University Belonging in Autistic Postsecondary Students: The Roles of Interoception, Social Support, and Sensory Responsivity
Bibliographic record
Abstract
Background. Autistic postsecondary education (PSE) students often face significant challenges that negatively impact their belonging within their university community, an essential predictor of well-being, academic success, and persistence. Among these barriers, sensory processing differences are frequently reported but remain underexamined in research. Sensory responsivity refers to the extent to which individuals experience discomfort in response to environmental stimuli (e.g., lights, sounds, textures). Two key factors may influence how sensory challenges affect belonging: interoceptive accuracy, or one’s ability to identify and interpret internal bodily sensations (e.g., hunger, tension), and perceived social support, or the extent to which individuals feel emotionally and socially connected. Objective. This study investigates how sensory responsivity relates to Autistic students’ sense of university belonging and whether this relationship is moderated by subjective interoceptive accuracy and social support. Hypotheses. I hypothesized that university belonging would differ based on racial and gender/sexual minority status (H1); that greater sensory responsivity (i.e., more discomfort from lights, sounds, etc) would be associated with lower university belonging (H2); and that both subjective interoceptive accuracy (i.e. accurately interpreting bodily sensations) (H3) and social support (H4) would moderate this association, such that higher levels of either would buffer against the negative impact of greater sensory responsivity. As an exploratory analysis (H5), I tested a three-way interaction among sensory responsivity, interoceptive accuracy, and social support, allowing for the possibility that the moderators may also interact without assuming a specific interaction structure. Methods. A total of 93 Autistic students enrolled at Canadian PSE institutions (Alberta, Ontario, and B.C.) completed a cross-sectional survey including measures of sensory responsivity (SeSS), interoceptive accuracy (ISQ), social support, and university belonging (UES). Descriptive statistics and group comparisons were conducted using t-tests and ANOVAs. Pearson correlations were calculated to assess bivariate relationships. Moderation analyses were conducted using the PROCESS macro in R (Hayes, 2022), with Model 2 used for two-way interactions and Model 3 for exploratory three-way interactions. Results. Contrary to H1, no significant group differences in university belonging were found based on racial or gender/sexual minority status. Supporting H2, higher sensory responsivity (more sensory discomfort) was significantly associated with lower university belonging. H3 and H4 were not supported. No two-way interactions were found between interoceptive accuracy and sensory responsivity, or between social support and sensory responsivity, in relation to sense of belonging. However, the exploratory three-way interaction (H5) was significant. The negative association between higher sensory responsivity and lower university belonging was strongest among students with both high interoceptive accuracy (i.e., more accurate at interpreting bodily signals) and low social support. When social support was high, this association disappeared. Discussion. These findings extend MacLennan et al.’s (2022) model by demonstrating how internal and external factors interact to shape the experiences of Autistic individuals in specific settings like PSE. They also underscore the importance of socially supportive and sensory-inclusive environments for fostering belonging among Autistic students. Addressing sensory barriers in higher education and strengthening social support may be critical for improving equity, retention, and well-being for Autistic students.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".