. The outcome of the analysis was plotted \u003cem\u003e\u0026ldquo;k\u0026rdquo;\u003c/em\u003e within 30 iterations for 2, 3, and 6 factors, whereby the cluster analysis of \u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3 was chosen as the optimal cluster division for maintaining meaningful population size, as well as in alignment with the previous online survey study\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The identification of the COVID-19 lockdown group in this study (slightly modified to include the \u0026lsquo;comply group\u0026rsquo;, \u0026lsquo;sufferer group\u0026rsquo; and \u0026lsquo;defiant group\u0026rsquo;) therefore showed how each grouping characteristic informed the cognitive (specifically, free memory recall), emotional, and neural processes underlying psychological responses to the COVID-19 lockdown rules.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e4.3.2 Statistical analyses\u003c/h2\u003e \u003cp\u003eMultivariate analysis of variance (MANOVA) was also conducted to analyse the significant differences in the means and effect sizes of COVID-19 lockdown groups, age, and gender on the outcome variables of free memory recall, anxiety, and depression. Furthermore, the associations between lockdown group responses and free memory recall, anxiety, and depression were determined through hierarchical multiple linear regression analysis. Parametric assumptions for all the statistical analyses above were considered and met or adjusted using inferred random sampling, and a sample size normality distribution\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e was used before the analyses were conducted. Additionally, running a 4-way MANOVA test comes with added assumptions such as the absence of multicollinearity, no univariate or multivariate outliers, equal population covariance matrices, homogeneity of variance, and multivariate normality residuals for all dependent variables.\u003c/p\u003e \u003cp\u003eAlthough the homogeneity of variance covariance and part of Levene\u0026rsquo;s test were violated, research has shown that Box\u0026rsquo;s M can be stricter and sensitive to the equality of covariance when the sample size is large; as such, violation of assumptions is not unusual within social science research \u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Since these two assumptions were thus violated and because of the robust method of MANOVA tests, the interpretation of the statistical tests was derived from Pillai\u0026rsquo;s Trace results rather than from Wilk\u0026rsquo;s Lambda\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. Outliers were statistically analysed using Cook\u0026rsquo;s and Mahalanobis distances of 18.47 for the 4 independent variables. All the assumptions for conducting multiple regression were checked, and all the assumptions were met. The residual errors were further normally distributed and fulfilled for each dependent variable. A stepwise hierarchical multiple linear regression analysis was utilised to depict the stepwise changes in the effect of the prediction between the focal independent variable and demographic variables on the dependent variables\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe data analysis was performed using IBM SPSS statistics version 27\u003csup\u003e73\u003c/sup\u003e, and the value of alpha (α) was set at .05 as a threshold for all the statistical tests, with Bonferroni corrections applied when necessary to account for multiple comparisons. The adjusted alpha level for the Bonferroni comparison was .0125, which was further used to assess the level of statistical significance between the dependent variables. A Bonferroni post hoc analysis was performed on all the significant findings to determine the significance of the effects of the independent variables on the dependent variables.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"5. Strengths and Limitations","content":"\u003cp\u003eA major strength of this study is that it\u0026nbsp;provides\u0026nbsp;informative data linking COVID-19 lockdown responses and cognitive-emotional\u0026nbsp;performance. This may improve our understanding of public perceptions that consequently inform responses to social isolation measures in the face of a severe viral pandemic. As such, this study was able to add to our understanding of cognitive-emotional processes that are involved in people’s behavioural and decision-making responses in the course of prolonged lockdown restriction measures during the pandemic. These data could inform strategies for improving and maintaining individual and group behavioural responses to future pandemics or other global crises. In terms of methodological rigour, the strength of this study was its use of \u003cem\u003ek\u003c/em\u003e-means cluster analysis to classify the lockdown groups based on similar responses on compliance to lockdown rules\u003csup\u003e15,36\u003c/sup\u003e. The use of \u003cem\u003ek\u003c/em\u003e-means also assisted in grouping individuals with similar traits to allow for correct analyses and\u0026nbsp;to\u0026nbsp;describe information and patterns that are specific and representative of the group traits within the cluster analysis\u003csup\u003e74\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHowever, our study has a few limitations.\u0026nbsp;First, the primary goal of this study was exploratory, where statistical analyses were designed to explore the relationships between variables of interest.\u0026nbsp;The\u0026nbsp;context of the study was also cross-sectional. Hence, its exploratory nature did not allow\u0026nbsp;us to ascertain\u0026nbsp;precisely defined hypotheses, while its cross-sectional outlook limited the ability to draw causal conclusions from the findings of the study. Future studies should\u0026nbsp;use a longitudinally designed\u0026nbsp;approach to enhance the precise evaluation of cognitive-emotional performance and responses of the sample in relation to COVID-19 lockdown measures. Another limitation was that despite the large sample size, the total sample could not be determined\u0026nbsp;to\u0026nbsp;be\u0026nbsp;representative of all the nationalities represented. Specifically, there were significant variations\u0026nbsp;in\u0026nbsp;sample representation across the continental regions, with Europe having the dominant sample size, while Africa, Asia, and Australasia were sparsely represented.\u0026nbsp;With\u0026nbsp;respect\u0026nbsp;to\u0026nbsp;this, caution should be exercised, as the generalisability of the findings to other cultures is limited.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this study\u0026nbsp;revealed\u0026nbsp;that common global behavioural responses to COVID-19 lockdown measures during 2020 were compliance, suffering, and defiant, and that complying with\u0026nbsp;these\u0026nbsp;rules was associated with better cognitive performance on a recall test.\u0026nbsp;Moreover, those who suffered during the pandemic had greater levels of anxiety, whereas those who were defiant and had greater engagement with social media reported higher levels of depression. Younger females were more susceptible to anxiety. In sum, these data may help to provide additional assistance to members of society who might face cognitive and emotional difficulties in response to threats and challenges in future global crises.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical clearance was obtained from the University of the Witwatersrand Human Research Ethics Committee (non-medical; protocol number: MASPR/21/08) and the Liverpool John Moores University Research Ethics Committee (approval code 20/NSP/035) to conduct this online survey research study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLeon, C. 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(Springer, 2012).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Department of Psychology, University of the Witwatersrand, South Africa.","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19 lockdown, free memory recall, anxiety, depression, public health measures","lastPublishedDoi":"10.21203/rs.3.rs-5083107/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5083107/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe unprecedented outbreak of the COVID-19 pandemic has altered the course of many lives, resulting in multiple health and social challenges. Due to the speed at which this pandemic spread, various public health ‘lockdown’ measures were introduced to mitigate its spread. The outcome of adherence to these measures has revealed the possible influence on individuals’ varying cognitive abilities. Accordingly, this study aimed to explore the predictive relationships between lockdown responses and COVID-19 restrictions, memory recall performance, and associated emotional responses while examining the sociodemographic influences of age and sex. Participants were drawn from a secondary dataset of an international online survey study of 1634 individuals aged 18–75 years across 49 countries. Participants’ demographic questionnaires, free memory recall, and hospital anxiety and depression scale scores were used to collect the data for analysis. Four-way MANOVA and hierarchical multiple regression were utilised to explore the mean differences and predict relationships between the study variables. Significant differences were found in memory recall performance and anxiety and depression scores across lockdown groups (the comply, sufferer, and defiant). Regression analysis indicated that age and gender were predictive markers of lockdown responses and anxiety (R2 = .14, F4,1625 = 66.15, p \u0026lt; .001, f2 = 0.17), while age was the only predictor of lockdown responses and depression association (b = -0.78, t(1625) = -4.35, p \u0026lt; .001). Lockdown compliance was associated with better free recall (M = 8.51, SD = 6.38, p \u0026lt; .001; 𝜂2 = .01), lockdown suffering was associated with greater anxiety (M = 9.97, SD = 4.36, p \u0026lt; .001; 𝜂2 = .06), and lockdown deviance was associated with greater depression (M = 7.90, SD = 3.12, p \u0026lt; .001; 𝜂2 = .05). The current study provides valuable information on the mechanisms of cognitive interpretations and emotional arousal in individuals’ social isolation responses to recent life stress and potential severe pandemics. This may support the need for robust interventions aimed at improving people’s psychological appraisals associated with anxiety in preparation for any new potential waves or future pandemics.\u003c/p\u003e","manuscriptTitle":"Associations between the lockdown group, free memory recall, and emotional responses during the COVID-19 lockdown: A global survey of 49 countries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-26 01:10:17","doi":"10.21203/rs.3.rs-5083107/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b3c47ce-c834-4a9f-9324-8571d483855b","owner":[],"postedDate":"September 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":37572496,"name":"Cognitive Neuroscience"},{"id":37572497,"name":"Psychology"}],"tags":[],"updatedAt":"2024-09-26T01:10:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-26 01:10:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5083107","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5083107","identity":"rs-5083107","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}