Childhood Maltreatment and the Association with Life Dissatisfaction
Bibliographic record
Abstract
This study examined the association between childhood maltreatment (witnessing violence in the household, and experiences of physical and emotional abuse by an adult prior to the age of 16,) and dissatisfaction with later life. Experiences in childhood have been shown to have influences on the developing child (both on the brain and body), with adverse experiences associated with increased risks for negative life outcomes (such as mental and physical illnesses). Dissatisfaction with life has also been shown to lead to negative health outcomes; therefore, the goal of this research was to determine if childhood maltreatment could predict life satisfaction/dissatisfaction. As a secondary analysis, this study used data from more than twenty-five thousand individuals aged 15 and over who participated in the Canadian Community Health Survey-Mental Health (2012). The data were analyzed using bivariate and multivariate logistic regressions. Two regression models were developed. Model 1 utilized a cumulative count variable representing ‘Number of Types of Childhood Maltreatment Experienced’ as the exposure variable, and model 2 utilized a binary exposure variable representing ‘Ever Abused’ as the exposure variable. Life dissatisfaction was measured using the survey item, “Using a scale of 0 to 10 where 0 means ‘Very dissatisfied’ and 10 means ‘Very satisfied’, how do you feel about your life as a whole right now?”, where scores of 0 to 4 represented dissatisfaction. Compared to individuals who did not experience maltreatment in childhood, experiencing four types was significantly associated with more than twice the odds of dissatisfaction with life (AOR= 2.356; CI 1.595- 3.481), and experiencing any maltreatment in childhood increased ones odds of later life dissatisfaction by 40% (AOR= 1.424; CI 1.119- 1.813). Both models controlled for: total household income, self-perceived physical health, self-perceived mental health, and measures of emotional and social support (has people to depend on, and has close relationships). The following variables were adjusted for, but determined statistically insignificant: age, importance of religion, family mental health, and education. The findings from this study suggest childhood maltreatment predicts life satisfaction in later life, prompting further research into preventing and mitigating the effects of child maltreatment.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".