PloS one · 2025
University service utilization patterns in students with specific learning disabilities: An institutional cross-sectional study.
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Asdaq Syed Mohammed Basheeruddin, Alharbi Mamdouh Saleh, Alansari Mohanad Abdullah, Alshuqayr Saleh, Alanazi Malek Fares, Alshahrani Saleh Rajih, Nayeem Naira, Alsanie Walaa F, Alamri Abdulhakeem S, Alhomrani Majid, Alshammary Amal F, Gilkaramenthi Rafiulla
Аннотация
BACKGROUND/OBJECTIVES: This study examined the relationship between university students' use of common and specific services and the presence of specific learning disabilities (SLDs). The objective was to identify how sociodemographic factors, health status, and learning disabilities impact service utilization, with a focus on improving accessibility and support for students with SLDs.
METHODS: Employing random but voluntary sampling, a cross-sectional survey of university students was conducted using a tool demonstrating good internal reliability (Cronbach's α = 0.859). The survey collected data on sociodemographics, health status, and self-reported specific learning disabilities (SLDs). Participants assessed their utilization of common university services (e.g., library, academic advising, LMS) and specific support services (e.g., one-to-one meetings, electronic books, dispensatory measures, compensatory tools). Data analysis included frequency distributions, Chi-square tests, Binary Logistic Regression, and Pearson correlation to examine associations between SLDs and service utilization patterns.
RESULTS: Participants (n = 302) were predominantly male (59.9%) and aged 18-25 years (89.7%), with high rates of dysgraphia (42.7%), dyscalculia (43%), and auditory processing disorder (23.8%). Regression analyses revealed: Frequent use of common services was significantly associated with visual perceptual/motor deficits (aOR=3.87, 95% CI = 1.82-8.21, P < .001), advanced academic year (aOR=1.29, 95% CI = 1.09-1.53, P = 0.004), and positive educational self-perception (aOR=2.32, 95% CI = 1.12-4.80, P = 0.024). For specific services, key predictors included female gender (aOR=2.07, 95% CI = 1.15-3.73, P = 0.015), dyslexia (aOR=2.73, 95% CI = 1.07-6.98, P = 0.036), auditory processing disorder (aOR=2.52, 95% CI = 1.17-5.41, P = 0.018), while sleep disturbances reduced utilization (aOR=0.46, 95% CI = 0.27-0.79, P = 0.005).
CONCLUSION: This study reveals significant underutilization of university services among students with specific learning disabilities (SLDs), despite high prevalence rates. Engagement patterns were strongly influenced by SLD type, academic progression, self-perception, gender, and health factors. To address these barriers, we recommend targeted interventions including: 1) disability-awareness campaigns to reduce stigma, 2) tailored accommodation (e.g., extended time, multimodal materials) aligned with specific SLD profiles, and 3) mandatory faculty training on inclusive instructional strategies and available support resources. These evidence-based measures are critical for improving accessibility and academic success for this vulnerable population.
METHODS: Employing random but voluntary sampling, a cross-sectional survey of university students was conducted using a tool demonstrating good internal reliability (Cronbach's α = 0.859). The survey collected data on sociodemographics, health status, and self-reported specific learning disabilities (SLDs). Participants assessed their utilization of common university services (e.g., library, academic advising, LMS) and specific support services (e.g., one-to-one meetings, electronic books, dispensatory measures, compensatory tools). Data analysis included frequency distributions, Chi-square tests, Binary Logistic Regression, and Pearson correlation to examine associations between SLDs and service utilization patterns.
RESULTS: Participants (n = 302) were predominantly male (59.9%) and aged 18-25 years (89.7%), with high rates of dysgraphia (42.7%), dyscalculia (43%), and auditory processing disorder (23.8%). Regression analyses revealed: Frequent use of common services was significantly associated with visual perceptual/motor deficits (aOR=3.87, 95% CI = 1.82-8.21, P < .001), advanced academic year (aOR=1.29, 95% CI = 1.09-1.53, P = 0.004), and positive educational self-perception (aOR=2.32, 95% CI = 1.12-4.80, P = 0.024). For specific services, key predictors included female gender (aOR=2.07, 95% CI = 1.15-3.73, P = 0.015), dyslexia (aOR=2.73, 95% CI = 1.07-6.98, P = 0.036), auditory processing disorder (aOR=2.52, 95% CI = 1.17-5.41, P = 0.018), while sleep disturbances reduced utilization (aOR=0.46, 95% CI = 0.27-0.79, P = 0.005).
CONCLUSION: This study reveals significant underutilization of university services among students with specific learning disabilities (SLDs), despite high prevalence rates. Engagement patterns were strongly influenced by SLD type, academic progression, self-perception, gender, and health factors. To address these barriers, we recommend targeted interventions including: 1) disability-awareness campaigns to reduce stigma, 2) tailored accommodation (e.g., extended time, multimodal materials) aligned with specific SLD profiles, and 3) mandatory faculty training on inclusive instructional strategies and available support resources. These evidence-based measures are critical for improving accessibility and academic success for this vulnerable population.