How to predict dropouts? New study looks at different elements

Young people dropping out of college, leaving education without a degree is a story of shattered dreams and possibilities. How can we predict who needs that bit of extra help to succeed? A new UK study using US data shows that teenagers who do not access healthcare when needed are at greater risk of dropping out of high school.

The study in short:

  • We explore the relationship between personality traits and school dropout.
  • We employ multiple treatment propensity score matching.
  • We use forgone health care as a proxy for psychological maturity of judgement.
  • Forgone health care is a consistently significant predictor of dropout.
  • Specific combinations of traits are associated with an increase in school dropout.

From the press release:

Teenagers who do not access healthcare when needed are at greater risk of dropping out of high school say researchers from Lancaster University in the UK.

More than one in five young people in the developed world drop out of high school, which leads to a higher risk of unemployment, ill health and crime.

The study in the Journal of Economic Psychology examined data from the US National Longitudinal Study of Adolescents to Adult Health, a nationally representative sample of 90,000 students in grades 7 to 12 at 132 schools.

The authors, Dr Eugenio Zucchelli and Dr. Giuseppe Migali, from Lancaster University said : “Forgone healthcare is a consistently significant predictor” and could be used to identify teenagers at risk of leaving before the age of 18.

Over a third of dropouts do not seek healthcare when needed compared with only over a quarter of other high school students.

Not using healthcare includes not choosing to access healthcare for reasons including “did not know who to see” and “I thought the problem will go away”; this was used as a marker of the ability to assess the long-term consequences of actions.

The researchers excluded teenagers who could not pay or did not have transport to visit the doctor and the ones with chronic conditions.

A risky attitude towards health is also common among more than half of dropouts, who are more likely to smoke, drink and take drugs.

High school graduates and dropouts differ on the Big Five personality traits used by psychologists.

Dropouts are more likely to have combinations of the following traits:

  • low conscientiousness
  • neuroticism
  • introversion

Researchers say “Individuals who forgo their healthcare and present low conscientiousness and introversion have the highest risk of dropout.”

Do note: correlation, not necessarily causal relation, still very relevant information.

Abstract of the study:

There is sparse evidence on the effects of personality traits on high school dropout, especially on whether combinations of different traits may uniquely influence dropout decisions. We employ single and multiple treatment matching together with rich data on US adolescents to explore the relationship between personality traits and their combinations on school attrition. Using the Big Five inventory, we find that introversion, and to a lesser extent neuroticism, are individually associated with higher probabilities of dropping out from school. Multiple treatment estimates show that blends of low levels of conscientiousness and neuroticism present higher likelihoods of an early exit. Furthermore, we exploit information on forgone health care and explore its role as a predictor of dropout, potentially proxying relevant traits associated with psychological maturity of judgement such as responsibility, perspective and temperance. These traits refer to the capacity of assessing the long-term consequences of actions and may influence an individual’s decision-making process, including dropout choices. Forgone health care appears to be a statistically significant predictor of dropout throughout our models. Individuals who forgo their health care and present low conscientiousness and introversion have the highest risk of dropout. Overall, our results are robust to alternative specifications and increasing levels of selection on unobservables. We suggest that given its predictive power, forgone health care could be used as a signalling device to help identifying individuals at higher risk of school dropout.

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Filed under At home, Education, Research

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