Adverse childhood experiences (ACEs), resilience, and outcomes in older adulthood: A scoping review
Bibliographic record
Abstract
BACKGROUND: Previous research has demonstrated a dose-response relationship between exposure to adverse childhood experiences (ACEs) and adverse outcomes in adulthood. Despite widely known associations, previous reviews have primarily focused on outcomes in younger and middle-aged adults exposed to ACEs to the exclusion of older adults and do not consider the potential role of resilience for understanding outcomes in older adulthood. OBJECTIVE: The present scoping review aimed to examine the extent and nature of existing literature on the influence of ACEs and resilience on the cognitive, physical, mental, and social health outcomes among older adults. METHODS: We conducted a search of five electronic databases (CINAHL, MEDLINE, PsycINFO, AgeLine, Scopus) using the following keywords: adversity, resilience, aging, and older adults. We limited our inclusion criteria to works published in English or French after 1998 as Felitti et al. published the first study describing ACEs in this year. RESULTS: Of the 4926 studies screened, 27 studies met the inclusion criteria. Overall, results from the included studies indicated that exposure to adversity during childhood was associated with worse outcomes in older adulthood. Additionally, we found that resilience and resiliency-related factors (e.g., problem-focused coping strategies) mitigated or reduced harms associated with ACEs to improve outcomes in older adulthood. CONCLUSIONS: Exposure to ACEs is associated with reduced functioning in later adulthood. Findings from this review indicate a need for further exploration into the role of ACEs, and the potential effects of resilience, on health outcomes in older adults to develop better individual- and population-level interventions for this group.
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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".