Background/Objectives: Loneliness is the sensation of feeling alone or emotionally isolated, even when one is surrounded by other people. It is associated with conditions such as depression, anxiety, harmful habits, and cardiovascular problems. The main objective of the present study was to develop and determine the psychometric properties of the Multidimensional Loneliness Scale (MLS), which is a self-report instrument. Methods: The present study is instrumental in nature, as it aims to analyze the psychometric properties of a new assessment instrument. A total of 484 adults, both men and women, aged between 18 and 55 years, participated in this research. Results: Exploratory factor analysis revealed the presence of four dimensions: social disconnection, family estrangement, loss of attachment figure, and intrapersonal emptiness. Confirmatory factor analysis demonstrated that the four-dimensional model exhibited a good fit (CFI = 0.91; RMSEA = 0.07; SRMR = 0.07; AIC = 737.87). The concurrent validity was evidenced by significant correlations with the De Jong Gierveld scale and the Revised UCLA Loneliness Scale. The reliability analysis demonstrated satisfactory internal consistency, with omega coefficients ranging from 0.84 to 0.92 and alpha coefficients from 0.84 to 0.93. Conclusions: The MLS is a self-report instrument designed to assess loneliness, and it has satisfactory psychometric properties.

Introduction: Sleep quality and academic stress are relevant variables in university mental health due to their impact on well-being and academic performance. Although several studies report an association between these constructs, findings remain inconclusive across different contexts and academic disciplines. Objective: To determine the correlation between sleep quality and academic stress among law students at a private university in Trujillo, Peru, 2025. Methodology: A basic, quantitative study with a non-experimental, cross-sectional, correlational design was conducted. The sample consisted of 51 students selected through non-probability convenience sampling. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and academic stress was measured with the SISCO SV-21 Inventory. Descriptive analyses included frequencies and percentages. Normality was tested using the Kolmogorov–Smirnov test (p < .05); therefore, Spearman’s rho was applied for correlational analysis (α = .05). Results: Moderate levels of sleep quality (50.0%) and academic stress (46.4%) predominated. The overall correlation was low, positive, and not statistically significant (ρ = 0.223; p = 0.116). Significant associations were identified between sleep quality and stress symptoms (ρ = 0.296; p = 0.035), and between daytime dysfunction and overall academic stress (ρ = 0.500; p < 0.001). Conclusions: No significant overall correlation was found; however, associations emerged at the dimensional level, particularly in symptomatic and functional components.