Psychometric Validation of the MOS Social Support Survey (MOS-10) in Newly Diagnosed Patients with Lung Cancer in Mexico

Introduction: Patients newly diagnosed with lung cancer experience a high symptom burden associated with the disease and are frequently diagnosed at advanced stages. Social support is an important resource for coping with the demands associated with the disease and its treatment. In this context, the Medical Outcomes Study Social Support Survey (MOS-SSS) is one of the most widely used instruments for assessing perceived social support. Aim: To examine the factorial structure, internal consistency, and measurement invariance of a 10-item brief version of the MOS Social Support Survey (MOS-10) in a Mexican sample of patients newly diagnosed with lung cancer. Methods: A non-experimental instrumental study was conducted using non-probability convenience sampling. The sample comprised 200 patients newly diagnosed with lung cancer. An exploratory factor analysis (EFA) was performed, followed by a confirmatory factor analysis (CFA) in the same sample. A sensitivity analysis using diagonally weighted least squares (DWLS) based on a polychoric correlation matrix was also conducted. Measurement invariance across sex and age groups was examined, and internal consistency was estimated using Cronbach’s alpha and McDonald’s omega. Results: The EFA identified a two-factor structure, Emotional/Informational/Affective Support and Tangible Support, which explained 69.55% of the variance. After CFA re-specification, a 10-item solution with satisfactory fit indices was obtained. The DWLS sensitivity analysis showed an overall factorial pattern consistent with that obtained using maximum likelihood estimation, although its fit indices should be interpreted cautiously given the estimation procedure used. Internal consistency was high for the total score (α = 0.92; ω = 0.93) and adequate for both dimensions. Evidence supported configural, metric, and scalar invariance across sex, whereas configural invariance was supported across age groups but full metric invariance was not established. Conclusion: The MOS-10 showed satisfactory evidence of factorial validity and internal consistency in this sample of Mexican patients newly diagnosed with lung cancer. However, the factorial structure should be cross-validated in an independent sample, and further studies are needed to examine temporal stability, convergent, discriminant, and criterion-related validity, responsiveness, and clinically meaningful score interpretation.

Authors

Institutions

Publication Details

Journal
Psicooncología
Published
2026-10-26
DOI
https://doi.org/10.5209/psic.110069
Primary Topic
Psychometric Methodologies and Testing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Psychometric Validation of the MOS Social Support Survey (MOS-10) in Newly Diagnosed Patients with Lung Cancer in Mexico

Joel Flores Juárez, O Arrieta, Óscar Galindo-Vázquez, Luis Antonio Cabrera-Miranda et al.
Psicooncología
Psychometric Methodologies and Testing
article

Psychometric Validation of the MOS Social Support Survey (MOS-10) in Newly Diagnosed Patients with Lung Cancer in Mexico

Joel Flores Juárez, O Arrieta, Óscar Galindo-Vázquez, Luis Antonio Cabrera-Miranda, María de los Ángeles Amaya-Hernández, J. Richard Alcantar-Correa, MA. Guadalupe Téllez-Jaramillo, Pamela Gómez-García
article en

Abstract

Introduction: Patients newly diagnosed with lung cancer experience a high symptom burden associated with the disease and are frequently diagnosed at advanced stages. Social support is an important resource for coping with the demands associated with the disease and its treatment. In this context, the Medical Outcomes Study Social Support Survey (MOS-SSS) is one of the most widely used instruments for assessing perceived social support. Aim: To examine the factorial structure, internal consistency, and measurement invariance of a 10-item brief version of the MOS Social Support Survey (MOS-10) in a Mexican sample of patients newly diagnosed with lung cancer. Methods: A non-experimental instrumental study was conducted using non-probability convenience sampling. The sample comprised 200 patients newly diagnosed with lung cancer. An exploratory factor analysis (EFA) was performed, followed by a confirmatory factor analysis (CFA) in the same sample. A sensitivity analysis using diagonally weighted least squares (DWLS) based on a polychoric correlation matrix was also conducted. Measurement invariance across sex and age groups was examined, and internal consistency was estimated using Cronbach’s alpha and McDonald’s omega. Results: The EFA identified a two-factor structure, Emotional/Informational/Affective Support and Tangible Support, which explained 69.55% of the variance. After CFA re-specification, a 10-item solution with satisfactory fit indices was obtained. The DWLS sensitivity analysis showed an overall factorial pattern consistent with that obtained using maximum likelihood estimation, although its fit indices should be interpreted cautiously given the estimation procedure used. Internal consistency was high for the total score (α = 0.92; ω = 0.93) and adequate for both dimensions. Evidence supported configural, metric, and scalar invariance across sex, whereas configural invariance was supported across age groups but full metric invariance was not established. Conclusion: The MOS-10 showed satisfactory evidence of factorial validity and internal consistency in this sample of Mexican patients newly diagnosed with lung cancer. However, the factorial structure should be cross-validated in an independent sample, and further studies are needed to examine temporal stability, convergent, discriminant, and criterion-related validity, responsiveness, and clinically meaningful score interpretation.

PsicooncologíaVol. 23(2)
Instituto Nacional de Cancerología (CO), Instituto Nacional de Cancerología (MX)
Openalex Percentile: Top 9%
Psychometric Methodologies and Testing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon