Associations Between Personality Traits and Energy Balance Behaviors in Emerging Adulthood: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Internalizing and externalizing personality traits are robust risk factors for substance use and mental health, and personality-targeted interventions are effective in preventing substance use and mental health problems in youth. However, there is limited evidence for how personality relates to other lifestyle risk factors, such as energy balance-related behaviors, and how this might inform prevention efforts. OBJECTIVE: This study aimed to examine concurrent cross-sectional associations between personality traits (ie, hopelessness, anxiety sensitivity, impulsivity, and sensation seeking) and sleep, diet, physical activity (PA), and sedentary behaviors (SB), 4 of the leading risk factors for chronic disease, among emerging adults. METHODS: Data were drawn from a cohort of young Australians who completed a web-based, self-report survey in 2019 during early adulthood. A series of Poisson and logistic regressions were conducted to examine the concurrent associations between the risk behaviors (sleep, diet, PA, and sitting and screen time) and personality traits (hopelessness, anxiety sensitivity, impulsivity, and sensation seeking) among emerging adults in Australia. RESULTS: A total of 978 participants (mean age 20.4, SD 0.5 years) completed the web-based survey. The results indicated that higher scores on hopelessness were associated with a greater daily screen (risk ratio [RR] 1.12, 95% CI 1.10-1.15) and sitting time (RR 1.05, 95% CI 1.0-1.08). Similarly, higher scores on anxiety sensitivity were associated with a greater screen (RR 1.04, 95% CI 1.02-1.07) and sitting time (RR 1.04, 95% CI 1.02-1.07). Higher impulsivity was associated with greater PA (RR 1.14, 95% CI 1.08-1.21) and screen time (RR 1.06, 95% CI 1.03-1.08). Finally, higher scores on sensation seeking were associated with greater PA (RR 1.08, 95% CI 1.02-1.14) and lower screen time (RR 0.96, 95% CI 0.94-0.99). CONCLUSIONS: The results suggest that personality should be considered when designing preventive interventions for lifestyle risk behaviors, particularly in relation to SB, such as sitting and screen time. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12612000026820; https://tinyurl.com/ykwcxspr.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".