Adherence to Physical Distancing and Health Beliefs About COVID-19 Among Patients With Cancer

Sajida Fawaz Hammoudi; Oli Ahmed; Hoyoung An; Youjin Hong; Myung Hee Ahn; Seockhoon Chung

doi:10.3346/jkms.2023.38.e336

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Hammoudi, Ahmed, An, Hong, Ahn, and Chung: Adherence to Physical Distancing and Health Beliefs About COVID-19 Among Patients With Cancer

Original Article

Psychiatry & Psychology

Journal of Korean Medical Science 2023; 38(43): e336.

Published online: 6 October 2023

DOI: https://doi.org/10.3346/jkms.2023.38.e336

Adherence to Physical Distancing and Health Beliefs About COVID-19 Among Patients With Cancer

Sajida Fawaz Hammoudi¹

, Oli Ahmed^2,³

, Hoyoung An⁴

, Youjin Hong⁵

, Myung Hee Ahn⁶

, Seockhoon Chung⁷

¹Faculty of Medical Sciences, Lebanese University, Beirut, Lebanon.

²Department of Psychology, University of Chittagong, Chattogram, Bangladesh.

³National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia.

⁴Department of Psychiatry, Keyo Hospital, Uiwang, Korea.

⁵Department of Psychiatry, Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Korea.

⁶Division of Psychiatry, Health Screening and Promotion Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

⁷Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

Address for Correspondence: Seockhoon Chung, MD, PhD. Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, 86 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea. schung@amc.seoul.kr

Address for Correspondence: Myung Hee Ahn, MD. Division of Psychiatry, Health Screening and Promotion Center, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea. tj-utopia@hanmail.net

Received 26 May 2023 Accepted 21 July 2023

The Korean Academy of Medical Sciences

https://creativecommons.org/licenses/by-nc/4.0/

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

This study aimed to validate questionnaires on adherence to physical distancing and health beliefs about coronavirus disease 2019 (COVID-19) among patients with cancer and explore their interaction with depression or viral anxiety among them.

Methods

Through an online survey, data from 154 cancer patients (female: 82.5%, breast cancer: 66.2%, current cancer treatment, presence: 65.6%) were collected from March to June 2022. The survey gathered responses to questionnaires on adherence to physical distancing, health beliefs about COVID-19, perceived social norms, Stress and Anxiety to Viral Epidemics-6 items, and Patient Health Questionnaire-2. Confirmatory factor analysis (CFA) for construct validity and structural equation model (SEM) were performed.

Results

The CFA showed a good model fit for adherence to physical distancing (comparative fit index [CFI] = 1.000, Tucker–Lewis index [TLI] = 0.930, root-mean-square-error of approximation [RMSEA] = 0.000, and standardized root-mean-square residual [SRMR] = 0.050) and a satisfactory model fit for health beliefs about COVID-19 (CFI = 0.978, TLI = 0.971, RMSEA = 0.061, and SRMR = 0.089). Through SEM, we found that personal injunctive norms were the main mediators linking health beliefs with physical distancing in patients with cancer. Depression also mediated the effects of viral anxiety and perceived severity on physical distancing (χ² = 20.073, df = 15, P = 0.169; CFI = 0.984; RMSEA = 0.047).

Conclusion

The questionnaires are reliable and valid. Patients with cancer may be able to adhere to physical distancing by addressing perceived severity, viral anxiety, perceived benefits, self-efficacy, perceived barriers, as well as personal injunctive norms.

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Graphical Abstract

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Keywords: Physical Distancing, COVID-19, Anxiety, Uncertainty, Stress

INTRODUCTION

Since the occurrence of coronavirus disease 2019 (COVID-19), the lives of people worldwide have undergone extensive changes.1 2 Especially, patients with cancer experienced difficulty with the utility of the healthcare system.3 Although physical distancing was an effective policy to prevent viral transmission,4 at some point, this led to the delay in the treatment of patients with cancer.5 6 This delay adversely affected their psychological health and increased anxiety levels.7 Many studies have shown that patients with cancer experience higher rates of distress and anxiety,8 9 and the more delay in the treatment, the higher the distress.3 Moreover, these patients experience higher psychological stress due to their fear of acquiring an infection,8 9 especially during a public health emergency. Patients with cancer faced many obstacles during the COVID-19 pandemic that impacted their psychological health and adherence, compliance, and the chance of receiving medical treatment on time.10

Due to the rapid and easy transmission of the COVID-19 virus, the most effective measure to be taken was physical distancing, which allowed the control of the infection to some extent.11 12 However, this has greatly affected society’s mental health.13 Studies have shown unfavorable associations between these strict physical distancing measures and mental health symptoms.14 There was a two to three-fold increase in anxiety and depression due to adherence to distancing, which led to higher social isolation15 than during the pre-pandemic era, exacerbating the psychological distress faced during adherence to these measures.16 Despite all the negative effects resulting from the actions taken, and the non-ending cycle of one measure impacting the society as a whole, adherence to physical distancing was important to save people’s well-being.17

Even though physical distancing may cause loneliness or depression,18 19 20 it can reduce the risk of infection transmission to patients with cancer. They have weakened immune systems due to their disease or treatment, which makes them more vulnerable to COVID-19 and its severe consequences.21 People are encouraged to practice physical distancing to minimize the spread of COVID-19 but to varying degrees of adherence. Previous studies22 23 have shown that patients with underlying diseases, including cancer survivors, were discovered to adhere well to physical distancing measures, wearing face masks, and avoiding crowded areas. This could be due to the patients’ increased awareness of vulnerability to infection.9 Living with cancer is already a stressful and uncertain experience, and the COVID-19 pandemic has added an extra layer of burden for these patients, including fear of contracting the infection while in an immunocompromised state. Therefore, patients with cancer are more likely to protect themselves from the virus by adhering to physical distancing measures. However, there is a lack of research into how these patients specifically adhere to physical distancing during the COVID-19 pandemic and the intrapersonal decision-making processes on health-related behaviors that influence physical distancing.

The health belief model (HBM)24 25 was constructed to help explain and predict health behaviors by examining people’s beliefs and attitudes about health threats and the perceived benefits of adopting health-related behaviors. The HBM suggests that health-related behavior depends on the desire to avoid illness and the belief that specific health actions will prevent illness. The model specifies that an individual’s behavior is influenced by six socio-behavioral factors26: perceived susceptibility, severity, benefits, barriers, the presence of cues to action, and self-efficacy. A recent analysis27 showed that the HBM has a good predictive ability of COVID-19 preventive behavior, including adherence to physical distancing. In this review, which included 32 studies, the perceived benefit was the most significant predictor in almost all (96.5%) studies, followed by self-efficacy (87.5%), cues to action (72.2%), perceived barrier (64%), susceptibility (59.4%), and severity (40%) in decreasing order.

Social norms predict behavior, because people are more likely to act if they feel normative pressure.28 29 30 Descriptive social norms refer to the typical behavior most people exhibit in a given situation. These norms are based on people’s perceptions of the behavior that is displayed. In contrast, injunctive norms refer to the behavior that is expected or required in a given situation. These indicate how people should behave and represent the norms people should follow. In previous COVID-19 prevention efforts, social norms have acted as a positive predictor for engaging in a range of health behaviors.31 32 Moreover, people are more reluctant to practice handwashing, mask-wearing, and social distancing when they believe others are not practicing these behaviors. Thus, a questionnaire on adherence to physical distancing and health beliefs about COVID-19 was developed by Gouin et al.33 The Korean version of the questionnaire was validated in the general population34 and healthcare workers in Korea.35 The aim of this study was, first, to examine the reliability and validity of questionnaires on adherence to physical distancing and health beliefs about COVID-19 among patients with cancer and, second, to explore how the various sections interacted with each other and with depression or viral anxiety among these patients.

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METHODS

Participants and procedure

We conducted an online survey between March and June 2022 at Asan Medical Center, Seoul, Korea. Participants included patients with cancer who visited the Asan Medical Center Cancer Institute and voluntarily responded to the survey delivered via a link on the poster for enrollment. We developed the survey form including questions on participants’ age, sex, marital status, cancer type, cancer stages, and current treatment modalities. In addition, we included questions on COVID-19, such as “Have you been quarantined due to COVID-19 infection?,” “Have you been infected with COVID-19?,” or “Did you get vaccinated?.” Participants were provided an e-gift coupon valued at $5 for participation. We referred to the Checklist for Reporting Results of Internet e-Surveys guidelines36 for developing the e-survey form.

Measures

Questionnaires on adherence to physical distancing, health beliefs about COVID-19, and perceived social norms

A questionnaire on adherence to physical distancing was developed by Gouin et al.33 It consists of seven items on adherence to physical distancing, 14 items on health beliefs about COVID-19, and three single items on perceived social norms. In this study, we applied the Korean version of the questionnaire.34 35

1) Adherence to physical distancing

The questionnaire on adherence to physical distancing includes seven items, which can be rated on a 5-point Likert scale. A higher total score means greater adherence to physical distancing policy. Previous study showed a good fit for a two-factor model for questionnaire on adherence to physical distancing.34 Factor I focuses on individual’s daily routines and maintaining physical distancing at home, while factor II emphasized the use of masks and protective measures in public spaces.

2) Health beliefs about COVID-19 and perceived social norms

The questionnaire on health beliefs about COVID-19 consists of five subcategories: perceived susceptibility to infection (3 items), perceived severity of viral infection (3 items), perceived benefits of physical distancing (3 items), barriers to physical distancing (4 items), and self-efficacy (a single item). The questionnaire on perceived social norms related to physical distancing consists of three single items, a single item of each for descriptive social norms, personal injunctive norms or moral norms, and social injunctive norms.

Stress and Anxiety to Viral Epidemics-6 (SAVE-6) items

The SAVE-6 is an assessment tool for measuring an individual’s viral anxiety.37 It was one of the subscales of the SAVE-9 developed to measure healthcare workers’ work-related and viral anxiety.38 The SAVE-6 consists of six items which can be rated on a 5-point Likert scale ranging from 0 (never) to 4 (always). The higher the total score, the greater the level of anxiety associated with viral infection. We applied the original Korean version of the scale in this study. Cronbach’s alpha for this sample was 0.884.

Patient Health Questionnaire-2 (PHQ-2)

The PHQ-2 is a brief version39 of the PHQ-9, an assessment tool for measuring one’s severity of depression.40 It consists of nine items which can be rated on a 4-point Likert scale ranging from 0 (not at all) to 3 (nearly every day). The higher the total score, the more severe the symptoms of depression are. We applied two items from the Korean version of the PHQ-9,41 which was validated. A split-half coefficient among this sample was 0.890.

Statistical analysis

First, the construct validity and reliability of the Korean version of questionnaires on adherence to physical distancing and health beliefs were examined among patients with cancer. In this study, we performed the confirmatory factor analysis (CFA) among seven items of adherence to physical distancing and four subscales (perceived susceptibility, perceived severity, perceived benefit, and barriers) of the health beliefs questionnaire. Construct validity of the single item of self-efficacy of health beliefs and three single items of the social norms were not examined because the study focus was primarily on overall scales rather than on individual items. The factor structure for both scales was examined through CFA. In CFA, a two-factor model for the adherence to physical distancing scale and a four-factor model for the HBM scale were examined using the diagonally weighted least squares (DWLS) estimation. In this test, model fit was assessed through a comparative fit index (CFI), Tucker–Lewis index (TLI), standardized root-mean-square residual (SRMR), and root-mean-square-error of approximation (RMSEA) values.42 Multigroup CFA was performed to assess the measurement invariance of these two scales across sex. Besides, item analysis was performed for each measure. Cronbach’s alpha and McDonald’s omega were calculated to test the reliability of internal consistency. Pearson’s correlation analysis was done to explore convergent validity.

Second, we examined the interaction between the various assessments and adherence to physical distancing. To begin with, we conducted a correlation analysis using Pearson’s “r.” Based on the results, we constructed a structural equation model (SEM) in which each variable was arranged so that its effects ultimately resulted in adherence to physical distancing among patients with cancer.

We used SPSS version 21.0 (IBM Corp., Armonk, NY, USA), AMOS version 27 for Windows (IBM Corp.), JASP version 0.14.1, jMetrik 4.1.1, and R version 4.1.2 (R Foundation, Vienna, Austria) with the lavaan package to perform statistical analyses.

Ethics statement

This study was approved by the Institutional Review Board (IRB) of Asan Medical Center and the requirement for informed consent was waived (IRB 2022-0054).

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RESULTS

Demographic characteristics of patients with cancer patients in this study are presented in Table 1.

Table 1

Demographic and clinical characteristics of patients with cancer (n = 154)

Variables			Values
Female sex			127 (82.5)
Age, yr			48.2 ± 9.7
Marital status
	Single		35 (22.7)
	Married, without kids		10 (6.5)
	Married, with kids		106 (68.8)
	Others		3 (1.9)
Cancer types
	Solid tumor		151 (98.1)
		Breast cancer	102 (66.2)
		Gastrointestinal, hepatobiliary, and pancreatic cancers	27 (17.5)
		Other malignancy	22 (14.3)
	Hematologic malignancy		3 (1.9)
Cancer stages (among cancer types with TNM classification, n = 141)
	Stage 0, I, II, III		111 (78.7)
	Stage IV		13 (9.2)
	I don’t know exactly		17 (12.1)
Surgery within 3 mon			13 (8.4)
Current cancer treatment, presence			101 (65.6)
Questionnaires, score
	Obsession with COVID-19 scale		4.0 ± 3.7 (0–15)
	Coronavirus Reassurance-Seeking Behaviors Scale		5.7 ± 4.8 (0–19)
	Stress and Anxiety to Viral Epidemics-6 items		12.9 ± 5.4 (0–22)
	Cancer-related Dysfunctional Beliefs and Attitude about Sleep-14 items		5.9 ± 2.4 (0.5–9.8)
	Intolerance of Uncertainty Scale-12 items		31.3 ± 8.5 (12–48)

Values are presented as number (%) or mean ± standard deviation.

TNM = tumor, node, metastasis, COVID-19 = coronavirus disease 2019.

Reliability and validity of questionnaires

Factor loadings for adherence to physical distancing ranged between 0.587 and 0.917, and those for health belief about the COVID-19 scale ranged between 0.475 and 0.880 (Table 2). The CFA with DWLS estimation showed a good model fit for adherence to physical distancing (CFI = 1.000, TLI = 0.930, RMSEA = 0.000, and SRMR = 0.050) and a satisfactory model fit for health beliefs about COVID-19 (CFI = 0.978, TLI = 0.971, RMSEA = 0.061, and SRMR = 0.089) (Table 3). The multi-group CFA showed that the Korean version of both scales could assess adherence to physical distancing and health beliefs about COVID-19 in the same way across sex. Item analysis results (Table 2) showed that all the items in both scales had good corrected item-total correlation (≥ 0.4).

Table 2

Factor structure of the questionnaire (n = 154)

Items			Response scale					Descriptive, mean ± SD	CITC	CID	Factor loading (CFA)
Items			0	1	2	3	4	Descriptive, mean ± SD	CITC	CID	Factor loading (CFA)
A) Questionnaire on adherence to physical distancing
	Distancing factor I
		Distancing 1	2.60	9.09	9.74	32.47	46.10	4.10 ± 1.07	0.615	0.859	0.641
		Distancing 2	0.65	9.15	10.46	33.33	46.41	4.15 ± 0.98	0.834	0.801	0.917
		Distancing 3	0.00	5.88	9.15	29.41	55.56	4.34 ± 0.87	0.780	0.819	0.841
		Distancing 4	0.65	6.49	9.09	28.57	55.20	4.31 ± 0.93	0.712	0.833	0.793
		Distancing 5	0.65	9.80	11.11	44.44	33.99	4.01 ± 0.95	0.540	0.875	0.587
	Distancing factor II
		Distancing 6	0.65	1.31	3.92	10.46	83.66	4.75 ± 0.65	0.555	-	0.708
		Distancing 7	0.00	1.95	2.60	9.09	86.36	4.79 ± 0.57	0.555	-	0.737
B) Questionnaire on health beliefs about COVID-19
	Perceived susceptibility
		Susceptibility 1	8.44	35.71	29.87	20.13	5.84	2.79 ± 1.04	0.637	0.841	0.780
		Susceptibility 2	5.20	33.12	42.86	16.88	1.95	2.77 ± 0.86	0.777	0.700	0.835
		Susceptibility 3	5.20	24.03	39.61	28.57	2.60	2.99 ± 0.91	0.690	0.775	0.775
	Perceived severity
		Severity 1	6.49	20.13	25.97	35.07	12.34	3.26 ± 1.11	0.630	0.845	0.765
		Severity 2	5.84	29.22	36.36	25.97	2.60	2.90 ± 0.94	0.752	0.706	0.820
		Severity 3	5.20	25.97	39.61	26.62	1.30	2.92 ± 0.89	0.706	0.756	0.823
	Perceived benefit
		Benefit 1	11.11	20.92	20.92	30.07	16.99	3.20 ± 1.26	0.813	0.844	0.880
		Benefit 2	7.14	21.43	12.99	42.86	15.58	3.38 ± 1.18	0.788	0.862	0.812
		Benefit 3	7.84	22.22	19.61	31.37	18.95	3.31 ± 1.23	0.797	0.856	0.894
	Perceived barrier
		Barrier 1	14.94	18.83	38.96	23.37	3.90	2.82 ± 1.07	0.358	0.896	0.475
		Barrier 2	16.99	25.49	26.14	25.49	5.88	2.77 ± 1.17	0.776	0.713	0.863
		Barrier 3	17.53	31.17	24.03	18.18	9.09	2.70 ± 1.21	0.767	0.718	0.865
		Barrier 4	18.83	30.52	35.71	12.99	1.95	2.48 ± 1.00	0.735	0.744	0.819

SD = standard deviation, COVID-19 = coronavirus disease 2019, CFA = confirmatory factor analysis, CITC = corrected item-total correlation, CID = Cronbach’s alpha if item deleted.

Table 3

Scale level psychometric properties of the questionnaire

Psychometric properties		Adherence to physical distancing		Health beliefs about COVID-19				Suggested cut-off
Psychometric properties		Distancing factor I	Distancing factor II	Susceptibility	Severity	Benefit	Barrier	Suggested cut-off
Cronbach’s alpha		0.866	0.709	0.834	0.831	0.898	0.824	≥ 0.7
Model fits of confirmatory factor analysis
	χ² (df, P value)	5.039 (13, 0.974), 0.388		91.956 (59, 0.004), 1.559				Nonsignificant
	CFI	1.000		0.978				> 0.95
	TLI	0.993		0.971				> 0.95
	RMSEA (90% CI value) (P value)	0.000		0.061				< 0.08
	SRMR	0.050		0.089				< 0.08

COVID-19 = coronavirus disease 2019, CFI = comparative fit index, TLI = Tucker–Lewis index, RMSEA = root-mean-square-error of approximation, SRMR = standardized root-mean-square residual.

The questions on adherence to physical distancing showed good reliability for factor I (Cronbach’s alpha = 0.866) and factor II (Cronbach’s alpha = 0.709). The health beliefs about COVID-19 also showed good reliability for perceived susceptibility (Cronbach’s alpha = 0.834), perceived severity (Cronbach’s alpha = 0.831), perceived benefit (Cronbach’s alpha = 0.898), and barriers to following physical distancing (Cronbach’s alpha = 0.824). The convergent validity of each subscale with each other is presented in Table 4.

Table 4

Correlation coefficients of each variable in all participants

Variables	Age	1	2	3	4	5	6	7	8	9	10
1. Adherence to physical distancing, total	0.03
2. Perceived susceptibility	−0.15	0.25^**
3. Perceived severity	−0.07	0.27^**	0.73^**
4. Perceived benefit	0.07	0.22^**	0.38^**	0.42^**
5. Perceived barrier	−0.06	−0.11	0.19^*	0.19^*	0.003
6. Self-efficacy	−0.05	0.28^**	0.35^**	0.40^**	0.46^**	0.06
7. Descriptive social norms	0.12	0.17^*	0.05	0.06	0.07	−0.07	−0.04
8. Personal injunctive norms or moral norms	0.05	0.38^**	0.23^**	0.24^**	0.39^**	−0.22^**	0.34^**	0.39^**
9. Social injunctive norms	0.05	−0.25^**	−0.25^**	−0.27^**	−0.20^*	0.02	-0.30^**	−0.02	−0.27^**
10. SAVE-6	0.05	0.29^**	0.56^**	0.66^**	0.34^**	0.20^*	0.27^**	0.13	0.24^**	−0.08
11. PHQ-2	−0.11	0.30^**	0.38^**	0.44^**	0.16^*	0.20^*	0.18^*	−0.05	0.08	−0.15	0.51^**

SAVE-6 = Stress and Anxiety to Viral Epidemics-6, PHQ-2 = Patients Health Questionnaire-2.

^*P < 0.05; ^**P < 0.01.

SEM for adherence to physical distancing

The correlation results suggested that a three-tier model would be possible. We arranged the first tier to include the health belief variables (perceived benefit, perceived barrier, perceived severity, and self-efficacy) and viral anxiety. The second tier included two of the perceived social norms variables (personal and social injunctive norms) and depression. The last tier consisted of physical distancing only. The model was arranged so that the effects “flowed” from the first towards the last tier. Through this model, we found that personal injunctive norms were the main mediators linking health beliefs with physical distancing in patients with cancer (Fig. 1). Depression also played a role by mediating the effects of viral anxiety and the perceived severity of physical distancing. Fit measures suggested that the model was acceptable (χ² = 20.073, df = 15, P = 0.169; CFI = 0.984; RMSEA = 0.047).

Fig. 1

Structural equation model of the variables. Numbers next to arrows correspond to standardized estimates. Structural equation model of the variables. Numbers next to arrows correspond to standardized estimates. Fit measures indicate a good fit (χ² = 20.073, df = 15, P = 0.169; comparative fit index = 0.984; root-mean-square-error of approximation = 0.047).

^*P < 0.05; ^**P < 0.01; ^***P < 0.001; ^†P < 0.1.

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DISCUSSION

We observed that the questionnaire on adherence to physical distancing and health beliefs about COVID-19 is a scale that could assess adherence to physical distancing in COVID-19 with good reliability and validity in patients with cancer. In this study, such patients’ personal injunctive norms and depression influenced adherence to physical distancing during the COVID-19 pandemic, while social injunctive norms did not have an impact. Perceived benefit and self-efficacy positively influenced personal injunctive norms, while perceived barriers had a negative influence. Moreover, viral anxiety and perceived severity influenced depression.

Questionnaires on adherence to physical distancing were already validated in Korea among the general population34 and healthcare workers.35 This study showed a good fit for a two-factor model among patients with cancer. Questionnaires on health beliefs about COVID-19, excluding a single item of self-efficacy, showed a good model fit for the four-factor model in CFA. Undoubtedly, physical distancing during the COVID-19 pandemic has affected the psychological aspect of people in general and patients with cancer in particular. In addition, many of those people have suffered a financial crisis that increased the burden on their mental health.43 Physical distancing is a weapon of two ends; on the one hand, it was an effective way to decrease the transmission of the virus, especially among patients with cancer that were more fragile and susceptible to severe infections, conferring them the feeling of security regarding their health. On the other hand, it increased stress and loneliness in these patients who needed a great degree of psychological support. Moreover, due to the complexity of medical services during this era, patients with cancer had more difficulty accessing their treatment than before.

In the SEM, we observed that depression and personal injunctive norms in patients with cancer influenced their adherence to physical distancing. More specifically, higher levels of depression were associated with lower adherence to physical distancing. According to previous studies, the increased depression in patients with cancer due to their disease and the pandemic led to less compliance with physical distancing. In addition, a high level of viral anxiety or perceived severity may be associated with a high level of depression. Patients with have been more worried about their health and the probability of being infected by the newly emerging virus. This has led to increased anxiety about viral illness. Furthermore, anxiety has a complicated relationship with the immune system, leading to the release of cortisol, a hormone that weakens the immune system.44 This perceived severity by patients with cancer has increased their depression, leading to less compliance with physical distancing.

Personal injunctive norms are characterized as internalized moral rules that individuals follow independently of others’ expectations and influences. These norms have been found to influence adherence to physical distancing among patients with cancer. Adherence to physical distancing is further influenced by perceived benefit and self-efficacy in a positive manner, as well as by perceived barriers in a negative manner. These influences occur through the pathway of personal injunctive norms.

Patients with cancer have impaired immune function due to the disease itself and its treatment. Therefore, when these patients are aware of the seriousness of their condition, they will exhibit more adherence to physical distancing by perceiving its benefit of having a less chance of acquiring the virus. Moreover, perceived barriers to perform the recommended action of physical distancing and self-efficacy of a patient have led to more adherence, which has made healthcare settings less prone to crowding, more affordable, and less risky. These effects of health beliefs on adherence to physical distancing are mediated by personal injunctive norms. However, in this study, social injunctive norms, which were considered (in)appropriate45 did not significantly influence adherence to physical distancing among patients with cancer. Because these patients have more comorbidities and are prone to more serious infections than the general population owing to a weakened immune system, it is crucial for them to adhere to physical distancing to reduce the possibility of acquiring the infection. This was possible for them because they were already aware of their condition and were able to comply with distancing.

There are limitations to this study. First, the study was conducted in Korea among patients with cancer who attended a tertiary-level, single general hospital. Patients’ emotional states may be affected by the level of readiness and preparedness of their healthcare facility during a pandemic. Therefore, the results cannot be generalized. Second, the design of the cross-sectional, anonymous online survey was a limitation of this study. The results of this study do not suggest a causal relationship between adherence to physical distancing and any other variable such as severity of depression. In addition, responses to web-based questionnaires that are self-reported may be biased. Third, this survey was conducted between March and June of 2022; therefore, the participants might have adjusted the 2 years during which the pandemic occurred. This factor might have influenced a participant’s response to a questionnaire. Finally, the sample size comprising 154 respondents is not representative of the Korean population as a whole.

In conclusion, the Korean version of the questionnaire regarding adherence to physical distancing and health beliefs about COVID-19 is useful in assessing adherence to physical distancing and related health beliefs among patients with cancer. To achieve adherence, this study emphasizes that it is essential to address perceived severity, viral anxiety, perceived benefits, self-efficacy, perceived barriers, as well as personal injunctive norms of patients with cancer. A healthcare professional must be aware of the cultural and social factors that influence patients’ beliefs and provide appropriate education and support for patients with cancer to remain safe in this pandemic.

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Notes

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Hammoudi SF, Ahmed O, Hong Y, Ahn MH, Chung S.
Data curation: Chung S.
Formal analysis: Hammoudi SF, Ahmed O, An H, Hong Y, Ahn MH, Chung S.
Methodology: Chung S.
Supervision: Chung S.
Validation: Chung S.
Writing - original draft: Hammoudi SF, Ahmed O, An H, Hong Y, Ahn MH, Chung S.
Writing - review & editing: Chung S.

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References

1. Baudouin C. COVID-19: the day after. J Fr Ophtalmol. 2020; 43(5):383–385. PMID: 32340758.

2. Wei R, Zhang Y, Gao S, Brown BJ, Hu S, Link BG. Health disparity in the spread of COVID-19: evidence from social distancing, risk of interactions, and access to testing. Health Place. 2023; 82:103031. PMID: 37120950.

3. Kim K, Kim H, Lee J, Cho IK, Ahn MH, Son KY, et al. Functional impairments in the mental health, depression and anxiety related to the viral epidemic, and disruption in healthcare service utilization among cancer patients in the COVID-19 pandemic era. Cancer Res Treat. 2022; 54(3):671–679. PMID: 34583461.

4. Islam N, Sharp SJ, Chowell G, Shabnam S, Kawachi I, Lacey B, et al. Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries. BMJ. 2020; 370:m2743. PMID: 32669358.

5. De Vincentiis L, Carr RA, Mariani MP, Ferrara G. Cancer diagnostic rates during the 2020 ‘lockdown’, due to COVID-19 pandemic, compared with the 2018-2019: an audit study from cellular pathology. J Clin Pathol. 2021; 74(3):187–189. PMID: 32561524.

6. Riera R, Bagattini AM, Pacheco RL, Pachito DV, Roitberg F, Ilbawi A. Delays and disruptions in cancer health care due to COVID-19 pandemic: systematic review. JCO Glob Oncol. 2021; 7(7):311–323. PMID: 33617304.

7. Cohen M, Yagil D, Aviv A, Soffer M, Bar-Sela G. Cancer patients attending treatment during COVID-19: intolerance of uncertainty and psychological distress. J Cancer Surviv. 2022; 16(6):1478–1488. PMID: 35066775.

8. Chung S, Youn S, Choi B. Assessment of cancer-related dysfunctional beliefs about sleep for evaluating sleep disturbance in cancer patients. Sleep Med Rev. 2017; 8(2):98–101.

9. Kim H, Cho IK, Lee D, Kim K, Lee J, Cho E, et al. Effect of cancer-related dysfunctional beliefs about sleep on fear of cancer progression in the coronavirus pandemic. J Korean Med Sci. 2022; 37(36):e272. PMID: 36123961.

10. Lee JB, Jung M, Kim JH, Kim BH, Kim Y, Kim YS, et al. Guidelines for cancer care during the COVID-19 pandemic in South Korea. Cancer Res Treat. 2021; 53(2):323–329. PMID: 33721486.

11. Pan L, Wang J, Wang X, Ji JS, Ye D, Shen J, et al. Prevention and control of coronavirus disease 2019 (COVID-19) in public places. Environ Pollut. 2022; 292(Pt B):118273. PMID: 34634404.

12. Wasserman D, van der Gaag R, Wise J. The term “physical distancing” is recommended rather than “social distancing” during the COVID-19 pandemic for reducing feelings of rejection among people with mental health problems. Eur Psychiatry. 2020; 63(1):e52. PMID: 32475365.

13. Newbold SC, Finnoff D, Thunström L, Ashworth M, Shogren JF. Effects of physical distancing to control COVID-19 on public health, the economy, and the environment. Environ Resour Econ. 2020; 76(4):705–729.

14. Mendez-Lopez A, Stuckler D, McKee M, Semenza JC, Lazarus JV. The mental health crisis during the COVID-19 pandemic in older adults and the role of physical distancing interventions and social protection measures in 26 European countries. SSM Popul Health. 2022; 17:101017. PMID: 34977323.

15. Benke C, Autenrieth LK, Asselmann E, Pané-Farré CA. Lockdown, quarantine measures, and social distancing: associations with depression, anxiety and distress at the beginning of the COVID-19 pandemic among adults from Germany. Psychiatry Res. 2020; 293:113462. PMID: 32987222.

16. Müller F, Röhr S, Reininghaus U, Riedel-Heller SG. Social isolation and loneliness during COVID-19 lockdown: associations with depressive symptoms in the German old-age population. Int J Environ Res Public Health. 2021; 18(7):3615. PMID: 33807232.

17. Chu DK, Akl EA, Duda S, Solo K, Yaacoub S, Schünemann HJ, et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet. 2020; 395(10242):1973–1987. PMID: 32497510.

18. Yang J, Zhang X, Yu M, Fisher JL, Paskett ED. Associations between cancer history, social distancing behaviors, and loneliness in adults during the COVID-19 pandemic. PLoS One. 2023; 18(2):e0281713. PMID: 36795688.

19. Gallagher S, Bennett KM, Roper L. Loneliness and depression in patients with cancer during COVID-19. J Psychosoc Oncol. 2021; 39(3):445–451. PMID: 33274697.

20. Miaskowski C, Paul SM, Snowberg K, Abbott M, Borno HT, Chang SM, et al. Loneliness and symptom burden in oncology patients during the COVID-19 pandemic. Cancer. 2021; 127(17):3246–3253. PMID: 33905528.

21. Gundavda MK, Gundavda KK. Cancer or COVID-19? A review of recommendations for COVID-19 vaccination in cancer patients. Curr Treat Options Oncol. 2021; 22(10):95. PMID: 34515857.

22. Faria de Moura Villela E, López RV, Sato AP, de Oliveira FM, Waldman EA, Van den Bergh R, et al. COVID-19 outbreak in Brazil: adherence to national preventive measures and impact on people’s lives, an online survey. BMC Public Health. 2021; 21(1):152. PMID: 33461508.

23. Islam JY, Camacho-Rivera M, Vidot DC. Examining COVID-19 preventive behaviors among cancer survivors in the United States: an analysis of the COVID-19 impact survey. Cancer Epidemiol Biomarkers Prev. 2020; 29(12):2583–2590. PMID: 32978173.

24. Champion VL, Skinner CS. The health belief model. Glanz K, Rimer BK, Viswanath K, editors. Health Behavior and Health Education: Theory, Research, and Practice. 4th ed. San Francisco, CA, USA: Jossey-Bass;2008. p. 45–65.

25. Cummings KM, Jette AM, Rosenstock IM. Construct validation of the health belief model. Health Educ Monogr. 1978; 6(4):394–405. PMID: 299611.

26. Glanz K, Rimer BK, Viswanath K. Health Behavior and Health Education: Theory, Research, and Practice. 4th ed. San Francisco, CA, USA: Jossey-Bass;2008.

27. Zewdie A, Mose A, Sahle T, Bedewi J, Gashu M, Kebede N, et al. The health belief model’s ability to predict COVID-19 preventive behavior: a systematic review. SAGE Open Med. 2022; 10:20503121221113668. PMID: 35898953.

28. Cislaghi B, Heise L. Theory and practice of social norms interventions: eight common pitfalls. Global Health. 2018; 14(1):83. PMID: 30119638.

29. Dempsey RC, McAlaney J, Bewick BM. A Critical appraisal of the social norms approach as an interventional strategy for health-related behavior and attitude change. Front Psychol. 2018; 9:2180. PMID: 30459694.

30. Schultz PW, Nolan JM, Cialdini RB, Goldstein NJ, Griskevicius V. The constructive, destructive, and reconstructive power of social norms. Psychol Sci. 2007; 18(5):429–434. PMID: 17576283.

31. Liu S, Zhu J, Liu Y, Wilbanks D, Jackson JC, Mu Y. Perception of strong social norms during the COVID-19 pandemic is linked to positive psychological outcomes. BMC Public Health. 2022; 22(1):1403. PMID: 35869459.

32. Latkin CA, Dayton L, Kaufman MR, Schneider KE, Strickland JC, Konstantopoulos A. Social norms and prevention behaviors in the United States early in the COVID-19 pandemic. Psychol Health Med. 2022; 27(1):162–177. PMID: 34794362.

33. Gouin JP, MacNeil S, Switzer A, Carrese-Chacra E, Durif F, Knäuper B. Socio-demographic, social, cognitive, and emotional correlates of adherence to physical distancing during the COVID-19 pandemic: a cross-sectional study. Can J Public Health. 2021; 112(1):17–28. PMID: 33464556.

34. Hong Y, An H, Cho E, Ahmed O, Ahn MH, Yoo S, et al. Psychometric properties of the Korean version of questionnaires on adherence to physical distancing and health beliefs about COVID-19 in the general population. Front Psychiatry. 2023; 14:1132169. PMID: 37484663.

35. Chung S, Lee T, Hong Y, Ahmed O, Silva WA, Gouin JP. Viral anxiety mediates the influence of intolerance of uncertainty on adherence to physical distancing among healthcare workers in COVID-19 pandemic. Front Psychiatry. 2022; 13:839656. PMID: 35733798.

36. Eysenbach G. Improving the quality of Web surveys: the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). J Med Internet Res. 2004; 6(3):e34. PMID: 15471760.

37. Chung S, Ahn MH, Lee S, Kang S, Suh S, Shin YW. The Stress and Anxiety to Viral Epidemics-6 Items (SAVE-6) scale: a new instrument for assessing the anxiety response of general population to the viral epidemic during the COVID-19 pandemic. Front Psychol. 2021; 12:669606. PMID: 34149565.

38. Chung S, Kim HJ, Ahn MH, Yeo S, Lee J, Kim K, et al. Development of the Stress and Anxiety to Viral Epidemics-9 (SAVE-9) scale for assessing work-related stress and anxiety in healthcare workers in response to viral epidemics. J Korean Med Sci. 2021; 36(47):e319. PMID: 34873885.

39. Löwe B, Kroenke K, Gräfe K. Detecting and monitoring depression with a two-item questionnaire (PHQ-2). J Psychosom Res. 2005; 58(2):163–171. PMID: 15820844.

40. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001; 16(9):606–613. PMID: 11556941.

41. Pfizer. Patient Health Questionnaire (PHQ) screeners. Updated 2010. Accessed January 10, 2022. www.phqscreeners.com .

42. Byrne BM. Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming. Mahwah, NJ, USA: Lawrence Erlbaum Associates;2001.

43. Kamble S, Joshi A, Kamble R, Kumari S. Influence of COVID-19 pandemic on psychological status: an elaborate review. Cureus. 2022; 14(10):e29820. PMID: 36337829.

44. Leonard BE, Song C. Stress and the immune system in the etiology of anxiety and depression. Pharmacol Biochem Behav. 1996; 54(1):299–303. PMID: 8728571.

45. Cialdini RB, Reno RR, Kallgren CA. A focus theory of normative conduct: recycling the concept of norms to reduce littering in public places. J Pers Soc Psychol. 1990; 58(6):1015–1026.

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