Predictive Tool for Psychological Well-Being in Chinese Adolescents
Author Information
Author(s): Lynn Henry, Bill Tsang
Primary Institution: Fudan University, Shanghai, China
Hypothesis
Can a simple questionnaire-based predictive instrument be developed for assessing psychosocial maladjustment among Chinese adolescents despite missing data?
Conclusion
The study successfully developed a predictive tool that can identify students at risk of psychosocial maladjustment, allowing for significant resource savings in psychological testing.
Supporting Evidence
- The predictive tool had an AUC of 0.75, indicating good discriminative ability.
- The negative predictive value of the tool was 88%, allowing for confident exclusion of normal students.
- The prevalence of psychosocial maladjustment was estimated to be 18.4% after applying multiple imputation.
Takeaway
Researchers created a quick questionnaire to help find kids who might be struggling with their feelings, even when some answers are missing. This way, they can help more kids without wasting time and money.
Methodology
The study used multiple imputation to handle missing data and developed a predictive tool based on questionnaires from 2919 sixth graders.
Potential Biases
The missing data may be related to unobserved variables, potentially introducing bias in the results.
Limitations
The study faced challenges with a high percentage of missing data, which could affect the validity of the results.
Participant Demographics
The participants were sixth graders from 21 schools in Shanghai, with a mean age of 11.9 years and 53% male.
Statistical Information
P-Value
0.05
Confidence Interval
95% CI: 0.73 to 0.78
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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