Self-reported psychological problems and coping strategies: a web-based study in Peruvian population during COVID-19 pandemic

Data from 434 individuals of the general population living in Peru were used. Furthermore, to determine the estimated sampling size, G-power statistic were used with a confidence interval of 0.10 and error range of 15%. We selected a cross-sectional survey design to examine the population’s psychological responses during the COVID-19 pandemic.

Respondents were asked to identify categorically key demographic information, which is subsequently analyzed using Stata Statistical Software 15.0 for Windows [41] as proportions. Linear regression was used to calculate whether there were univariate associations between sociodemographic data, the GHQ scale and COPE-28 questionnaire.

To establish the relationship between psychological health and both active and passive coping strategies, structural equation models (SEM) were used. Path analysis [42] was done with comparative adjustment index (CAI), with values ≥ .90 [43] the root mean square error of approach (RMSEA), with values ≤ .80 [44] and the goodness-of-fit Index (GFI > .8 or > .9) was used to evaluate how well the models fit [45]. From the correlations, the final model was elaborated with path analysis, using data from participants scoring higher in psychological distress to determine the most used active and passive coping strategies within this group.

From the 450 respondents who completed the survey, only 434 (38.70% males and 61.30% females) were recruited into the study with a response rate of 100% (Table 1). The mean age of participants was 33.87  ± 12.6, whose age range from 18 to 68 years old coming from 16 departments of Perú. The majority were well-educated (> = 85.00%), Peruvian (94.20%), employed (57.40%) and single (71.20%). Regarding social factors, a great number were afraid of contracting coronavirus (71.40%), 47.70% were worried about limited access to cleaning products, and 38.90% about social distancing, followed by 27.80% worried about not being able to work. Regarding employment, 42,60% were unemployed at the quarantine period, and 40.09% were university students.

The sample adjusts to a normal distribution (±1.5 threshold) [46] where 40.80% (n = 177) of respondents reported psychological distress in contrast to non-cases (59.20%), with a cut-off point of 23/24 [36]. Men reported lower somatic and anxiety/insomnia symptom scores than women (β = − 1.87; β = − 1.91) respectively. The 59–68 age group has fewer somatic symptoms than younger age groups (β = − 2.09). Likewise, the 29–38-year-old group scored less in anxiety / insomnia (β = − 1.46) over the rest of the age groups. It is also observed that the groups from 49 to 58 years old (β = − 1.35) and 59 to 68 years old (β = − 3.11) score lower in social dysfunction than the younger age groups. With respect to severe depression, the 29–68 year-old group present lower scores (β = − 1.26 to − 2.36), with respect to the 18–28 year-old group (β = − 1.32). When observing educational levels, participants who have graduate (β = 13.16), undergraduate (β = 7.32) and university (β = 3.02) degrees present higher somatic symptoms than those who have high school. Similar tendency is presented in the anxiety / insomnia scales; graduate (β = 13.18), undergraduate (β = 6.45) and college (β = 1.61); in the social dysfunction scale: graduate (β = 6.98), undergraduate (β = 4.94) and college (β = 2.01); Also, in severe depression: graduate (β = 4.84), undergraduate (β = 3.02) and college (β = 0.16). Likewise, there are lower somatic symptoms (β = − 0.89), in participants who have moderate concern for the absence of hygiene products (protection, antibacterial gel, chinstraps and others) than those who do not worry about them.

Men are less likely than women to use positive reframing coping strategies (β = − 0.33). The 59–68 age group is identified as using less of the planning (β = − 0.81), positive reframing (β = − 1.14), and acceptance (β = − 0.96) coping strategies than the younger age group, similarly in the 39–48 age group (β = − 0.58) and the 49–58 age group (β = − 0.99), who are also less likely to use positive reframing strategy (β = − 0.66) and acceptance strategies (β = − 0.57). Looking at the level of study, participants with postgraduate degrees (β = − 0.53) and bachelor’s degrees (β = − 0.65) use the planning strategy less than participants with high school education, while participants with college education use positive reframing (β = 0.62) compared to those with high school education. We found that married participants use the planning coping strategy (β = − 0.79) and positive reframing (β = − 0.87) less than singles and cohabitants. It is evident that those who score moderate concern for the absence of hygiene products (protection, antibacterial gel, chinstraps, and others), are those most unlikely to use the positive reframing strategies (β = − 0.41) (see Tables 2 and 3).

Further statistical test regarding passive coping strategies (Table 4) revealed that, men are less likely to use religion (β = − 0.84), self-distraction (β = − 0.33), and venting (β = − 0.35) compared to women in the studied population. The 39–48 age group employs more religion-base responses (β = 0.74) than younger age groups. Regarding self-distraction behavior, it occurs to a lesser extent as age increases, i.e., for those in the age group 29 to 38 years (β = − 0.54); 39 to 48 years (β = − 0.64); 49 to 58 years (β = − 1.09) and 59 to 68 years (β = − 1.42). Similarly, is the case for the self-blaming strategy in all age categories: 29–38 age group (β = − 0.37), 39–48 age group (β = − 0.50), 49–58 age group (β = − 0.80). The older group (59–68 years old) uses the venting strategy to a lesser extent compared to the younger age groups. It should be noted that, while college students use more religion-based (β = 0.61) and venting (β = 0.50) strategies, bachelor’s degree students use self-blaming behaviors (β = 0.64); In contrast to professionals with graduate degrees who more likely use self-distraction (β = 0.76), self-blame (β = 1.07), and venting (β = 0.88) as passive coping strategies compared to high-school going participants in the studied population. As shown in Table 5.

Table 6 depicts health indicators. The positive correlation suggests an increase in somatic symptoms (r = 0.20**), anxiety (r = 0.13**) and social dysfunction (r = 0.15**) among those with better strategy of emotional support. Moreover, greater anxiety/insomnia (r = 0.16**) and social dysfunction (r = 0.13**) among those with higher social support. The planning strategy correlates inversely with severe depression (r = − 0.19**). The higher is the situation-acceptance strategy, the lower the indicators of somatic symptoms (r = − 0.10*), anxiety/insomnia (r = − 0.10*), and severe depression (r = − 0.11*) (*p < 0.05) among the respondents. Finally, active strategies of positive reframing and humor do not correlate with any indicator measured by the General Health Scale (GHQ).

Results derived from standardized path analysis coefficients shows active and passive responses (Figs. 1 and 2). As such, social acceptance and support-seeking behaviors are active strategies, which are more likely to be used by individuals who rated with psychological distress. The model retrieved acceptable goodness-of-fit indexes (X²/gl = 3.09; GFI = 0.880; IFC = 0.85 and RMSEA = 0.10 (IC90% 0.08, 0. 12). Although it is a model that does not strictly meet the expected parameters, the values are close and indicate that the active strategies used by participants with psychological distress are acceptance (negative), social support (positive); the passive strategies such as denial (positive way), self-distraction (positive), self-blaming (positive), disconnection (positive) and venting (negative). Except humor (active strategy) and substance use (passive strategy) that do not support the explanation. The model explains 19% of the variance (R² = 0.19) on the impact of the active and passive coping strategies among patients with psychological distress, with adequate adjustment index. The strategies that do not support the model are humor (active strategy) and substance use (passive strategy). (Fig. 1).

On the contrary Fig. 2 describes coefficients for active and passive strategies for participants who reported absence of psychological distress. For one hand, the model has acceptable goodness-of-fit indices (X²/gl = 5.73; GFI = 0.86; CAI = 0.75 and RMSEA = 0.11 / IC90% 0.09, 0. 139), with close values to the expected parameters, indicating that active strategies among participants without psychological distress are: emotional support (positive) and planning (positive). For the other hand, the passive strategies people without mental illness reported are self-distraction (positive), self-blame (positive), and disconnection (positive). Particularly, the active strategies that do not support the model are humor and social support. This model (R² = 0. 21) explain 21% of the variance, that is that 21% of the participants who do not present psychological distress use the aforementioned coping strategies, with adequate adjustment indexes.

Contrary to expectations, we did not find a significant difference between people using active and passive coping strategies. Initially, we thought that active coping was typically used among people experiencing absence of mental distress. Surprisingly, both passive and active had been identified, regardless of psychological status among the studied population.

Controversy remains regarding stress-coping behavior when responding to unknown stressors [30]. Although, on the one hand, people with psychological distress are found to be more likely to use passive mechanisms to reduce emotional stress (i.e., through behaviors such as denial, self-distraction, self-blaming and behavioral disengagement), they also score high on active behavioral coping, (i.e., that they actively confront to emotional tension, through low acceptance of the situation, and high social support seeking). On the other hand, those participants without psychological distress were more likely to use active coping that included social support, followed by passive forms such as self-distraction, disconnection from activities, and planning. Further, studies made by Petzold’s indicate that acceptance of anxiety and negative emotions seems to be supportive passive strategies [54] to maintain psychological equilibrium. In this regard, people scoring high only in emotion-based response are more likely to report psychiatric symptoms, in contrast to those using both active problem-resolution and emotion management [9].

In our findings, the use of coping strategies is correlated with gender. We found that men use positive reframing strategies to a lesser extent than women. Students-based research described opposite results, where young men are more likely to use positive management responses (positive reframing and planning in stressful situations) [55]. The reason for this is not clear but it may have something to do with the ongoing pandemic, participants responded to the questionnaire under an unusual circumstance that may had influenced or distorted their self-perception in the face of the uncertainty [25, 56] and their ability to analyze and solve the problems [57]. Contrastingly, Asian-based studies reported the deployment of active styles focusing on active problem solving (active, social support and planning), which may significantly predict responses of anxiety (3.40%), anger (2.20%) and sadness (0.90%). Particularly, first-liner women workers may be more likely to use proactive, problem-centered coping in the face of the pandemic and less likely to use passive strategies than men [13]. This has some minor fluctuations in North America, where women are more likely to report strategies that focus on passive behaviors such as distraction, religion, and less humor [58].

Interestingly, there seems to be a relationship between religion-related coping beliefs and gender. The great deal of female respondent in our study (61.30%) informed using religion-based strategies probably to mitigate stress, being this explained by the Peruvian population identified as Catholic (nearly 76%) [53], compared to progressive countries. Also in line with recent Chinese studies in social networks, where most of women used belief-based responses during the pandemic [9].

Another passive coping style is related to self-distraction, which is less likely to occur as age increases (> 28 years old). It is noteworthy mentioning that whilst passive coping contributes on lessening powerlessness in the face of stress, it may also operate as a maladaptive strategy leading to psychological distress [5]. We found that the use of passive responses (denial, self-distraction, self-incrimination, venting, and religion) may reflect the unprecedented impact of the COVID-19 pandemic; that metaphorically it is understood as a chain of misadjusted responses that begins by rejecting the deadly consequences of the disease, not accepting reality, resorting then to activities to avoid thinking about the crisis and confronting the problem. Evidently, this study captures the nature of human perceptions in contexts of uncertainty. Individual variance in analyzing an addressing demanding life situations serves a moderating agent [30], particularly for mental health outcomes. These findings are of critical importance for developing and/or strengthening active and passive coping modalities to educate by gender, age, and level of education in the general population.

Although our survey was conducted two weeks after emergency was declared by the Peruvian government and being our study one of the first to investigate the impact of COVID-19 on mental health and coping strategies in the face of the crisis in Peru. Additional research is urged to monitor participants in the aftermath of the pandemic. Particularly, given the long-term need for severe restrictions and the impact on economic activity, and to examine the evolution of psychological distress after the state of emergency. Other studies on low-income populations with poor internet connection and restricted health access may provide further insight into coping strategies and the effects on mental health.