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Loneliness and depression are the most prevalent mental health issues among older adults, and their relationship has been documented in studies using reflective psychopathological models based on the total scores. However, mental health problems should be investigated at the level of individual symptoms in order to develop intervention strategies aimed at mitigating the adverse impact of both variables. The goal was to examine the extent to which symptoms of loneliness relate to symptoms of depression in elderly Peruvians using the network method in 328 Peruvian adults with an average age of 68.44 years (SD = 7.64). The participants were selected through non-probability convenience sampling, which may limit the generalizability of the results. The Patient Health Questionnaire-2 (PHQ-2) and three-item UCLA Loneliness Scale were used in this study. Network analysis was used to identify central and bridging symptoms within the network of loneliness and depressive symptoms. Furthermore, the invariance in symptom networks between men and women was estimated. The results indicated that 'feeling excluded' was the most central symptom. Furthermore, the symptoms 'feeling excluded' and 'anhedonia' have the strongest relationship and can be considered as bridge symptoms between loneliness and depressive disorders. Symptom networks were invariant between men and women ( M  = .26; p  = .42; S = .09; p  = .38). In conclusion, the network structure provides valuable insights into the relationship between the symptoms of loneliness and depression in older Peruvian adults. The results suggest that the symptoms 'feeling excluded' and 'anhedonia' could serve as potential targets for psychological interventions aimed at efficiently reducing loneliness and depression.

Background: A meta-analysis of randomized controlled trials has suggested a bidirectional relationship between sleep problems and mental health issues. Despite these findings, there is limited conclusive evidence on the relationship between sleep quality, depression, anxiety, and burnout., Objective: The current study aimed to evaluate the relationships between sleep quality symptoms, anxiety, depression, and burnout in samples of adult individuals from two Latin American countries, Peru and El Salvador, through network analysis and to identify key symptoms that reinforce the correlation and intensify the syndromes., Methods: A total of 1012 individuals from El Salvador and Peru participated, with an average age of 26.5 years (SD = 9.1). Symptom networks were constructed for both countries based on data from the Jenkins Sleep Scale, Patient Health Questionnaire-2, General Anxiety Disorder-2, and a single burnout item., Results: The results indicated that Depressed Mood, Difficulty Falling Asleep, and Nervousness were the most central symptoms in a network in the participating countries. The strongest conditional associations were found between symptoms belonging to the same construct, which were similar in both countries. Thus, there is a relationship between Nervousness and Uncontrollable Worry, Anhedonia and Depressed Mood, and Nighttime Awakenings and Difficulty in Staying Asleep. It was observed that burnout is a bridge symptom between both countries and presents stronger conditional associations with Tiredness on Awakening, Depressed Mood, and Uncontrollable Worry. Other bridge symptoms include a Depressed Mood and Nervousness. The network structure did not differ between the participants from Peru and El Salvador., Conclusion: The networks formed by sleep quality, anxiety, depression, and burnout symptoms play a prominent role in the comorbidity of mental health problems among the general populations of Peru and El Salvador. The symptom-based analytical approach highlights the different diagnostic weights of these symptoms. Treatments or interventions should focus on identifying central and bridge symptoms., (© 2024. The Author(s).)

Introduction: Depression is a frequent psychological problem in the general population. There are no single conclusive causes for its development; on the contrary, it arises from the interaction of other emotional disorders. Determining risk factors is a primary objective to identify vulnerable individuals and optimize prevention., Objective: To analyze risk factors of the depression through network analysis in Peruvian adults from the general population., Methods: Cross-sectional study with a quantitative approach. A total of 567 Peruvian adults who answered several instruments assessing depressive symptoms, insomnia, suicidal ideation and anxiety participated. An undirected network model with all psychological variables and a predictive path diagram was estimated to identify risk factors for depression. Measures of centrality, precision and stability were also analyzed., Results: The network structure showed that depression, insomnia, suicidal ideation, and anxiety were mutually associated. In terms of expected influence and predictability, depression obtained the highest value, followed by anxiety. In the prediction plot, all psychological variables were directly connected with depression, with anxiety having the highest connection. The tests of accuracy and stability (CS = 0,75), were robust., Conclusions: The results of the study suggest that problems with insomnia, suicidal ideation, and anxiety, are considerable risk factors for depression. Identifying and intervening early on those risk factors in adults in the general population could help to prevent the development of depressive symptoms., Competing Interests: Declaration of competing interest The author has no conflicts of interest to declare., (Copyright © 2024. Published by Elsevier España, S.L.U.)

This study aimed to evaluate the psychometric properties of the Grief Impairment Scale (GIS) using a network psychometric model. A total of 1048 individuals from Peru and El Salvador participated. A network psychometric model was used to determine internal structure, reliability, and cross-country invariance. The results indicate that the GIS items were grouped into a single network structure through Exploratory Graph Analysis. Reliability was estimated by structural consistency, and it was found that when replicating the network structure within an empirical dimension, a single network structure was consistently obtained, and all items remained stable. Furthermore, the network structure was invariant, thus functioning similarly across the different country groups. In conclusion, the GIS presented solid psychometric evidence of validity based on its internal structure, reliability, and cross-country invariance. Therefore, the GIS is a psychometrically sound measure of functional impairment symptoms due to grief for Peruvian and Salvadoran individuals., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.