Cognitive Correlates of Resilience in Adults Experiencing Homelessness
Bibliographic record
Abstract
OBJECTIVE: In adults who have experienced homelessness, greater psychological resilience is related to better quality of life, community functioning, and social cognition. Domain-specific cognitive functioning is positively associated with resilience in housed populations; however, these relationships have yet to be explored among adults experiencing homelessness. The aim of this study is to examine the relationships between domain-specific cognitive function and psychological resilience among adults experiencing homelessness. METHOD: One hundred and six adults who have experienced homelessness were recruited in Toronto, Canada, and 88 were included in analyses (51% female, mean age = 43 years). Study measures assessed psychological resilience as well as domain-specific cognition (vocabulary, oral reading, processing speed, episodic memory, and executive functioning) using the NIH Toolbox Cognition Battery. Additional covariates of interest included psychological distress, social network size, substance misuse, and major psychiatric disorders. Hierarchical regression modeling explored the contributions of each cognitive domain to resilience while accounting for established covariates. RESULTS: Oral reading was positively associated with higher resilience, explaining 12.45% of the variance in resilience while controlling for age, education, gender, substance misuse, psychological distress, and social network size. Performance on measures of executive functioning, processing speed, and visual memory were not found to be related to self-reported resilience. CONCLUSION: The results suggest that verbal vocabulary, shaped by the accumulation of experiences across one's lifetime, may be an important contributor to psychological resilience. Better crystallized abilities may reflect more enriched early life experiences that are critical to better coping skills and well-being of adults experiencing homelessness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".