Positive Childhood Experiences and Socio-Economic Association
Bibliographic record
Abstract
Positive Childhood Experiences are protective social determinants of health factors that mitigate downstream consequences of exposure to chronic adversity and abuse specific to Adverse Childhood Experiences (ACEs). ACEs are defined by the CDC as potentially traumatic experiences during childhood that increase mal-adaptive and risky behaviors, negative health outcomes, and relative health care utilization throughout the lifecycle. This study examines the association between PCE scores and important socio-economic measures. A cross-sectional study using the 2021 Tennessee Behavioral Risk Factor Surveillance Survey PCE module was conducted. The PCE’s module included 7 questions to assess PCE’s during childhood. The 7 PCE questions were consolidated into a measure categorized by low: 0-1 PCE, middle: 2-4 PCEs, and high: 5-7 PCEs. The association between PCE’s and three independent variables of interest were examined: income, employment status, and education. Income was defined by household income and categorized into high ($100,000+) middle ($50,000-$99,000), and low income ($0-$49,000). Education was categorized into high (graduated college or technical school), middle (graduated high school/attended college or technical school), and low education levels (did not graduate high school). Employment status was dichotomized into employed vs unemployed. Chi-square test of independence was used to investigate associations between PCE’s scores and the 3 socio-economic variables, income, employment status, and education, independently. There was a significant association between PCE score and income (P=.001). Over a quarter of individuals with a high PCE score (27%) were in the lowest income category, while 53% were in the highest income category. Of the individuals with a low PCE score 49% were in the lowest income category while 31% were in the highest income category. For individuals with a middle PCE score, 39% were in the lowest income category, while 42% were in the highest income category. The association between PCE score and education level was also significant (P=.001). Of individuals with a low PCE score 61% were employed, those with a middle PCE score 74% were employed, and of samples with a high PCE score 88% were employed. Analysis of PCE score and employment status was also significant (P=.001). Of the individuals with a low PCE score 21% were in the highest education category, of individuals with a middle PCE score 31% were in the highest education category, and of individuals with a high PCE score 41% were in the highest education category. Evidence continues to mount that PCE’s are associated with improved mental health, better social skills, and overall self-reported quality of life on an individual and population level. The findings of this study suggest that positive childhood experiences impact individuals’ ability to overcome adversity if income, education, and employment levels are accepted as proxy measure for quality of life and highlight the importance of fostering positive environments for children to prevent long term negative health, social, and economic impacts. Future research could further explore the mechanisms through which positive childhood experiences lead to positive outcomes, and the implications for interventions aimed at promoting positive childhood experiences across socio-demographic categories.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".