Original Research Article Psychological Reports 2024, Vol. 0(0) 1–37 © The Author(s) 2024 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/00332941241231209 journals.sagepub.com/home/prx Pandemic Grief and Suicidal Ideation in Latin American Countries: A Network Analysis Tomás Caycho-Rodrı́guez and Jonatan Baños-Chaparro Facultad de Psicologı́a, Universidad Cient́ıfica del Sur, Lima, Peru José Ventura-León Facultad de Ciencias de la Salud, Universidad Privada del Norte, Lima, Peru Sherman A. Lee Department of Psychology, Christopher Newport University, Newport News, VA, USA Lindsey W. Vilca and Carlos Carbajal-León South American Center for Education and Research in Public Health, Universidad Norbert Wiener, Lima, Peru Daniel E. Yupanqui-Lorenzo Escuela de Psicologı́a, Universidad de Ciencias y Humanidades, Lima, Peru Pablo D. Valencia Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de Mexico, Tlanepantla de Baz, Mexico Mario Reyes-Bossio and Nicol Oré-Kovacs Facultad de Psicologı́a, Universidad Peruana de Ciencias Aplicadas, Lima, Peru Claudio Rojas-Jara Departamento de Psicologı́a, Facultad de Ciencias de la Salud, Universidad Católica del Maule, Talca, Chile Corresponding Author: Tomás Caycho-Rodrı́guez, Universidad Cient́ıfica del Sur, Peru Campus Villa II, Ctra. Panamericana S 19, Villa EL Salvador, Lima 01, Peru. Email: tcaycho@cientifica.edu.pe Data Availability Statement included at the end of the article https://us.sagepub.com/en-us/journals-permissions https://doi.org/10.1177/00332941241231209 https://journals.sagepub.com/home/prx https://orcid.org/0000-0002-5349-7570 https://orcid.org/0000-0003-2996-4244 https://orcid.org/0000-0003-1878-3472 https://orcid.org/0000-0003-4655-1927 mailto:tcaycho@cientifica.edu.pe http://crossmark.crossref.org/dialog/?doi=10.1177%2F00332941241231209&domain=pdf&date_stamp=2024-02-06 Miguel Gallegos Facultad de Ciencias de la Salud, Universidad Católica del Maule, Talca, Chile; Centro Interdisciplinario de Investigaciones en Ciencias de la Salud y del Comportamiento, Consejo Nacional de Investigaciones Cient́ıficas y Técnicas, Buenos Aires, Argentina Roberto Polanco-Carrasco Centro de Estudios Académicos en Neuropsicologı́a, Rancagua, Chile Mauricio Cervigni Facultad de Psicologı́a, Universidad Nacional de Rosario, Rosario, Argentina; Consejo Nacional de Investigaciones Cient́ıficas y Técnicas, Buenos Aires, Argentina Pablo Martino Laboratorio de Investigaciones en Ciencias del Comportamiento (LICIC), Facultad de Psicologı́a, Universidad Nacional de San Luis, San Luis, Argentina Marlon Elı́as Lobos-Rivera Escuela de Psicologı́a, Facultad de Ciencias Sociales, Universidad Tecnológica de El Salvador, San Salvador, El Salvador Rodrigo Moreta-Herrera Escuela de Psicologı́a, Pontificia Universidad Católica del Ecuador, Ambato, Ecuador Diego Alejandro Palacios Segura Centro de Desarrollo Humano, Universidad Mariano Gálvez, Guatemala Antonio Samaniego-Pinho Carrera de Psicologı́a, Facultad de Filosof́ıa, Universidad Nacional de Asunción, Asunción, Paraguay Andrés Buschiazzo Figares Centro de Estudios Adlerianos, Instituto Alfred Adler, IAIP Uruguay, Montevideo, Uruguay Diana Ximena Puerta-Cortés Programa de Psicologı́a, Universidad de Ibagué, Ibagué, Colombia Andrés Camargo School of Health and Sport Sciences, Fundación Universitaria del Área Andina, Bogotá, Colombia Julio Torales Facultad de Ciencias Médicas, Cátedra de Psicologı́a Médica, Universidad Nacional de Asunción, San Lorenzo, Paraguay; Instituto Regional de Investigación en Salud, Universidad Nacional de Caaguazú, Coronel Oviedo, Paraguay; Facultad de Ciencias Médicas, Universidad Sudamericana, Pedro Juan Caballero, Paraguay 2 Psychological Reports 0(0) https://orcid.org/0000-0002-5633-2050 https://orcid.org/0000-0003-0134-5927 José Arkangel Monge Blanco Asociación Nicaragüense Para el Desarrollo de la Psicologı́a, Managua, Nicaragua Pedronel González Universidad Jesús de Nazareth, Tegucigalpa, Honduras Vanessa Smith-Castro Instituto de Investigaciones Psicológicas, Facultad de Ciencias Sociales, Universidad de Costa Rica, San Jose, Costa Rica Olimpia Petzold-Rodriguez Lone Star College, Conroe, TX, USA Raymundo Calderón Colegio Estatal de Psicólogos en Intervención de Jalisco A.C., Guadalajara, Mexico Wendy Yamilet Matute Rivera Universidad Jesús de Nazareth, Tegucigalpa, Honduras Daniela Ferrufino-Borja Centro de Investigación y Asesoramiento Psicológico, Facultad de Humanidades, Comunicación y Artes, Universidad Privada de Santa Cruz de la Sierra, Santa Cruz, Bolivia Agueda Muñoz-del-Carpio-Toia Vicerrectorado de Investigación, Escuela de Postgrado, Universidad Católica de Santa Marı́a, Arequipa, Peru Jorge Palacios Facultad de Psicologı́a, Universidad del Valle de México, Querétaro, Mexico Carmen Burgos-Videla Instituto de Investigación en Ciencias Sociales y Educación, Universidad de Atacama, Copiapó, Chile Ana Marı́a Eduviges Florez León Asociación Panameña de Psicólogos, Ciudad de Panamá, Panama Ibeth Vergara Escuela de Psicologı́a, Universidad Latina de Panamá, Panama Diego Vega Escuela de Psicologı́a, Universidad Latina de Costa Rica, San José, Costa Rica Caycho-Rodŕıguez et al. 3 Marion K. Schulmeyer Centro de Investigación y Asesoramiento Psicológico, Facultad de Humanidades, Comunicación y Artes, Universidad Privada de Santa Cruz de la Sierra, Santa Cruz, Bolivia Hassell Tatiana Urrutia Rios and Arelly Esther Lira Lira Asociación Nicaragüense Para el Desarrollo de la Psicologı́a, Managua, Nicaragua Nicol A. Barria-Asenjo Departamento de Ciencias Sociales, Universidad de Los Lagos, Osorno, Chile Jesús Ayala-Colqui Universidad Tecnólogica del Perú, Lima, Peru Luis Hualparuca-Olivera Departamento de Humanidades, Universidad Continental, Huancayo, Peru Abstract This study aimed to characterize the network structure of pandemic grief symptoms and suicidal ideation in 2174 people from eight Latin American countries. Pandemic grief and suicidal ideation were measured using the Pandemic Grief Scale and a single item, respectively. Network analysis provides an in-depth characterization of symptom-symptom interactions within mental disorders. The results indicated that, “desire to die,” “apathy” and “absence of sense of life” are the most central symptoms in a pandemic grief symptom network; therefore, these symptoms could be focal elements for preventive and treatment efforts. Suicidal ideation, the wish to die, and the absence of meaning in life had the strongest relationship. In general, the network structure did not differ among the participating countries. It identifies specific symptoms within the network that may increase the likelihood of their co-occurrence and is useful at the therapeutic level. Keywords COVID-19, pandemic grief, suicidal ideation, Latin America, network Introduction The COVID-19 pandemic has resulted in the death of millions of people worldwide and has impacted everyone is lives in some way or another (Kumar, 2023). Although the number of diagnosed cases and deaths has declined markedly in recent months, as of 4 Psychological Reports 0(0) March 2023, COVID-19 caused 676,609,955 known diagnosed cases and 6,881,955 deaths worldwide (Coronavirus Resource Center, 2023). In Latin America, Brazil tops the list of countries with the highest number of COVID-19 deaths with 700,556 deaths, followed by Mexico (333,555), Peru (219, 849), Colombia (142,690), Argentina (130,472) (Coronavirus Resource Center, 2023). All of these deaths gen- erated grief responses that affected the physical and psychological health of the be- reaved (Kumar, 2023). It has been estimated that the death of one person from COVID-19 affected an average of nine people (Verdery et al., 2020); Thus, it has been suggested that more than 50 million people were mourning the death of a family member or loved one due to COVID-19, with Latin Americans representing a sig- nificant number of those bereaved. Grief is a painful but natural emotional response to the death of a loved one (Skalski et al., 2022). However, losing a loved one during a pandemic has been particularly difficult for the bereaved. In a meta-analysis of 15 studies involving 9289 participants during the COVID-19 pandemic, the prevalence rates of grief symptoms was 45.1% and grief disorder was 46.4% (Kustani et al., 2023). In Latin America, the prevalence of dysfunctional grief due to the pandemic ranged from 7.3% (Chile and Brazil) to 14.6% (El Salvador) (Caycho-Rodriguez et al., 2021a, 2022a). Another recent study reported that, in El Salvador, 35.1% presented clinically elevated symptoms of dysfunctional grief by the COVID-19 among people who lost a family member or loved one (Lobos- Rivera et al., 2023). The unexpectedness of death, isolation, inability to say good-bye to loved ones, disrupted or canceled funerals, and lack of social support were factors that contributed to the heightened levels of grief during the current global emergency (Eisma et al., 2020; Eisma et al., 2021). Bereavement is known to be associated with a wide range of adverse physical and mental health outcomes (Stroebe et al., 2007 Suicidal ideation is one of those adverse outcomes of grief (Molina et al., 2019) and this phenomenon was especially salient for those suffering from heightened levels of grief during the COVID-19 pandemic (Evren et al., 2022; Lee &Neimeyer, 2022). It has been suggested that people with complicated grief have a 9.7 increased risk of suicidal ideation and behavior (Levi-Belz & Lev-Ari, 2022). This is related to recent studies during the pandemic, which have reported high rates of suicidal ideation among people who have experienced pandemic bereavement (Caycho-Rodriguez, et al., 2021a; Caycho-Rodrı́guez, Lee, et al., 2022; Drucker et al., 2023; Escobar-Agreda et al., 2023; Evren et al., 2022; Lee & Neimeyer, 2022). Similar results have been observed in other studies before the COVID-19 pandemic (Levi-Belz & Aisenberg, 2021; Oon-Arom et al., 2019). Based on the interpersonal psychological theory of suicide (IPTS; Van Orden et al., 2010), a theoretical framework is offered to conceptualize and describe possible re- lationships between grief symptoms and suicidal ideation in people who have expe- rienced the death of a loved one. IPTS has received empirical support from different studies (Hill et al., 2019) and proposes that suicidal ideation is a product of the in- teraction between perceived burden and frustrated belongingness. First, perceived burden is understood as the belief that a grieving person becomes a burden to others and Caycho-Rodŕıguez et al. 5 that they would benefit from his or her death. Second, frustrated belonging is a feeling of loneliness and lack of social support (Van Orden et al., 2010). Based on this theoretical framework, grief reactions to the death of a loved one generate deficiencies in social support networks that detract from the bereaved person’s sense of belonging (Layne et al., 2017). In this sense, if the social support network is insufficient to meet the needs of the bereaved, they may experience long periods of frustrated belong- ingness, which plays an important role in the development of suicidal ideation (Hill et al., 2019). However, the presence of other variables that mediate the relationship between bereavement and suicidal ideation, such as type of attachment, has been suggested. Thus, people grieving the loss of a loved one who presents an avoidant attachment have difficulty expressing their grief externally and trusting other people. Thus, grief is directed towards oneself, presenting as suicidal ideation. This finding is in agreement with other recent findings that emphasize the relationship between insecure attachment, suicidal ideation, and problems in coping with grief (Smigelsky et al., 2019; Tidwell et al., 2021). The prevalence of COVID-19 grief and its relationship with suicidal ideation are major public health concerns (Hill et al., 2019). Despite the amount of knowledge about grief during the pandemic (Kumar, 2023), little attention has been paid to studying the possible mechanisms that explain the relationship between pandemic grief symptoms and suicidal ideation in people who have lost a loved one due to COVID-19. Therefore, research exploring the mechanisms by which grief leads to an increased risk of suicide should identify the symptoms of pandemic grief that increase the risk of suicide among bereaved persons. It has been suggested that the network analysis approach is suitable for studying the relationships between different aspects of mental health (Borsboom, 2017). Network analysis is a novel statistical method that models the relationships between psychological constructs. The study of network analysis between symptoms of pandemic grief and suicidal ideation is important as it allows the multicomponent nature of each of the constructs to be represented by identifying individual “nodes” or symptoms. Most previous studies on the relationship between pandemic grief and suicidal ideation have conceptualized both variables as reflecting common underlying illnesses or causes (Borsboom, 2008). Based on this conceptualization, it can be postulated that bereavement causes sad mood and insomnia, among other symptoms. This assumption of a common cause has been supported by psychopathological models, which are based on the hypothesis that symptoms are indicators of the underlying latent variables. Furthermore, summing individual scores to create a total score that describes the severity of mental health problems, such as dysfunctional grief, assumes that symptoms are indicators of the same underlying condition (Borsboom & Cramer, 2013). However, using total scores as indicators of bereavement levels does not allow for differences and interactions between symptoms to be observed and would create a misleading picture of the prevalence of bereavement and its relationship with other variables such as suicidal ideation (Borsboom & Cramer, 2013). This has made it difficult to understand the potential pathological pathways between pandemic grief and suicidal ideation as well 6 Psychological Reports 0(0) as to identify targets for more effective interventions. It has been suggested that analysis of individual symptoms may provide information that could not be obtained based on aggregate total scores alone (Liang et al., 2022). Few studies have examined possible interactions between pandemic bereavement symptoms and suicidal ideation and have indicated that the desire to die and lack of meaning in life are related to the presence of suicidal ideation in bereaved people from different countries (Jonson et al., 2023; Lew et al., 2020). Likewise, it has also been indicated that meaning of life can suppress negative dispositions towards suicidal orientation (Lew et al., 2020). Thus, this study would allow the identification of relationships between symptoms by associating nodes through “edges” (Kroeze et al., 2017). Likewise, this study would allow the identi- fication of relationships between symptoms by associating nodes through “edges” (Kroeze et al., 2017). In addition, there are nodes in the network that are more closely related to each other and form “clusters” or subcomponents. The quantification of each node is given through centrality indices, which inform the relative impact or influence of this node on others within the clusters and network in general (Borgatti, 2005). Identifying central nodes would allow clinicians working with those bereaved by COVID-19 specific areas to focus on their interventions. Thus, network analysis would allow exploration of the complex relationships that exist within and between constructs, becoming a useful tool for analyzing the mechanisms underlying pandemic grief and suicidal ideation (Borsboom & Cramer, 2013). Finally, having evidence that the network of symptoms of pandemic grief and suicidal ideation is invariant across different Latin American countries is important, as it may prove useful to inform on the most central symptoms of pandemic grief that are most related to suicidal ideation that are common across countries. This will facilitate more precise epidemiological in- vestigations, theoretical approaches, and treatments in Latin America region (Killikelly & Maercker, 2023). Future studies could consider those symptoms most closely linked to a country so that mental health professionals can identify these symptoms and consider them to improve diagnostic systems and treatment outcomes (Falzarano et al., 2022). This is even more important considering that sociocultural factors, such as cultural identity, can predict and shape the expression of grief (Adiukwu et al., 2022; Lund, 2021). Thus, the meaning a person has about death and the emotional expression generated can be shaped by cultural factors (Neimeyer et al., 2014; Silverman et al., 2021). Cross-cultural research has reported the presence of differences in grief ex- pressions in different cultural contexts (Smid et al., 2018). Therefore, the general objective of the present study was to characterize the network structure of pandemic grief symptoms and suicidal ideation in people from eight Latin American countries who experienced the death of a loved one due to the COVID-19 pandemic. The specific objectives were as follows: (1) identify the central nodes in each variable; (2) identify the pandemic grief symptoms most related to suicidal ideation; and (3) test whether the network structures between pandemic grief and suicidal ideation vary among the countries assessed. Network analysis is a technique used to understand the relationships between different mental health problems during the COVID-19 pandemic, both in Peru (Ventura-León et al., 2022) and in other Latin Caycho-Rodŕıguez et al. 7 American countries (Caycho-Rodrı́guez, Ventura-León, et al., 2022). To the best of our knowledge, network analysis has not been used to assess the relationship between the symptoms of bereavement due to COVID-19 and suicidal ideation in any Latin American country. Method Participants Residents of eight Latin American countries (Chile, Colombia, Ecuador, El Salvador, Guatemala, Mexico, Paraguay, and Peru) participated in this study. The following inclusion criteria were used: a) to be of legal age according to the legislation of each of the participating countries; b) to have suffered the death of a loved one; c) to reside in one of the eight participating countries; d) to have access to the Internet; and e) to provide informed consent to participate in the study. The participants were selected using non-probability snowball sampling to obtain a greater number of responses. Importantly, this type of sampling limited the sample to be representative of the population that experienced the death of a loved one from the pandemic in each participating country. However, non-probability sampling has been used in studies conducted during periods of health crises such as the COVID-19 pandemic (Connelly & Gayle, 2020), as it allowed the collection of data from a larger number of participants from different locations and obtained higher response rates than other sampling techniques (Baltar & Brunet, 2012; Riyaz et al., 2020). The number of participants was calculated using the Monte Carlo simulation method (Constantin et al., 2023) which suggested a minimum participation of 710 people. The number of participants in this study was significantly higher than the suggested number of participants. Instruments Sociodemographic Survey. An Ad Hoc survey was conducted to obtain information on the country of residence, age, sex, marital status, and educational level. Pandemic Grief Scale (PGS). The PGS is a measure of the frequency of dysfunctional grief reactions due to the death of a loved one due to COVID-19 over a 2-week period (Lee & Neimeyer, 2022). It comprises five items, with four response options ranging from zero (not at all) to 3 (almost every day). The total score of the PGS ranges from zero to 15, with a higher score indicating a higher frequency of COVID-19 be- reavement symptoms. Likewise, scores ≥7 indicated the presence of problematic symptoms that required further evaluation and/or treatment. In this study, the Spanish version of the PGS was used, which has been adapted and validated in different Latin American countries (Caycho-Rodrı́guez et al., 2021, 2023). The single item of suicidal ideation (Lee &Neimeyer, 2022) was “I wish I were dead so I wouldn’t have to deal with this loss,” and measures the frequency of suicidal 8 Psychological Reports 0(0) ideation. The item has four Likert-type response options, ranging from zero (not at all) to 3 (almost every day). In this study, we used the Spanish version of the single suicide ideation item used in different studies in Latin American countries during the pandemic (Caycho-Rodrı́guez et al., 2021, 2023). Procedure The study was conducted simultaneously in all the participating countries. The data collection procedure was the same for all countries. An online questionnaire was developed using the Google Form platform and consisted of multiple-choice questions on the sociodemographic characteristics of the participants, the five items of the PGS, and a single item on suicidal ideation. The questionnaire was distributed through social networks (e.g., Facebook and Instagram) and email. Before answering the questionnaire, all participants read the informed consent form, where the objective of the research was stated and informed that people could refuse to answer any question and withdraw from the study at any time. All individuals provided free and informed consent online to participate in the study. Table 1 shows the population of each participating country and their scenarios regarding the number of deaths and confirmed COVID-19 cases at the end of data collection as of April 2023. Despite the underreporting of cases and deaths, the number of cases and deaths per 100,000 inhabitants was higher in Mexico than in other countries. This study was conducted in accordance with the principles of the Declaration of Helsinki. This study was part of an international project on mental health, involving different countries in Latin America, including Peru. The data from the study are part of a larger project “Study of mental health and COVID-19 in a post-pandemic context in Latin America and the Caribbean” that was reviewed and approved by the Institutional Committee for the Protection of Human Subjects in Research (CIPSHI) of the University of Puerto Rico (No. 2223-006). Data Analysis Statistical analyses were performed using the free software, RStudio version 4.1.1. In the first stage, the demographic characteristics of each country are explored using absolute and relative frequencies. Subsequently, the description function included in the psych package was used to analyze the descriptive statistics of the items using arithmetic mean and standard deviation (Revelle, 2018). Similarly, prior to the analysis of a network structure, the topological overlap of the nodes was examined, with the aim of identifying redundant nodes that may affect the local and global properties of the network. A redundancy greater than 25% (p-value = .05 was determined to determine statistical significance using the goldbricker function in the networktools package (Jones, 2021). In the second stage, a network was constructed using a Pairwise Markov Random Field (PMRF), which is a class of undirected multivariate network models in which Caycho-Rodŕıguez et al. 9 variables are represented by nodes connected by edges (blue lines are positive cor- relations, red lines are negative correlations, and the thickness of the edges describes the magnitude of the correlation). This indicates the conditional association between two variables after controlling for all other variables in the network (Isvoranu et al., 2022). Given the objectives of this study, a non-regularized network with partial correlation coefficients was estimated through the estimateNetwork function in the bootnet package using the non-regularized ggmModSelect algorithm, which performs an it- eration process in which it selects an optimal Gaussian graphical model (GGM) ac- cording to the extended Bayesian information criterion (EBIC), in which the model with the lowest and best-fitting EBIC to the data was selected (Epskamp et al., 2018). Owing to the Gaussian approach and ordinal variables, Spearman’s partial correlation method was used for edge quantification (Isvoranu & Epskamp, 2023). Finally, to ensure a visually interpretable model, the function and package qgraph were used with Table 1. Summary of Information for Each Studied Country. Country (Population) Target Population The Status of COVID-19 at the End of Data Collection The Situation as of March 2023 Confirmed Cases (Death) Confirmed Cases (Death) Chile (19.49 million) General population over the age of 18 812.344 (20.310) 5.192.286 (64.273) Colombia (51.52 million) General population over the age of 18 2.056.052 (59.766) 6.359.093 (142.339) Ecuador (17.8 million) General population over the age of 18 282.599 (15.713) 1.057.121 (36.014) El Salvador (6.314 million) General population over the age of 18 59.235 (2000) 201.785 (4.230) Guatemala (17.11 million) General population over the age of 18 174.542 (6.393) 1.238.247 (20.182) México (126.7 million) General population over the age of 18 2,236,606 (2.403) 7.483.444 (333.188) Paraguay (6.704 million) General population over the age of 18 137.603 (2.807) 808.401 (19.878) Perú (33.72 million) General population over the age of 18 1,286,757 (45,263) 4.487.553 (219.539) 10 Psychological Reports 0(0) the Fruchterman-Reingold algorithm, which performs a dynamic procedure to calculate a layout such that the most connected nodes will be dragged towards the center of the network and the most disconnected nodes are located at the periphery of the network (Fruchterman & Reingold, 1991). In the third stage, the network architecture is analyzed through its local properties (inference in specific parts of the network) and global properties (inference in the general network). Regarding the local metrics, the centrality of the nodes was estimated using the expected influence of the centrality function in the qgraph package, which considers the edges of one node with another node in opposite directions (Isvoranu et al., 2022). Predictability was examined using the normalized precision (nCC) recommended for ordinal items, which quantifies the predictability of a node in a network structure using the mgm function and package (Haslbeck and Waldorp, 2018, 2020). In the network graph, the predictability can be seen as a black circle surrounding each node. For global metrics, the assessment of the overall network connectivity was calculated using the density (D) with the mean function, which quantifies the proportion of connections present in a graph. In addition, node organization was explored through transitivity (C4), which determines the average global clustering of nodes in a net- work, and average edge properties were explored using the Average Shortest Path Length (APL), which calculates the average geodesic distance between each pair of nodes (Isvoranu& Epskamp, 2023). Because some network structures may exhibit high node clustering but low APL, the small-world index (S) was estimated to assess the degree of association between nodes, with S >1 being recommended (Isvoranu et al., 2022). These global metrics were obtained using the smallworldIndex function in the qgraph package and are useful for understanding how the network architecture transmits information across a set of nodes (Isvoranu et al., 2022). Recent psychology studies have analyzed global properties because they are a key aspect in the network structure of psychological variables, given that they can reveal the vulnerability of the network through the connections between symptoms and behavior, which may be relevant for psychological problems such as pandemic grief and suicidal ideation in vulnerable populations (Baños-Chaparro & Ynquillay-Lima, 2023; Dalege et al., 2017; Watters et al., 2016). In the fourth stage, an accuracy and stability analysis was performed using the Bootnet and corStability functions in the Bootnet package. Regarding accuracy, the nonparametric bootstrap method based on 1000 samples was applied to construct the 95% confidence intervals (CI) of the weights of the network edges. Then, the stability analysis for the expected influence index was performed using the case-dropping bootstrap procedure, which removes participants from the data iteratively (e.g., 10%, 20%, and so on). This method can be summarized by the Correlation Stability co- efficient (CS), which should be greater than .25 and preferably greater than .50 (Isvoranu et al., 2022). To assess network differences between countries, a network comparison test for multiple groups based on 1000 random permutations was applied using the NCT function in the NetworkComparisonTest package (van Borkulo et al., 2022). This process was performed on the basis of network structure invariance and Caycho-Rodŕıguez et al. 11 overall strength invariance, using the Holm-Bonferroni correction for statistical sig- nificance, in which a p-value less than .05 indicates differences between two underlying networks (van Borkulo et al., 2022). In addition, the similarity of the networks was analyzed through the cor basis function for edge weights using Spearman’s correlation (rs), in which a high correlation would mean that the network structures are highly similar (Isvoranu et al., 2022). Results Sociodemographic Characteristics of the Participants A total of 2174 participants participated in this study. The average age ranged from 27.09 years (Ecuador) to 40.71 years (Guatemala). The majority of the participants were women, representing more than 61% of the total in each country. Guatemala and Paraguay had the lowest (106) and highest (328) numbers of women, respectively. The number of men ranged from 45 (Chile) to 165 (El Salvador). Regarding marital status, the majority of participants in each country reported being single at the time of responding to the survey. The countries with the highest percentages of single participants were Colombia (76.7%), Ecuador (74.3%), and El Salvador (75.6%). In the remaining countries, the percentage of single respondents ranged from 42.1% (Guatemala) to 65.8% (Paraguay). Finally, with respect to educational level, the majority of participants in all countries reported having completed or incomplete university studies. The highest percentage of people with university education was reported in Peru (86.3%), whereas the lowest percentage was in El Salvador (67.1%). Table 2 shows the sociodemographic characteristics of the study participants in each country. Local and Global Network Properties The lowest mean pandemic grief scores were found in Chile (M = 1.31) and Paraguay (M = 1.36) (Table 3). The highest values were found in Ecuador and Mexico (M = 1.52), followed by El Salvador (M = 1.46) and Colombia (M = 1.40). Chile (SD = .71) and Paraguay (SD = .77) presented the lowest standard deviations, while Mexico (SD = .88), Ecuador (SD = .85), and El Salvador (SD = .85) had the highest values. Regarding mean scores for suicidal ideation, Ecuador had the highest score (M = 1.39), followed by El Salvador (M = 1.34) and Mexico (M = 1.33). Chile (M = 1.18) and Guatemala (M = 1.23) have the lowest scores. Likewise, the highest standard deviation values were found in Mexico (SD = .81) and El Salvador (SD = .80), while the lowest values were found in Chile (SD = .60) and Guatemala (SD = .67). In the topological overlap analysis, there were no suggestions for overlapping pairs of nodes, indicating the absence of redundancy between the nodes included in the network for each country. The network structures of pandemic grief and suicidal ideation are presented in Figure 1. The purpose of presenting the network structures as a whole is to visualize the 12 Psychological Reports 0(0) T ab le 2. D em og ra ph ic C ha ra ct er is tic s of Pa rt ic ip an ts in Ea ch C ou nt ry . C hi le (n = 17 9) C ol om bi a (n = 21 5) Ec ua do r (n = 29 5) El Sa lv ad or (n = 43 7) G ua te m al a (n = 17 1) M ex ic o (n = 20 2) Pa ra gu ay (n = 44 1) Pe ru (n = 23 4) G en de r (% ) W om en 13 4 (7 4. 9) 14 8 (6 8. 8) 19 8 (6 7. 1) 27 0 (6 1. 8) 10 6 (6 2) 12 0 (5 9. 5) 32 8 (7 4. 3) 16 8 (7 1. 8) M en 45 (2 5. 1) 67 (3 1. 2) 97 (3 2. 9) 16 5 (3 7. 7) 65 (3 8) 80 (4 0) 11 1 (2 5. 2) 66 (2 8. 2) T ra ns ge nd er /n on bi na ry 0 (0 .0 ) 0 (0 .0 ) 0 (0 .0 ) 2 (0 .5 ) 0 (0 .0 ) 2 (0 .5 ) 2 (0 .5 ) 0 (0 .0 ) A ge (M ± D E) 36 .6 0 ± 10 .7 3 27 .9 0 ± 11 .0 7 27 .0 9 ± 8. 49 28 .0 6 ± 7. 43 40 .7 1 ± 12 .3 4 30 .4 5 ± 11 .9 2 30 .7 4 ± 9. 94 31 .9 6 ± 10 .9 2 M ar ita ls ta tu s (% ) Si ng le 81 (4 5. 2) 16 5 (7 6. 7) 21 9 (7 4. 3) 33 0 (7 5. 6) 72 (4 2. 1) 12 2 (6 0. 4) 29 0 (6 5. 8) 14 9 (6 3. 7) M ar ri ed 52 (2 9. 1) 25 (1 1. 6) 52 (1 7. 6) 67 (1 5. 3) 71 (4 1. 5) 64 (3 1. 7) 10 4 (2 3. 6) 49 (2 0. 9) D iv or ce d 15 (8 .4 ) 4 (1 .9 ) 17 (5 .8 ) 8 (1 .8 ) 13 (7 .6 ) 9 (4 .4 ) 12 (2 .7 ) 8 (3 .4 ) C oh ab ita nt 28 (1 5. 6) 18 (8 .4 ) 6 (2 .0 ) 32 (7 .3 ) 12 (7 ) 4 (2 ) 34 (7 .7 ) 26 (1 1. 1) W id ow er 3 (1 .7 ) 3 (1 .4 ) 1 (0 .3 ) 0 (0 .0 ) 3 (1 .8 ) 3 (1 .5 ) 1 (0 .2 ) 2 (0 .9 ) H ig he r ed uc at io n (% ) N o 12 (6 .7 ) 46 (2 1. 4) 53 (1 8) 11 8 (2 7) 16 (9 .3 ) 14 (6 .9 ) 51 (1 1. 6) 15 (6 .4 ) Y es ,t ec hn ic al le ve la 21 (1 1. 7) 24 (1 1. 2) 8 (2 .7 ) 26 (5 .9 ) 14 (8 .2 ) 34 (1 6. 9) 16 (3 .6 ) 17 (7 .3 ) Y es ,u ni ve rs ity le ve la 14 6 (8 1. 6) 14 5 (6 7. 4) 23 4 (7 9. 3) 29 3 (6 7. 1) 14 1 (8 2. 5) 15 4 (7 6. 2) 37 4 (8 4. 8) 20 2 (8 6. 3) a B ot h co m pl et e an d in co m pl et e st ud ie s w er e in cl ud ed . Caycho-Rodŕıguez et al. 13 T ab le 3. D es cr ip tiv e St at is tic s, Lo ca la nd G lo ba lN et w or k Pr op er tie s. C ou nt ri es St at is tic s Lo ca lN et w or k Pr op er tie s G lo ba lN et w or k Pr op er tie s PG S1 PG S2 PG S3 PG S4 PG S5 SI D C 4 A PL S C hi le (n = 17 9) M 1. 23 1. 41 1. 34 1. 23 1. 34 1. 18 .1 61 .4 5 1. 40 1. 03 D E .6 9 .7 8 .7 4 .6 3 .7 2 .6 0 IE 1. 04 .7 4 .8 0 .3 5 1. 02 .8 9 P 63 .6 % 38 .8 % 12 .5 % 4% 40 % 44 .4 % C ol om bi a (n = 21 5) M 1. 31 1. 45 1. 42 1. 42 1. 41 1. 28 .1 68 .2 1 1. 47 .5 7 D E .8 0 .8 7 .8 4 .8 1 .8 4 .7 3 IE 1. 06 .5 3 .8 4 .4 5 .9 5 1. 22 P 73 .5 % 38 .2 % 50 .9 % 34 .5 % 53 .8 % 64 .7 % Ec ua do r (n = 29 5) M 1. 35 1. 63 1. 58 1. 54 1. 49 1. 39 .1 80 .6 0 1. 27 1. 11 D E .7 7 .9 1 .8 8 .8 8 .8 3 .7 9 IE .8 8 .8 7 1. 06 .6 3 1. 02 .9 5 P 60 .3 % 46 .6 % 50 % 37 .8 % 53 .7 % 50 % El Sa lv ad or (n = 43 7) M 1. 33 1. 53 1. 53 1. 47 1. 46 1. 34 .1 77 .7 5 1. 27 1. 39 D E .7 7 .9 0 .8 9 .8 5 .8 4 .8 0 IE .9 2 .8 9 1. 04 .6 1 1. 05 .7 9 P 53 .8 % 44 .2 % 43 .2 % 31 .5 % 45 .5 % 43 .7 % G ua te m al a (n = 17 1) M 1. 23 1. 44 1. 37 1. 34 1. 38 1. 23 .1 61 .5 3 1. 53 1. 35 D E .6 8 .8 5 .8 0 .7 7 .8 2 .6 7 IE .5 7 .6 5 1. 36 .3 3 1. 15 .7 7 P 40 .9 % 61 .4 % 72 .2 % 12 .1 % 63 .9 % 59 .1 % M ex ic o (n = 20 2) M 1. 31 1. 69 1. 61 1. 50 1. 47 1. 33 .1 67 .4 8 1. 33 .9 8 D E .7 6 .9 8 .9 4 .8 9 .8 5 .8 1 IE .8 4 .6 3 1. 28 .5 9 .8 2 .8 4 P 42 .9 % 31 .7 % 48 .6 % 23 .7 % 41 .7 % 50 % (c on tin ue d) 14 Psychological Reports 0(0) T ab le 3. (c on tin ue d) C ou nt ri es St at is tic s Lo ca lN et w or k Pr op er tie s G lo ba lN et w or k Pr op er tie s PG S1 PG S2 PG S3 PG S4 PG S5 SI D C 4 A PL S Pa ra gu ay (n = 44 1) M 1. 30 1. 38 1. 38 1. 38 1. 35 1. 25 .1 78 .6 8 1. 27 1. 25 D E .7 6 .7 9 .7 9 .7 8 .7 4 .7 0 IE .8 9 .9 0 .8 8 .6 6 1. 15 .8 6 P 35 .7 % 34 .6 % 35 % 21 .6 % 45 .4 % 45 .9 % Pe ru (n = 23 4) M 1. 31 1. 56 1. 52 1. 45 1. 39 1. 30 .1 73 .3 0 1. 40 .6 9 D E .7 2 .8 9 .8 8 .8 6 .8 1 .7 7 IE 1. 18 .7 0 .8 7 .5 7 1. 11 .7 7 P 57 .8 % 35 .4 % 46 .7 % 36 .5 % 44 .6 % 53 .8 % N ot e. M = m ea n; SD = st an da rd de vi at io n; IE = ex pe ct ed in fl ue nc e; P = pr ed ic ta bi lit y; PG S1 = Iw is he d to di e in or de r to be w ith th e de ce as ed ;P G S2 = Ie xp er ie nc ed co nf us io n ov er m y ro le in lif e or fe lt lik e m y id en tit y w as di m in is he d be ca us e of th e lo ss ;P G S3 = N ot hi ng se em ed to m at te rm uc h to m e be ca us e of th is lo ss ;P G S4 = I fo un d it di ffi cu lt to ha ve po si tiv e m em or ie s ab ou t th e de ce as ed ;P G S5 = Ib el ie ve th at w ith ou t th e de ce as ed ,l ife w as m ea ni ng le ss ,e m pt y, or co ul d no t go on ;S I: su ic id al id ea tio n. D = de ns ity ;C 4 = tr an si tiv ity ;A PL = av er ag e sh or te st pa th le ng th ;S = sm al l-w or ld in de x. Caycho-Rodŕıguez et al. 15 differences in connections that exist in each country, which is useful for a better understanding of the results. In general, it is evident that the conditional associations of the nodes in the underlying networks of each country are positive, although a difference in the magnitude of the edges in each country can be appreciated. For example, the networks of Ecuador (11 edges), Paraguay (11 edges), and El Salvador (11 edges) presented the highest connectivity of the proportion of edges present compared with Chile (nine edges), Guatemala (eight edges), and Colombia (eight edges), which presented a lower number of edges in the individual node relationships. Nevertheless, in all countries, the strongest conditional associations were observed between suicidal ideation and PGS1 (“I wanted to die to be with the person who died”), as well as connections with PGS5 (“I believed that, without the deceased person, life was meaningless, empty or could not continue”) and to a lesser extent with PGS3 (“Nothing seemed important because of this loss”). In relation to local network properties, Figure 2 and Table 3 show that the most central nodes according to expected influence (EI) for pandemic grief were PGS3 for Guatemala (EI = 1.36), Mexico (EI = 1.28), and Ecuador (EI = 1.06). PGS1 was more central in Peru (EI = 1.18), Colombia (EI = 1.06), and Chile (EI = 1.04). In Paraguay Figure 1. Network structure of pandemic grief and suicidal ideation in eight Latin American countries. 16 Psychological Reports 0(0) (EI = 1.15) and El Salvador (EI = 1.05), the central node is PGS5. The EI for suicidal ideation had the highest value in Colombia (EI = 1.22) and the lowest values in Peru and Guatemala (EI = .77). Similarly, the node with the highest predictability in the un- derlying networks was PGS1 in five countries (Chile, Colombia, Ecuador, El Salvador, and Peru). On the other hand, the node with the highest predictability in the underlying networks was PGS1 in five countries such as Chile (63.6%), Colombia (73.5%), Ecuador (60.3%), El Salvador (53.8%) and Peru (57.8%). PGS3 presented the highest predictability value in Guatemala (72.2%), and SI in Mexico (50%) and Paraguay (45.9%). The second node with the highest predictability was PGS5 in Ecuador (53.7%), El Salvador (45.5%), Guatemala (63.9%), and Paraguay (45.4%). This was followed by SI in Chile (44.4%), Colombia (64.7%), and Peru (53.8%). Only in Mexico (48.6%) did PGS3 have the second highest value. PGS4 had the lowest predictability value in most countries including Chile (4%), Colombia (34.5%), Ecuador (37.8%), El Salvador (31.5%), Guatemala (12.1%), Mexico (23.7%), and Paraguay (21.6%). Except for Peru, PGS2 had the lowest predictive value (35.4%). Regarding global network properties, Table 3 shows that the values of density, C4, and APL are adequate for each network structure in the eight Latin American countries. Using the values of C4 and APL, the S index was >1 in five countries (Chile, Ecuador, El Salvador, Guatemala, and Paraguay), although Mexico (S = .98) presented a fairly close approximation, compared to Colombia (S = .57) and Peru (S = .69). The properties of S indicate that the topology of the networks in these countries contains some small-world properties. Figure 2. Expected influence centrality index. Caycho-Rodŕıguez et al. 17 Accuracy of the Network Structure and Stability of the Centrality Index Overall, the nonparametric bootstrap CIs resampled 1000 times for the edges of the networks in the eight countries are shown in Figure 3. In general, the bootstrap and sample means overlapped, while the confidence intervals (shaded gray) were small in Chile, Colombia, Ecuador, and Guatemala, and the widest intervals were evident in El Figure 3. Nonparametric bootstrapping confidence intervals of estimated edges for the network structure. 18 Psychological Reports 0(0) Salvador, Mexico, Paraguay, and Peru. In addition, the EI index estimate exceeded the acceptable stability values in Chile (CS ≈ .36), Colombia (CS ≈ .59), Ecuador (CS ≈ .36), El Salvador (CS ≈ .44), Guatemala (CS ≈ .60), Mexico (CS ≈ .28), Paraguay (CS ≈ .36), and Peru (CS ≈ .28). The range of CS coefficients across countries was between .28 and .60, which suggests that between 28% and 60% of the data could be removed to retain a 95% certainty correlation of .70 with the original data set (Figure 4). This shows that EI centrality estimates are interpretable on a country-by- country basis. Figure 4. Stability of the expected influence centrality index. Caycho-Rodŕıguez et al. 19 Comparative Analysis of Networks by Country Table 4 reports the network comparisons among the eight Latin American countries. In the network structure invariance test, it was observed that twenty-three groups reported no differences and only five groups indicated statistically significant differences. These differences were found mainly in the network structure of Chile versus Ecuador (p = .03), El Salvador (p = .04) andMexico (p = .01). In addition, Colombia versus El Salvador (p = .01) and Mexico (p = .01). Regarding the global strength invariance test, no differences Table 4. Invariance of Network Structure and Global Strength by Country. Structures of the Network Network Structure Invariance Global Force Invariance Similarity of Edge Weights Countries p p Spearman 1 versus 2 .05 .23 .53 1 versus 3 .03 .40 .47 1 versus 4 .04 .27 .64 1 versus 5 .28 .54 .49 1 versus 6 .01 .28 .34 1 versus 7 .10 .34 .12 1 versus 8 .52 .20 .70 2 versus 3 .53 .14 .71 2 versus 4 .01 .24 .37 2 versus 5 .10 .93 .71 2 versus 6 .01 .29 .62 2 versus 7 .18 .33 .57 2 versus 8 .28 .59 .78 3 versus 4 .57 .54 .47 3 versus 5 .59 .19 .45 3 versus 6 .31 .65 .72 3 versus 7 .72 .44 .53 3 versus 8 .58 .27 .52 4 versus 5 .31 .41 .33 4 versus 6 .10 .99 .26 4 versus 7 .48 .88 .09 4 versus 8 .13 .59 .45 5 versus 6 .07 .35 .39 5 versus 7 .80 .50 .49 5 versus 8 .09 .52 .59 6 versus 7 .30 .89 .33 6 versus 8 .05 .64 .44 7 versus 8 .57 .76 .56 Note. 1 = Chile; 2 = Colombia; 3 = Ecuador; 4 = El Salvador; 5 = Guatemala; 6 = Mexico; 7 = Paraguay; 8 = Peru. 20 Psychological Reports 0(0) were found in the network structures between countries, since the statistical significance was significantly greater than .05. Similarly, the results for similarity of edge weights correlated on average at a low to moderate level, with the lowest correlations found between the countries of El Salvador and Paraguay (rs = .09), as well as Chile and Paraguay (rs = .12). The highest correlations were found between the network structures of Colombia and Peru (rs = .78), Ecuador and Mexico (rs = .72), Colombia and Guatemala (rs = .71) and Ecuador (rs = .71), and Chile and Peru (rs = .70). Discussion The present study was the first to evaluate pandemic grief, that is, dysfunctional grief produced by the death of a loved one due to COVID-19, as a network, which provided a more detailed analysis of the symptoms of pandemic grief that are valuable for maintaining its coherence as a system. This was also the first study to examine symptom-level interactions between pandemic grief and suicidal ideation in a Latin American context. This study aimed to characterize the network structure of pandemic grief symptoms and suicidal ideation in samples from eight Latin American countries, identify the central nodes in each variable, determine the stability of the network, and test whether the networks changed between the countries assessed. The first major finding was that the participants in this study appeared to be adapting relatively well to their loss. Specifically, the mean PGS scores did not indicate the presence of prob- lematic symptoms of pandemic grief that needed assessment and/or treatment. No high frequency of suicidal thoughts was observed. Although it has been speculated that poor public health spending, healthcare problems, and scarce economic resources available to citizens during the COVID-19 pandemic may increase the likelihood of suicidal ideation due to low hope for the future (Cheung et al., 2021), our results suggest that many of these issues did not severely affect the bereaved during this phase of the pandemic. For example, during data collection in Ecuador, 15,713 deaths due to COVID-19 were reported, which led the country to face one of the most severe periods of the disease, called the third wave of mortality of the pandemic. Although Chile had a higher number of diagnosed cases and deaths during the data collection period, its health response may have been related to the lower presence of symptoms of pandemic grief and suicidal ideation. It is important to note that the samples from Ecuador and Mexico presented the highest mean scores for pandemic grief, while Ecuador presented the highest mean score for suicidal ideation. In contrast, the Chilean sample had the lowest scores for pandemic grief and suicidal ideation. The desire to die to be with the deceased person, apathy about things, and lack of meaning in life were the most central or representative symptoms of pandemic grief for people in the eight countries. The desire to die was also the symptom with the highest predictability. The presence of the death wishes node and its high predictability were expected given that this PGS item also measures suicidal ideation. This grief-related death wish is also a characteristic diagnostic symptom of persistent complex be- reavement disorder according to the DSM-5 (American Psychiatric Association [APA], Caycho-Rodŕıguez et al. 21 2013), and is highly associated with traumatic grief (Lee & Neimeyer, 2022). Moreover, thoughts of death have been highly prevalent during the COVID-19 pandemic, not only because of the large number of people who died of COVID-19, but also because of the stressors related to social distancing, economic instability, and other consequences of the confinement that countries resorted to in order to mitigate the impact of COVID-19 (Fitzpatrick et al., 2020). Although apathy is not a symptom of persistent complex grief disorder, according to the DSM-5 (APA, 2013), it has been suggested that it reflects a preoccupation with death, which is a criterion for prolonged grief disorder, according to the International Classification of Disease (World Health Organization, 2019). Apathy leaves people who have loved ones killed by COVID-19 with low levels of motivation to engage in other activities (Lee &Neimeyer, 2022). Likewise, according to the dual process model of coping with grief, apathy reflects an inability to adaptively cope with the death of a loved one and has a restoration orientation (Stroebe & Schut, 2020). Finally, the finding that the absence of meaning in life was also a representative symptom of pandemic grief was expected. Not only is meaninglessness a symptom of both persistent complex grief disorder (APA, 2013) and prolonged grief disorder (APA, 2022), it has repeatedly been found to be one of the most significant predictors of dysfunctional grief in research studies (Lee & Neimeyer, 2022; Neimeyer, 2019). During the COVID-19 pandemic, problems with a sense of life during this global health emergency were found to be inversely related to a host of negative mental health outcomes (Milman et al., 2020). Nevertheless, this study is not the first to report the presence of symptoms of apathy, desire to die, and loss of meaning in life as indicators of bereavement problems. It is one of the first studies to evaluate, from a network approach, their relationships with each other in people bereaved by the COVID-19 pandemic at the Latin American level. Moreover, the centrality estimates were interpretable for each country. As such, de- creased desire to die, apathy, and lack of meaning in life can be identified as inter- vention targets for mental health professionals dealing with people experiencing grief complications from the death of a loved one due to COVID-19 in the countries evaluated. Regarding the interconnection between the nodes, the results of this study revealed that suicidal ideation, PGS1 (“I wanted to die to be with the person who died”) and PGS5 (“I believed that, without the deceased person, life was meaningless, empty or could not continue”) had the strongest relationship. That is, the desire to die and lack of meaning in life were related to the presence of suicidal ideation in people with pandemic bereavement. These findings are consistent with those of previous studies conducted in different countries (Jonson et al., 2023; Lew et al., 2020). The desire to die is not specific to dysfunctional grief as it is also a symptom of depression (Jonson et al., 2023), which is consistently associated with suicidal ideation (Amit et al., 2020). The desire to die is also associated with suicidal ideation through its links with social determinants such as social support and feelings of belongingness (Du et al., 2021). Regarding meaning with life, the present study provided evidence that it may suppress negative dispositions toward suicidal orientation and, as such, can be leveraged by 22 Psychological Reports 0(0) health professionals as a support mechanism for bereaved struggling with suicidal ideation (Lew et al., 2020). Previous research supports this approach (Kleiman & Beaver, 2013). According to the interpersonal theory of suicide (Joiner et al., 2009), it has been suggested to generate resilience against suicide (Van Orden et al., 2012). Likewise, meaninglessness generates existential frustration, leading to existential emptiness related to boredom and apathy (Frankl, 1969). In this sense, grieving people may experience that their lives have no purpose or challenge, which promotes suicidal ideation (Dogra et al., 2011). Taken together, these findings suggest the need for positive interventions that have been effective in reducing the risk of suicidal ideation (Sun et al., 2022). Overall, this study reported no differences in the network structure and overall strength of mental health problems between countries, indicating that the distribution and pairwise associations of these grief-related symptoms were similar among the participating countries. There are no other studies comparing network structures be- tween pandemic grief symptoms and suicidal ideation in Latin America or in other countries in other regions of the world. There were also statistically significant dif- ferences between some countries, such as Chile and Ecuador, El Salvador, Mexico, Colombia, El Salvador, and Mexico. Some possible explanations for these differences have already been mentioned in the first paragraphs of this discussion. However, it is important to mention that a country’s culture may impact patterns, emotional expe- riences, and grief management (Jakoby, 2012; Lund, 2021; Silverman et al., 2021). In this sense, Latin America is a region characterized by a set of stressors, such as in- equality, poverty, and the high presence of chronic diseases (Pablos-Méndez et al., 2020), which generate differences in the experience of grief for the death of a loved one. Likewise, the high number of people diagnosed with and killed by COVID-19 in Latin America also negatively affects people’s ability to accept the death of their loved ones (e Silva, & Pitzurra, 2020). Similarly, the culture of each country affects the expression of suicidal thoughts (Hjelmeland, 2010, 2011). For example, Asian American indi- viduals with suicidal ideation tend to underestimate the severity of warning signs of the onset of these thoughts and are less likely to perceive the need for help compared to Latin American individuals (Chu et al., 2011). However, despite evidence of cultural differences between countries, the results indicate that there may be sufficient simi- larities in the symptom network of pandemic grief and suicidal ideation, considering that the relationships between these symptoms are the same across participating countries. In addition, it is possible that network differences among some countries may be partially masked by the negative impact of the pandemic on mental health, as Latin American countries may have been equally affected by public health measures and fear of the pandemic and its consequences (Caycho-Rodrı́guez et al., 2022). Limitations First, non-probabilistic snowball sampling was used, which did not allow represen- tative samples to be obtained and limited the generalizability of the findings to the Caycho-Rodŕıguez et al. 23 general population of all the participating countries. Therefore, it is recommended that future studies use probability sampling procedures to generate representative samples of each population. Second, the use of non-probability sampling resulted in some subgroups being overrepresented, for example, a greater number of women, single people, and university graduates. Thus, the characteristics of participants from the eight countries were not directly comparable. Future studies should attempt to work with more homogeneous groups with respect to their sociodemographic characteristics. In addition, the findings were based on a non-clinical sample, where severity levels of grief symptoms might be low and suicidal ideation might barely be present. Future studies should evaluate the networks of pandemic grief and suicidal ideation using clinical samples. Third, the number of participants differed among the participating countries, ranging from 171 in Guatemala to 441 in Paraguay. This should lead to future studies involving different countries to ensure a homogeneous number of participants in each group. Fourth, the use of online surveys may generate bias, since participants may respond with little sincerity or may not understand the instructions or descriptions of the items. Fifth, all symptoms of pandemic grief and suicidal ideation were assessed using self-reporting questionnaires. Although both the PGS and the single item of suicidal ideation have been validated and used previously, the use of a clinical interview by a mental health professional may have improved the reliability of the assessment. Sixth, the study covered only a brief period during the third year of the pandemic. Future research should investigate changes in grief symptoms and suicidal ideation during the later phases of the pandemic and after its end. Seventh, the different policies and strategies to mitigate the spread of COVID-19, and the different numbers of cases and deaths in the participating countries, may have meant that the pandemic grief expe- rience may have been different. This may have been a confounding factor in this study. Eighth, the PGS assesses the frequency of occurrence of only five symptoms of pandemic grief; therefore, the observed findings should be interpreted in the context of the symptoms included in the network. Ninth, the cross-sectional nature of the data means that only causal relationships between pandemic grief symptoms and suicidal ideation can be suggested. That is, only undirected networks were estimated, where edges do not indicate directionality, which reduces practical implications for health professionals. Thus, future studies on the relationship between pandemic grief symptoms and suicidal ideation should examine longitudinal data to corroborate the causal directions suggested in this study. Therefore, it would be advisable to use intraindividual network time-series analysis (Borsboom & Cramer, 2013). Despite these limitations, the results are valuable for future studies on the relationship between pandemic grief symptoms and suicidal ideation in different countries. Conclusion and Implications In conclusion, the mean PGS scores did not indicate the presence of problematic symptoms of pandemic grief in need of assessment and/or treatment or a high frequency of suicidal thoughts. Also, “desire to die”, “apathy” and “absence of meaning in life” 24 Psychological Reports 0(0) are the most central symptoms in a network of pandemic grief symptoms. Suicidal ideation, the wish to die, and the absence of meaning in life had the strongest relationship. Similarly, the network structure did not differ among participating countries. Identifying the core symptoms and the relationships between symptoms within the symptom invariant network model of pandemic grief and suicidal ideation has clinical significance, not for one but for all countries involved in the study. Focusing on these symptoms could contribute to the prevention of grief problems due to the death of a loved one from an infectious disease and suicidal ideation, and improve the efficacy of treatments targeting these symptoms in residents of the Latin American countries evaluated (Sun et al., 2022). Specifically, early interventions for these core and bridging symptoms could stop the activation of other symptoms, alleviate further psychological burden, and provide important contributions to individual treatment. Cognitive Be- havioral Therapies (CBT) targeting core symptoms and bridging symptoms, including “wish to die,” “apathy,” and “absence of meaning in life” through education, guidance, support, could rapidly improve healthy integration of loss and reduce the risk of suicidal ideation for those struggling with their grief (Laranjeira et al., 2022). Likewise, it has also been suggested that Internet-based treatments could be useful in reducing grief-related symptoms by working on distressing memories through exposure and cognitive restructuring of dysfunctional ideas related to grief (Wagner et al., 2020). Along the same lines, it has been indicated that self-directed digital interventions are effective in reducing suicidal ideation, which is important especially where there is absence or limited access to health services, as in most Latin American countries (Torok et al., 2020). As noted, these findings have profound theoretical and practical im- plications, underscoring the importance of the symptoms of bereavement and suicidal ideation and the need to explore the dynamics between themwithin the intricate domain of mental health. This has become even more relevant in the current context, where the pandemic has undoubtedly left profound repercussions on people’s mental health worldwide. Appendix List of Abbreviations PGS Pandemic grief scale PMRF Pairwise Markov random field GGM Gaussian graphical model EBIC Extended Bayesian information criterion APL Average shortest path length CI confidence intervals CS Correlation stability coefficient rs Spearman’s correlation. Caycho-Rodŕıguez et al. 25 Author Contributions TC-R, JB-CH provided initial conception, organization, and main writing of the text. JB-CH and JV-L analyzed the data and prepared all figures and tables. ShAL, LWV, CC-L, D EY-L, PDV, MR-B, NO-K, CR-J, MG, RP-C, MC, PM, MEL-R, RM-H, DAPS, AS-P, ABF, DXP-C, AC, JT, JAMB, PG, VS-C, OP-R, RC, WYMR, DF-B, AM-del-C-T, JP, CB-V, AMEFL, IV, DV, MKSh, HTUR, AELL, NAB-A, JA-C and LH-O were involved in data collection and acted as con- sultants and contributors to research design, data analysis, and text writing. The first draft of the manuscript was written by TC-R, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article. Ethical Statement Ethical Approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Institutional Committee for the Protection of Human Subjects in Research (CIPSHI) of the University of Puerto Rico (No. 2223-006). Informed Consent Statement Informed consent was obtained from all individual participants included in the study. ORCID iDs Tomás Caycho-Rodrı́guez  https://orcid.org/0000-0002-5349-7570 José Ventura-León  https://orcid.org/0000-0003-2996-4244 Sherman A. Lee  https://orcid.org/0000-0003-1878-3472 Mario Reyes-Bossio  https://orcid.org/0000-0003-4655-1927 Pablo Martino  https://orcid.org/0000-0002-5633-2050 Rodrigo Moreta-Herrera  https://orcid.org/0000-0003-0134-5927 Data Availability Statement The database is available with a request to the corresponding author. 26 Psychological Reports 0(0) https://orcid.org/0000-0002-5349-7570 https://orcid.org/0000-0002-5349-7570 https://orcid.org/0000-0003-2996-4244 https://orcid.org/0000-0003-2996-4244 https://orcid.org/0000-0003-1878-3472 https://orcid.org/0000-0003-1878-3472 https://orcid.org/0000-0003-4655-1927 https://orcid.org/0000-0003-4655-1927 https://orcid.org/0000-0002-5633-2050 https://orcid.org/0000-0002-5633-2050 https://orcid.org/0000-0003-0134-5927 https://orcid.org/0000-0003-0134-5927 References Adiukwu, F., Kamalzadeh, L., Pinto da Costa, M., Ransing, R., de Filippis, R., Pereira-Sanchez, V., Larnaout, A., Gonzalez-Diaz, J. 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Senior Researcher at the Universidad Cientı́fica del Sur, Research Renacyt Distinguished category. His research interests are psychometrics, psychogerontology, cross-cultural research. Jonatan Baños-Chaparro, Associate researcher at the Scientific University of the South, postgraduate professor at the Ricardo Palma University and academic advisor at the Universidad Peruana Unión, Tarapoto Branch. Dr. Jose Ventura-León. I am a doctor in Psychology and I have a Master’s degree in Educational Psychology. I currently work as a university professor and full-time re- searcher on psychometric, methodological and psychological topics. Sherman A. Lee, PhD, is an associate professor of psychology at Christopher Newport University. He studies negative feeling states, such as anxiety and grief, and the role personality and religion play in those emotional experiences. He teaches courses in the Caycho-Rodŕıguez et al. 33 https://doi.org/10.1037/met0000476 https://doi.org/10.1037/met0000476 https://doi.org/10.1080/13607863.2012.657156 https://doi.org/10.1037/a0018697 https://doi.org/10.3389/fpsyg.2022.837606 https://doi.org/10.1073/pnas.2007476117 https://doi.org/10.3389/fpsyt.2020.00525 https://doi.org/10.3389/fpsyt.2020.00525 https://doi.org/10.1080/00223891.2016.1172077 https://doi.org/10.1080/00223891.2016.1172077 https://icd.who.int/browse11/l-m/en#/ psychology of personality, psychology of the humananimal bond (Anthrozoology), and the psychology of death, dying, and bereavement (Thanatology). Lindsey W. Vilca, Master in Psychology. Professor and researcher at the Norbert Wiener University in Lima, Peru. His research interests are psychometrics and clinical and health Psychology. Carlos Carbajal-León, Dr. in psychology and Master in Educational Psychology. South American Center for Education and Research in Public Health, Norbert Wiener University, Lima, Peru. Research professor at the Peruvian University of Applied Sciences. Daniel E. Yupanqui-Lorenzo, Researcher at the University of Sciences and Humanities. Pablo D. Valencia, PhD Student, School of Higher Studies (F.E.S.) Iztacala, National Autonomous University of Mexico. Mario Reyes-Bossio, Master in Psychology, University of San Martı́n de Porres. Researcher at the Peruvian University of Applied Sciences. Nicol Oré-Kovacs, Master in Psychology, Researcher at the Peruvian University of Applied Sciences. Claudio Rojas-Jara, Master in drug addiction. Master in prevention and treatment of addictive behaviors. Academic of the Department of Psychology, Faculty of Health Sciences, Universidad Catolica del Maule, Chile. Miguel Gallegos, Doctor of Psychology from the National University of Rosario, Argentina, and Doctor of Education from the Federal University of Minas Gerais, Brazil. Post-doctorate from the National Autonomous University of Mexico, and the Pontificia Universidade Catolica de Minas Gerais, Brazil. Roberto Polanco-Carrasco, Bachelor of Psychology, Scientific Editor of Cuadernos de Neuropsicologıa – Panamerican Journal of Neuropsychology. Director of the Chilean Association of Scientific Journals of Psychology. Mauricio Cervigni, Doctor in Psychology from the National University of Rosario (UNR). Researcher at the National Council for Scientific and Technical Research (CONICET - Argentina). Professor-Researcher at the National University of Rosario (UNR). Pablo Martino, Doctor in Psychology (National University of San Luis-Arg). Adjunct professor at the Faculty of Psychology, National University of Rosario. National Council for Scientific and Technical Research postdoctoral fellow. Marlon Elı́as Lobos-Rivera, Psychologist. Master in University Education. Research professor at the School of Psychology, Faculty of Social Sciences, Technological University of El Salvador. 34 Psychological Reports 0(0) Rodrigo Moreta-Herrera, Clinical Psychologist and University Master’s Degree in Psychology. Doctor (c) in Psychology from the University of Girona. Professor and researcher at the Pontifical Catholic University of Ecuador. Diego Alejandro Palacios Segura, Clinical Psychologist, Master in Clinical Psy- chology andMental Health. Psychotherapist at the Human Development Center Clinics -CDH- and teacher at the University of San Carlos de Guatemala. Antonio Samaniego-Pinho, Psychologist with a specialty in Occupational Psychol- ogy. Master in Clinical Psychology. Teacher in the career of Psychology at the Faculty of Philosophy (National University of Asuncion). Andrés Buschiazzo Figares, Degree in Psychology (University of the Republic, Uruguay). Psychotherapist. Academic Director of the Center for Adlerian Studies, Uruguay. Diana Ximena Puerta-Cortés, Doctor in Psychology (Ramon LLull University of Barcelona, Spain). Master’s degree in psychology with an emphasis on addictions and violence (Universidad Catolica de Colombia). She is a researcher for the GESS group and director of the NeuroTech research hotbed. Professor at the University of Ibagué in Colombia. Andrés Camargo, Doctor of Psychology, School of Health and Sport Sciences, Fundación Universitaria del Area Andina, Bogotá, Colombia. Julio Torales, Head of the Neuroscience Department. School of Medical Sciences, Universidad Nacional de Asunción. José Arkangel Monge Blanco, Doctor of Psychology, Nicaraguan Association for the Development of Psychology. Pedronel González, Doctor of Psychology, Jesus of Nazareth University, Honduras. Vanessa Smith-Castro, Doctor of Psychology, Institute of Psychological Research, Faculty of Social Sciences, University of Costa Rica. Olimpia Petzold-Rodriguez, Doctor of Psychology, Lone Star College, Conroe, The United States of America. Raymundo Calderón, Master of Science in Education. National Director of Psy- chology, Universidad Del Valle de México. Wendy Yamilet Matute Rivera, Doctor of Psychology, Research Department Uni- versidad Jesús de Nazareth; Honduras. Daniela Ferrufino-Borja, Graduate in Psychology, Psychological Research and Counseling Center, Faculty of Humanities, Communication and Arts, Private Uni- versity of Santa Cruz de la Sierra, Santa Cruz, Bolivia. Caycho-Rodŕıguez et al. 35 Agueda Muñoz-del-Carpio-Toia, Doctor of Medicine and Master of Public Health. Full-time Research Professor in the Vice-Rector’s Office for Research. Professor at the Graduate School of the Catholic University of Santa Marı́a (UCSM). Jorge Palacios, Doctor of Psychology, Professor of Psychology, Faculty of Health Sciences, Universidad del Valle de Mexico, Mexico City, Mexico. Carmen Burgos-Videla, Teacher of Basic General Education, Graduate with a master’s degree in Education, curricular design by competencies. Doctor in Educational Sciences. Academic, researcher at the University of Atacama. Ana Marı́a Eduviges Florez León, Graduate in Psychology, Coordinator of the School of Psychology at the Universidad Latina. Ibeth Vergara, Graduate in Psychology. Professor, School of Psychology, Universidad Latina de Panamá, Panama. Diego Vega, Graduate in Psychology. Professor, School of Psychology, Universidad Latina de Costa Rica, San José, Costa Rica. MarionK. Schulmeyer, Graduate in Philosophy and Letters, Psychology Section from the Universidad Pontificia Comillas (Spain). Dean of the Faculty of Humanities and Communication of the Private University of Santa Cruz de la Sierra, Santa Cruz, Bolivia. Hassell Tatiana Urrutia Rios, Doctor of Psychology, Nicaraguan Association for the Development of Psychology. Arelly Esther Lira Lira, Doctor of Psychology, Nicaraguan Association for the Development of Psychology. Nicol A. Barria-Asenjo. Psychologist from the University of Los Lagos, Chile. She is a collaborator in the Chilean Association of Scientific Journals of Psychology. Editorial assistant at Revista Cuadernos de Neuropsicologı́a - Panamerican Journal of Neuro- psychology. She has participated and directed national calls in the field of Chilean psychology. She has various national and international publications, addressing topics from different fields, including scientific research, psychoanalysis, philosophy and politics. Jesús Ayala-Colqui. Master in Higher Education from the Scientific University of the South (Peru), Bachelor and Bachelor in Philosophy from the Universidad Nacional Mayor de San Marcos (Peru). He has been a scholarship recipient from Santander at UNAM (Mexico), from LASPAU at Harvard University (United States) and from the UAI (Chile). He has been invited as a speaker in Mexico, Brazil, Argentina, Chile, Cuba and Costa Rica. He has edited a book on Foucault (Lima, 2020) and another on Heidegger (Sao Paulo, 2022). He is a member of the Philosophy of Technology Seminar (UNAM, Mexico), the Interuniversity 36 Psychological Reports 0(0) Seminar of Ontology and Metaphysics (Mexico), the Inter-American Society of Psychology (SIP) and the Ibero-American Foucault Network. Luis Hualparuca-Olivera. Licensed psychologist, collegiate, and authorized master’s degree in Clinical and Health Psychology. With experience in clinical psychology, and practice in cognitive behavioral therapy (CBT), crisis interventions, and group management. Renacyt researcher and I collaborate with the preparation of the chapter "Cross-cultural application" of the book "ICD-11 personality disorders" with support from the WHO after an invitation for the contract with the publisher Oxford University Press. Caycho-Rodŕıguez et al. 37 Pandemic Grief and Suicidal Ideation in Latin American Countries: A Network Analysis Introduction Method Participants Instruments Sociodemographic Survey Pandemic Grief Scale (PGS) Procedure Data Analysis Results Sociodemographic Characteristics of the Participants Local and Global Network Properties Accuracy of the Network Structure and Stability of the Centrality Index Comparative Analysis of Networks by Country Discussion Limitations Conclusion and Implications Appendix List of Abbreviations Author Contributions Declaration of Conflicting Interests Funding Ethical Statement Ethical Approval Informed Consent Statement ORCID iDs Data Availability Statement References Author Biographies