Perception of COVID-19 threat, low self-efficacy, and external locus of control lead to psychological distress during the COVID-19 pandemic

ABSTRACT

While it is well documented that the COVID-19 pandemic has had critical consequences for individuals’ mental health, few studies to date have investigated the influence of psychological factors on psychological distress in the context of COVID-19. This study explores the influences of self-efficacy, health locus of control, and COVID-19 threat perception on psychological distress (DASS-21). 180 adults completed an online set of standardised questionnaires. Results indicated that self-efficacy had a significant relationship with all three subscales of psychological distress. However, COVID-19 threat perception was significantly associated with stress. External health locus of control was significantly associated with depression by the chance externality subscale, and stress by the powerful others externality subscale. Additionally, external health locus of control was found to moderate the relationship between COVID-19 threat perception and depression.

KEYWORDS:

• Self-efficacy
• health locus of control
• COVID-19 threat perception
• psychological distress
• depression
• anxiety
• stress

The COVID-19 pandemic has posed severe consequences for people’s mental and physical health (Xiong et al., 2020): individuals have experienced increased psychological distress seemingly across all cultures (Salari et al., 2020; Wang et al., 2020). In the context of previous epidemics (SARS: Cheng et al., 2004; H1N1: Wheaton et al., 2012), and with growing evidence in the COVID-19 context, psychological attributes both predict and protect against adverse mental health consequences. These include self-efficacy, perceived threat of illness, and health locus of control (LoC). Low self-efficacy is associated with higher levels of psychological distress including for COVID-19 (Shacham et al., 2020; Yildirim & Güler, 2020). Shahzad et al. (2020) and Paredes et al. (2021) found that perceived threat of COVID-19 predicted psychological distress, however the relationship was not cross-culturally validated (see, Rehman et al. (2021). Sigurvinsdottir et al. (2020) found external LoC predicted elevated symptoms of psychological distress, and a moderation effect whereby COVID-19 risk perception predicted distress only when external locus was medium to high. Health LoC has previously moderated the relationship between stressful life events and psychological distress (Hutner & Locke, 1984) and illness severity and emotional distress (Shelley & Pakenham, 2004). As LoC has previously often been found to have a moderating role in predicting distress, this will be examined in the present study. As depression, anxiety, and stress have also increased during this time (Salari et al., 2020), it is important to understand the factors influencing psychological distress so as to intervene appropriately.

The aim of the present study is to explore how self-efficacy, health LoC, and an individual’s perceived threat of COVID-19 influence levels of psychological distress in the context of COVID-19 with two hypotheses. First, Self-efficacy, health LoC, and COVID-19 threat perception will be associated with psychological distress (multiple linear analyses controlling for age and gender). Second, External Health LoC is predicted to moderate the relationship between COVID-19 threat perception and psychological distress (moderation analysis using the PROCESS approach: Hayes, 2013).

Methods

Design

A cross-sectional online study with five independent variables (self-efficacy, three health LoC subscales: internality, powerful others externality and chance externality, and COVID-19 threat perception) and three dependent variables (depression, anxiety, and stress).

Participants

Participants were 180 adults (80% female; age range = 18–80, M = 37.43, SD = 17.12). Participants were recruited using two primary methods: word of mouth and through the University of Surrey Psychology Research Participation System.

Measures

General Self-Efficacy scale (GSE: Schwarzer & Jerusalem, 1995). A widely used self-report measure comprised 10 items on 7-point Likert scales. Previous studies have found the GSE to have a high internal validity, with Cronbach’s alphas between .76 and .90 (Schwarzer & Jerusalem, 1995).

Multidimensional Health Locus of Control (MHLC: Wallston et al., 1978). This widely used measure contains 18 items with 6-point Likert scales, and has three subscales of internality, powerful others externality, and chance externality. Previous studies have found the MHLC to be moderately reliable, with Cronbach’s alphas ranging from .62 to .76 (Kuwahara et al., 2004; Moshki et al., 2007).

Perceived Coronavirus Threat Questionnaire (PCHQ: Conway et al., 2020). This recently developed measure in response to the COVID-19 pandemic. This has six items rated on 7-point Likert scales with strong psychometric properties.

Depression, Anxiety and Stress Scale (DASS-21). Three subscales contain seven items each for depression, anxiety, and stress. These have strong internal consistency and excellent discriminative, concurrent, and convergent validities (Coker et al., 2018).

Procedure

Ethical approval was obtained from the University of Surrey Ethics Committee. Following informed consent, participants answered demographics, followed by four questionnaires using the Qualtrics platform.

Results

Linear hierarchical regression tested the relationship between each dependent variable and self-efficacy, the three MHLC subscales, and COVID-19 threat perception (age and gender in model 1; self-efficacy, the three MHLC subscales, and COVID-19 threat perception added in model 2). See table 1 for descriptives.

Table 1. Descriptive statistics and correlations for study variables (N = 179).

Variable	M	SD	1	2	3	4	5	6	7	8
1. Age	37.53	17.12	-
2. DASS-21 anxiety	3.36	3.57	−.30**	-
3. DASS-21 depression	5.37	4.63	−.19*	.64**	-
4. DASS-21 stress	6.59	4.31	−.28**	.76**	.63**	-
5. Self-efficacy	30.56	4.60	.17*	−.32**	−.36**	−.31**	-
6. COVID-19 threat perception	23.54	6.11	.06	.17*	.16*	.22**	−.05	-
7. MHLC internality	20.17	3.30	.08	−.16*	−.07	−.10	.26**	−.10	-
8. MHLC chance	15.99	3.27	−.07	.18*	.27**	.08	−.11	.08	−.22**	-
9. MHLC powerful others	13.85	3.18	.02	.19*	.10	.21**	−.03	.28**	−.09	.23**

*p < .05. **p < .01.

DASS-21 anxiety

A bootstrapped multiple linear hierarchical regression was run for anxiety due to violating assumptions of homoscedasticity. The predictors in Model 1 were found to explain 9% of the variance in anxiety scores whilst Model 2 explained 20%, with a significant change between these values, F(5, 171), p < .001 (see, Table 2). Only lower self-efficacy was significantly associated with greater anxiety, (B_{self-efficacy} = −0.19, p = .003).

Table 2. Summary of bootstrapped hierarchical regression analysis for variables predicting anxiety. Confidence intervals and standard errors based on 1000 bootstrap samples (N = 179).

	Model 1			Model 2
Variable	B	SE B	β	B	SE B	β
Age	−0.06** (−0.83, 1.63)	0.02	−.31	−0.06** (−0.08, −0.03)	0.01	−.27
Gender	0.40 (−0.83, 1.63)	0.62	0.05	0.13 (−1.05, 1.30)	0.59	0.02
Self-efficacy				−0.19** (−0.30, −0.09)	0.06	−0.25
COVID-19 threat perception				0.07 (−0.01, 0.16)	0.04	0.13
MHLC internality				−0.03 (−0.19, 0.12)	0.08	−0.03
MHLC chance				0.10 (−0.06, 0.25)	0.09	0.09
MHLC powerful others				0.14 (−0.02, 0.30)	0.10	.12
Adjusted R^2	0.09			0.20

*p < .05. **p < .01. Adjusted R² reported as there are multiple predictors.

DASS-21 depression (Table 3)

Table 3. Summary of hierarchical regression analysis for variables predicting depression (N = 179).

	Model 1			Model 2
Variable	B	SE B	β	B	SE B	β
Age	−0.05*	0.02	−.19	−0.04	0.02	−.13
Gender	0.34	0.83	.03	0.30	0.78	.03
Self-efficacy				−0.33**	0.07	−.33
COVID-19 threat perception				0.10	0.05	.13
MHLC internality				0.13	0.10	0.09
MHLC chance				0.33*	0.10	0.23
MHLC powerful others				0.02	0.11	0.01
Adjusted R^2	0.03			0.19

*p < .05. **p < .01. Adjusted R² reported as there are multiple predictors.

Both reduced self-efficacy and greater MHLC chance subscale predicted greater depression (see table 4), with those who have higher levels of self-efficacy or a lower score in the MHLC chance subscale displaying lower levels of depression (B_{self-efficacy} = −0.33, p < .001; B_{MHLC_chance} = 0.33, p = .001).

Table 4. Summary of hierarchical regression analysis for variables predicting stress (N = 179).

	Model 1			Model 2
Variable	B	SE B	β	B	SE B	β
Age	−0.07**	0.02	−.28	−0.06**	0.02	−.25
Gender	0.89	0.76	.09	0.41	0.73	0.04
Self-efficacy				−0.24**	0.07	−0.25
COVID-19 threat perception				0.12*	0.05	0.17
MHLC internality				0.02	0.09	0.02
MHLC chance				−0.006	0.10	−0.004
MHLC powerful others				0.21*	0.10	0.15
Adjusted R^2	0.08			0.19

*p < .05. **p < .01. Adjusted R² reported as there are multiple predictors.

DASS-21 stress

Greater self-efficacy, greater COVID-19 threat perception, and greater MHLC powerful others subscale predicted greater stress (B_{self-efficacy} = −0.24, p < .001; B_COVID-19 = 0.12, p = .02; B_{MHLC_powerful others} = 0.21, p = .03).

Moderation analysis

A moderation analysis was carried out using PROCESS (Hayes (2013) to see the influence of each of the MHLC subscales on the relationship between COVID-19 threat perception and each of the DASS-21 subscales.

Depression

A significant moderation effect was found for MHLC powerful others subscale, F(4, 174) = 4.27, p = .04, R² = .17. The interaction of COVID-19 threat perception and MHLC powerful others was significant, b = 0.03, t(174) = 2.07, p = .04, indicating that the relationship between COVID-19 threat perception and depression scores is moderated by MHLC powerful others externality. From examination of simple slopes (see, Figure 1), it can be seen that when MHLC powerful others scores are low, there is a non-significant positive relationship between COVID-19 threat perception and depression scores, b = 0.007, 95% CI [−0.13, 0.14), t = 0.10, p = .92. At the mean values of MHLC powerful others scores, there is a significant positive relationship between COVID-19 threat perception and depression scores, b = 0.11, 95% CI [0.002, 0.22], t = 2.01, p = .046. When MHLC powerful others scores are high, there is a significant positive relationship between COVID-19 threat perception and depression scores, b = 0.21, 95% CI [0.06, 0.37], t = 2.68, p = .008. From Johnson-Neyman significance regions, when MHLC powerful others scores are at least 13, COVID-19 threat perception scores and depression scores are significantly related, t(174) = 1.97, p = .05, b = −0.08. As MHLC powerful others scores increase, the relationship between COVID-19 threat perception and depression becomes stronger.

Figure 1. Simple slopes of the DASS-21 depression subscale moderation analysis.

Low = 1 standard deviation (SD) below the mean, High = 1 standard deviation (SD) above the mean.

DASS-21 anxiety and stress subscales

No significant moderations of the three MHLC subscales were found for the anxiety and stress subscale.

Discussion

The most prominent and reliable predictor of distress was low self-efficacy – consistent with much previous research (Yildirim & Güler, 2020; Shelley & Pakenham, 2004; Ghaderi & Rangaiah, 2011; Abdel-Khalek & Lester, 2017; Hu et al., 2020). High self-efficacy may be protective for mental health due to its role in health behaviour change: according to social-cognitive models of health behaviour, self-efficacy is key to forming behavioural intentions and initiation of action (Sutton, 2005). In turn, this may lead individuals to engage in fewer risk-taking behaviours in the context of COVID-19, lowering chance of infection and subsequent adverse mental health symptoms (Sigurvinsdottir et al., 2020).

Results with COVID-19 threat perception were mixed as it was not significantly associated with depression or anxiety. This contradicts findings by Shahzad et al. (2020) who found COVID-19 threat perception to be positively associated with both depression and anxiety within a population of frontline paramedics. It is, however, in line with Rehman et al. (2021): possibly threat perception was not as pronounced in the current general population sample, though it did have a small association with greater stress overall.

While health external LoC did not predict anxiety, it did play a role in both depression and stress. Chance LoC predicted greater depression, consistent with previous research (Khumalo & Plattner, 2019; Sigurvinsdottir et al., 2020). Greater powerful others LoC predicted greater stress, consistent with Sigurvinsdottir et al. (2020). Higher scores on the powerful others externality subscale indicates a stronger belief in external forces controlling health, such as doctors and medical professionals but also politicians and those in authority. In the case of COVID-19 it is difficult to know which ‘others’ led to this result, and why.

Turning to moderation analysis, depression was significantly moderated by powerful others. For those who had a high powerful others score, as their COVID-19 threat perception scores increased, so did their depression scores – consistent with Sigurvindottir et al. (2020), the only previous study to examine this. This may be due to greater perceived failings by authorities during the pandemic including the healthcare system (Mehta et al., 2021). Major limitations of the present study include the lack of measurement for previous or current COVID-19 infection status and quarantine status. Though formally sufficiently powered, the sample size of 180 limits generalisability. The sample was extremely diverse in respect of age which may have influenced the findings. We note that while older respondents were rare it is important to not limit the age range of studies of this nature to working age adults as is common in the literature.

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