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Article

Influence of Loneliness, Anxiety, and Depression on Suicidal Ideation in Peruvian Adults during the COVID-19 Pandemic

by
Carlos De La Cruz-Valdiviano
1,
Aldo Bazán-Ramírez
1,*,
Carmela Henostroza-Mota
1,
Marina Cossío-Reynaga
2 and
Rocío Yrene Torres-Prado
3
1
Facultad de Psicología, Universidad Nacional Federico Villarreal, Lima CP 15082, Peru
2
Dirección de Servicios de Salud, Dirección de Salud Apurímac II, Andahuaylas CP 03701, Peru
3
Escuela de Posgrado, Universidad Cesar Vallejo, Lima CP 15314, Peru
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(4), 3197; https://doi.org/10.3390/su15043197
Submission received: 11 January 2023 / Revised: 5 February 2023 / Accepted: 6 February 2023 / Published: 9 February 2023
(This article belongs to the Section Health, Well-Being and Sustainability)
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Abstract

:
Our aim was to determine the influence of the variables Death Anxiety, Loneliness, and Depression on suicidal ideation in Peruvian adults during the COVID-19 pandemic. The sample consisted of 1342 subjects from Lima–Callao and regions of Peru, selected with non-probabilistic purposive sampling. A predictive, non-experimental design with the cross-sectional measurement using previously validated questionnaires was conducted. The differential effect of the variables Death Anxiety, Loneliness, and Depression on suicidal ideation was found. The two models obtained through structural equation modeling highlight a significant predictive relationship of Depression directly on suicidal ideation, while Loneliness is the second factor that best predicts suicidal ideation’s indirect relationships. Likewise, being single and unemployed were found to be significantly associated (p < 0.05) and to have a differential effect on Death Anxiety, Loneliness and Depression. The same trend was evidenced by people aged less than 30, with no schooling, not practicing sports and sleeping less than 4 h; however, neither having had COVID-19 nor place of residence was found to influence suicidal ideation. As a conclusion, depressive symptomatology is the best predictor of suicidal ideation. Likewise, loneliness indirectly influences suicidal ideation.

1. Introduction

In context of the COVID-19 pandemic, social confinement, and isolation, the psychological problems associated with COVID-19 [1,2,3], e.g., suicidal behavior [4], suicidal thinking and ideation [5,6,7], suicide risks [8], have increased in various places and various social and educational contexts. An acute problem in the field of health psychology is related to the high rates of suicide, which is the second leading cause of death in the world among the adolescent and young adult population aged 15–29 years; thus, it is considered by the World Health Organization (WHO) as a public health problem [9].
In Peru, the frequency of completed suicide has been increasing, for example, from 577 suicides in 2018 to 638 in 2019 and 614 in 2020, i.e., an average of two suicides per day has been reported each year, according to the National Death Information System [10]. Therefore, early detection and assessment of suicidal ideation and its associated factors are essential for suicide prevention, and it is advisable to have reliable instruments for the interpretation and informed inferences of the scores obtained.
Before each completed suicide, there are many suicide attempts, and behind these, suicidal ideation is present, commonly associated with an a priori planning where some warning signs can be shown [11]. According to Beck’s hopelessness theory of suicide [12], suicidal ideation occurs when people place a special value on problems, creating feelings of worthlessness. Similarly, he observes a disastrous present and a catastrophic future, which leads to the belief that suicide is the way out of these problems. Beck’s theory of suicidal ideation was based on depressive patients in whom he identified precise factors for the origin of suicidal ideation, which is characterized by the presence of automatic negative thoughts.
Of these various variables associated with suicidal ideation, three were taken for this study: Loneliness, Death Anxiety, and Depression. With them, the research problem formulated was: What is the effect of the variables, Death Anxiety, Loneliness, and Depressive symptoms on suicidal ideation in Peruvian adults during the third wave of the COVID-19 pandemic, between June and August 2022?
Research on the effects during the COVID-19 pandemic, in different populations, of variables such as Loneliness, Death Anxiety, Depression, and Suicidal Ideation, has shown diverse evidence. A systematic review published in 2021 revealed that the levels of symptoms of anxiety, depression, hopelessness, sadness, loneliness, and suicidal ideation increased in the context of social isolation, with those aged 21 to 40 years being the most affected [13]. Another recent UK population survey showed that young adults coping poorly and with pre-existing mental health conditions were significantly associated with suicidal thoughts and self-harm; in addition, loneliness was significantly associated with suicidal thoughts but not self-harm [14]. A significant positive correlation has also been found between physical and mental health with anxiety, depression, irritability, and loneliness [15].
In a study with Cuban adults and geriatric patients with Alzheimer’s disease, it was found that the measures of restraint and social isolation during the COVID-19 pandemic indicate negative sequelae in the well-being and mental health of the participants [16]. In the UK, one study reported that suicidal ideation increased over time, but anxiety symptoms and levels of defeat decreased over the course of the pandemic; however, levels of depressive symptoms did not change significantly; around loneliness, levels did not change significantly during the surges [17]. In Canada, with 7002 people, suicidal ideation was found to be more common among those younger than 65 years, single, indigenous, LGBT2Q+, coupled with a pre-existing mental health condition [18].
A study in Mexico showed that the prevalence of suicidal ideation was 2.3%, that 1.5% showed a suicide plan or attempt, and that suicide attempts were more common in urban than in rural areas [19]. Similarly, in Russia, positive and significant correlations between suicidal thinking and depression were found in 908 people [20]. In France, loneliness and boredom were independent predictors of depression, anxiety and insomnia in vulnerable people, whereas daily physical activity was a protective factor; virtual contacts also protected against suicidal ideation [21]. In Shanghai, during the COVID-19 pandemic, it was found that, in patients with major depressive disorder, trait anxiety could significantly mediate the relationship between impulsivity and suicidal ideation [22].
On the other hand, in a university population in Southeast Brazil, the relationship of factors associated with suicidal ideation during the pandemic in the year 2021 was investigated, finding a prevalence of suicidal ideation of 26.33%, and a significant association between depressive symptoms and suicidal ideation, highlighting an important aspect, that presenting depressive symptoms increases the probability of manifesting suicidal ideation [23].
In Spain, due to COVID-19, a significant increase in depressive symptoms and suicidal ideation was reported, with women, unemployed people, and students reflecting high levels of these conditions, as well as that the strong symptoms of depression and suicidal ideation were related to the loss of a close person by COVID-19, having suffered the disease severely or working remotely [24]. A recent qualitative and quantitative study with a sample of Italian young adults during the COVID-19 pandemic found that the dysfunctional cognitive thinking style “all or nothing” was a significant predictor of traumatic psychological distress [2].
As can be observed, several studies have shown evidence of how these three variables (Loneliness, Death Anxiety, and Depression) influenced suicidal ideation differently during the period of the COVID-19 pandemic. Therefore, the present research was proposed with the main objective of determining the effect of the variables Death Anxiety, Loneliness and Depression on suicidal ideation in Peruvian adults during the third wave of the COVID-19 pandemic.

2. Materials and Methods

2.1. Type and Design of Research

A predictive, basic non-experimental type of research was conducted with the cross-sectional measurement using self-report scales.

2.2. Participants

A total of 1342 adults between 18 and 70 years of age (M = 27.92, SD = 13.017, 51.27% men) participated in this study, selected through a non-probabilistic intentional sampling. For the selection of participants, the following inclusion criteria were established: adults between 18 and 70 years of age residing in Peruvian territory; those who had accepted the informed consent; those who had completed the responses to the instruments in Google Forms, through the online link sent to them.
Once the responses to the Google form were obtained, the number of subjects amounted to 1386; however, upon careful review, 44 subjects had to be eliminated (21 said they were retired, widowed, or divorced, all under 20 years of age; 11 were born or live in another country; 12 did not complete their answers) to avoid possible bias in the information.
Those aged 18–30 years stand out (40% male and 32% female). In total, 79% of women and 80% of men live in the department of Lima, 82% of males and 71% of females are single, 42% of males and 36% of females have not completed higher education, 44% of males and 40.5% of females are unemployed, 60% of men and 35% of women stated that they practice some kind of sport, and 72% of men and 72% of women sleep less than 7 h. Likewise, 42% of men and 48.5% of women reported having been ill with COVID-19.

2.3. Instruments

Death Anxiety Scale (DAS). This scale for adults was designed and validated in the United States by Donald Templer in 1970 [25]. It consists of 15 items distributed in three dimensions: fear of life coming to an end, fear of agony or illness and fear of death. For the present study, the version adapted to samples of Peruvian adults was used [26]. Appendix A shows the adapted version, whose factor structure resulted from the exploratory factor analysis with ordinal data obtained using the FACTOR program, version 12.03.02 Fear of life coming to an end comprised items 8, 10, 12, 15, fear of dying comprised items 4, 6, 9, 11, 13, 14, and fear of death comprised items 1, 2, 3, 5 and 7. In other words, the original version used was modified.
Scale of loneliness by Jong Gierveld and Theo van Tilburg. This scale for adults was designed and validated in Amsterdam [27]. In 2013, it was adapted and translated into Spanish [28]; in 2017, it was adapted in Peru and validated with young people and adults [29]; and in 2020, it was adapted in Lima, Norte Peru [30]. The scale is made up of 11 items distributed in two dimensions: social loneliness (wanting to count on someone when needed) and emotional loneliness (lack or abandonment by loved ones).
The response alternatives are 1 = no; 2 = more or less, and 3 = yes. The authors of this scale recommend that the responses be dichotomized for calculating the overall loneliness score, giving one point to the response options “more or less” or “no” for items 1, 4, 7, 8, and 11 (inverse); in the case of the remaining items, give one point if the response is more or less or yes. Finally, to obtain a total score for the scale, the score of all the items must be added up; this score will range from 0 (absence of loneliness) to 11 (maximum loneliness).
Patient Health Questionnaire-2 (PHQ-2). The Patient Health Questionnaire-2 was developed by Spitzer [31]; it is a reliable unidimensional screening instrument for the assessment of depressive symptoms. In Peru, it was validated in an adult population [32]. It assesses depressive symptoms during the last two weeks using two items: (1) feeling discouraged, depressed, or hopeless, and (2) having little interest or pleasure in doing things. Each item presents four response options with scores ranging from 0 to 3 (0 = not at all, 1 = several days, 2 = more than half the days, and 3 = almost every day). The score ranges from 0 to 6, where higher scores indicate greater depressive symptoms. For this study, internal consistency was assessed (α = 0.75, ω = 0.76).
Suicidal Ideation Frequency Inventory (SIFI). The original English version [33] was adapted to Spanish [34], and, in turn, was adapted to the general Peruvian adult population [35]. The evidence was analyzed based on content, internal structure, reliability, measurement invariance according to sex and age, as well as the relationship with other variables. The SIFI is a unidimensional measure (CFI = 0.99, RMSEA = 0.03 [90% CI: 0.00–0.08], SRMR = 0.03, WRMR= 0.37) with adequate reliability (ω = 0.80 and H= 0.91) and invariance according to sex and age (ΔCFI < 0.010; ΔSRMR < 0.030). Likewise, SIFI scores were correlated with depression (r = 0.67; p = 0.001), presenting a strong effect size.
Sociodemographic file. It included information on age, sex, place of residence (Li-ma/Province), employment status (permanent job, temporary job, unemployed, retired), sports practice (yes/no), hours of sleep per day (4 h or less/7 h or less/9 h or less), marital status (married, single, widowed, divorced or separated), education (primary school/secondary school/technical/university/no education), if you had COVID-19 illness (yes/no).

2.4. Psychometric Properties of the Instruments Used in This Study

Table 1 shows the reliability and dimensional structure indicators for three scales (Death Anxiety, Loneliness, Depression, and Suicidal Ideation) obtained with the factor program using the procedure for determining the number of dimensions by implementing parallel analysis [36], for polychoric correlation matrices with ordinal data and the unweighted least squares (ULS) factor extraction method, PROMIN rotation [37] and robust Varimax. Likewise, this table includes internal consistency indices for the Depression scale, which has only two items, obtained via analysis with IBM SPSS v. 26 [38].
Likewise, confirmatory analysis and construct validity were performed for two of the scales used. For the Death Anxiety scale with three dimensions and Loneliness with two dimensions, confirmatory factor analysis was estimated with the EQS 6.4 program. For the first case, optimal convergent and divergent construct validity was obtained, confirming three dimensions of Anxiety: fear of dying, fear of end of life, and fear of death. The goodness of fit of the AFC model obtained concerning the hypothesized model was good (Chi Sq. = 400.48; P = 0.00; CFI = 0.95; RMSEA = 0.05).
In the case of the Loneliness scale, an adequate model of divergence validity between constructs (emotional loneliness and social loneliness dimensions) was not obtained, and the program suggested, for modification of the model under test and improvement of the goodness-of-fit indexes, that two of the items load simultaneously on the two dimensions. Although this little divergence between constructs affects the goodness of fit of the model tested with two dimensions, it was decided to consider these dimensions separately since the covariation index between the two constructs is low, =0.43.

2.5. Procedure

The study was carried out in five phases: (1) the researchers implemented the suitable instruments; (2) the condition of free access was verified and in its absence, the authorization of the authors of the instrument was managed to apply them for research purposes; (3) in the current context where the pandemic continued, the survey was completed virtually through a Google form based on the instruments; the participants were contacted via social networks such as WhatsApp or Facebook; these were first acquaintances and relatives, and we then asked that it be spread to the contacts of those who were participating, and so on; (4) we proceeded with the data collection based on the subjects who consented to be participants, to whom the purpose of the study, the informed consent, the instructions for answering the questionnaires, confidentiality and anonymity were explained in the previously written instructions, according to the regulations that protect their identity and their answers through the link that was sent to them; (5) when the optimal sample quantity was reached, between June and August 2022, the form was closed and the statistical processing began.

2.6. Data Analysis

Initially, descriptive analyses were performed to observe the frequencies and measures of central tendency of the indices obtained (mean) for the variables anxiety about dying, anxiety about the end of life, anxiety about death, emotional loneliness, social loneliness, suicidal ideation, and depression. The fit to the normal distribution of the data was verified utilizing the Kolmogorov–Smirnov test, with the IBM SPSS v. 26 statistical programs [38]; in all cases, they present a distribution that does not conform to normality.
Considering the indices (means) of the three dimensions of Anxiety, two dimensions of Loneliness, the two items of Depression and the five items of Anxiety, a hypothetical model of prediction of suicidal ideation was proposed (see Figure 1). According to Figure 1, suicidal ideation is predicted by three factors or latent variables: Loneliness, Death Anxiety, and Depression. Likewise, this model contemplates that the factors of Death Anxiety and Depression are mediators of the relationship between the Loneliness factor and the Suicidal Ideation factor.
The testing of this hypothetical model is performed using structural equation modeling (SEM) as a multivariate statistical analysis technique. Structural equation modeling is an extension of several multivariate techniques such as regression analysis and factor analysis. Initially, hypotheses about the relationship between variables, unidirectional or bidirectional, are developed based on theory, previous evidence, or both [39]. These relationships are identified as direct and indirect according to the model-conforming variables that mediate the effect of one variable on the other [40,41]. The EQS 6.4 program was used for this study.

3. Results

3.1. Structural Relationships between Loneliness, Anxiety, Depression, and Suicidal Ideation

Based on the theoretical model proposed in Figure 1 and based on the results of the exploratory factor analysis and internal consistency shown in Table 1, a reduced structural regression model was tested to explain suicidal ideation as an effect of loneliness, anxiety, and depression. A factor or latent variable was constructed for Loneliness taking as a factorial indicator direct scores in the Emotional Loneliness dimension and the Social Loneliness dimension. Similarly, a latent variable was constructed for Death Anxiety with its three dimensions: fear of dying, fear of the end of life, and fear of death.
Figure 2 presents the resulting structural regression model, which achieved good goodness of fit (p ≤ 0.05; CFI = 0.96 and RMSEA = 0.07). Figure 2 shows that the state of Depression is the best predictor of suicidal ideation (regression coefficient = 0.62). The Loneliness factor highly and significantly predicted the Depression factor (regression coefficient = 0.76) and the Anxiety factor (regression coefficient = 0.63), and to a lesser extent, though significant, predicted the suicidal ideation factor (regression coefficient = 0.16). It was also observed that Death Anxiety did not have a significant effect on suicidal ideation.
A complementary model was also tested, which included, instead of the latent factor, two composite manifest variables, one for suicidal ideation and the other for depression. In both cases, average indexes were taken as the manifest variable (See Figure 3). The predictive weight of Anxiety on suicidal ideation is the same as that found in the model in Figure 2. While it is true that Depression is the best predictor of suicidal ideation, the prediction coefficient (0.41) is lower than the prediction coefficient shown in Figure 2, but the predictive weight of the factor Loneliness increased notably (from 0.16 in Figure 2 to 0.33 in Figure 3).
Likewise, Loneliness continues to be highly and significantly predictive of anxiety and Depression, although with slightly lower regression coefficient values than those found in Figure 2. The most relevant aspect of this second model obtained is the importance of the increase in the predictive value of loneliness on suicidal ideation.

3.2. Descriptive Analysis by Sex, Age Groups, Playing Sports, and COVID-19 Infection

Table 2 presents comparative data in the dimensions of Loneliness and Anxiety, as well as in the factors of Depression and suicidal ideation, according to the sex of the participants, analyzed with the Mann–Whitney U test for non-parametric data. Significant differences according to sex were found only in the dimensions of fear of dying and fear of death in the Anxiety factor and the factors of Depression and suicidal ideation. Women presented greater signs of anxiety in fear of agony and fear of death, greater depressive symptomatology, and greater signs of suicidal ideation.
Table 3 compares Loneliness, Anxiety, Depression, and Suicidal Ideation, according to the place of residence. Lima refers to Metropolitan Lima and the constitutional province of Callao, while Province refers to other departments of Peru. Significant differences were found only in MA in its three dimensions, standing out more in those living in provinces.
In terms of ages, the following have significant differences reported according to age group: Death Anxiety (in the dimension fear of the end of life), Emotional Loneliness and Social Loneliness, Depressive Symptomatology, and Suicidal Ideation. Participants in the age group 18 to 30 years had higher scores in Anxiety, Loneliness, Depression, and Suicidal Ideation.
Referring to the comparison of the variables Loneliness and Suicidal Ideation concerning marital status, this shows differences in the mean ranges, with a higher frequency of single people. The Kruskal–Wallis H values and gl allow us to verify that there are significant differences (p < 0.05): the single subjects present greater Loneliness (social and emotional) and Suicidal Ideation. As for the other variables (Death Anxiety and Depression), there are significant differences, although not exactly more severe in singles (widowed and/or divorced people stand out).
In the following analysis, referring to the comparison of the study variables concerning employment status, differences are observed in the average ranges, affecting the unemployed and those with casual employment. The Kruskal–Wallis H and gl values show that there are significant differences (p < 0.05), i.e., unemployed subjects and those with a casual job present greater Anxiety about death, Loneliness, Depression, and Suicidal Ideation.
Likewise, in another analysis, the comparison concerning the degree of education is reported; differences are observed in the average ranges in favor of no education and being a university student. The Kruskal–Wallis H and gl values show that there are significant differences (p < 0.05), i.e., the subjects mentioned present greater Death Anxiety, Loneliness, Depression, and Suicidal Ideation.
Table 4 shows the comparison of the averages obtained in the variables measured, considering the sports practice; it can be observed that except for the Final Fear dimension, significant differences (p < 0.05) were found between those who practice sports and those who do not. People who do not do physical exercise have high averages in two of the dimensions of Anxiety, in the two dimensions of Loneliness, and in Depression and Suicidal Ideation.
The comparison according to hours of sleep revealed significant differences (p < 0.05) in social Loneliness, Depression and Suicidal Ideation. People who reported sleeping less than 4 h were the ones who presented greater signs in these aspects. Finally, comparisons were drawn between the study variables regarding whether or not the patient suffered from COVID-19, showing differences in the average ranges in favor of those who suffered from this disease. The Mann–Whitney U values and Z scores show that there were significant differences (p < 0.05) only in the Fear of Agony and Fear of Death dimensions of the variable Death Anxiety.

4. Discussion

The results of this study allow us to determine the differential effect of the variables Death Anxiety, Loneliness, and Depression on suicidal ideation in Peruvian adults during the third wave of the COVID-19 pandemic. The two models obtained through structural equation modeling show a significant predictive relationship between depressive symptomatology directly on suicidal ideation.
This first finding is consistent with those obtained from other studies, for example, that mood disorders are highly associated with suicide, especially in patients with major depression [1,2,3,4,42]. Our data agree with findings where the presence of clinically significant depression is related to the presence of suicidal ideation [5], and that depressive symptoms increase the likelihood of reflecting suicidal ideation [22,23,24]. Our data also coincide with those found in depressive patients in France, with high levels of anxiety, insomnia, suicidal ideation, and traumatic stress [21].
On the other hand, the results of this research revealed the fundamental role of loneliness in explaining both suicidal ideation and its effect on depression and anxiety. The data obtained in this work are consistent with previous findings on the predictive effect of loneliness on suicidal thoughts and behaviors [15]. Likewise, data have reported that loneliness increased the probability of depression, anxiety, and insomnia during the COVID-19 period in Cuban adults [16]. In the context of the pandemic, many people have spent the confinement alone or away from their families; suicidal ideation was found to increase over time in confinement [25].
Although evidence of the effect of loneliness on anxiety was found in this study, no significant effect of death anxiety on suicidal ideation was found. This finding is contrary to data from other investigators who did report significant relationships between anxiety and suicidal thoughts and ideation [2,5]. However, a non-significant relationship has also been found between death anxiety and suicidal behavior [43], which does not imply that a person who reflects a fear of death will not make a suicide attempt.
Likewise, the two structural models obtained in this study show a very slight but negative effect (−0.02), both on the latent factor of Suicidal Ideation (construct) and the composite variable of Suicidal Ideation (index). Although this predictive relationship is not significant, the finding of Tarter and colleagues also showed a weak but significant negative correlation between suicide attempt data and death anxiety [44]. Likewise, our results would be in agreement with the findings of Cotton and Range in that, while hopelessness significantly predicts suicidality, death disgust was positively associated with suicidal ideation [45]. From our data and the other findings presented here, it can be pointed out that high anxiety, especially anxiety due to fear of death, could prevent suicidal thoughts and behaviors, i.e., a non-significant or negative relationship between anxiety scores and suicidal ideation is to be expected.
An aspect to reflect on is whether confinement is associated with an increase in suicidal thoughts and ideation. The data reported by O’Connor et al. [17] suggest that anxiety symptoms and levels of defeatism due to confinement decreased as time in confinement passed. It has also been reported that the pandemic generated positive mental health outcomes, and that sadness/despair and suicidal ideation decreased over the course of the pandemic [46].
Another important aspect derived from our results is that all the associated variables, such as sex, age group, marital status, education, employment status, playing sports, and hours of sleep, have a differential and significant influence on suicidal ideation. People who are part of the younger age group, being female, single, unemployed, without schooling, and not exercising are more likely to present higher indicators of suicidal ideation. Moreover, sleeping less than four hours per night will influence the symptoms of increased suicidal ideation. These results are in line with studies that observed specific characteristics associated with higher probabilities of suicidal ideation related to COVID-19, such as being younger, single, reporting a higher substance use [17] and, similarly, being female, young age, lower schooling, and being single were reported as factors associated with suicidal ideation [18].
Another aspect that emerges from our study is that no significant differences were found in the signs of suicidal ideation due to having been ill or not with COVID-19, i.e., having been ill by COVID-19 does not affect suicidal ideation. However, having been ill with COVID does influence anxiety regarding fear of agony, and anxiety about the fear of death. This aspect is important, given that being at risk of losing one’s life due to COVID-19 can generate anxiety, both fear of illness or agony, and fear of death. In addition, it was found that residing in the province or Lima has no significant effect on suicidal ideation. However, living in the province influences the fear of dying, fear of the end of life, and fear of death, probably due to having faced a new illness that forced preventive isolation, as well as feeling vulnerable and having little access to health centers.

5. Limitations

This study is based on a cross-sectional study and not on a longitudinal design, which does not allow measuring over time and, thus, obtaining more relevant data. The type of non-probabilistic sampling limits the ability to generalize the analyzed population more conclusively. The sample evaluated was derived from the general population, which includes mainly non-clinicians where we had the opportunity to detect cases of suicidal ideation; in this regard, it was not possible to delimit the specific cases of suicide attempts. More studies focusing on cases of suicide attempts, clinical populations, and rural settings are needed.

6. Conclusions

It was found that the variables marital status (single), age group under 30, unemployed, no schooling, and no sports practice were significantly associated (p < 0.05) and had a differential effect on states of loneliness, anxiety about death and depression; differences in anxiety about death and depression, hours of sleep (<4 h) in social loneliness and depression were reported for females; additionally, the differences generated by living in a province were observed in the dimensions of death anxiety. Depressive symptomatology is the best predictor of suicidal ideation followed by loneliness. Likewise, loneliness also has an indirect influence on suicidal ideation, mediated by depression.
This study is in the field of public health and mental health, specifically around suicidal ideation in the context of a pandemic and the variables associated with it. Based on this, it is of interest to explore the current panorama of how preventive actions are being carried out, which will allow us to know the limitations and successes of these strategies, aiming at improvement, not only involving health professionals but also promoters and citizens themselves, in the challenge of preventing and reducing the risk of suicide in order to achieve a biopsychosocial balance. All this is suggested within the framework of the Global Goals of the 2030 Agenda for Sustainable Development, with Goal 3 being to ensure healthy lives and promote well-being for all at all ages.

Author Contributions

Conceptualization, C.D.L.C.-V., A.B.-R. and C.H.-M.; methodology, A.B.-R. and C.D.L.C.-V.; software, M.C.-R.; validation, A.B.-R., C.D.L.C.-V., M.C.-R. and C.H.-M.; formal analysis, R.Y.T.-P. and M.C.-R.; investigation, C.D.L.C.-V., A.B.-R. and C.H.-M.; resources, M.C.-R. and R.Y.T.-P.; data curation, M.C.-R., A.B.-R. and R.Y.T.-P.; writing—original draft preparation, A.B.-R., C.D.L.C.-V. and C.H.-M.; writing—review and editing, A.B.-R. and M.C.-R.; supervision, R.Y.T.-P.; project administration, C.D.L.C.-V.; funding acquisition, C.D.L.C.-V., A.B.-R. and C.H.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Universidad Nacional Federico Villarreal (Peru), number 106-FPS.

Institutional Review Board Statement

The original research project was reviewed by experts from the Vice-Rectory for Research of the Universidad Nacional Federico Villarreal (UNV), and approved by Rectoral Resolution, No. 243-2022-CU-UNFV (3 May 2022). In addition, the study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Psychology, Universidad Nacional Federico Villarreal (UNV).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The authors declare that the database of our project is available to researchers who require it, upon reasonable request from the authors, and that we have the authorization of our institution.

Conflicts of Interest

The authors declare that we have no conflicts of interest of any kind. We have not received support from any political party or for-profit institutions either. In addition, the funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table
Table A1. Death Anxiety Scale and its factorial structure with the FACTOR program.
Table A1. Death Anxiety Scale and its factorial structure with the FACTOR program.
No.ItemsFear of AgonyFear of
End of
Life		Fear of
Death
1I am very afraid of dying. 0.883
2I think of death. 0.751
3It makes me nervous when people talk about death. 0.590
5I am afraid of dying. 0.869
7I am bothered by certain thoughts about death. 0.612
4It scares me to death to think that I would have to have surgery.0.816
6I am afraid of the possibility of cancer.0.713
9I am afraid of dying a painful death0.379
11I am afraid of having a heart attack.0.592
13It scares me to hear people talk about a third world war.0.522
14I am horrified to see a corpse.0.464
8I often worry about how quickly time passes. 0.879
10I am very concerned about the issue of the afterlife. 0.333
12I think life is too short. 0.768
15I think I have reason to fear for the future. 0.463

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Figure 1. Model of the relationship between loneliness and suicidal ideation, mediated by death anxiety and depression.
Figure 1. Model of the relationship between loneliness and suicidal ideation, mediated by death anxiety and depression.
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Figure 2. Structural regression of suicidal ideation as an effect of anxiety, loneliness and depression. Note. Anxiety: Death Anxiety (dimensions: fear of agony, fear of end of life, fear of death). Loneliness (dimensions: emotional, social). Suicidal Idea: Suicidal Ideation (Items: Suic-Idea1, Suic-Idea2, Suic-Idea3, Suic-Idea4, Suic-Idea5). The asterisk (*) signifies the standardized value of the variance of the predictor variables in a structural model, whether these are latent variables (factors) or manifest variables. Errors associated with the measurement of a manifest variable (E) and disturbances (errors) associated with the measurement of a latent variable (D) are also predictor variables, whose variance is measured between 0 and 1.
Figure 2. Structural regression of suicidal ideation as an effect of anxiety, loneliness and depression. Note. Anxiety: Death Anxiety (dimensions: fear of agony, fear of end of life, fear of death). Loneliness (dimensions: emotional, social). Suicidal Idea: Suicidal Ideation (Items: Suic-Idea1, Suic-Idea2, Suic-Idea3, Suic-Idea4, Suic-Idea5). The asterisk (*) signifies the standardized value of the variance of the predictor variables in a structural model, whether these are latent variables (factors) or manifest variables. Errors associated with the measurement of a manifest variable (E) and disturbances (errors) associated with the measurement of a latent variable (D) are also predictor variables, whose variance is measured between 0 and 1.
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Figure 3. Complementary structural regression model to explain suicidal ideation. The asterisk (*) signifies the standardized value of the variance of the predictor variables in a structural model, whether these are latent variables (factors) or manifest variables. Errors associated with the measurement of a manifest variable (E) and disturbances (errors) associated with the measurement of a latent variable (D) are also predictor variables, whose variance is measured between 0 and 1.
Figure 3. Complementary structural regression model to explain suicidal ideation. The asterisk (*) signifies the standardized value of the variance of the predictor variables in a structural model, whether these are latent variables (factors) or manifest variables. Errors associated with the measurement of a manifest variable (E) and disturbances (errors) associated with the measurement of a latent variable (D) are also predictor variables, whose variance is measured between 0 and 1.
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Table
Table 1. Results of the exploratory factor analysis and internal consistency of the scales.
Table 1. Results of the exploratory factor analysis and internal consistency of the scales.
Bartlett’s StatisticKMOGFISkewness Corrected for Small SampleKurtosisDimensions *αω
Death Anxiety Scale (DAS)
6503.7 (df = 105;
p = 0.000010)		0.92 (very good)1.00Coef. 24.47 Df. 680
p. 1.0000		Coef. 362.20
p < 0.05		Fear
Agony		0.90.91
Fear End
life
Fear
Death
Scale of loneliness
=6093.9 (df = 55;
p = 0.000010)		0.85 (good)0.99Coef. 4.62
p. 1.0000		Coef. 160.80
p < 0.05		Social Loneliness0.890.89
Emotional Loneliness
Patient Health Questionnaire-2 (PHQ-2)
p < 0.050.500 Unidimensional0.80
Suicidal Ideation Frequency Inventory (SIFI)
5114.2 (df = 10;
p = 0.000)		0.90 (good)1.00Coef. 19.27
p. 1.0000		Coef. 100.41
p < 0.05		Unidimensional0.960.96
* The number of dimensions for each scale was established by default according to the original layout of the instrument. The dimensions were labeled according to the proximity between the items and their correspondence with the construct of the dimension they were intended to measure from the beginning. KMO: Kaiser–Meyer–Olkin test. GFI: goodness-of-fit index. α: standardized Cronbach’s alpha. ω: McDonald’s omega.
Table
Table 2. Death Anxiety, Loneliness, Depression and suicidal ideation according to the sex.
Table 2. Death Anxiety, Loneliness, Depression and suicidal ideation according to the sex.
VariablesDimensionsSexnM.R.M–W-UZAsymp. Sig. (2-Tailed)
Death anxietyFear of Agony MEAN (AM4, AM6, AM9, AM11, AM13, AM14)masculine688621.71190,719.5−4.860 *
feminine654723.88
Fear of End of life MEAN (AM8,AM10,AM12,AM15)masculine688647.35208,357.5−2.360.02 *
feminine654696.91
Fear of death MEAN (AM1, AM2, AM3, AM5, AM7)masculine688619.15188,959.5−5.130 *
feminine654726.57
LonelinessEmotional Loneliness MEAN (S2, S3, S5, S6, S9, S10)masculine688652.95212,211.5−1.810.07
feminine654691.02
Social Loneliness MEAN (S1, S4, S7, S8, S11)masculine688672.91224,008−0.140.89
feminine654670.02
DepressionDepression MEAN (Dep1, Dep2)masculine688630.72196,917−4.190 *
feminine654714.40
I. Suic.Suicidal ideation MEAN (Ide_Sui1, Ide_Sui2, Ide_Sui3, Ide_Sui4, Ide_Sui5)masculine688632.65198,247.5−4.020 *
feminine654712.37
* p-value < 0.05. M.R.: Mean Rank. M–W-U: Mann–Whitney U.
Table
Table 3. Anxiety, Loneliness, Depression, and Suicidal Ideation according to the place of residence.
Table 3. Anxiety, Loneliness, Depression, and Suicidal Ideation according to the place of residence.
VariablesDimensionsResidencenM.RM–W-UglAsymptotic Sig.
Death anxietyFear of Agony MEAN (AM4,AM6,AM9, AM11, AM13, AM14)Lima1064660.10135,767.500−2.1200.034 *
Province278715.13
Fear of End of life MEAN (AM8,AM10,AM12,AM15)Lima1064658.39133,951.000−2.4470.014 *
Province278721.66
Fear of Death MEAN (AM1, AM2, AM3, AM5, AM7)Lima1064657.02132,485.500−2.7080.007 *
Province278726.93
LonelinessEmotional Loneliness MEAN (S2, S3, S5, S6, S9, S10)Lima1064668.44144,639.500−0.5700.569
Province278683.21
Social Loneliness MEAN (S1, S4, S7, S8, S11)Lima1064666.16142,219.000−0.9910.322
Province278691.92
DepressionDepression MEAN (Dep1, Dep2)Lima1064672.61146,714.000−0.2180.828
Province278667.25
Suic.I.Suicidal Ideation MEAN (Ide_Sui1, Ide_Sui2, Ide_Sui3, Ide_Sui4, Ide_Sui5)Lima1064668.25144,441.500−0.6400.522
Province278683.93
* p-value < 0.05. M.R.: Mean Rank. M–W-U: Mann–Whitney U.
Table
Table 4. Anxiety, Loneliness, Depression and Suicidal Ideation according to sport practice.
Table 4. Anxiety, Loneliness, Depression and Suicidal Ideation according to sport practice.
VariablesDimensionsS.P.nM.R.M–W-UglAsymptotic Sig.
Death anxietyFear of Agony MEAN (AM4, AM6, AM9, AM11, AM13, AM14)yes649644.41207,297−2.4930.013 *
no693696.87
MEAN (AM8, AM10, AM12, AM15)yes649662.67219,147−0.8160.415
no693679.77
Fear of end of life MEAN (AM1, AM2, AM3, AM5, AM7)yes649641.57205,451.5−2.7680.006 *
no693699.53
LonelinessEmotional Loneliness MEAN (S2, S3, S5, S6, S9, S10)yes649637.30202,685−3.1420.002 *
no693703.53
Social Loneliness MEAN (S1, S4, S7, S8, S11)yes649641.28205,268−2.7820.005 *
no693699.80
DepressionDepression MEAN (Dep1, Dep2)yes649646.21198,565−3.9310.00 *
no693695.18
Suic. I.Suicidal Ideation MEAN (Ide_Sui1, Ide_Sui2, Ide_Sui3, Ide_Sui4, Ide_Sui5)yes649630.96208,467.5−2.4670.014 *
no693709.47
* p-value < 0.05. M.R.: Mean Rank. M–W-U: Mann–Whitney U.
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De La Cruz-Valdiviano, C.; Bazán-Ramírez, A.; Henostroza-Mota, C.; Cossío-Reynaga, M.; Torres-Prado, R.Y. Influence of Loneliness, Anxiety, and Depression on Suicidal Ideation in Peruvian Adults during the COVID-19 Pandemic. Sustainability 2023, 15, 3197. https://doi.org/10.3390/su15043197

AMA Style

De La Cruz-Valdiviano C, Bazán-Ramírez A, Henostroza-Mota C, Cossío-Reynaga M, Torres-Prado RY. Influence of Loneliness, Anxiety, and Depression on Suicidal Ideation in Peruvian Adults during the COVID-19 Pandemic. Sustainability. 2023; 15(4):3197. https://doi.org/10.3390/su15043197

Chicago/Turabian Style

De La Cruz-Valdiviano, Carlos, Aldo Bazán-Ramírez, Carmela Henostroza-Mota, Marina Cossío-Reynaga, and Rocío Yrene Torres-Prado. 2023. "Influence of Loneliness, Anxiety, and Depression on Suicidal Ideation in Peruvian Adults during the COVID-19 Pandemic" Sustainability 15, no. 4: 3197. https://doi.org/10.3390/su15043197

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