Next Article in Journal
Suppressing MDSC Recruitment to the Tumor Microenvironment by Antagonizing CXCR2 to Enhance the Efficacy of Immunotherapy
Previous Article in Journal
Genome-Wide DNA Methylation Signatures Predict the Early Asymptomatic Doxorubicin-Induced Cardiotoxicity in Breast Cancer
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 13
Issue 24
10.3390/cancers13246294
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Mental Health and Adherence to COVID-19 Protective Behaviors among Cancer Patients during the COVID-19 Pandemic: An International, Multinational Cross-Sectional Study

by
Angelos P. Kassianos
1,2,
Alexandros Georgiou
3,
Maria Kyprianidou
1,
Demetris Lamnisos
4,
Jeļena Ļubenko
5,
Giovambattista Presti
6,
Valeria Squatrito
6,
Marios Constantinou
7,
Christiana Nicolaou
8,
Savvas Papacostas
9,
Gökçen Aydin
10,
Yuen Yu Chong
11,
Wai Tong Chien
11,
Ho Yu Cheng
11,
Francisco J. Ruiz
12,
Maria B. Garcia-Martin
12,
Diana Obando
12,
Miguel A. Segura-Vargas
12,
Vasilis S. Vasiliou
13,
Louise McHugh
14,
Stefan Höfer
15,
Adriana Baban
16,
David Dias Neto
17,18,
Ana Nunes da Silva
19,
Jean-Louis Monestès
20,
Javier Alvarez-Galvez
21,
Marisa Paez Blarrina
22,
Francisco Montesinos
22,23,
Sonsoles Valdivia Salas
24,
Dorottya Őri
25,26,
Bartosz Kleszcz
27,
Raimo Lappalainen
28,
Iva Ivanović
29,
David Gosar
30,
Frederick Dionne
31,
Rhonda M. Merwin
32,
Andreas Chatzittofis
33,
Evangelia Konstantinou
3,
Sofia Economidou
3,
Andrew T. Gloster
34,
Maria Karekla
1,* and
Anastasia Constantinidou
3,33,35,*add Show full author list remove Hide full author list
1
Department of Psychology, University of Cyprus, Nicosia 2109, Cyprus
2
Department of Applied Health Research, University College London, London WC1E 6BT, UK
3
Bank of Cyprus Oncology Centre, Nicosia 2006, Cyprus
4
Department of Health Sciences, European University of Cyprus, Nicosia 2109, Cyprus
5
Psychological Laboratory, Faculty of Public Health and Social Welfare, Riga Stradins University, LV-1007 Riga, Latvia
6
Human and Social Sciences Department, University of Enna Kore, 94100 Enna, Italy
7
Department of Psychology, University of Nicosia, Nicosia 1516, Cyprus
8
Department of Nursing, School of Health Sciences, Cyprus University of Technology, Limassol 3041, Cyprus
9
Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
10
Department of Psychological Counseling and Guidance, Hasan Kalyoncu University, Gaziantep 27010, Turkey
11
The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
12
Department of Psychology, Universidad de La Sabana, Chia 140013, Colombia
13
School of Applied Psychology, University College Cork (UCC), T23 XE10 Cork, Ireland
14
School of Psychology, University College Dublin, D04 V1W8 Dublin 4, Ireland
15
Department of Medical Psychology, Medical University Innsbruck, 6020 Innsbruck, Austria
16
Department of Psychology, Babes-Bolyai University, 400015 Cluj-Napoca, Romania
17
ISPA—Instituto Universitário, 1149-041 Lisboa, Portugal
18
Applied Psychology Research Center Capabilities & Inclusion, 1149-041 Lisbon, Portugal
19
Department of Psychology, University of Lisbon, 1649-013 Lisbon, Portugal
20
LIP/PC2S, Université Grenoble Alpes, 38000 Grenoble, France
21
Department of Biomedicine, Biotechnology and Public Health, University of Cadiz, 11009 Cadiz, Spain
22
Instituto ACT, 28049 Madrid, Spain
23
Department of Psychology, Universidad Europea de Madrid, 28049 Madrid, Spain
24
Department of Psychology and Sociology, Universidad de Zaragoza, 50013 Zaragoza, Spain
25
Department of Mental Health, Heim Pal National Pediatric Institute, H-1089 Budapest, Hungary
26
Institute of Behavioral Sciences, Semmelweis University, H-1089 Budapest, Hungary
27
Private Practice, 41-200 Sosnowiecz, Poland
28
Department of Psychology, University of Jyväskylä, 40014 Jyväskylä, Finland
29
Department of Child Psychiatry, Institute for Children’s Diseases, Clinical Centre of Montenegro, 81000 Podgorica, Montenegro
30
Department of Child, Adolescent and Developmental Neurology, University Children’s Hospital Ljubljana, University Medical Center Ljubljana, 1000 Ljubljana, Slovenia
31
Département de Psychologie, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada
32
Department of Psychiatry and Behavioral Science, Duke University, Durham, NC 27708, USA
33
Medical School, University of Cyprus, Nicosia 1678, Cyprus
34
Division of Clinical Psychology & Intervention Science, Department of Psychology, University of Basel, 4055 Basel, Switzerland
35
Cyprus Cancer Research Institute, Nicosia 2109, Cyprus
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Authors to whom correspondence should be addressed.
Cancers 2021, 13(24), 6294; https://doi.org/10.3390/cancers13246294
Submission received: 12 October 2021 / Revised: 22 November 2021 / Accepted: 7 December 2021 / Published: 15 December 2021
Review Reports Versions Notes

Abstract

:

Simple Summary

Whilst information on the impact of COVID-19 on cancer care continues to increase exponentially, little is known about the impact of COVID-19 on the mental health and coping behaviors of cancer patients. This study constitutes a sub-study of a large international survey conducted during the first wave of the pandemic, looking specifically at the impact of COVID-19 on the mental health and protective behaviors of cancer participants, compared to non-cancer participants. It also explored whether cancer participants perceived COVID-19 as a bigger threat compared to their cancer and whether this perception affected their psychological outcomes, such as their perceived level of stress. Overall, cancer participants appeared better adapted compared to non-cancer participants, well-functioning, resilient and able to adjust, and prepared to deal with what is otherwise a worldwide crisis; perhaps as a result of their previous cancer experience. Whilst good news, these results should not lead to a dismissal of the specific needs of cancer patients and as the pandemic drags on, cancer population dedicated studies should be performed to ensure adequate care for these patients.

Abstract

A population-based cross-sectional study was conducted during the first COVID-19 wave, to examine the impact of COVID-19 on mental health using an anonymous online survey, enrolling 9565 individuals in 78 countries. The current sub-study examined the impact of the pandemic and the associated lockdown measures on the mental health, and protective behaviors of cancer patients in comparison to non-cancer participants. Furthermore, 264 participants from 30 different countries reported being cancer patients. The median age was 51.5 years, 79.9% were female, and 28% had breast cancer. Cancer participants reported higher self-efficacy to follow recommended national guidelines regarding COVID-19 protective behaviors compared to non-cancer participants (p < 0.01). They were less stressed (p < 0.01), more psychologically flexible (p < 0.01), and had higher levels of positive affect compared to non-cancer participants. Amongst cancer participants, the majority (80.3%) reported COVID-19, not their cancer, as their priority during the first wave of the pandemic and females reported higher levels of stress compared to males. In conclusion, cancer participants appeared to have handled the unpredictable nature of the first wave of the pandemic efficiently, with a positive attitude towards an unknown and otherwise frightening situation. Larger, cancer population specific and longitudinal studies are warranted to ensure adequate medical and psychological care for cancer patients.

1. Introduction

The unparalleled health crisis caused by COVID-19 has created a major impact on cancer care worldwide. Early reports suggested that the prevalence of cancer in patients with COVID-19 is high and that cancer patients and cancer survivors are at-risk population groups for COVID-19 [1,2]. More importantly, cancer patients appear to be at higher risk of developing severe complications associated with COVID 19 [1,3] leading to fatality rates of 10–30% as shown in single center studies [3,4] and a mortality rate of 25.6% in a pooled analysis of 52 studies [5]. Cancer-specific characteristics including cancer type—hematological malignancies, lung cancer—and metastatic (versus early) disease, but also other risk factors which may coexist with cancer including older age and multiple comorbidities, have rendered patients with cancer more vulnerable to SARS–COV-2 [4,6,7,8,9] and its sequalae. Therefore, understanding how cancer patients adhere to protective behaviors, recommended by local and international organizations, is important.
The Health Belief Model [10] is one of the theories used, to explain adherence to behaviors which can pertain to how vulnerable individuals consider themselves regarding a disease (perceived susceptibility), and how severe they consider the disease (perceived severity). The model has been used to understand COVID-19 related behaviors, such as intentions to vaccinate [11], adopting contact tracing [12], and adherence to protective behaviors [13]; but how this evidence translates to cancer patients’ behaviors is yet to be examined. There can be differences in how cancer patients (similarly to other chronic patients) adhere to self-protective behaviors reflecting their response to adjustments in risk assessment found elsewhere [14]. Thus, an individual’s assessment of risk may influence their behavior [15].
Many studies focused on the role of anticancer treatment particularly systemic therapy during the pandemic, with some but not all, reporting worsening of COVID-19-related outcomes, essentially increased mortality, in cancer patients undergoing active therapy [16,17]. These results prompted the implementation of updated recommendations by professional oncology societies on most cancer types to aid treatment decision making during the pandemic [18,19,20,21,22,23,24,25]. Yet, the challenges in cancer care linked directly or indirectly to COVID-19 are multifaceted. Delayed diagnosis, disruption of therapies, interruption or downscaling of screening programs, and follow-ups have been documented since the start of the pandemic in March 2020 [26]. Although long-term consequences may be indecipherable at present, predictive modelling indicated increases in the number of deaths due to delays in cancer diagnosis [27] and a detrimental impact on healthcare finances due to delayed access to cancer services [28].
Whilst information on all aforementioned COVID-19-influenced areas of cancer care continues to build exponentially, little is known about the impact of COVID-19 on cancer patients’ mental health. Since the COVID-19 pandemic, cancer patients and survivors have suffered from financial strains [29], especially for those with low income [30]; increased levels of loneliness [31] and their health-related quality of life, mainly their social, emotional, and cognitive functioning [32]. At a general population level, the abrupt and profound disruption of daily routines, has unsurprisingly brought increases in psychological distress, higher anxiety and depression levels, anger, and confusion [33,34,35]. The psychological implications on wellbeing have been explored in different countries [36,37,38,39,40,41,42], different professional groups including medical professionals and nurses [43,44,45], and in different population groups [46,47,48]. At the same time, identifying factors that have demonstrated facilitating wellbeing, such as psychological flexibility (ability to cope with, accept, and adjust to difficult situations) and mindfulness qualities (ability to be in the present moment rather than lost in past or future thinking) [49,50,51,52], social support [53,54], and tackling the impact of income loss, [55] can help to develop interventions that can ameliorate the impact of stress.
An international population-based cross-sectional study was conducted during the first lockdown period (April 2020–June 2020) to explore how people across the world reacted to COVID-19 by examining outcomes of stress, depression, affect, and wellbeing [33]. With the participation of 9565 people from 78 countries, the results showed that on average about 10% of the sample had low levels of mental health whilst 50% had only moderate mental health. In the current study we focused on the responses of the cancer participants who participated in the international study.
In this study, we sought to examine: (1) the level of adherence to protective behaviors of cancer participants in comparison to non-cancer participants and whether the factors associated with adherence differ between cancer participants and those without cancer (protective behaviors hypothesis); (2) the impact of the pandemic and the associated lockdown measures on mental health and emotional status of cancer participants in comparison to non-cancer participants and whether the factors associated with elevated levels of stress differ between cancer participants and those without cancer (mental health and coping hypothesis); and (3) whether cancer participants perceived COVID-19 as a bigger threat compared to their cancer and whether perceiving COVID-19 as a bigger threat affected their psychological outcomes (beliefs about COVID-19 hypothesis). We hypothesized that (1) cancer participants being more susceptible to COVID-19 will demonstrate higher adherence to protective behaviors; (2) the mental health of cancer participants would be more highly affected compared to non-cancer participants. The third objective is exploratory and thus no a priori hypothesis was made.

2. Materials and Methods

Ethics approval was obtained from the Cyprus National Bioethics Committee (ref.: EEBK EP2020.01.60) followed by site approvals in participating countries. All participants provided electronic informed consent prior to completing the online survey (by clicking ‘yes’).

2.1. Participants

Individuals aged 18 and older, residing in any country were able to read in a study language (English, Greek, German, French, Spanish, Turkish, Dutch, Latvian, Italian, Portuguese, Finnish, Slovenian, Polish, Romanian, Hong Kong, Hungarian, Montenegrin, Persian) were eligible to participate. There were no other exclusion criteria. Participants who agreed to participate in the study were invited to provide electronic informed consent and completed a 20-min online survey via a secured Google platform. No incentives were provided for participation. Participants were able to enroll in the study only once.

2.2. Study Design

A population-based cross-sectional study was conducted using an anonymous online survey which was distributed directly by the thirty-three participating universities to students and academic staff and through respective websites. The survey was also distributed through local press, social media, professional networks, local hospitals and health centers, social institutions, and through professional groups’ email lists in the participating countries. Data were collected for a period of two months—between 7 April and 7 June 2020—during which time a state of emergency for COVID-19 was declared by the World Health Organization (WHO) as well as in the majority of countries participating in the study.

2.3. Study Measures

The participants were assessed with well validated and established measures and in cases where measures were not already available in a language, they were subject to forward and backward translation procedures [56]. All measures were selected after a consensus agreement among the research members of the study.

2.3.1. Measures for All Participants

All participants responded to a number of measures which were subsequently used for comparisons between cancer participants and non-cancer participants.
Socio-demographic and medical characteristics—including age, gender, marital status, employment status, educational level, parenthood status and living conditions, as well as cancer site at diagnosis were documented.
Lockdown and COVID-19 infection information—including length of lockdown, whether participants needed to leave home for work, had any change in their finances, whether they were able to obtain basic supplies, and the amount of living space they were confined in during the lockdown. Participants were also asked whether they, their partner, or significant other was diagnosed with COVID-19 at the time of their participation.
Adherence to COVID-19 protective behaviors (isolating, keeping distance, and hand washing), self-efficacy, and intentions to follow protective behaviors were also asked. Details on the questions asked on these measures are summarized in Table S1. In general, participants were asked to respond on a Likert-type scale for each behavior ranging from 0 to 10 and one question on whether they intended to follow recommended behaviors for the following week with a 7-point Likert scale. Self-efficacy was assessed using an adapted version of the new general self-efficacy scale [57] with a computed score for each participant with higher scores indicating higher self-efficacy.
Social support and family functioning—Participants responded to Oslo Social Support Scale (OSS), a well-validated instrument assessing social determinants of health [58], and the Brief Assessment of Family Functioning (BAFFS), a measure with adequate internal consistency, construct, and concurrent validity assessing family functioning [59]
Mental Health—Participants responded to questions related to perceived stress (Perceived Stress Scale, PSS) [60], depressive symptomatology (Multidimensional State Boredom Scale, MSBS) [61], wellbeing (Mental Health Continuum Short Form for Adults, MHCSF) [62], positive/negative affect (Positive and Negative Affect Scale, PANAS) [63], mindfulness (Cognitive Affective Mindfulness Scale, CAMS) [64], and psychological flexibility (Psy-Flex) [65]. These measures’ factorial, convergent, content, and construct validity as well as reliability has been well established with cancer patients and the general population in the literature [66,67,68,69]. Details of mental health parameters and the corresponding measures are available in Table S1 and scoring information are available elsewhere [33].
Beliefs about COVID-19—A modified version of a questionnaire that measures the Health Beliefs Model’s perceived susceptibility and perceived severity parameters was used [70].

2.3.2. Measures for Cancer Participants Only

Apart from the backbone questionnaire completed by all participants, specific questions were addressed to cancer participants only.
Cancer information—Participants reported the type of cancer, whether they were on anti-cancer therapy at the time of the survey, and whether the therapy was adjuvant (preventative) or for active disease.
Feelings towards cancer and COVID-19—Participants responded to three questions assessing what scared them the most at that moment, what they thought could harm them more, and what was their health priority at that moment (cancer or COVID-19). Subsequently their response to the question about priority, was used as an outcome in logistic regression models.

2.4. Statistical Analyses

Participants’ characteristics are presented descriptively using mean ± standard deviation (SD) for continuous variables with normal distributions and as median and interquartile range (IQR) for measures that do not follow the normal distribution.
For the beliefs about COVID-19 hypothesis and the protective behaviors hypothesis, Pearson’s chi-square test was employed to detect any differences between the variable on cancer diagnosis (cancer participants vs. those without) with the variable on their current priority (cancer vs. COVID-19). T-test and Kolmogorov–Smirnov test were applied to detect any differences between cancer participants and non-cancer participants and those with cancer vs. COVID-19 as their priority, and the continuous characteristics of the participants. The following cut-off values were used for the evaluation of the effect sizes: ‘tiny’ ≤ 0.05, ‘very small’ from 0.05 to 0.10, ‘small’ from 0.10 to 0.20, ‘medium’ from 0.20 to 0.30, ‘large’ from 0.30 to 0.40 and ‘very large’ > 0.40 [71].
For the protective behaviors hypothesis and the mental health and coping hypothesis, multivariate linear regression modelling was performed to evaluate the significance of different psychological and behavioral parameters on stress and in the level of keeping distance which constitutes behavior that was newly introduced into people’s routine [72] after accounting for different demographic and socio-economic characteristics, and psychological flexibility. Specifically, multivariate linear regression models were used, adjusting for different socio-demographic and socio-economic characteristics (i.e., age, gender). Firstly, we added perceived social support (model 1), then perceived susceptibility and perceived severity of COVID-19 (model 2), change in finances during lockdown and availability of obtaining all the basic supplies (model 3), and psychological flexibility (model 4). Finally, we applied a multivariate regression model adjusted for all predictors including cancer as priority, age, gender, cancer type, whether they were receiving anti-cancer therapy, perceived social support, perceived susceptibility and perceived severity, change in finances during quarantine and availability of obtaining all the basic supplies, and psychological flexibility (model 5). Β-coefficients and the corresponding 95% CIs were reported. The statistical hypotheses were two-sided with statistical significance level set at α = 0.05. Statistical analysis was conducted using STATA 14.0 statistical software (Stata Corp, College Station, TX, USA).

3. Results

3.1. Participants

Of the 9565 participants, 264 reported being cancer patients (Table 1). The median age of cancer participants was 51.5 years whereas for the non-cancer participants was 34 years (n = 9301, p < 0.01). The majority of cancer participants were female (79.9%) with males generally being older (M = 55, IQR = 40, 64.5) than females (M = 50, IQR = 40, 59, p = 0.04) and reporting worse losses in terms of their personal finances (44% vs. 25%, p = 0.02). Female cancer patients reported higher levels of stress (median = 15, IQR = 10, 21) than men (median = 12, IQR = 9, 17, p = 0.03). Cancer participants were residents in 30 different countries (see Supplementary Material). The majority were women with breast cancer (28%), followed by women with cancers of the female reproductive system (22%). Almost one third (31%) reported receiving adjuvant (preventative) therapy at the time of the survey, whilst 12% were receiving therapy for active disease. The remaining 57% were not receiving any therapy at the time. Most participants were working full time with more cancer participants being married (53%) compared to those without cancer (36%, p < 0.01). All information on participants’ sociodemographic information and further comparisons between cancer and non-cancer participants, as well as male and female cancer participants, are presented in Table 1, Table 2, Table S1, and Table S2, respectively.

3.2. Comparisons between Cancer Participants and Participants Not Reporting Cancer

3.2.1. COVID-19 Protective Behaviors

Participants reporting cancer diagnosis were more likely to keep the recommended physical distance from other people (median = 10, IQR = 9, 10) when going out compared to non-cancer participants with a small effect size (median = 9, IQR = 8, 10, p < 0.01, d = 0.19). There were no differences between the two groups on limiting unnecessary traveling and washing hands (Table 2). Moreover, cancer participants reported a slightly higher level of self-efficacy on following the recommended national guidelines on COVID-19 protective behaviors compared to non-cancer participants with a small effect size (p < 0.01, d = 0.2). In addition, a higher percentage of cancer participants (67%) stated that they intended on following the recommendations for social distancing for the following week compared to non-cancer participants (57%, p < 0.01).

3.2.2. Coping Styles, Social Support and Family Functioning

There were no significant differences between the two groups on coping with stressors including using emotional support, humor, and self-blaming (Table S1). A higher number of cancer participants reported more social support (31%) compared to non-cancer participants (23%) but with tiny effect size (p < 0.01, d = 0.03). There were no significant differences between the two groups on family functioning (Table 2).

3.2.3. Mental Health Outcomes

Cancer participants were less stressed (median = 15, IQR = 10, 20) than non-cancer participants with a medium effect size (median = 17, IQR = 12, 22, p < 0.01, d = 0.27). There were some differences between the two groups in terms of the three dimensions of wellbeing with largest differences reported on eudemonic psychological wellbeing with cancer participants (median = 23, IQR = 18, 26) scoring higher than non-cancer participants with medium effect size (median = 21, IQR = 15, 24, p < 0.01, d = 0.24). For all dimensions, cancer participants reported higher levels of wellbeing with one in two flourishing (50%) and 41.9% having moderate status of mental health (Table 2). Similar trends were found for non-cancer participants but with fewer of them flourishing (39.6%) compared to cancer patients. Cancer participants reported slightly higher levels of positive affect (median = 30, IQR = 25, 37) and thus propensity to experience positive emotions and interact with others positively compared to non-cancer participants with moderate effect size (median = 29, IQR = 23, 35, p < 0.01, d = 0.21). Further, cancer participants reported lower levels of negative affect (median = 26, IQR = 20, 33) and thus less tendency to experience the world in a negative way, compared to non-cancer participants with small effect size (median = 28, IQR = 25, 38, p < 0.01, d = 0.19). Finally, cancer participants were more psychologically flexible and thus taking their thoughts lightly, accepting their experiences, and engaging in what is important to them in the face of challenging situations compared to non-cancer participants, with large effect size (p < 0.01, d = 0.37) (Table 2). Furthermore, cancer participants reported being more mindful (living more in the here and now) compared to non-cancer participants (p = 0.04, d = 0.17) (Table 2).

3.2.4. Beliefs towards COVID-19

Cancer participants felt more susceptible to being infected with COVID-19 (median = 11, IQR = 7.5, 14) compared to non-cancer participants with very large effect size (median = 8, IQR = 6, 11, p < 0.01, d = 0.56) and considered the disease to be slightly more severe (median = 14, IQR = 12, 17) compared to non-cancer participants with large effect size (median = 13, IQR = 10, 15, p < 0.01, d = 0.37).

3.3. Predictors of Stress and of Adhering to COVID-19 Protective Behaviors

Among cancer participants, in the multivariate model adjusted for all predictors (social support, perceived susceptibility, perceived change in finances during quarantine, availability of obtaining all the basic supplies, and psychological flexibility), results suggested that it was more likely to adhere to keeping physical distances when going out when feeling less susceptible to COVID-19, perceiving the disease as more severe, having losses in finances due to the pandemic, and being psychologically flexible (model 5, Table 3). In the second multivariate model adjusted for all predictors, we found females reporting higher levels of stress compared to males. Higher levels of stress were also related to increased perceived susceptibility to COVID-19, not being able to obtain all the basic supplies, and being less psychologically flexible (model 5, Table 4).

3.4. Comparisons according to Participants’ Primary Health Concern (Priority): Cancer or COVID-19

We investigated cancer participants further according to whether they reported having cancer as their primary health concern (cancer priority group) or COVID-19 (COVID-19 priority group) during the study period. An impressive 80.3% of cancer participants reported that COVID-19 was their top priority at the time compared to the remaining 19.7% who continued to view cancer as their top priority. Those in the cancer priority group were less likely to be university students (2%) than those in the COVID-19 priority group (12%, p = 0.04) but they did not significantly differ in other socio-demographic characteristics. All characteristics of both groups are available in Table 5 and in Table S3.

3.4.1. COVID-19 Protective Behaviors

There were no statistically significant differences between the cancer priority group (56%) or the COVID-19 priority group (73%) on COVID-19 protective behaviors and self-efficacy. However, it was more likely for those in the COVID-19 priority group (78%) to report that following the recommended national guidelines was important to them, compared to those in the cancer priority group (Table 5). Specifically, 62.1% of the COVID-19 priority group and 51.9% of the cancer priority group reported keeping distance from other people when going out all the time, respectively. Moreover, among COVID-19 priority group, 73.2% reported self-isolating and limiting unnecessary travelling according to national guidelines while the corresponding percentage among the cancer priority group was 55.8%. Finally, a similar percentage of individuals among the cancer priority group (65.3%) and the COVID-19 priority group (61.5%) reported washing their hands regularly with water and soap. Participants who had COVID-19 as their priority considered the disease as more severe (median = 15, IQR = 13, 17) compared to those that had cancer as their priority, with very large effect size (median = 12.5, IQR = 9, 15, p < 0.01, d = 0.74) (Table 5).

3.4.2. Mental Health Outcomes

There were no significant differences between the two groups on their perceived stress, mindfulness, pro-social behavior, boredom, mental wellbeing, and psychological flexibility (Table S3). Those in the cancer priority group reported higher positive affect (median = 32, IQR = 28.5, 38) compared to those in the COVID-19 priority group with large effect size (median = 30, IQR = 24, 37, p < 0.03, d = 0.34) suggesting they were more likely to experience positive emotions and interact with others positively despite challenges in their lives (Table 5). No differences were found between the two groups on negative affect.

4. Discussion

The implications of the COVID-19 pandemic on cancer patients and cancer care are feared to be immense. This study focused on the impact of COVID-19 on the mental health of cancer participants and their adherence to COVID-19 protective behaviors through an international population-based cross-sectional study using an anonymous online questionnaire. The analyses included comparisons of the parameters examined in the primary study [33] between cancer participants and non-cancer participants, aiming at describing the characteristics of the cancer subgroup and examining whether cancer participants’ behaviors, background experience with a chronic disease, and coping mechanisms led to different responses compared to those of non-cancer participants as well as comparing cancer participants according to their current health priority (cancer or COVID-19).
Examining the characteristics of the group of participants who reported being cancer patients, it primarily comprised of women with either breast cancer or cancer of the female reproductive system, however patients with different cancer types, from different age groups and different countries, participated in the study. About one third (31%) of the participants were receiving adjuvant treatment, 12% were receiving treatment for active disease, but the majority were not receiving any treatment at the time of the study, probably representing either cancer survivors, patients whose disease was under control, or both. In line with other studies, women with cancer were more likely to experience higher levels of stress compared to men [73].

4.1. Adherence to COVID-19 Protective Behaviors

In line with our first hypothesis, cancer participants demonstrated higher adherence to protective behaviors compared to non-cancer participants. It is important to note that during the data collection no vaccine was available for COVID-19. This may have affected study findings, since individual’s perceived susceptibility to COVID-19 may be affected and this can impact behavior. Cancer participants reported being more likely to keep physical distancing when going out, had higher self-efficacy to follow recommended protective behaviors, and stronger intentions to do so than those without cancer. This may be attributed to higher levels of mortality and morbidity identified in chronic patients who consequently are more protective of themselves and others [74,75]. We further identified, that whether those with cancer adhered to protective behaviors or not was associated with their beliefs towards COVID-19 (susceptibility to COVID-19, considering it more severe), having lost finances, being more stressed, and generally being more psychologically flexible, thus more likely to adapt to changing life situations. Cancer participants compared to non-cancer participants who worried about COVID-19 were more likely to take protective measures against COVID-19, such as limiting unnecessary travelling. Therefore, beyond being diagnosed with cancer, their beliefs towards the disease were strongly associated with their behavior; in line with the Health Belief Model. No other statistically significant differences were identified in terms of socio-demographic characteristics, lockdown information, health behaviors, or social support factors between cancer participants who had COVID-19 as their priority during the first wave and those who did not.
Despite the fear of COVID-19 contamination, cancer participants presented with protective factors of high self-efficacy and an intention to follow recommended guidelines not only of social distancing but also of adhering to measures such as hand washing. This may be due to the general attitude of individuals who have learned to live with a chronic disease and demonstrate flexibility and adjustability in order to cope with the challenges and unpredictability of an underlying health condition. On the other hand, this may be associated with the fear they experienced with this new thread which appeared more severe than cancer itself and led the vast majority of patients to set COVID-19 as their main priority [76]. Furthermore, in all risk efficacy parameters, cancer participants scored higher than non-cancer participants, demonstrating their perception that they can deal with such a difficult situation and get through it even when things get tough.

4.2. Mental Health

Contrary to our second hypothesis, this study found that cancer participants were less stressed and had better eudemonic psychological wellbeing, coping better (1 in 2 flourishing), with higher positive affect and less negative affect and with higher psychological flexibility than those without cancer. The levels of stress cancer patients experienced in this study were also lower than those of frontline healthcare workers found in a recent study [77]. This interesting finding may again be related to individuals who have had a cancer experience developing the abilities to better deal with new health-related threats compared to those who had never before experienced such threat. Higher levels of stress within the group reporting cancer experiences, were associated with being female, believing that they are more susceptible to COVID-19, difficulties in obtaining basic supplies, and being less psychologically flexible. A study including a community reported females having higher levels of stress, which was confirmed in this study [78].
Closer examination of the results showed that the cancer participants’ responses to COVID-19 was not influenced by the status of active treatment as shown in other studies, including, for example, a multicenter study by Sigorski et al. [79] of 306 cancer patients of all subtypes in Poland receiving systematic therapy during the first wave of the pandemic. They showed that COVID-19 associated fear and anxiety were significantly lower than cancer-associated anxiety. Several studies on specific cancer types including sarcoma [80] and lymphoma [73] showed that patients on active treatment, particularly treatment with curative intent, were significantly more worried about both COVID-19 and cancer compared to cancer patients not on treatment (i.e., cancer survivors with their disease under control). Not surprisingly, higher anxiety and depression levels were documented in patients with advanced disease and on treatment with palliative intent versus those with curative intent [81,82]. These findings suggest that cancer patients’ mental health should be examined in light of the state of their treatment and psychological treatment provided only to those cancer patients who face difficulties.
Several studies reported increased levels of stress and anxiety in cancer patients since the start of the pandemic, with anxiety being related to their ongoing treatment, COVID-19 related hospital admissions, and severity of COVID-19 related symptoms [83,84]. Large scale epidemiological studies coming from China suggested that cancer patients tended to have overall worse mental health compared to the general population during the COVID-19 crisis [85]. In contrast, some studies [76] showed no elevation of levels of distress or COVID-19-related fear in cancer patients; instead, equally elevated COVID-19-related fear in cancer and non-cancer patients were documented in Germany. In our original study of 9565 participants, it was shown that the pandemic was experienced as a stressful situation by most people (11% reporting the highest levels of stress) [33]. Interestingly, in this study, cancer participants reported lower levels of perceived stress and depressive symptomatology compared to non-cancer participants. At the same time, they reported higher levels of positive affect, lower levels of negative affect, and a higher level of psychological flexibility compared to non-cancer participants, suggesting a flexible and positive outlook towards an unknown and otherwise frightening situation perhaps by accepting their experiences and engaging in what is important to them. Half of the cancer participants in our study were patients off cancer treatment and perhaps long-term survivors, which may partly explain the lower levels of perceived stress, higher level of acceptance, and high levels of social support and intention to help others in need. These individuals may as a result of their cancer experience have become better adapted and well-functioning, resilient, and adjustable, prepared to deal with what is otherwise a worldwide crisis.

4.3. Beliefs about COVID-19

This study found that cancer participants considered themselves to be more susceptible to COVID-19 and were more afraid of it than cancer at the present time (first wave). Among these cancer patients, more than 80% considered COVID-19 as their priority with no important differences on behavioral adherence to protective behaviors among those whose priority was cancer. This study showed that cancer participants—as most people across the world—felt threatened by COVID-19. Cancer participants felt they were more susceptible to being infected by COVID-19 which they considered a severe disease, more so than non-cancer participants. Not many of these participants experienced a COVID-19 infection themselves (2.3%) or had direct experience through a partner or close other (1.5% and 7.2, respectively) at the time; yet the majority (65%) reported that COVID-19 scared them the most and that COVID-19 could harm them more than anything else (71%). It could be assumed that this is related to the reports on COVID-19 during the early days of the pandemic, which suggested that the prevalence of COVID-19 in patients with cancer was high and that cancer patients comprised an at-risk population for COVID-19 [1,2]. Indeed, frequency, duration, and diversity of media exposure are related to COVID-19-asscociated fear in the general population [86] and cancer patients are likely no exception. Interestingly, however, cancer participants in this study reported shorter screen time (TV, smartphones, laptops) (Table S1) during the study period compared to non-cancer participants; they therefore likely had less exposure to multimedia and scary information compared to non-cancer participants.
It was interesting to identify three factors consistently associated with both perceived stress and adherence to protective behaviors: the Health Belief Model parameters of perceived susceptibility and perceived severity and the Acceptance and Commitment Therapy (ACT) [87] construct of psychological flexibility. COVID-19 is a context where people’s attitudes towards the disease strongly influence how they feel and behave and add to a large body of literature on how the Health Belief Model can be used to understand health behaviors [88,89]. Psychological flexibility is comprised of inter- and intra-personal skills that refer to behaviors relating to recognizing and adapting to situations via making changes towards what is most meaningful and functional for the person [90]. There are mountains of evidence demonstrating that individuals who exhibit psychological flexibility adapt better to significant life stressors [90,91].

4.4. Strengths and Limitations

The limitations of the study comprise the small sample of cancer participants, variation of the study sample including the multiple national backgrounds of the participants, the different types and cancer statuses, and the varying treatments and treatment stages, participants were in. Moreover, the study did not target cancer patients only and their specific needs. It is also possible that participants’ willingness to report that they have been diagnosed with cancer may differ from country to country according to social norms and these differences may impact the generalizability of the findings. In addition, findings related to perceived susceptibility of COVID-19 may have been affected by the lack of an available COVID-19 vaccine during data collection. These parameters could alternatively be considered as strengths of the study if it was not for the relatively small number of cancer participants overall. Some of the limitations originate from the fact that this was a population-based and not a cancer-specific survey addressing issues relevant to all participants and not to cancer patients per se and perhaps their specific needs. A cross-sectional study provides a view of one time point and this study therefore reports on the mental health status at the specific time period during the first wave of the pandemic. Many of these parameters may vary with time and as such, longitudinal studies are needed to allow comparisons in time and as the pandemic progresses. Finally, this has been a nomothetical study and individual cancer patients may present with specific psychological needs that merit attention and should be considered. Thus, the good news that cancer participants managed well during the first wave of the pandemic should not lead to a dismissal of specific needs of individuals or of how their well-being may be affected in the long-term.

5. Conclusions

Overall, this study suggests that cancer participants were well adapted and able to handle the first wave of the pandemic and its unpredictable and uncontrollable nature. There is, however, value in proceeding to examine the cancer population on its own merit and investigate more in depth how this population has been affected, especially in the long run. As the pandemic drags on and reports of patients not being able to attend follow-up appointments and routine procedures needing to be postponed, they may bear psychological taxing effects with additional distress. All these need to be considered so that cancer patients receive adequate medical and psychological care.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/cancers13246294/s1. Table S1. Health behavior data, COVID risk Self-Efficacy, Importance and Intentions, Coping (COPE B), Perceived Stress (PSS) data. Cognitive Affective, Mindfulness Scale data, Pro-Social Behaviour data, Brief Assessment of Family Functioning data, MSBS, Mental Health Continuum Short Form for Adults data, Positive and Negative Affect data, Illness (COVID) Perceptions data, Beliefs about COVID data, separately for cancer patients and free of cancer individuals. Table S2. Male vs Female cancer participants comparisons in: socio-demographic characteristics, health behaviour data, COVID risk Self-Efficacy, Importance and Intentions, Coping (COPE B), Perceived Stress (PSS) data. Cognitive Affective, Mindfulness Scale data, Pro-Social Behaviour data, Brief Assessment of Family Functioning data, MSBS, Mental Health Continuum Short Form for Adults data, Positive and Negative Affect data, Illness (COVID) Perceptions data, Beliefs about COVID data. Table S3. Socio-demographic characteristics, health behavior data, COVID risk Self-Efficacy, Importance and Intentions, Coping (COPE B), Perceived Stress (PSS) data. Cognitive Affective, Mindfulness Scale data, Pro-Social Behaviour data, Brief Assessment of Family Functioning data, MSBS, Mental Health Continuum Short Form for Adults data, Positive and Negative Affect data, Illness (COVID) Perceptions data, Beliefs about COVID data, separately for cancer patients with cancer priority and for COVID priority.

Author Contributions

Conceptualization: A.P.K., A.T.G., M.K. (Maria Karekla), and A.C. (Anastasia Constantinidou); data curation, A.P.K. and M.K. (Maria Karekla); formal analysis, M.K. (Maria Kyprianidou) and D.L.; investigation, A.P.K., D.L., J.Ļ., G.P., V.S., M.C., C.N., S.P., G.A., Y.Y.C., W.T.C., H.Y.C., F.J.R., M.B.G.-M., D.O., M.A.S.-V., V.S.V., L.M., S.H., A.B., D.D.N., A.N.d.S., J.-L.M., J.A.-G., M.P.B., F.M., S.V.S., D.Ő., B.K., R.L., I.I., D.G., F.D., R.M.M., A.T.G., and M.K. (Maria Karekla); methodology, A.P.K., D.L., A.T.G., M.K. (Maria Karekla), and A.C. (Andreas Chatzittofis); project administration, A.P.K., A.T.G., and M.K. (Maria Karekla); supervision, A.P.K., A.T.G., M.K. (Maria Karekla), and A.C. (Anastasia Constantinidou); visualization, M.K. (Maria Kyprianidou); writing—original draft, A.P.K., A.G., M.K. (Maria Karekla), and A.C. (Anastasia Constantinidou); writing—review and editing, A.P.K., A.G., M.K. (Maria Kyprianidou), D.L., J.Ļ., G.P., V.S., M.C., C.N., S.P., G.A., Y.Y.C., W.T.C., H.Y.C., F.J.R., V.S.V., L.M., S.H., A.B., D.D.N., A.N.d.S., J.-L.M., J.A.-G., M.P.B., F.M., S.V.S., D.Ő., R.L., I.I., D.G., R.M.M., A.C. (Andreas Chatzittofis), E.K., S.E., A.T.G., M.K. (Maria Karekla), and A.C. (Anastasia Constantinidou). All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of Cyprus National Bioethics Committee (protocol code EEBK EP2020.01.60, 3 April 2020).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Electronic informed consent has been obtained from the patient(s) to publish this paper.

Data Availability Statement

The data from this study are available by the corresponding author on reasonable request.

Acknowledgments

We wish to thank the following people for their work in helping to implement the study: Spyros Demosthenous, Christiana Karashali, Diamanto Rovania (University of Cyprus); Maria Antoniade (European University of Cyprus); Ioanna Menoikou (Cyprus University of Technology); Elias Ioannou (University of Nicosia); Sonja Borner, Victoria Firsching-Block, Alexander Fenn (University of Basel); Cristīne Šneidere, Ingrīda Trups-Kalne, Lolita Vansovica, Sandra Feldmane, (Riga Stradiņš University); David Nilsson (Lund University); M.A.S.-V. (Fundación Universitaria Konrad Lorenz); Claudia Lenuţa Rus, Catalina Otoiu, and Cristina Vajaean (Babes-Bolyai University).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Liang, W.; Guan, W.; Chen, R.; Wang, W.; Li, J.; Xu, K.; Li, C.; Ai, Q.; Lu, W.; Liang, H. Cancer Patients in SARS-CoV-2 Infection: A Nationwide Analysis in China. Lancet Oncol. 2020, 21, 335–337. [Google Scholar] [CrossRef]
  2. Desai, A.; Sachdeva, S.; Parekh, T.; Desai, R. COVID-19 and Cancer: Lessons from a Pooled Meta-Analysis. JCO Glob. Oncol. 2020, 6, 557–559. [Google Scholar] [CrossRef] [PubMed]
  3. Mehta, V.; Goel, S.; Kabarriti, R.; Cole, D.; Goldfinger, M.; Acuna-Villaorduna, A.; Pradhan, K.; Thota, R.; Reissman, S.; Sparano, J.A. Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System. Cancer Discov. 2020, 10, 935–941. [Google Scholar] [CrossRef] [PubMed]
  4. Kuderer, N.M.; Choueiri, T.K.; Shah, D.P.; Shyr, Y.; Rubinstein, S.M.; Rivera, D.R.; Shete, S.; Hsu, C.-Y.; Desai, A.; de Lima Lopes, G., Jr. Clinical Impact of COVID-19 on Patients with Cancer (CCC19): A Cohort Study. Lancet 2020, 395, 1907–1918. [Google Scholar] [CrossRef]
  5. Saini, K.S.; Tagliamento, M.; Lambertini, M.; McNally, R.; Romano, M.; Leone, M.; Curigliano, G.; de Azambuja, E. Mortality in Patients with Cancer and Coronavirus Disease 2019: A Systematic Review and Pooled Analysis of 52 Studies. Eur. J. Cancer 2020, 139, 43–50. [Google Scholar] [CrossRef]
  6. Zeidan, A.M.; Boddu, P.C.; Patnaik, M.M.; Bewersdorf, J.P.; Stahl, M.; Rampal, R.K.; Shallis, R.; Steensma, D.P.; Savona, M.R.; Sekeres, M.A. Special Considerations in the Management of Adult Patients with Acute Leukaemias and Myeloid Neoplasms in the COVID-19 Era: Recommendations from a Panel of International Experts. Lancet Haematol. 2020, 7, e601–e612. [Google Scholar] [CrossRef]
  7. Dai, M.; Liu, D.; Liu, M.; Zhou, F.; Li, G.; Chen, Z.; Zhang, Z.; You, H.; Wu, M.; Zheng, Q. Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak. Cancer Discov. 2020, 10, 783–791. [Google Scholar]
  8. Tian, J.; Yuan, X.; Xiao, J.; Zhong, Q.; Yang, C.; Liu, B.; Cai, Y.; Lu, Z.; Wang, J.; Wang, Y. Clinical Characteristics and Risk Factors Associated with COVID-19 Disease Severity in Patients with Cancer in Wuhan, China: A Multicentre, Retrospective, Cohort Study. Lancet Oncol. 2020, 21, 893–903. [Google Scholar] [CrossRef]
  9. Tian, Y.; Qiu, X.; Wang, C.; Zhao, J.; Jiang, X.; Niu, W.; Huang, J.; Zhang, F. Cancer Associates with Risk and Severe Events of COVID-19: A Systematic Review and Meta-Analysis. Int. J. Cancer 2021, 148, 363–374. [Google Scholar] [CrossRef] [PubMed]
  10. Becker, M.H. The Health Belief Model and Sick Role Behavior. Health Educ. Monogr. 1974, 2, 409–419. [Google Scholar] [CrossRef]
  11. Wong, L.P.; Alias, H.; Wong, P.-F.; Lee, H.Y.; AbuBakar, S. The Use of the Health Belief Model to Assess Predictors of Intent to Receive the COVID-19 Vaccine and Willingness to Pay. Hum. Vaccines Immunother. 2020, 16, 2204–2214. [Google Scholar] [CrossRef] [PubMed]
  12. Walrave, M.; Waeterloos, C.; Ponnet, K. Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach. JMIR Public Health Surveill. 2020, 6, e20572. [Google Scholar] [CrossRef] [PubMed]
  13. Tong, K.K.; Chen, J.H.; Yu, E.W.; Wu, A.M.S. Adherence to COVID-19 Precautionary Measures: Applying the Health Belief Model and Generalised Social Beliefs to a Probability Community Sample. Appl. Psychol. Health Well-Being 2020, 12, 1205–1223. [Google Scholar] [CrossRef] [PubMed]
  14. Petherick, A.; Goldszmidt, R.; Andrade, E.B.; Furst, R.; Hale, T.; Pott, A.; Wood, A. A Worldwide Assessment of Changes in Adherence to COVID-19 Protective Behaviours and Hypothesized Pandemic Fatigue. Nat. Hum. Behav. 2021, 5, 1145–1160. [Google Scholar] [CrossRef]
  15. Chan, H.F.; Skali, A.; Savage, D.A.; Stadelmann, D.; Torgler, B. Risk Attitudes and Human Mobility during the COVID-19 Pandemic. Sci. Rep. 2020, 10, 19931. [Google Scholar] [CrossRef] [PubMed]
  16. Lee, L.Y.; Cazier, J.B.; Starkey, T.; Turnbull, C.D.; Team, U.C.C.M.P.; Kerr, R.; Middleton, G. COVID-19 Mortality in Patients with Cancer on Chemotherapy or Other Anticancer Treatments: A Prospective Cohort Study. Lancet 2020, 395, 1919–1926. [Google Scholar] [CrossRef]
  17. Jee, J.; Foote, M.B.; Lumish, M.; Stonestrom, A.J.; Wills, B.; Narendra, V.; Avutu, V.; Murciano-Goroff, Y.R.; Chan, J.E.; Derkach, A. Chemotherapy and COVID-19 Outcomes in Patients with Cancer. J. Clin. Oncol. 2020, 38, 3538–3546. [Google Scholar] [CrossRef]
  18. Dreyling, M.; Aurer, I.; Federico, M.; Jerkeman, M.; Kersten, M.J.; Linton, K.M.; Mey, U.; Tilly, H.; Buske, C. EHA/ESMO Clinical Practice Guidelines for the Management of Malignant Lymphoma: Recommendations for the Second Phase of the COVID-19 Pandemic. HemaSphere 2021, 5, e529. [Google Scholar] [CrossRef]
  19. Curigliano, G.; Banerjee, S.; Cervantes, A.; Garassino, M.C.; Garrido, P.; Girard, N.; Haanen, J.; Jordan, K.; Lordick, F.; Machiels, J.-P. Managing Cancer Patients during the COVID-19 Pandemic: An ESMO Multidisciplinary Expert Consensus. Ann. Oncol. 2020, 31, 1320–1335. [Google Scholar] [CrossRef]
  20. Colombo, I.; Zaccarelli, E.; Del Grande, M.; Tomao, F.; Multinu, F.; Betella, I.; Ledermann, J.A.; Gonzalez-Martin, A.; Sessa, C.; Colombo, N. ESMO Management and Treatment Adapted Recommendations in the COVID-19 Era: Gynaecological Malignancies. ESMO Open 2020, 5, e000827. [Google Scholar] [CrossRef]
  21. Passaro, A.; Addeo, A.; Von Garnier, C.; Blackhall, F.; Planchard, D.; Felip, E.; Dziadziuszko, R.; De Marinis, F.; Reck, M.; Bouchaab, H. ESMO Management and Treatment Adapted Recommendations in the COVID-19 Era: Lung Cancer. ESMO Open 2020, 5, e000820. [Google Scholar] [CrossRef]
  22. De Azambuja, E.; Trapani, D.; Loibl, S.; Delaloge, S.; Senkus, E.; Criscitiello, C.; Poortmans, P.; Gnant, M.; Di Cosimo, S.; Cortes, J. ESMO Management and Treatment Adapted Recommendations in the COVID-19 Era: Breast Cancer. ESMO Open 2020, 5, e000793. [Google Scholar] [CrossRef]
  23. Marron, J.M.; Joffe, S.; Jagsi, R.; Spence, R.A.; Hlubocky, F.J. Ethics and Resource Scarcity: ASCO Recommendations for the Oncology Community during the COVID-19 Pandemic. J. Clin. Oncol. 2020, 38, 2201–2205. [Google Scholar] [CrossRef]
  24. Pennell, N.A.; Dillmon, M.; Levit, L.A.; Moushey, E.A.; Alva, A.S.; Blau, S.; Cannon, T.L.; Dickson, N.R.; Diehn, M.; Gonen, M. American Society of Clinical Oncology Road to Recovery Report: Learning from the COVID-19 Experience to Improve Clinical Research and Cancer Care. J. Clin. Oncol. 2021, 39, 155–169. [Google Scholar] [CrossRef]
  25. Basu, P.; Alhomoud, S.; Taghavi, K.; Carvalho, A.L.; Lucas, E.; Baussano, I. Cancer Screening in the Coronavirus Pandemic Era: Adjusting to a New Situation. JCO Glob. Oncol. 2021, 7, 416–424. [Google Scholar] [CrossRef]
  26. Wise-Draper, T.M.; Desai, A.; Elkrief, A.; Rini, B.I.; Flora, D.B.; Bowles, D.W.; Shah, D.; Rivera, D.; Johnson, D.B.; Lopes, G. LBA71 Systemic Cancer Treatment-Related Outcomes in Patients with SARS-CoV-2 Infection: A CCC19 Registry Analysis. Ann. Oncol. 2020, 31, S1201–S1202. [Google Scholar] [CrossRef]
  27. Maringe, C.; Spicer, J.; Morris, M.; Purushotham, A.; Nolte, E.; Sullivan, R.; Rachet, B.; Aggarwal, A. The Impact of the COVID-19 Pandemic on Cancer Deaths Due to Delays in Diagnosis in England, UK: A National, Population-Based, Modelling Study. Lancet Oncol. 2020, 21, 1023–1034. [Google Scholar] [CrossRef]
  28. Degeling, K.; Baxter, N.N.; Emery, J.; Jenkins, M.A.; Franchini, F.; Gibbs, P.; Mann, G.B.; McArthur, G.; Solomon, B.J.; IJzerman, M.J. An Inverse Stage-Shift Model to Estimate the Excess Mortality and Health Economic Impact of Delayed Access to Cancer Services Due to the COVID-19 Pandemic. Asia Pac. J. Clin. Oncol. 2021, 17, 359–367. [Google Scholar] [CrossRef] [PubMed]
  29. Baddour, K.; Kudrick, L.D.; Neopaney, A.; Sabik, L.M.; Peddada, S.D.; Nilsen, M.L.; Johnson, J.T.; Ferris, R.L.; Mady, L.J. Potential Impact of the COVID-19 Pandemic on Financial Toxicity in Cancer Survivors. Head Neck 2020, 42, 1332–1338. [Google Scholar] [CrossRef] [PubMed]
  30. Chen, Y.S.; Zhou, Z.N.; Glynn, S.M.; Frey, M.K.; Balogun, O.D.; Kanis, M.; Holcomb, K.; Gorelick, C.; Thomas, C.; Christos, P.J.; et al. Financial Toxicity, Mental Health, and Gynecologic Cancer Treatment: The Effect of the COVID-19 Pandemic among Low-Income Women in New York City. Cancer 2021, 127, 2399–2408. [Google Scholar] [CrossRef] [PubMed]
  31. Rentscher, K.E.; Zhou, X.; Small, B.J.; Cohen, H.J.; Dilawari, A.A.; Patel, S.K.; Bethea, T.N.; Van Dyk, K.M.; Nakamura, Z.M.; Ahn, J.; et al. Loneliness and Mental Health during the COVID-19 Pandemic in Older Breast Cancer Survivors and Noncancer Controls. Cancer 2021, 127, 3671–3679. [Google Scholar] [CrossRef]
  32. Ciążyńska, M.; Pabianek, M.; Szczepaniak, K.; Ułańska, M.; Skibińska, M.; Owczarek, W.; Narbutt, J.; Lesiak, A. Quality of Life of Cancer Patients during Coronavirus Disease (COVID-19) Pandemic. Psychooncology 2020, 29, 1377–1379. [Google Scholar] [CrossRef]
  33. Gloster, A.T.; Lamnisos, D.; Lubenko, J.; Presti, G.; Squatrito, V.; Constantinou, M.; Nicolaou, C.; Papacostas, S.; Aydın, G.; Chong, Y.Y. Impact of COVID-19 Pandemic on Mental Health: An International Study. PLoS ONE 2020, 15, e0244809. [Google Scholar] [CrossRef] [PubMed]
  34. Presti, G.; Mchugh, L.; Gloster, A.; Karekla, M.; Hayes, S.C. The Dynamics of Fear at the Time of Covid-19: A Contextual Behavioral Science Perspective. Clin. Neuropsychiatry 2020, 17, 65–71. [Google Scholar]
  35. Presti, G.; Dal Lago, B.; Fattori, A.; Mioli, G.; Moderato, P.; Sciaretta, L.; Costantino, M.A. Mental Health Support to Staff in a Major Hospital in Milan (Italy) during the COVID-19 Pandemic: A Framework of Actions. Gen. Psychiatry 2020, 33, e100244. [Google Scholar] [CrossRef]
  36. Meiring, R.M.; Gusso, S.; McCullough, E.; Bradnam, L. The Effect of the COVID-19 Pandemic Movement Restrictions on Self-Reported Physical Activity and Health in New Zealand: A Cross-Sectional Survey. Int. J. Environ. Res. Public Health 2021, 18, 1719. [Google Scholar] [CrossRef]
  37. Nurunnabi, M.; Almusharraf, N.; Aldeghaither, D. Mental Health and Well-Being during the COVID-19 Pandemic in Higher Education: Evidence from G20 Countries. J. Public Health Res. 2020, 9, 2010. [Google Scholar] [CrossRef]
  38. Kim, S.C.; Quiban, C.; Sloan, C.; Montejano, A. Predictors of Poor Mental Health among Nurses during COVID-19 Pandemic. Nurs. Open 2021, 8, 900–907. [Google Scholar] [CrossRef]
  39. Kobayashi, L.C.; O’Shea, B.Q.; Kler, J.S.; Nishimura, R.; Palavicino-Maggio, C.B.; Eastman, M.R.; Vinson, Y.R.; Finlay, J.M. Cohort Profile: The COVID-19 Coping Study, a Longitudinal Mixed-Methods Study of Middle-Aged and Older Adults’ Mental Health and Well-Being during the COVID-19 Pandemic in the USA. BMJ Open 2021, 11, e044965. [Google Scholar] [CrossRef] [PubMed]
  40. Kafle, K.; Shrestha, D.B.; Baniya, A.; Lamichhane, S.; Shahi, M.; Gurung, B.; Tandan, P.; Ghimire, A.; Budhathoki, P. Psychological Distress among Health Service Providers during COVID-19 Pandemic in Nepal. PLoS ONE 2021, 16, e0246784. [Google Scholar]
  41. Islam, M.; Islam, U.S.; Mosaddek, A.S.M.; Potenza, M.N.; Pardhan, S. Treatment, Persistent Symptoms, and Depression in People Infected with COVID-19 in Bangladesh. Int. J. Environ. Res. Public Health 2021, 18, 1453. [Google Scholar] [CrossRef]
  42. Chong, Y.Y.; Chien, W.T.; Cheng, H.Y.; Lamnisos, D.; Ļubenko, J.; Presti, G.; Squatrito, V.; Constantinou, M.; Nicolaou, C.; Papacostas, S. Patterns of Psychological Responses among the Public during the Early Phase of Covid-19: A Cross-Regional Analysis. Int. J. Environ. Res. Public Health 2021, 18, 4143. [Google Scholar] [CrossRef] [PubMed]
  43. Fiest, K.M.; Leigh, J.P.; Krewulak, K.D.; Plotnikoff, K.M.; Kemp, L.G.; Ng-Kamstra, J.; Stelfox, H.T. Experiences and Management of Physician Psychological Symptoms during Infectious Disease Outbreaks: A Rapid Review. BMC Psychiatry 2021, 21, 91. [Google Scholar] [CrossRef]
  44. Aughterson, H.; McKinlay, A.R.; Fancourt, D.; Burton, A. Psychosocial Impact on Frontline Health and Social Care Professionals in the UK during the COVID-19 Pandemic: A Qualitative Interview Study. BMJ Open 2021, 11, e047353. [Google Scholar] [CrossRef] [PubMed]
  45. Chatzittofis, A.; Karanikola, M.; Michailidou, K.; Constantinidou, A. Impact of the COVID-19 Pandemic on the Mental Health of Healthcare Workers. Int. J. Environ. Res. Public Health 2021, 18, 1435. [Google Scholar] [CrossRef] [PubMed]
  46. Cheema, M.; Mitrev, N.; Hall, L.; Tiongson, M.; Ahlenstiel, G.; Kariyawasam, V. Depression, Anxiety and Stress among Patients with Inflammatory Bowel Disease during the COVID-19 Pandemic: Australian National Survey. BMJ Open Gastroenterol. 2021, 8, e000581. [Google Scholar] [CrossRef]
  47. Hawes, M.T.; Szenczy, A.K.; Olino, T.M.; Nelson, B.D.; Klein, D.N. Trajectories of Depression, Anxiety and Pandemic Experiences; A Longitudinal Study of Youth in New York during the Spring-Summer of 2020. Psychiatry Res. 2021, 298, 113778. [Google Scholar] [CrossRef] [PubMed]
  48. Carmassi, C.; Cerveri, G.; Bertelloni, C.A.; Marasco, M.; Dell’Oste, V.; Massimetti, E.; Gesi, C.; Dell’Osso, L. Mental Health of Frontline Help-Seeking Healthcare Workers during the COVID-19 Outbreak in the First Affected Hospital in Lombardy, Italy. Psychiatry Res. 2021, 298, 113763. [Google Scholar] [CrossRef]
  49. Chiesa, A.; Serretti, A. Mindfulness-Based Stress Reduction for Stress Management in Healthy People: A Review and Meta-Analysis. J. Altern. Complement. Med. 2009, 15, 593–600. [Google Scholar] [CrossRef]
  50. Gloster, A.T.; Meyer, A.H.; Lieb, R. Psychological Flexibility as a Malleable Public Health Target: Evidence from a Representative Sample. J. Context. Behav. Sci. 2017, 6, 166–171. [Google Scholar] [CrossRef] [Green Version]
  51. Gu, J.; Strauss, C.; Bond, R.; Cavanagh, K. How Do Mindfulness-Based Cognitive Therapy and Mindfulness-Based Stress Reduction Improve Mental Health and Wellbeing? A Systematic Review and Meta-Analysis of Mediation Studies. Clin. Psychol. Rev. 2015, 37, 1–12. [Google Scholar] [CrossRef] [PubMed]
  52. Panayiotou, G.; Karekla, M.; Mete, I. Dispositional Coping in Individuals with Anxiety Disorder Symptomatology: Avoidance Predicts Distress. J. Context. Behav. Sci. 2014, 3, 314–321. [Google Scholar] [CrossRef]
  53. Golden, J.; Conroy, R.M.; Bruce, I.; Denihan, A.; Greene, E.; Kirby, M.; Lawlor, B.A. Loneliness, Social Support Networks, Mood and Wellbeing in Community-Dwelling Elderly. Int. J. Geriatr. Psychiatry J. Psychiatry Late Life Allied Sci. 2009, 24, 694–700. [Google Scholar] [CrossRef]
  54. Panayiotou, G.; Karekla, M. Perceived Social Support Helps, but Does Not Buffer the Negative Impact of Anxiety Disorders on Quality of Life and Perceived Stress. Soc. Psychiatry Psychiatr. Epidemiol. 2013, 48, 283–294. [Google Scholar] [CrossRef]
  55. Paul, K.I.; Moser, K. Unemployment Impairs Mental Health: Meta-Analyses. J. Vocat. Behav. 2009, 74, 264–282. [Google Scholar] [CrossRef]
  56. Beaton, D.E.; Bombardier, C.; Guillemin, F.; Ferraz, M.B. Guidelines for the Process of Cross-Cultural Adaptation of Self-Report Measures. Spine 2000, 25, 3186–3191. [Google Scholar] [CrossRef] [Green Version]
  57. Chen, G.; Gully, S.M.; Eden, D. Validation of a New General Self-Efficacy Scale. Organ. Res. Methods 2001, 4, 62–83. [Google Scholar] [CrossRef] [Green Version]
  58. Kocalevent, R.-D.; Berg, L.; Beutel, M.E.; Hinz, A.; Zenger, M.; Härter, M.; Nater, U.; Brähler, E. Social Support in the General Population: Standardization of the Oslo Social Support Scale (OSSS-3). BMC Psychol. 2018, 6, 31. [Google Scholar] [CrossRef]
  59. Mansfield, A.K.; Keitner, G.I.; Sheeran, T. The Brief Assessment of Family Functioning Scale (BAFFS): A Three-Item Version of the General Functioning Scale of the Family Assessment Device. Psychother. Res. 2019, 29, 824–831. [Google Scholar] [CrossRef] [PubMed]
  60. Cohen, S.; Kamarck, T.; Mermelstein, R. Perceived Stress Scale. Meas. Stress Guide Health Soc. Sci. 1994, 10, 1–2. [Google Scholar]
  61. Fahlman, S.A.; Mercer-Lynn, K.B.; Flora, D.B.; Eastwood, J.D. Development and Validation of the Multidimensional State Boredom Scale. Assessment 2013, 20, 68–85. [Google Scholar] [CrossRef]
  62. Keyes, C.L.; Wissing, M.; Potgieter, J.P.; Temane, M.; Kruger, A.; Van Rooy, S. Evaluation of the Mental Health Continuum–Short Form (MHC–SF) in Setswana-Speaking South Africans. Clin. Psychol. Psychother. 2008, 15, 181–192. [Google Scholar] [CrossRef] [PubMed]
  63. Watson, D.; Clark, L.A.; Tellegen, A. Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scales. J. Pers. Soc. Psychol. 1988, 54, 1063. [Google Scholar] [CrossRef] [PubMed]
  64. Feldman, G.; Hayes, A.; Kumar, S.; Greeson, J.; Laurenceau, J.-P. Mindfulness and Emotion Regulation: The Development and Initial Validation of the Cognitive and Affective Mindfulness Scale-Revised (CAMS-R). J. Psychopathol. Behav. Assess. 2007, 29, 177. [Google Scholar] [CrossRef]
  65. Gloster, A.T.; Block, V.J.; Klotsche, J.; Villanueva, J.; Rinner, M.T.; Benoy, C.; Walter, M.; Karekla, M.; Bader, K. Psy-Flex: A Contextually Sensitive Measure of Psychological Flexibility. J. Context. Behav. Sci. 2021, 22, 13–23. [Google Scholar] [CrossRef]
  66. Bergomi, C.; Tschacher, W.; Kupper, Z. The Assessment of Mindfulness with Self-Report Measures: Existing Scales and Open Issues. Mindfulness 2013, 4, 191–202. [Google Scholar] [CrossRef] [Green Version]
  67. Crawford, J.R.; Henry, J.D. The Positive and Negative Affect Schedule (PANAS): Construct Validity, Measurement Properties and Normative Data in a Large Non-Clinical Sample. Br. J. Clin. Psychol. 2004, 43, 245–265. [Google Scholar] [CrossRef] [PubMed]
  68. de Carvalho, J.S.; Pereira, N.S.; Pinto, A.M.; Marôco, J. Psychometric Properties of the Mental Health Continuum-Short Form: A Study of Portuguese Speaking Children/Youths. J. Child Fam. Stud. 2016, 25, 2141–2154. [Google Scholar] [CrossRef]
  69. Golden-Kreutz, D.M.; Browne, M.W.; Frierson, G.M.; Andersen, B.L. Assessing Stress in Cancer Patients: A Second-Order Factor Analysis Model for the Perceived Stress Scale. Assessment 2004, 11, 216–223. [Google Scholar] [CrossRef]
  70. Woringer, M.; Nielsen, J.J.; Zibarras, L.; Evason, J.; Kassianos, A.P.; Harris, M.; Majeed, A.; Soljak, M. Development of a Questionnaire to Evaluate Patients’ Awareness of Cardiovascular Disease Risk in England’s National Health Service Health Check Preventive Cardiovascular Programme. BMJ Open 2017, 7, e014413. [Google Scholar] [CrossRef]
  71. Funder, D.C.; Ozer, D.J. Evaluating Effect Size in Psychological Research: Sense and Nonsense. Adv. Methods Pract. Psychol. Sci. 2019, 2, 156–168. [Google Scholar] [CrossRef]
  72. Ghio, D.; Lawes-Wickwar, S.; Tang, M.Y.; Epton, T.; Howlett, N.; Jenkinson, E.; Stanescu, S.; Westbrook, J.; Kassianos, A.; Watson, D.; et al. What Influences People’s Responses to Public Health Messages for Managing Risks and Preventing Infectious Diseases? A Rapid Systematic Review of the Evidence and Recommendations. BMJ Open 2020, 11, e048750. [Google Scholar] [CrossRef]
  73. Romito, F.; Dellino, M.; Loseto, G.; Opinto, G.; Silvestris, E.; Cormio, C.; Guarini, A.; Minoia, C. Psychological Distress in Outpatients with Lymphoma during the COVID-19 Pandemic. Front. Oncol. 2020, 10, 1270. [Google Scholar] [CrossRef] [PubMed]
  74. Özdin, S.; Bayrak Özdin, Ş. Levels and Predictors of Anxiety, Depression and Health Anxiety during COVID-19 Pandemic in Turkish Society: The Importance of Gender. Int. J. Soc. Psychiatry 2020, 66, 504–511. [Google Scholar] [CrossRef] [PubMed]
  75. Wang, D.; Yin, Y.; Hu, C.; Liu, X.; Zhang, X.; Zhou, S.; Jian, M.; Xu, H.; Prowle, J.; Hu, B. Clinical Course and Outcome of 107 Patients Infected with the Novel Coronavirus, SARS-CoV-2, Discharged from Two Hospitals in Wuhan, China. Crit. Care 2020, 24, 188. [Google Scholar] [CrossRef] [PubMed]
  76. Musche, V.; Bäuerle, A.; Steinbach, J.; Schweda, A.; Hetkamp, M.; Weismüller, B.; Kohler, H.; Beckmann, M.; Herrmann, K.; Tewes, M. COVID-19-Related Fear and Health-Related Safety Behavior in Oncological Patients. Front. Psychol. 2020, 11, 1984. [Google Scholar] [CrossRef]
  77. Adhikari, S.P.; Rawal, N.; Shrestha, D.B.; Budhathoki, P.; Banmala, S.; Awal, S.; Bhandari, G.; Poudel, R.; Parajuli, A.R. Prevalence of Anxiety, Depression, and Perceived Stigma in Healthcare Workers in Nepal During Later Phase of First Wave of COVID-19 Pandemic: A Web-Based Cross-Sectional Survey. Cureus 2021, 13, e16037. [Google Scholar] [CrossRef]
  78. Shrestha, D.B.; Thapa, B.B.; Katuwal, N.; Shrestha, B.; Pant, C.; Basnet, B.; Mandal, P.; Gurung, A.; Agrawal, A.; Rouniyar, R. Psychological Distress in Nepalese Residents during COVID-19 Pandemic: A Community Level Survey. BMC Psychiatry 2020, 20, 491. [Google Scholar] [CrossRef]
  79. Sigorski, D.; Sobczuk, P.; Osmola, M.; Kuć, K.; Walerzak, A.; Wilk, M.; Ciszewski, T.; Kopeć, S.; Hryń, K.; Rutkowski, P. Impact of COVID-19 on Anxiety Levels among Patients with Cancer Actively Treated with Systemic Therapy. Esmo Open 2020, 5, e000970. [Google Scholar] [CrossRef]
  80. Younger, E.; Smrke, A.; Lidington, E.; Farag, S.; Ingley, K.; Chopra, N.; Maleddu, A.; Augustin, Y.; Merry, E.; Wilson, R. Health-Related Quality of Life and Experiences of Sarcoma Patients during the COVID-19 Pandemic. Cancers 2020, 12, 2288. [Google Scholar] [CrossRef]
  81. Zhang, H.; Yin, J.; Wang, X.; Yuan, D.; Zhu, K.; Li, K.; Xu, G.; Dang, C.; Jia, R.; Zhang, Y. Patients’ Responses to the Sudden Interruption of Chemotherapy During the Outbreak of the Novel Coronavirus: A Cross-Sectional Study. Cancer Manag. Res. 2021, 13, 351. [Google Scholar] [CrossRef] [PubMed]
  82. Klaassen, Z.; Wallis, C.J.D. Assessing Patient Risk from Cancer and COVID-19: Managing Patient Distress. Urol. Oncol. 2021, 39, 243–246. [Google Scholar] [CrossRef] [PubMed]
  83. Miaskowski, C.; Paul, S.M.; Snowberg, K.; Abbott, M.; Borno, H.; Chang, S.; Chen, L.M.; Cohen, B.; Hammer, M.J.; Kenfield, S.A. Stress and Symptom Burden in Oncology Patients during the COVID-19 Pandemic. J. Pain Symptom Manag. 2020, 60, e25–e34. [Google Scholar] [CrossRef] [PubMed]
  84. Juanjuan, L.; Santa-Maria, C.A.; Hongfang, F.; Lingcheng, W.; Pengcheng, Z.; Yuanbing, X.; Yuyan, T.; Zhongchun, L.; Bo, D.; Meng, L. Patient-Reported Outcomes of Patients with Breast Cancer during the COVID-19 Outbreak in the Epicenter of China: A Cross-Sectional Survey Study. Clin. Breast Cancer 2020, 20, e651–e662. [Google Scholar] [CrossRef] [PubMed]
  85. Wang, Y.; Duan, Z.; Ma, Z.; Mao, Y.; Li, X.; Wilson, A.; Qin, H.; Ou, J.; Peng, K.; Zhou, F. Epidemiology of Mental Health Problems among Patients with Cancer during COVID-19 Pandemic. Transl. Psychiatry 2020, 10, 263. [Google Scholar] [CrossRef] [PubMed]
  86. Bendau, A.; Ströhle, A.; Petzold, M.B. Mental Health in Health Professionals in the COVID-19 Pandemic. Adv. Exp. Med. Biol. 2021, 1318, 737–757. [Google Scholar]
  87. Bowden, T.; Bowden, S. Acceptance and Commitment Therapy (ACT): An Overview for Practitioners. Aust. J. Guid. Couns. 2012, 22, 279. [Google Scholar] [CrossRef]
  88. Carpenter, C.J. A Meta-Analysis of the Effectiveness of Health Belief Model Variables in Predicting Behavior. Health Commun. 2010, 25, 661–669. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Jones, C.J.; Smith, H.; Llewellyn, C. Evaluating the Effectiveness of Health Belief Model Interventions in Improving Adherence: A Systematic Review. Health Psychol. Rev. 2014, 8, 253–269. [Google Scholar] [CrossRef] [PubMed]
  90. Gloster, A.T.; Karkela, M. A.T.; Karkela, M. A Multi-Level, Multi-Method Approach to Testing and Refining Intervention Targets. In Beyond the DSM; New Harbinger: Oakland, CA, USA, 2020. [Google Scholar]
  91. Gloster, A.T.; Walder, N.; Levin, M.; Twohig, M.; Karekla, M. The Empirical Status of Acceptance and Commitment Therapy: A Review of Meta-Analyses. J. Context. Behav. Sci. 2020, 18, 181–192. [Google Scholar] [CrossRef]
Table
Table 1. Socio-demographic and medical characteristics of the participants who were recruited in the study overall and separately for cancer and non-cancer participants.
Table 1. Socio-demographic and medical characteristics of the participants who were recruited in the study overall and separately for cancer and non-cancer participants.
Total
(n = 9565)		Cancer
Participants
(n = 264, 2.8%)		Non-Cancer
Participants
(n = 9301, 97.2%) 		p-ValueEffect Size
Socio-demographic Characteristics
Age median
(years (IQR)) a		 34 (24–46)51.5 (40,60)34 (26,45)0.15 g1.05 i
Gender (n (%)) bMale2101 (22.0)52 (19.7)2049 (22.0)0.66 h0.01 j
Female7431 (77.7)211 (79.9)7220 (77.6)
Other/Non-Binary33 (0.3)1 (0.4)32 (0.3)
Employment status
(n (%)) b		Working full time5108 (53.4)134 (50.8)4974 (53.5)<0.01 h**0.15 j
Working part time1674 (17.5)49 (18.6)1625 (17.5)
Unemployed 2218 (23.2)24 (9.1)2194 (23.6)
On parental leave 241 (2.2)6 (2.3)208 (2.2)
Retired 351 (3.7)51 (19.3)300 (2.2)
Working as a health professional (n (%)) cYes1556 (16.6)54 (21.3)1502 (16.5)0.33 h0.02 j
No 7819 (83.4)200 (78.7)7619 (83.5)
University student
(n (%)) d		Yes2718 (28.8)26 (10.1)2692 (29.3)0.04 h*0.07 j
No 6735 (71.2)232 (89.9)6503 (70.7)
Education level (n (%)) ePrimary77 (0.8)2 (0.8)75 (0.8)0.74 h0.04 j
Secondary 2348 (25.2)49 (18.6)2299 (24.3)
Higher 6887 (74.0)213 (80.6)7097 (74.9)
Marital status (n (%)) bSingle2947 (31.2)48 (18.3)2899 (31.6)0.88 h0.09 j
In a relationship/Engaged/Married5912 (62.6)178 (68.3)5734 (62.5)
Divorced/Widower581 (6.2)35 (13.4)546 (5.9)
Have children (n (%)) bYes3899 (40.8)174 (65.9)3725 (40.1)0.24 h0.09 j
No 5666 (59.2)90 (34.1)5576 (59.9)
Living situation (n (%)) bLive alone1397 (14.6)47 (17.8)1350 (14.5)0.45 h0.07 j
Live with parents1991 (20.8)19 (7.2)1972 (21.2)
Live with one of parents484 (5.1)5 (1.9)479 (5.2)
Live with own family5171 (54.1)185 (70.1)4986 (53.6)
Live with friends/roommates522 (5.5)8 (3.0)514 (5.5)
COVID-19 Infection
Infected by COVID-19 (n (%)) bYes135 (1.4)6 (2.3)129 (1.4)0.48 h0.01 j
No 8417 (88.0)230 (87.1)8187 (88.0)
Unsure or have had symptoms but not diagnosed1013 (10.6)28 (10.6)985 (10.6)
Partner been infected by COVID-19 (n (%)) fYes70 (0.7)4 (1.5)66 (0.7)0.27 h0.02 j
No 8732 (92.2)243 (92.4)8489 (92.2)
Unsure or (s)he has had symptoms but not diagnosed670 (7.1)16 (6.1)654 (7.1)
Others infected by COVID-19 (n (%)) eYes538 (5.6)19 (7.2)519 (5.6)0.38 h0.01 j
No 8227 (86.0)227 (86.0)8000 (86.0)
Unsure or (s)he has had symptoms but not diagnosed799 (8.4)18 (6.8)781 (8.4)
Abbreviations: IQR, interquartile range; a n = 9563; b n = 9565; c n = 9375; d n = 9453; e n = 9564; f n = 9472; g differences between cancer participants and participants not reporting cancer were examined with t-test if outcomes were continuous variables with normal distributions; h differences between cancer participants and participants not reporting cancer were examined with χ2 test if categorical outcomes; i effect sizes were examined with Cohen’s d if outcomes were continuous variables; j effect sizes were examined with Cramér’s V if outcomes were categorical variables. * Statistically significant p < 0.05 ** Statistically significant p < 0.01.
Table
Table 2. Comparisons between participants reporting cancer vs. no cancer.
Table 2. Comparisons between participants reporting cancer vs. no cancer.
Total
(n = 9565)		Cancer
Participants
(n = 264, 2.8%)		Non-Cancer
Participants
(n = 9301, 97.2%) 		p-ValueEffect Size
COVID-19 Protective Behaviors (score 0–10)
Keeping distance from other people when going out (median (IQR)) a 9 (8, 10)10 (9–10)9 (8–10)<0.01 c*0.19 e
Self-isolating, limiting unnecessary travelling according to national guidelines (median (IQR)) a 10 (9, 10)10 (9–10)10 (9–10)0.05 c*0.03 e
Washing hands regularly with water and soap (median (IQR)) a 10 (9, 10)10 (9–10)10 (9–10)0.04 c*0.17 e
Protective behaviors self-efficacy (median (IQR)) 6.2 (5.6–7)6.6 (5.9–7)6.2 (5.6–7)<0.01 c**0.20 e
Coping Styles and Social Support
Social support (OSS)e (Ν (%)) bLow 2337 (24.4)52 (19.8)2285 (24.6)<0.01 d**0.03 f
Moderate 4999 (52.3)129 (49.0)4870 (52.4)
High 2227 (23.3)82 (31.2)2145 (23.0)
Family functioning (BAFFS) (median (IQR)) 6 (4–7)5 (4–6)6 (4–7)0.45 c0.10 e
Mental Health Outcomes
Perceived stress (PSS) (median (IQR)) 17 (12–22)15 (10–20)17 (12–22)<0.01 c**0.27 e
Levels of perceived stress (Ν (%)) bLow 3159 (33.0)119 (45.3)3040 (32.7)<0.01 d**0.04 f
Moderate 5344 (55.9)120 (45.6)5224 (56.2)
High 1060 (11.1)24 (9.1)1036 (11.1)
Psychological flexibility (Psy-Flex) (median (IQR)) 34 (30, 37)35 (32, 38)34 (30, 37)<0.01 c**0.37 e
Mindfulness (CAMS) (median (IQR)) 27 (24–29)27 (25–30)27 (24–29)0.04 c*0.19 e
Prosocialness (PSA) (median (IQR)) 23 (20, 26)23 (20–26)23 (20–26)0.99 c0.01 e
Depressive symptomatology (MSBS—reinforcement) (median (IQR)) 3 (3–3)3 (3–3)3 (2,3)0.77 c0.10 e
Depressive symptomatology (MSBS -boredom) (median (IQR)) 2 (1.5–3)2 (1.5–2.5)2 (1.5–3)<0.01 c**0.24 e
Wellbeing total (MHCSF) (median (IQR)) 42 (31–52)46 (36–54)42 (31–52)<0.01 c**0.22 e
Hedonic wellbeing (MHCSF) (median (IQR)) 11 (8–12)12 (9–13)11 (8–12)<0.01 c**0.19 e
Eudemonic social wellbeing (MHCSF) (median (IQR)) 11 (7–16)12 (8–17)11 (7–16)0.21 c0.16 e
Eudemonic psychological wellbeing (MHCSF) (median (IQR)) 21 (15–24)23 (18–26)21 (15–24)<0.01 c**0.24 e
Wellbeing type (MHCSF)Languishing 882 (10.1)20 (8.1)862 (10.2)<0.01 d**0.04 f
Moderately mentally healthy4345 (50.0)104 (41.9)4241 (50.2)
Flourishing 3468 (39.9)124 (50.0)3344 (39.6)
Positive affect (PANAS) (median (IQR)) 29 (23–35)30 (25–37)29 (23–35)0.01 c*0.21 e
Negative affect (PANAS) (median (IQR)) 28 (21–38)26 (20–33)28 (21–38)0.01 c*0.19 e
Beliefs about COVID-19
Perceived susceptibility (median (IQR)) 9 (6–11)11 (7.5, 14)8 (6–11)<0.01 c**0.56 e
Perceived severity (median (IQR)) 13 (10–15)14 (12–17)13 (10–15)<0.01 c**0.37 e
Abbreviations: BAFFS = Brief Assessment for Family Functioning Scale; CAMS = Cognitive and Affective Mindfulness Scale; IQR = interquartile range; MHCSF = Mental Health Continuum Short Form; MSBS = Multidimensional State Boredom Scale; OSS = Oslo Social Supports Scale; PANAS = Positive and Negative Affect Scale; PSA = Prosocialness Scale for Adults; PSS = Perceived Stress Scale; a Ν = 9565; b N = 9563 c differences between cancer and non-cancer participants were examined with χ2 test; d differences between cancer and non-cancer participants were examined with Kolmogorov–Smirnov test; e effect size between cancer and non-cancer participants was examined with Cohen’s d; f effect size between cancer and non-cancer participants was examined with Cramér’s V. * Statistically significant p < 0.05 ** Statistically significant p < 0.01.
Table
Table 3. Multivariate linear regression of the level of keeping distance as a linear combination of social support (model 1), perceived susceptibility and perceived severity (model 2), change in finances during quarantine and availability of obtaining all the basic supplies (model 3), psychological flexibility (model 4), and all the predictors (model 5) after adjusting for different socio-demographic and socio-economic characteristics (i.e., age, gender).
Table 3. Multivariate linear regression of the level of keeping distance as a linear combination of social support (model 1), perceived susceptibility and perceived severity (model 2), change in finances during quarantine and availability of obtaining all the basic supplies (model 3), psychological flexibility (model 4), and all the predictors (model 5) after adjusting for different socio-demographic and socio-economic characteristics (i.e., age, gender).
Coefficient
Model 1Model 2Model 3Model 4Model 5
Priority of Health Concern during Pandemic
CancerRefRefRefRefRef
COVID-190.57 (0.07, 1.07) *0.29 (−0.23, 0.80)0.63 (0.13, 1.14) *0.62 (0.12, 1.11) *0.43 (−0.09, 0.94)
Age0.01 (−0.01, 0.02)0.00 (−0.02, 0.02)0.01 (−0.01, 0.02)0.00 (−0.02, 0.02)−0.01 (−0.02, 0.01)
Gender
MaleRefRefRefRefRef
Female −0.11 (−0.78, 0.56)−0.17 (−0.87, 0.46)−0.02 (−0.71, 0.67)−0.18 (−0.85, 0.48)−0.18 (−0.86, 0.49)
Cancer Type
Thyroid RefRefRefRefRef
GI0.31 (−0.71, 1.33)0.11 (−0.89, 1.10)0.42 (−0.60, 1.44)0.41 (−0.59, 1.42)0.33 (−0.66, 1.32)
Breast0.33 (−0.45, 1.11)0.38 (−0.41, 1.10)0.43 (−0.35, 1.22)0.38 (−0.38, 1.15)0.48 (−0.27, 1.23)
Soft molecular−0.84 (−3.97, 2.29)−0.56 (−3.51, 2.57)−0.83 (−3.95, 2.29)−0.69 (−3.76, 2.39)−0.28 (−3.28, 2.72)
Female reproductive0.43 (−0.47, 1.33)0.34 (−0.54, 1.21)0.56 (−0.35, 1.47)0.43 (−0.45, 1.32)0.49 (−0.38, 1.36)
Leukemia 0.29 (−0.72, 1.30)0.30 (−0.67, 1.29)0.43 (−0.60, 1.46)0.26 (−0.73, 1.25)0.43 (−0.56, 1.42)
Lymphoma 0.19 (−0.85, 1.24)0.08 (−0.98, 1.05)0.25 (−0.79, 1.29)0.32 (−0.71, 1.34)0.16 (−0.84, 1.17)
Cervical 0.01 (−1.70, 1.71)−0.20 (−1.89, 1.42)0.14 (−1.56, 1.85)−0.09 (−1.77, 1.59)−0.18 (−1.82, 1.47)
Skin0.25 (−0.69, 1.18)0.24 (−0.67, 1.14)0.34 (−0.59, 1.28)0.22 (−0.69, 1.14)0.32 (−0.58, 1.21)
Lung1.06 (−0.88, 3.00)1.35 (−0.70, 3.06)1.24 (−0.69, 3.16)1.18 (−0.71, 3.07)1.28 (−0.58, 3.13)
Urine0.34 (−0.99, 1.66)0.23 (−0.97, 1.59)0.37 (−0.96, 1.69)0.50 (−0.80, 1.80)0.57 (−0.71, 1.85)
Testicular0.53 (−1.49, 2.54)0.33 (−1.62, 2.32)0.52 (−1.49, 2.53)0.04 (−1.97, 2.04)−0.01 (−1.96, 1.96)
Prostate0.57 (−0.83, 1.98)0.87 (−0.59, 2.15)0.82 (−0.60, 2.24)0.54 (−0.83, 1.91)0.92 (−0.46, 2.30)
Bone 0.22 (−1.45, 1.90)0.50 (−1.18, 2.08)0.26 (−1.41, 1.92)0.16 (−1.48, 1.80)0.34 (−1.26, 1.95)
Brain 0.13 (−1.53, 1.80)0.42 (−1.13, 2.12)0.10 (−1.56, 1.76)0.17 (−1.46, 1.81)0.54 (−1.06, 2.14)
Cancer Therapy
Yes RefRefRefRefRef
No −0.39 (−0.90, 0.12)−0.31 (−0.81, 0.19)−0.46 (−0.97, 0.05)−0.39 (−0.89, 0.10)−0.38 (−0.88, 0.11)
Social Support0.05 (−0.04, 0.14) 0.03 (−0.06, 0.12)
Beliefs about COVID-19
Perceived susceptibility −0.08 (−0.14, −0.01) * −0.07 (−0.13, −0.01) *
Perceived severity 0.15 (0.07, 0.23) * 0.14 (0.06, 0.22) *
Finances in Quarantine
Have got better Ref Ref
Stayed the same 1.12 (0.03, 2.21) * 1.18 (0.13, 2.23) *
Have got worse 1.25 (0.13, 2.38) * 1.36 (0.27, 2.45) *
Access to Basic Supplies
Yes Ref Ref
No −0.20 (−1.08, 0.67) −0.13 (−0.97, 0.72)
Psychological Flexibility 0.06 (0.02, 0.10) *0.05 (0.01, 0.09) *
Note: * Statistically significant p < 0.05.
Table
Table 4. Multivariate linear regression of stress as a linear combination of social support (model 1), perceived susceptibility and perceived severity (model 2), change in finances during quarantine and availability of obtaining all the basic supplies (model 3), psychological flexibility (model 4), and all the predictors (model 5) after adjusting for different socio-demographic and socio-economic characteristics (i.e., age, gender).
Table 4. Multivariate linear regression of stress as a linear combination of social support (model 1), perceived susceptibility and perceived severity (model 2), change in finances during quarantine and availability of obtaining all the basic supplies (model 3), psychological flexibility (model 4), and all the predictors (model 5) after adjusting for different socio-demographic and socio-economic characteristics (i.e., age, gender).
Coefficient (p-Value)
Model 1Model 2Model 3Model 4Model 5
Priority of Health Concern during Pandemic
CancerRefRefRefRefRef
COVID-190.73 (−1.50, 2.97)0.66 (−1.69, 2.92)0.97 (−1.22, 3.17)0.38 (−1.71, 2.46)0.29 (−1.82, 2.41)
Age−0.16 (−0.24, −0.08) *−0.12 (−1.20, −0.04) *−0.15 (−0.23, −0.08) *−0.10 (−0.18, −0.03) *−0.07 (−0.14, 0.01)
Gender
MaleRefRefRefRefRef
Female 0.53 (−2.46, 3.52)1.49 (−1.51, 4.50)1.41 (−1.59, 4.41)1.16 (−1.63, 3.95)3.01 (0.24, 5.78) *
Cancer Type
Thyroid RefRefRefRefRef
GI−1.03 (−5.57, 3.50)−1.27 (−5.77, 3.22)−0.33 (−4.79, 4.12)−2.00 (−6.23, 2.22) *−1.48 (−5.56, 2.60) *
Breast−3.99 (−7.45, −0.53) *−4.40 (−7.81, −1.00) *−3.80 (−7.20, −0.40) *−4.43 (−7.65, −1.21) *−4.32 (−7.40, −1.24) *
Soft molecular−13.12 (−27.03, 0.79)−13.99 (−27.70, −0.27) *−11.05 (−24.64, 2.54)−14.45 (−27.40, −1.50) *−14.21 (−26.54, −1.88) *
Female reproductive−4.70 (−8.68, −0.67) *−4.67 (−8.62, −0.72) *−4.47 (−8.41, −0.52) *−4.71 (−8.43, −0.98) *−4.68 (−8.25, −1.10) *
Leukemia −5.60 (−10.07, −1.12) *−6.25 (−10.66, −1.83) *−5.95 (−10.41, −1.48) *−5.35 (−9.52, −1.19) *−6.39 (−10.45, −2.33) *
Lymphoma −7.52 (−12.16, −2.90) *−7.85 (−12.42, −3.28) *−7.56 (−12.10, −3.03) *−8.76 (−13.07, 4.45)−8.11 (−12.25, −3.98) *
Cervical −8.10 (−15.67, −0.52) *−7.40 (−14.87, 0.07)−9.03 (−16.47, −1.59) *−7.21 (−14.27, −0.16) *−7.46 (−14.21, −0.70) *
Skin−6.62 (−10.77, −2.48) *−6.40 (−10.47, −2.32) *−6.65 (−10.71, −2.59) *−6.43 (−10.29, −2.57) *−6.36 (−10.04, −2.68) *
Lung−5.95 (−14.56, 2.66)−7.70 (−16.12, 0.73)−8.08 (−16.46, 0.30)−7.19 (−15.15, 0.77)−7.72 (−15.36, −0.09) *
Urine−0.88 (−6.74, 4.98)−0.05 (−5.80, 5.69)1.37 (−4.38, 7.12)−2.26 (−7.73, 3.21)−0.69 (−5.94, 4.57)
Testicular−13.54 (−22.49, −4.59) *−10.95 (−19.84, −2.05) *−13.09 (−21.83, −4.35) *−9.10 (−17.50, −0.62) *−7.83 (−15.90, 0.24)
Prostate−6.16 (−12.38, 0.07)−5.97 (−12.15, 0.20)−5.10 (−11.29, 1.09)−5.90 (−11.68, −0.12) *−3.64 (−9.30, 2.03)
Bone 1.36 (−6.06, 8.79)−0.21 (−7.54, 7.11)0.47 (−6.79, 7.73)1.91 (−5.01, 8.82)0.63 (−5.97, 7.23)
Brain 0.53 (−6.87, 7.93)0.17 (−7.15, 7.48)1.99 (−5.24, 9.22)0.25 (−6.64, 7.13)0.27 (−6.32, 6.86)
Cancer Therapy
Yes RefRefRefRefRef
No −1.00 (−3.26, 1.25)−0.49 (−2.75, 1.77)−1.05 (−3.27, 1.17)−0.94 (−3.05, 1.16)−0.58 (−2.62, 1.46)
Social Support−0.57 (−0.96, −0.17) * −0.18 (−0.56, 0.19)
Beliefs about COVID-19
Perceived susceptibility 0.57 (0.28, 0.86) * 0.42 (0.15, 0.68) *
Perceived severity −0.26 (−0.62, 0.10) −0.18 (−0.51, 0.15)
Finances in Quarantine
Have got better Ref Ref
Stayed the same −0.18 (−4.93, 4.56) −1.40 (−5.70, 2.91)
Have got worse 3.49 (−1.41, 8.38) 1.73 (−2.73, 6.20)
Access to Basic Supplies
Yes Ref Ref
No 5.69 (1.88, 9.50) * 4.97 (1.49, 8.44) *
Psychological Flexibility −0.54 (−0.71, −0.38) *−0.42 (−0.60, −0.25) *
Note: * Statistically significant p < 0.05.
Table
Table 5. Comparisons between cancer participants who had cancer as their priority vs. those who had COVID-19 as their priority.
Table 5. Comparisons between cancer participants who had cancer as their priority vs. those who had COVID-19 as their priority.
Cancer Priority (n = 52)COVID-19 Priority (n = 191)p-ValueEffect Size
Socio-demographic Characteristics
Median age of participants (years (IQR)) a 54.5 (44, 57.5)50 (39, 60)0.15 m0.07 n
Gender (n (%)) aMales12 (23.1)35 (18.3)0.66 k0.06 o
Females40 (76.9)155 (81.2)
Other/Non-Binary0 (0.0)1 (0.5)
Employment status (n (%)) aWorking full time134 (50.8)4974 (53.5)<0.01 k**0.15 o
Working part time49 (18.6)1625 (17.5)
Unemployed 24 (9.1)2194 (23.6)
On parental leave 6 (2.3)208 (2.2)
Retired 51 (19.3)300 (2.2)
Working as a health professional (n (%)) bYes13 (26.0)36 (19.7)0.33 k0.06 o
No 37 (74.0)147 (80.3)
University student (n (%)) cYes1 (2.0)22 (11.8)0.04 k*0.14 o
No 50 (98.0)164 (88.2)
Education level (n (%)) dPrimary0 (0.0)2 (1.1)0.74 k0.09 o
Secondary 9 (17.3)34 (18.2)
Higher 43 (82.7)151 (80.7)
Marital status (n (%)) eSingle10 (19.6)34 (18.0)0.88 k0.10 o
In a relationship/Engaged/Married35 (68.6)128 (67.7)
Divorced/Widower6 (11.8)27 (14.3)
Having children (n (%)) aYes37 (71.2)119 (62.3)0.24 k0.08 o
No 15 (28.8)72 (37.7)
Living situation (n (%)) aLiving alone7 (13.5)38 (19.9)0.45 k0.12 o
Living with parents5 (9.6)14 (7.3)
Living with one of parents2 (3.9)3 (1.6)
Living with own family38 (73.1)131 (68.6)
Living with friends/roommates0 (0.0)5 (2.6)
Type of cancer (n (%)) fBreast cancer19 (36.5)47 (25.7)0.670.23 o
Female reproductive system cancers3 (5.8)24 (13.1)
Cervical cancers0 (0.0)4 (22)
Thyroid cancer4 (7.7)19 (10.4)
GI cancer7 (13.5)10(5.5)
Leukemia and blood cancers3 (5.8)14 (7.7)
Lymphomas4 (7.7)13 (7.1)
Testicular cancers0 (0.0)3 (1.6)
Lung cancers3 (5.8)5 (2.7)
Skin cancers4 (7.7)21 (11.5)
Brain cancers1 (1.9)3 (1.6)
Prostate cancers2 (3.8)8 (4.4)
Bone cancers0 (0.0)4 (2.2)
Urine cancers2 (3.8)6 (3.3)
Soft molecular cancers0 (0.0)2 (1.1)
In therapy (n (%)) dYes15 (28.8)40 (20.9)0.23 k0.08 o
No 37 (71.2)151 (79.1)
Type of therapy (n (%)) gAdjuvant preventative12 (70.6)31 (73.8)0.80 k0.20 o
For active disease5 (29.4)11 (26.2)
The scariest thing at this moment? (n (%)) hCancer44 (89.8)37 (19.9)<0.01 k**0.60 o
COVID-195 (10.2)149 (80.1)
The most harmful thing at this moment? (n (%)) iCancer43 (84.3)28 (14.8)<0.01 k**0.62 o
COVID-198 (15.7)161 (85.2)
COVID-19 Protective Behaviors
Keeping distance from other people when going out (median (IQR)) a 10 (8.5–10)10 (9–10)0.77 l0.28 n
Self-isolating, limiting unnecessary travelling according to national guidelines (median (IQR)) a 10 (9–10)10 (9–10)0.16 l0.38 n
Washing hands regularly with water and soap (median (IQR)) a 10 (9–10)10 (9–10)0.99 l0.20 n
Coping and Social Support
Social support (OSS) j (n (%)) hLow 9 (17.3)43 (22.6)0.70 k0.05 o
Moderate 25 (48.1)88 (46.3)
High 18 (34.6)59 (31.1)
Perceived Stress (PSS)
Scoree (n (%)) hLow 24 (46.1)81 (42.6)0.58 k0.07 o
Moderate 25 (48.1)89 (46.8)
High 3 (5.8)20 (10.6)
Beliefs about COVID-19
Perceived susceptibility (median (IQR)) 9.5 (6.5–13)11 (8–14)0.34 g0.28 n
Perceived severity (median (IQR)) 12.5 (9–15)15 (13–17)<0.01 g**0.74 n
Abbreviations: SD = standard deviation; IQR = interquartile range; OSS = Oslo Social Support Scale; PSS = Perceived Stress Scale a n = 264; b n = 254; c n = 258; d n = 260; e n = 261; f n = 235; g n = 145; h n = 242; i n = 244; j n = 263; k differences between cancer priority and COVID priority were evaluated by the chi-square test. l Differences between cancer priority and COVID priority were evaluated by the Kolmogorov–Smirnov test. m differences between cancer priority and COVID priority were evaluated by the t-test; n effect size between males and females was examined with Cohen’s d; o effect size between males and females was examined with Cramér’s V. * Statistically significant p < 0.05 ** Statistically significant p < 0.01.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Kassianos, A.P.; Georgiou, A.; Kyprianidou, M.; Lamnisos, D.; Ļubenko, J.; Presti, G.; Squatrito, V.; Constantinou, M.; Nicolaou, C.; Papacostas, S.; et al. Mental Health and Adherence to COVID-19 Protective Behaviors among Cancer Patients during the COVID-19 Pandemic: An International, Multinational Cross-Sectional Study. Cancers 2021, 13, 6294. https://doi.org/10.3390/cancers13246294

AMA Style

Kassianos AP, Georgiou A, Kyprianidou M, Lamnisos D, Ļubenko J, Presti G, Squatrito V, Constantinou M, Nicolaou C, Papacostas S, et al. Mental Health and Adherence to COVID-19 Protective Behaviors among Cancer Patients during the COVID-19 Pandemic: An International, Multinational Cross-Sectional Study. Cancers. 2021; 13(24):6294. https://doi.org/10.3390/cancers13246294

Chicago/Turabian Style

Kassianos, Angelos P., Alexandros Georgiou, Maria Kyprianidou, Demetris Lamnisos, Jeļena Ļubenko, Giovambattista Presti, Valeria Squatrito, Marios Constantinou, Christiana Nicolaou, Savvas Papacostas, and et al. 2021. "Mental Health and Adherence to COVID-19 Protective Behaviors among Cancer Patients during the COVID-19 Pandemic: An International, Multinational Cross-Sectional Study" Cancers 13, no. 24: 6294. https://doi.org/10.3390/cancers13246294

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop