Obsessive–compulsive disorder during the COVID-19 pandemic: unveiling the traits that hold the key—a cross-sectional study

Abstract

Background

The COVID-19 pandemic has significantly impacted global mental health, notably obsessive–compulsive disorder (OCD). Our aim is to reveal the intricacies of how OCD presents itself during a pandemic and its association with sociodemographic factors, offering insights that may enhance mental health management and improve readiness for future public health crises.

Methods

This cross-sectional study was conducted during the COVID-19 pandemic in 2022. Utilizing a cluster sampling approach, participants were recruited online and administered the Obsessive–Compulsive Inventory-Revised (OCI-R). The acquired dataset was subsequently analyzed using SPSS software (v.27) and R programming language (v.4.4.1).

Results

In this study, 593 eligible individuals were included. Among them, 54.8% were female, and the participants had a mean age of 40.71 ± 11.7. Based on OCI-R, 73.2% of the participants scored ≥ 21, indicating more Likelihood of disturbing from OCD. Satisfaction with monthly income and sex significantly differed between OCD positive and negative groups. The logistic regression analysis demonstrated that individuals exhibiting checking traits had a substantially higher probability, approximately 23.09 times, of indicating OCD. Additionally, we uncovered that checking, ordering, and neutralizing traits were more greatly impacted by sociodemographic factors.

Conclusions

This study highlights the notable increase in new cases of mental health disorders, including OCD, due to the impact of COVID-19. It recommends proactive consideration of OCD risk factors during stressful events like pandemics, focusing on predisposing traits and sociodemographic factors to prevent and manage the disorder effectively.

Background

The COVID-19 pandemic has exerted profound and far-reaching effects on global health, significantly influencing both physical and mental well-being across diverse populations [1]. Among the mental health conditions affected by the pandemic, obsessive–compulsive disorder (OCD) has been particularly notable [2]. OCD is characterized by persistent, intrusive thoughts (obsessions) and repetitive behaviors (compulsions), and its prevalence has increased due to heightened stress, uncertainty, and fear associated with the pandemic [3, 4]. In Iran, as in many other countries, the mental health toll of the pandemic has necessitated urgent investigations into how these unprecedented circumstances have influenced OCD traits and symptomatology [5, 6].

One of the persistent sequelae of the COVID-19 pandemic is the Long COVID syndrome, a condition characterized by prolonged symptoms following recovery from the acute phase of infection [7]. These symptoms encompass a broad spectrum, including fatigue, cognitive impairments, respiratory issues, and psychological disturbances [8]. The multifaceted complications of Long COVID can profoundly impact an individual's quality of life, often exacerbating pre-existing mental health conditions or precipitating new ones [9]. A comprehensive understanding of these complications is essential to fully grasp the pandemic's impact on mental health, particularly among individuals predisposed to anxiety-related disorders such as OCD [1, 10].

The mental and psychological sequelae of COVID-19 extend beyond individuals directly infected by COVID-19. The pandemic has precipitated widespread anxiety, depression, and stress due to factors such as social isolation, economic instability, and the persistent threat of infection [1, 11]. These psychological stressors have created conditions conducive to the exacerbation of OCD symptoms. The prevalence of OCD has increased during the pandemic as individuals experience heightened fears of contamination and engage in excessive handwashing and cleaning rituals, paralleling public health guidelines but escalating to a pathological degree [2, 12].

This study aims to delve into the specific traits of OCD that have been mainly influenced during the COVID-19 pandemic in Iran. Pre-existing mental health diagnoses unexpectedly were not associated with symptom exacerbation, except in the case of OCD. Young people generally showed the most marked symptom increases, although this pattern was reversed in some samples [13]. By examining the prevalence and characteristics of OCD in this context and its association with sociodemographic factors, we hope to identify key traits that have been amplified or altered due to pandemic-related stressors. Understanding these traits can inform targeted interventions and support mechanisms for those struggling with OCD during such global crises. Our goal is to unveil the nuances of how OCD manifests in the shadow of a pandemic, providing insights that could aid in better mental health management and preparedness for future public health emergencies.

Methods

Study design

This cross-sectional study was conducted to examine the prevalence of OCD and the severity of its subscales among the Iranian population during the COVID-19 pandemic in January and February 2022. The study was approved by the ethics committee of Shahrekord University of Medical Sciences (IR.SKUMS.MED.REC.1400.011). In this study, cluster sampling was employed, and a total of 602 participants from seven provinces were included. We utilized a cluster sampling approach to facilitate practical data collection and to capture diversity across different regions. The country was divided into seven major geographical clusters (North, South, East, West, Central, Northwest, Southwest). From each geographical region, one province was purposively selected based on feasibility and existing research collaborations. Within each selected provincial cluster, the survey was distributed as an online Google form to a variety of online platforms and groups (local university mailing lists, social media communities, public health portals) that were accessible to the general population of that province. All individuals accessing the link from these clusters who met the eligibility criteria were invited to participate, thus employing a census-type method within each accessed online group. The participants were required to provide their consent by signing an online written consent form before the data collection process.

The Obsessive–Compulsive Inventory-Revised (OCI-R) checklist was used to evaluate participants. In addition to evaluating DSM-5.0 (APA. 20) diagnostic criteria for OCD [14], demographic characteristics and socioeconomic information, including age, sex, job, marital status, level of education, satisfaction with monthly income, and place of residence, were asked. The eligibility criteria included providing written consent, having the ability to read and comprehend Persian, residing in Iran, having internet access, not experiencing any stressful events in the past month, and having no history of care seeking for psychological problems. Exclusion criteria encompassed inaccessibility, refusal to provide self-consent, encountering a sudden stressful event during the completion of the checklist, and being ill with or without a positive PCR test for COVID-19.

Data collection

OCI-R questionnaire comprises 18 items divided into six subscales: Washing, Checking, Ordering, Obsessing, Hoarding, and Neutralizing. According to the OCI-R developers, it is recommended to use a cutoff score of 21. This means that individuals who achieve a total score of 21 or higher on the OCI-R are likely to have OCD [15]. Subscale scores range from 0 to 12 and indicate the combined rating for that specific subscale. Each item is assessed on a five-point Likert scale (ranging from 0 to 4) to indicate the level of distress or bother experienced during the previous month. The total score ranges from 0 to 72. The OCI-R has demonstrated excellent psychometric properties. Each subscale is connected to three questions in the checklist, which are rated using a 5-point Likert-type scale. Numerous studies have shown that the OCI-R, along with its subscales, effectively distinguishes between individuals with and without OCD [15]. In this regard, we utilized a pre-existing validated and reliable Persian version of the OCI-R, demonstrating excellent psychometric properties in a large non-clinical sample [16]. The OCI-R-Persian demonstrates impressive internal consistency, with alpha values ranging from 0.77 to 0.86. It also exhibits strong test–retest reliability, with correlation coefficients ranging from 0.62 to 0.76. The correlations between the individual subscales and the total scale range from 0.51 to 0.76, indicating a substantial level of correlation. However, the inter-correlations between the subscales are only moderately strong, with the lowest inter-correlations observed in the neutralizing subscale. The test–retest reliability for the total scale is 0.75, which, although slightly lower than the coefficients reported by the leading OCI-R developer group [15], still indicates excellent test–retest reliability. Additionally, the convergent and divergent validity of the OCI-R-Persian total scale and subscales are satisfactory. Overall, the OCI-R-Persian proves to be a concise, comprehensible, and time-efficient measure for assessing OCD in the general population.

Endpoints

The primary objective of this study was to ascertain the prevalence of OCD amidst the ongoing pandemic while also identifying the subscale most profoundly associated with the disorder. The secondary objective was to examine the potential relationships between sociodemographic characteristics and scores on individual subscales with disturbing OCD.

Statistical analysis

Out of 602 participants, nine incomplete responses were excluded from the analysis. Descriptive statistics were used to assess the data, including mean values, standard deviation, and percentage distributions. The association of sociodemographic characteristics and OCI-R subscales was examined using the Chi-square Test. The data were analyzed by SPSS v.27. The Firth's bias-reduced logistic regression used penalized maximum likelihood estimation. It fits a logistic regression model applying Firth's correction to the likelihood. All the modeling was implemented by the logistf package in R v.4.4.1. A p < 0.05 was considered significant.

Results

Among 593 individuals included in this study to assess OCD symptoms during COVID-19, 54.8% were female (n = 329). The participants had a mean age of 40.71 ± 11.7, ranging from 11 to 68 years old. During our study in the days of the COVID-19 struggle, our findings exhibited higher scores of neutralizing, checking, and washing subscales of OCI-R compared to the other subscales. The mean ± SD scores of each subscale in the general population are shown in Fig. 1.

Fig. 1.

The mean + SD score of subscales in the general population

According to the framework of OCI-R, the participants were divided into two groups of ≥ 21 score, indicating more possibility of OCD, and < 21 score. In this study, 73.2% of the participants scored ≥ 21 and 26.8% less. The mean age of OCD positive group was 40.63 ± 11.58, and the OCD negative group was 41.13 ± 12.19. Table 1 displays the characteristics of participants in detail.

Table 1.

Participants characteristics (n = 593)

Variable	OCD + (%)	OCD − (%)	P value
Sex
Male (n = 269)	67.2	32.8	< 0.01*
Female (n = 324)	78.3	21.7
Age
< 25 years (n = 88)	77.3	22.7	0.11
25–35 years (n = 120)	66.7	33.3
35–45 years (n = 150)	78.7	21.3
> 45 years (n = 235)	71.5	28.5
Place of residence
Rural (n = 109)	66.1	33.9	0.06
Urban (n = 484)	74.8	25.2
Education level
Undergraduate (n = 13)	61.5	38.5	0.55
Up to bachelor's degree (n = 106)	75.5	24.5
A master's degree or higher (n = 474)	73	27
Marital status
Single (n = 171)	73.7	26.3	0.86
Married (n = 422)	73	27
Employment status
Jobless (n = 126)	73.8	26.2	0.85
Student (n = 72)	76.4	23.6
Part/full-time job (n = 105)	70.5	29.5
Retired (n = 290)	73.1	26.9
Satisfaction with monthly income
Totally satisfied (n = 34)	44.1	55.9	< 0.01*
Partially satisfied (n = 158)	77.2	22.8
Their income was less than their needs (n = 176)	74.3	25.7
Totally dissatisfied (n = 225)	74.1	25.9

^*Considered significant.

Logistic regression analysis revealed significant associations between specific obsessive–compulsive traits and a probable OCD indication. A predominance of checking traits was associated with a substantially higher likelihood of indicating OCD. Washing, ordering, neutralizing, hoarding, and obsessing traits were also significantly associated with an increased probability of an OCD indication (Table 2).

Table 2.

Logistic regression analysis of OCD traits and their association with likelihood of indicating clinically significant OCD

Trait	Odds ratio (95% confidence interval)	P value
Checking	23.09 (10.10–52.81)	< 0.01*
Washing	17.74 (7.16–43.98)	< 0.01*
Ordering	14.66 (1.79–120.04)	< 0.01*
Neutralizing	10.66 (5.34–21.25)	< 0.01*
Hoarding	6.45 (2.96–14.07)	< 0.01*
Obsessing	4.30 (1.55–11.91)	< 0.01*

We also examined the association between washing, checking, ordering, obsessing, hoarding, and neutralizing subscales and sociodemographic factors among the OCD positive and negative groups. Figure 2 shows that checking, ordering, and neutralizing behaviors were more significantly influenced by sociodemographic characteristics, while washing and obsessing behaviors showed lower significant dependency than the others. Table 3 displays the p-value of their association.

Fig. 2.

The significant association between sociodemographic characteristics and OCI-R subscales between OCD groups (all p < 0.05)

Table 3.

P-values of the association between sociodemographic features and OCD subscales

Features	Subscales
	Sex	Marital status	Place of residence	Level of education	Job	Satisfaction with monthly income
Washing	0.74	0.16	0.02*	0.48	0.95	0.42
Checking	< 0.01*	0.24	0.22	< 0.01*	0.01*	0.22
Ordering	< 0.01*	0.03*	0.32	0.01*	0.10	0.56
Obsessing	0.45	0.34	0.15	0.37	0.03*	0.32
Hoarding	0.33	0.01*	0.37	0.36	< 0.01*	0.56
Neutralizing	< 0.01*	0.41	< 0.01*	0.28	0.34	0.01*

^*Considered significant

Discussion

In a cluster sample of 593 individuals from the Iranian general population assessed for OCD prevalence and preponderant subscale during COVID-19, participants exhibited higher scores in the neutralizing, checking, and washing subscales of the OCI-R. Of these, 73.2% scored ≥ 21, indicating a higher Likelihood of OCD, while 26.8% scored < 21. Logistic regression analysis identified significant associations between specific traits and OCD likelihood: checking (OR = 23.09), washing (OR = 17.74), ordering (OR = 14.66), neutralizing (OR = 10.66), hoarding (OR = 6.45), and obsessing (OR = 4.30). Sociodemographic factors were also found to influence these behaviors significantly (Fig. 2).

Studies suggest that pandemics like COVID-19 lead to increased obsessions and compulsions in the general population due to fear of contamination and the nature of quarantine status, driving people to adhere strictly to protocols to relieve anxiety. Specifically among Iranian society, Shabani et al. [17] attributed increased health anxiety caused by uncertainty as the leading cause of mental disorders during COVID-19. According to the available literature on COVID-19 global crisis, studies corroborate a surge in mental health challenges, including OCD [2, 10, 18–20]. In this regard, Benatti et al. [21] observed a notable emergence of new obsession and compulsion phenotypes, along with a significant worsening of pre-existing ones. Additionally, participants were more likely to experience suicidal ideation, increased internet checking behaviors, sleep disturbances, avoidance behaviors, and difficulties at work.

Following, several research studies provide evidence for the emergence of new cases of OCD and/or worsening symptoms in individuals [20, 22, 23]. These cases are commonly associated with pre-existing psychological issues, elevated scores on the Yale-Brown Obsessive Compulsive Scale (Y-BOCS), symptoms related to contamination and washing behaviors, lower levels of perceived social support, reduced mobility, and heightened interpersonal conflicts [20, 23]. In confirmation, Dehghani et al. [24] noted that OCD manifestations in Iranian adults decreased following the relative reduction of the virus's spread and associated fear and anxiety.

The present study highlights a specific pattern of symptom exacerbation in participants who exhibited significantly higher scores on the neutralizing, checking, and washing subscales of the OCI-R compared to other subscales. This observation aligns with the nature of the pandemic, where fear of contamination and heightened awareness of hygiene practices likely played a significant role in triggering and intensifying these specific OCD subtypes [4, 12]. For example, the study by Otte et al. [22] demonstrated increased severity across all dimensions of obsessive–compulsive symptoms, with a predominant escalation in washing behaviors. Besides, several studies have indicated that new cases of OCD have increased, and symptoms of OCD have been exacerbated in individuals with a pre-existing history of the disease or a family history of psychiatric disorders [4, 25]. The extent of behavior escalation in different studies was reported to be influenced by various symptoms, particularly washing and checking [20, 26].

Further analysis underscores that checking, washing, and neutralizing traits emerged as strong predictors of exceeding the clinical cutoff score on the OCI-R, indicating a higher likelihood of experiencing clinically significant OCD symptoms. The substantial odds ratios associated with these traits highlight their potential as early warning signs for identifying individuals at increased risk, particularly during times of heightened stress and uncertainty, such as the COVID-19 pandemic [22].

Studies have consistently demonstrated that specific OCD traits, such as checking, washing, and neutralizing, are significantly correlated with the severity of OCD symptoms. For instance, Abramowitz et al. [27] found that individuals exhibiting these traits were more likely to experience severe OCD symptoms and related distress, highlighting the strong association between these behaviors and the overall burden of the disorder. Additionally, other studies reported that these traits are not only prevalent but also persistent, often becoming more pronounced during periods of increased stress. Their result indicated that stress acts as a catalyst, intensifying these symptoms and exacerbating the overall clinical presentation of OCD [28, 29].

The persistence and exacerbation of these traits during stress underscore the importance of targeted interventions. During global crises such as the COVID-19 pandemic, individuals with these specific OCD traits may require specialized therapeutic strategies to manage their symptoms effectively [30]. Cognitive Behavioral Therapy (CBT), particularly Exposure and Response Prevention (ERP), has been shown to be effective in addressing these traits by helping individuals gradually face their fears and reduce their compulsive behaviors [10, 30].

Moreover, the implementation of stress management techniques and psychoeducation about the nature of OCD and its exacerbation during stressful times could be beneficial. Interventions that focus on these specific traits could potentially mitigate the exacerbation of OCD symptoms, providing a more targeted and practical approach to treatment during periods of heightened stress and uncertainty [31, 32]. This evidence underscores the necessity for a nuanced understanding of OCD traits and the development of tailored interventions to support individuals affected by this disorder in times of crisis.

Furthermore, the study reveals a differential impact of sociodemographic factors on various OCD symptom dimensions. Specifically, checking, ordering, and neutralizing behaviors were significantly influenced by these factors, whereas washing and obsessing behaviors showed less dependency. This finding suggests that specific OCD subtypes might be more susceptible to external stressors and individual characteristics, underscoring the need for personalized interventions tailored to specific symptom profiles and risk factors. Personalized patient education should also be incorporated into the training program 38.

In detail, among earlier studies, Fitzpatrick et al. [33] found that fear of COVID-19 was higher in densely populated urban areas, particularly among women and married people with children. The present study corroborates this by reporting that OCD traits are more severe in women than in men. Other studies have also reported higher rates of fear among women compared to men during the pandemic [34, 35]. This finding suggests that women are more psychologically vulnerable than men during the COVID-19 pandemic, potentially due to their emotional nature and greater responsibilities in marital, maternal, and family caregiving roles [36]. Regarding marital status, the current study showed no significant effect on the incidence of OCD. This aligns with findings from other studies that reported no difference in OCD prevalence between single and married individuals [37]. Overall, these findings emphasize the complex interplay between sociodemographic factors and OCD symptoms, highlighting the necessity for nuanced, individualized approaches in understanding and treating OCD, particularly during periods of heightened stress such as the COVID-19 pandemic.

Limitations and future directions

While this study provides valuable insights, it is essential to acknowledge its limitations. The cross-sectional design limits our ability to establish causal relationships between the pandemic and OCD symptom exacerbation. Additionally, the reliance on self-reported measures, while common in OCD research, introduces the possibility of response and/or recall bias. Also, this research focused solely on the potential presence of OCD without taking into account individual personality types and traits. Evaluations of psychiatric and psychological concerns must take a biopsychosociospiritual approach, which, unfortunately, was lacking in this study. Besides, what is lacking is a previous baseline and a consideration of the biological impact of the personal history of infection, COVID-19 vaccine, quarantine, and distancing. Moving forward, there is a need for more comprehensive investigations in this area.

Future research should explore the longitudinal impact of the pandemic on OCD symptoms, employing longitudinal designs and objective measures to gain a more comprehensive understanding of the long-term mental health consequences of this global crisis. Further investigation into the interplay between specific OCD subtypes, sociodemographic factors, and environmental stressors is crucial for developing targeted interventions and support systems for individuals struggling with OCD, both during and beyond times of global uncertainty.

Conclusions

The findings of this study underscore the substantial rise in new cases of mental health disorders, notably OCD, amidst the backdrop of the COVID-19 pandemic. It is recommended that due consideration be given to the potential onset of OCD during periods of heightened stress, such as pandemics. By emphasizing the significance of predisposing traits and sociodemographic variables concerning the likelihood of OCD manifestation, interventions can be tailored to effectively mitigate the risks and repercussions associated with this disorder promptly. Such targeted efforts hold promise in both the prevention and management of OCD within the context of public health crises.

Abbreviations

OCD

Obsessive–Compulsive disorder

OCI-R

The Obsessive–Compulsive Inventory-Revised

Y-BOCS

Yale-brown obsessive compulsive scale

CBT

Cognitive behavioral therapy

ERP

Exposure and response prevention

Author contributions

M.L: Conceptualization, Methodology, Formal analysis, Data Curation, Supervision, Writing—Review & Editing. R.R: Project administration, Methodology, Writing—Review & Editing, and Visualization. F.G: Investigation, Resources. M.AB: Writing—Original Draft and Writing—Review & Editing. F.Z: Methodology, Writing—Original Draft. Z.K: Validation and Resources. H.Gh: Conceptualization, Methodology, Validation, and Resources. S.P: Writing—Review & Editing.

Funding

This study was funded by Shahrekord University of Medical Sciences [No. 5834].

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

The study was approved by the ethics committee of Shahrekord University of Medical Sciences (Ethics code: IR.SKUMS.MED.REC.1400.011). Online written informed consent was obtained from the patients. The study conducted in accordance with the Helsinki Declaration.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.