Confirmatory Factor Analysis. CFA was performed to analyze whether the scales’ factorial structure could be retrieved in a Peruvian sample. The three-factor model showed a good fit of the data, with SB-χ² (87) = 184.22, CFI = 0.99, RMSEA = 0.05, 90% CI [0.04, 0.06].

The standardized factor loadings were, except only one item, above the conventional threshold, according to which a standardized loading greater than 0.50 is considered very significant (see Table 1).

Regarding factor correlations, inter-correlations were significant and high between the factors family and friends (r = 0.61; t = 5.57; p < 0.001) and family and others (r = 0.75; t = 7.55; p < 0.001); and moderate between others and friends (´r = 0.48; t = 5.20; p < 0.001).

Table 1 Table 1 SS-A Primary Factor Loadings, Internal Consistency, Means and Standard Deviations for Three-factor model

MultiGroup Confirmatory Factor Analysis. To test whether the factor structure is comparable for female and male students, an MGCFA was conducted for the three-factor model.

The fit of the configural model was acceptable SB-χ² (174) = 272.82, CFI = 0.98, RMSEA = 0.05. In Step 2, the factor loadings (Λ) were constrained to be equal groups. This level of invariance was nested within the previous model (configural). The fit of this model was also acceptable SB-χ² (189) = 291.72, CFI = 0.98, RMSEA = 0.05. There is a tendency to look at the difference between CFI values, suggesting that difference values should not exceed .01. Relying on this criterion, factor loadings between girls’ and boys’ sample were considered invariant. Further, in step 3, the fit of the scalar model (intercepts constrained to be equal across groups) was again acceptable SB-χ² (192) = 294.23, CFI = 0.98, RMSEA = 0.05. Finally, in step 4 error invariance was constrained to be equal across groups with an acceptable fit SB-χ² (207) = 305.61, CFI = 0.98, RMSEA = 0.05. The Social Support Appraisals Scale therefore shows factorial invariance across females and males, which can be seen in table 2.

Table 2 Table 2 Measurement invariance across gender Note.

Δ=LMetric Invariance Model; ∆Φ= Scalar Invariance Model; ΔΦΘ_δ = Invariance of Measurement Errors Model; RMSEA = Root Mean Square Error of Approximation; ΔRMSEA= difference in Root Mean Square Error of Approximation between nested models; CFI = Comparative Fit Index; ΔCFI = Difference in index between nested models.

Reliability.Table 1 shows Jöreskog’s Rho’s (ρ). All sub-scales present acceptable internal consistency above .50, ranging from .72 (others) to 0.85 (friends). Nevertheless, if removing item FAM6 from family sub-scale, reliability improves (ρ= 0.92).

Social Support- Academic Stress. The scale Coping was significantly associated with Family (r = 0.21), friends (r = 0.22) and others (r = 0.23). Furthermore, Symptoms showed a negative correlation with the three social support subscales. Likewise, the Stressors scale was negatively associated to Friends (r = -0.15) and Others (r = -0.14). Finally, the Stressors scale did not show significant associations to the Family subscale.

Social Support Appraisals Scale is an instrument that provides valuable information about each person’s help he or she believes in receiving. Its efficiency has been proven in diverse cultures: Mexican (Nava et al., 2015) and Brazilian (Leme, 2013). These examples of Latin-American context showed evidence of the multidimensionality of its structure.

Our goal was to test some psychometric properties in a Peruvian sample. To fulfill this aim, we first evaluated the factorial structure of the scale. Secondly, we tested the Measurement Invariance (MI) across gender. After that, we inspected the reliability of the subscales, and finally, we performed associations with one related variable (academic stress).

Concerning the factor structure, we were able to verify the scale’s dimensionality, which is shown as an appropriate instrument, and the three-factor model based on literature (Vaux et al., 1986) could be confirmed in the Peruvian sample and replicated in diverse cultures. Multi-group Confirmatory Factor Analysis confirmed the latent structure’s invariance across gender and the robustness of the 3-factor structure. Measurement invariances (MI) evaluated in this study involved examining a set of increasingly restrictive models: the configural invariance model, the metric invariance model, the scalar invariance model and the error variance invariance model. As pointed out before, MI has not been addressed in previous attempts to measure social support appraisals (SS-A), and it is important as it proves that the SS-A scores are unaffected by gender bias.

Some studies claim to have found gender differences (Soman et al., 2016), yet without analyzing gender measurement invariance, one cannot be certain of such results’ the validity.

All three sub-scales Family, Friends, and Others had reliability above the specialized psychometric literature’s cutoff. These results are similar to what is reported in several studies with the SS-A (Cárdenas-Castro et al., 2015; Squassoni & Matsukura, 2014).

The instrument also showed significant positive correlations with the subscale Coping of the Academic Stress Scale (Wenli et al., 2016), hence the higher the perceived social support of a student, the greater coping strategies he/she might use (Perera & Digiacomo, 2015). A negative association with the subscale Symptoms and Stressors was found, meaning that perceived social support and academic stress of college students are inversely proportional (Glozah & Pevalin, 2014).

Results confirmed the hypothesized relationships between perceived social support and academic stress (Khan et al., 2016). Academic stress can lead to a deficient performance in the university, in which students frequently experience a lack of concentration, having an impact on their productivity (Essel & Owusu, 2017). Nonetheless, the social support’s protective role can encourage student motivation and commitment to learning activities (Dupont et al., 2015).

Perceived family support has been shown to improve student interest and academic achievement (Mattanah et al., 2011). Likewise, when students perceive the support of friends, they are stimulated, not only at the cognitive but also at the emotional aspect (Friedlander et al., 2007). One can conclude that perceived social support is crucial for preventing or reducing academic shortcomings.

Notwithstanding, some limitations have to be addressed. First, in this study, we used a non-random sample; consequently, this group only represents a population sector, with specific characteristics: university students from private institutions. Therefore, it is recommendable for future studies, expanding the research, and carrying out studies with different samples, involving public institutions and other Peru regions to have a more representative sample at a macro level. Second, related to the nature of the data (cross-sectional). Collecting information at a single point in time can be disadvantageous due to susceptibility to errors (biases and confounding factors). For future research, we suggest longitudinal studies that can establish causal relationships between variables and thus provide more reliable inferences. Finally, although we have used an alternative measure of reliability (ρ) that seems adequate to the data features than Cronbach’s alpha (Sijtsma, 2009), test-retest reliability could have given more stability across time.

To summarize, the present study results provide empirical support for the factorial structure of the Social Support Appraisals Scale. In this sense, the SS-A can be seen as a trustworthy measure for assessing social support in this particular sample and can be used for meaningful comparisons across gender. It can also be considered to assess the relationship between stressful events in the school setting and social support in education at home, guided by technology and social isolation. Results bode well for this tool’s utility and its applicability to diverse groups, contexts, and regions in Latin America.