1. INTRODUCTION

During the COVID-19 pandemic, the world's population underwent a change at social, economic, and health levels (Rahman et al., 2021; Dai et al., 2021; Valencia, 2020). During this period, some people experienced helplessness and loss of autonomy as their daily routines were altered, further aggravated by financial and mental distress due to daily information on the morbidity and mortality of the disease (Powell et al., 2021). In this context, not all people respected the rules implemented to prevent the spread of the pandemic (Roblain et al., 2022; Abrutyn, 2021; Drury, 2022). This phenomenon is known as social anomie, which could be explained by the need to satisfy needs in the social, emotional, sexual, economic, and health aspects, turning these demands into actions to evade social norms (Cueto & Viotti, 2020). Social anomie has been characterized by social destabilization, unrest, and social distrust during the pandemic. Social destabilization and unrest indicate the presence of discrepancies, inconsistencies, and the lack of laws that generate confusion and destabilization at the social level. This problem would lead to a lack of confidence in applying precautionary measures against COVID-19 (Halvaiepour & Nosratabadi, 2021). This behavior of going against imposed social norms is more common in more vulnerable populations (Lázaro-Aquino, 2021).

Failure to comply with the rules during the pandemic led to an increase in the mortality rate in the population due to constant exposure to the virus (Brenner & Bhugra, 2020; De Sousa, 2021). Brazil was one of the countries where most people did not comply with health regulations to prevent contagion, which caused this country to have the highest mortality rate in Latin America (Malamud & Núñez, 2020). Similarly, in Cuba, during the pandemic, the majority of the people rejected the imposition of regulations to prevent contagion since these prevented the daily development of activities carried out by the population, thus increasing the number of infections and, with it, an increase in the mortality rate (Hernández et al., 2022). This behavior also occurred in Chile, as the emergence of COVID-19 intensified social anomie behavior in people due to dissatisfaction and resentment against the new measures implemented by the government, expressed in violent actions, such as looting and vandalism, among other actions that brought the country to the brink of institutional danger (Guerrero & Pérez, 2020). This behavior also caused more infections and deaths (Linn et al., 2021).

Ecuador went through a similar situation because social anomie during the state of emergency generated severe social dysfunction, as the most vulnerable people, socially and economically, considered it necessary to go against the new norms to satisfy their basic needs (Padilla, 2020). These anomic behaviors also caused an increase in the mortality and contagion rate (León & Vaca, 2021). In the same context, in Bolivia, there was a continuous increase in infections and deaths because the population, due to economic necessity, was motivated to disobey the confinement measures imposed by the government to stop the spread of COVID-19, with many people joining informal jobs (Birbuet, & López, 2020; Cardona et al., 2020). In the same sense, the Argentine government prohibited routine activities due to the progressively increasing infections, resulting in the defiance of norms and laws and constant rebellious behavior by people at the individual and collective levels, causing more infections and deaths (Maisley, 2022). Peru was not immune to these social conditions, where the implementation of restrictive measures affected people economically and socially, generating progressive discontent in the vast majority and adding to the need to obtain essential resources, causing non-compliance with the new norms established by the country. All of this increased the rate of infections and deaths (Caycho, 2021).

On the other hand, women have been the most affected group during the COVID-19 pandemic, as the rates of violence against women increased, where, in many cases, the victim, due to restrictive health measures, was forced to live with her aggressor. Also, in this group, the number of unwanted pregnancies, greater psychiatric medication, and suicide attempts increased (Saletti-Cuesta & Aizenberg, 2022; Guil, 2023; Narváez & Acosta-Ramirez, 2022; Cisneros & Yautentzi, 2021). Regarding young people, this group presented higher levels of social anomie, negative affect, and frustration compared to adults. In addition, they presented greater maladaptive behaviors against social norms, such as getting involved in strikes, marches, sit-ins, or even actions considered criminal. This problem could partly be explained by perceived inequality and hopelessness (Barrera et al., 2022). On the other hand, the experience of high expectations in people can produce an anomic pathology because, by not having met these expectations, the degree of anguish and frustration in individuals is generated and intensified, being a contributing factor in the increase in the number of young people who experience higher levels of anxiety and depression (Jacobsen & Nørup, 2020).

These findings confirm that psychological, emotional, cultural, and social conditions determine people's mental state. The COVID-19 pandemic caused people to be directly affected by situations of socioeconomic deprivation and constant social confusion, altering their daily methods of living in the face of a government that does not adjust to their objectives and needs, which motivates them to have defiant behavior and rejection of the social norms established by the States (Cisneros & Yautentzi, 2021; Lantz, 1986; Lantz & Harper, 1989). In relation to this, several studies claim that social anomie is related to depression and stress (Lantz & Harper, 1990; Reinarman et al., 2000).

Consequently, stressors and their influence at a social level negatively intervene in people's mental health, contributing to the increase in anxiety and depression, in addition to suicide. Among other psychological problems, such as post-traumatic stress due to the significant impact of anomie (Larizgoitia et al., 2004; Madariaga, 2019). That is, the different ways of perceiving and developing in society are related to depression. Situations influenced by social anomie result in behaviors that go against norms and laws (Blanco & Díaz, 2006). Therefore, there has been a progressive increase in social anomie due to the needs and aspirations that people have, negatively impacting their mental health, which generates an evident deviation in behavior; this is greater for those who experience social anomie directly (Villegas, 2020).

Faced with this problem, it is important to measure social anomie adequately, and only one instrument has been found to measure this construct (Vilca et al., 2022). The Social Anomie scale (SAS-10) presents ten items that form a Bi-factor model, a model made up of two factors (behavioral and affective) and a general factor. The behavioral factor refers to the lack of compliance with norms and laws. In contrast, the affective factor refers to the degree of dissatisfaction, discomfort, or concern generated by the norms and laws implemented by the government (Halvaiepour & Nosratabadi, 2021; Roblain et al., 2022). The SAS-10 scale presented adequate initial evidence of reliability (ωH=.70) and validity based on the internal structure (χ 2=62.86; df=25; p=.000; CFI=.99; TLI=.99; WRMR=.52; RMSEA=.061 [IC90% .042-.080]) (Vilca et al., 2022). The psychometric properties of the SAS-10 scale have been studied in twelve Latin American countries, where the model that best fit in most countries was a model with two related dimensions, specifically in Peru, where the model presented adequate fit indices (χ 2=43.11; df=25; p=.014; CFI=.99; TLI=.99; SRMR=.026; RMSEA=.060 [IC90% .027-.089]) (Caycho-Rodríguez, et al., 2023).

These results show a discrepancy regarding Peru's factorial structure of the SAS-10 scale. In addition, the instrument shows some limitations, such as the lack of evidence on the factorial invariance of the scale. This evidence is crucial because it allows for more accurate interpretations of the differences found when comparing between groups (Caycho, 2017; Caycho, 2019). Also, no evidence has been shown of validity based on the relationship with other variables. This evidence would allow the comparison of the variable studied with other variables and to analyze whether the scores derived from the scale are related to other variables (Balkin, 2017).

Therefore, this research aims to study the psychometric functioning of the SAS-10 scale in a community population in Peru. In addition, it aims to evaluate the impact of social anomie on mental health indicators, such as anxiety and depression.

2. METHODS

Participants

Table 1 shows that 957 young people and adults between 18 and 30 (75.5%) and 30 to 68 (24.5%) participated in the study, of which 75.1% were women and 24.9% were men. It is also noted that most of the participants come from the coast (53.8%), live with their family of origin (60.3%) and are single (72.6%). In addition, it is observed that 38.8% only study and 29.6% study and work simultaneously. For this research, a non-probabilistic convenience sampling was used, and the following inclusion criteria were used: (a) be of legal age, (b) give informed consent, (c) be Peruvian, and (d) know how to read and write.

Table 1: Sociodemographic data of participants

Measures

Brief Scale of Social Anomie (SAS-10)

In the present study, the Brief Social Anomie Scale (SAS-10) was used to study the presence of social anomie indicators (Vilca et al., 2022). The scale comprises ten items representing two dimensions: Affective (items from 1 to 5) and Behavioral (items from 6 to 10). In addition, all items have four response categories: Strongly disagree (0), Disagree (1), Agree (2), and Strongly agree (3). The scale does not present inverse items; therefore, a higher score shows a greater presence of social anomie at a general level. Specific scores can also be obtained for each dimension since the model underlying the test is a Bi-factor model. In the original study, the scale's internal structure showed adequate fit indices (χ2=62.86; df=25; p=.000; CFI=.99; TLI=.99; CFI=.99; WRMR=.52; RMSEA=.061 [IC90% .042-.080]). In addition, it showed adequate internal consistency indices (ωH=0.70) (Vilca et al., 2022).

Mental Health Inventory-5 (MHI-5)

It was developed by Berwick et al. (1991) and adapted to Spanish by Rivera-Riquelme, Piqueras, and Cuijpers (2019). The present study's version adapted to Peru presented robust evidence of its unidimensional factor structure (χ2=24.03; df=4; p=.000; CFI=.99; TLI=.99; CFI=.99; RMSEA=.071 [IC90% .045-.099]) (Vilca, et al., 2022). The MHI-5 is made up of five items that assess the presence of psychological well-being (items 2 and 4) and psychological distress (reverse items 1, 3, and 5). In addition, the Spanish version has four response categories ranging from "never" (0) to "always" (3), where a higher score indicates better mental health status.

Data analysis

For the Confirmatory Factor Analysis (CFA), the WLSMV estimator was used since the items are at the ordinal level (Brown, 2015). The criteria used to evaluate the model fit were the following: RMSEA (< .08), SRMR (< .08), CFI (> .95), and TLI (> .95) (Kline, 2023; Schumacker & Lomax, 2004). The scale's internal consistency was evaluated through Cronbach's alpha coefficient (Cronbach, 1951) and the omega coefficient (McDonald, 1999). A value greater than .70 was considered adequate (Viladrich et al., 2017). The omega coefficient (McDonald, 1999) was used to evaluate the internal consistency of the scale, where a value greater than .70 is adequate (Viladrich et al., 2017). The H coefficient was also used since it allows us to evaluate how well a latent variable is represented by a set of items (Hancock & Mueller, 2001). Likewise, the hierarchical omega coefficient was also used (Zinbarg et al., 2005). To evaluate the strength of the general factor in the Bi-factor models, the Explained Common Variance was reported (Sijtsma, 2009).

The factorial invariance of the scale according to the age of the participants was evaluated through a sequence of hierarchical variance models: configural invariance, metric invariance, scalar invariance, and strict invariance. The chi-square difference (Δχ2) was used to compare the differences in the sequence of models, where non-significant values (p>.05) suggested invariance between the groups. The differences in the RMSEA (ΔRMSEA) and CFI (ΔCFI) were also taken into account, where differences less than <.015 and <.10, respectively, show the invariance of the model (Chen, 2007).

An SEM model assessed the scale's validity for other variables. In this model, it was hypothesized that the dimensions of mental health are related to the dimensions of social anomie. The WLSMV estimator was used to estimate the model, and the same adjustment indicators used in the CFA were considered. All statistical analyses were performed using the "lavaan" package (Rosseel, 2012) for the CFA and SEM and the "semTools" package (Jorgensen et al., 2018) to perform factorial invariance.

Procedure

The study was approved by the ethics committee of the Faculty of Health Sciences. In addition, the study followed the Helsinki standards (World Medical Association, 2013). A non-probabilistic snowball sampling was used for data collection since it was the most appropriate method to access the participants. A virtual form prepared on the Google Forms platform was used, and it was shared through social networks such as Facebook, WhatsApp, Messenger, and Instagram. In the first phase of the form, the research objectives and informed consent were shown; only people who voluntarily agreed to participate in the study accessed the next section of the form. The second section presented the questions referring to sociodemographic data. Finally, in the third section, the questions of the scales used in the study were shown. It is important to note that people completed the form within five to ten minutes.

3. RESULTS

Descriptive análisis

Table 2 shows the descriptive data for the social anomie scale (SAS-10). The mean score for item 4 was 3.07, the highest score, and the mean score for item 3 was 1.78, the lowest score. Regarding asymmetry and kurtosis, adequate results were found for all items, falling within the range of +/-1.5.

Table 2: Descriptive statistics of the scale items

Note. M = Median; SD = Standard deviation; g1 = Asymmetry; g2 = Kurtosis; TD=Totally disagree; D=Disagree; A=Agree; TA=Totally agree

Validity based on internal structure

The study found that the Bi-factor model with two specific factors presents adequate fit indices (χ2 = 126.38; df = 25; p < .01; RMSEA = .065 [IC90% .054 – .077]; SRMR = .029; CFI=.99; TLI=.98). However, a complementary analysis of the Bi-factor model's performance shows that the general factor presents a low ECV (.58), evidencing that the general factor only manages to explain 58% of the variance of the items. Regarding the specific ECV, factor 1 (.29) and factor 2 (.13) manage to explain 29% and 13% of the common variance, respectively. It was also evident that most of the items are not strongly influenced by the general factor (I-ECV < .50). The PUC was equal to .56, which suggests that the general factor explains 56% of the correlations and 44% are contaminated by multidimensionality. The ARPB is equal to .31, indicating that the factor loadings of the bifactor model and the factor loadings of a unidimensional model differ by 31%. The H coefficient is equal to .89, which shows stability in other studies, while the Hs of factor 1 (affect) was greater than .70. This result shows problems in the functioning of the proposed Bi-factor model.

Given these results, other plausible models, such as the two-dimensional model, were studied. The study found that this model presents adequate data fit indices (χ2 = 207.86; df = 34; p < .01; RMSEA = .073 [IC90% .064 – .083]; SRMR = .045; CFI=.98; TLI=.98). Furthermore, it can be seen in Figure 1 that all items have high factorial weights in the factor to which they belong. Both factors are significantly related (.52). Although the Bi-factor model shows slightly higher fit indices than the two-dimensional model, it also has performance problems. Therefore, for the following statistical analyses, the two-dimensional model was chosen.

Factorial invariance according to sex and age

Table 3 shows that the factorial structure of the scale has shown evidence of being strictly invariant between men and women in the sequence of invariance models proposed: metric invariance (ΔCFI = .010; ΔRMSEA = .009), scalar (ΔCFI = .000; ΔRMSEA = -.002) and strict invariance (ΔCFI = .001; ΔRMSEA = .003). Similarly, the scale has shown evidence of measurement invariance across adults aged 18 to 30 and 31 to 68 years: (ΔCFI = -.006; ΔRMSEA = .000), scalar (ΔCFI = -.002; ΔRMSEA = -.001), and strict invariance (ΔCFI = .001; ΔRMSEA = -.003).

Table 3: Invariance indices according to sex and age of participants

Nota: χ2 = Chi square; df = degrees of freedom; SRMR: Standardized Root Mean Square Residual; TLI = Tucker-Lewis Index; CFI = Comparative Fit Index; RMSEA = Root Mean Square Error of Approximation; Δχ2 = Differences in Chi square; Δdf = Differences in degrees of freedom; ΔCFI = Change in Comparative Fix Index; ΔRMSEA = Change in Root Mean Square Error of Approximation

Scale reliability

In the present study, it was shown that both dimensions of the scale present adequate reliability indices in the total sample of participants: Affect (ω = .78) and Behavior (ω = .85). Similarly, the affect dimension showed adequate levels of internal consistency in the specific groups of men (ω = .78), women (ω = .78), 18 to 30 years (ω = .77) and 31 to 68 years (ω = .81). The behavioral dimension also presented adequate internal consistency indices in the specific groups of men (ω = .88), women (ω = .84), 18 to 30 years (ω = .85) and 31 to 68 years (ω = .88).

Explanatory odelo f social anomie

Based on the literature review, an SEM model was proposed to assess the relationship between mental health and social anomie. This study found that the structural model presented adequate fit indices (χ2 = 274.78; df = 84; p = .000; RMSEA = .049 [IC90% .042 – .055]; SRMR = .038; CFI=.98; TLI=.98). In addition, the measurement models are adequately represented by their items since they have high factor weights. It can be observed in Figure 2 that the psychological well-being dimension is not related to the effect (-.06; p > .05) and conduct (-.08; p > .05) dimensions of social anomie. Also, it can be seen that psychological distress does have a significant impact on the affect (.15; p < .05) and conduct (.14; p < .05) dimensions of social anomie.

Figure 2. Predictive model of social anomie

Declarations

Authors' contributions:

RDG, LWV, and TC-R provided initial conception, organization, and main writing of the text. LWV prepared all figures and tables. RDG and LWV were involved in data collection and acted as consultants and contributors to research design, data analysis, and text writing, read and approved the draft.

Conflicts of interest

The author(s) declare(s) that there is no conflict of interest with respect to the research, authorship, and/or publication of this article.

Funding details

The author(s) did not receive financial support for the research, authorship, and/or publication of this article.

Acknowledgments:

Not aplicable

Data availability statement

The database can be freely accessed in the following repository:
https://doi.org/10.17605/OSF.IO/F6RGV

Ethics approval

The study was approved by the ethics committee of the Faculty of Health Sciences of the Peruvian Union University (2022-CE-FCS - UPeU-112). In addition, the study followed the Helsinki standards (World Medical Association, 2013). In addition, informed consent was obtained from all participants.

ORCID iDs

Ricardo D. Gonzales    http://orcid.org/0000-0001-6278-5761
Lindsey W. Vilca    https://orcid.org/0000-0002-8537-9149
Tomás Caycho-Rodríguez    https://orcid.org/0000-0002-5349-7570

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• Este artículo es de acceso abierto distribuido bajo los términos y condiciones de la Licencia Creative Commons Attribution (CC BY) (https://creativecommons.org/licenses/by/4.0/)
• Cómo citar: Gonzales RD, Vilca LW, Caycho-Rodríguez T. “New evidence on the psychometric performance of the Brief Social Anomie Scale (SAS-10) in post-pandemic Peruvian adults”, Avances en Psicometría Iberoamericana (API), vol. 1, Diciembre 2025 https://doi.org/10.26495/rtjrxe46