PARENT REPORTS OF THE PREVALENCE OF ADVERSE CHILDHOOD EXPERIENCES AMONG CHILDREN AND TEENS IN THE CAPE COAST METROPOLIS, GHANA
Bibliographic record
Abstract
Adverse childhood experiences (ACEs) — potentially traumatizing events that occur in childhood — have been linked to serious health problems later in life. Despite the documented negative effects of ACEs, and the high prevalence of ACEs in lower-middle-income countries, research about ACE prevalence is sparse for locales in Sub-Saharan Africa. This descriptive study examined the prevalence of ACEs among 800 children and teens in the Cape Coast Metropolis, Ghana, as reported by their parents (or caregivers), who were recruited from February to April 2021. Parent-reported sociodemographic characteristics and ACEs experienced by the children and teens were collected with the Center for Youth Wellness ACE Questionnaire (CYW ACE-Q). Analysis of the parents’ reports indicated that about 84.9% of the children and teens had been exposed to at least one ACE, 69.1% had experienced two or more ACEs, and 51.8% had experienced three or more ACEs. The most prevalent ACEs, according to the parents, were community violence (50.2%), separated parents (34.0%), physical abuse (33.4%), and emotional abuse (28.9%). This study thus reveals a high prevalence of ACEs in the Cape Coast Metropolis of Ghana, suggesting the need for policies and actions aimed at reducing community violence and protecting children from abuse in the Metropolis.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".