Flickr/Valentin Ottone

Quantum change in public health

If a person talks about quantum change in physics, it will not be surprising at all. However, it is rather new to discuss quantum change in relation to public health, particularly in studying health behavior such as smoking cigarettes, drinking alcohol, using drugs, engaging in risky sex, using a condom for HIV prevention or participating in exercise for better health.

In fact, human behavior has certain similarities to the light ray that consists of a continuous component like the waves and a discrete component like the particles. The continuous part can be predicted with accuracy as many researchers usually do with regression models. However, the discrete part can hardly be predicted using the conventional methods.

In my first book Behavioral Medicine published in Chinese in 1989, I proposed the idea of quantum change, considering the fact that many people know the fact that smoking can cause cancer, but they choose to keep smoking; while almost everyone knows exercise is good only a few actually participate in physical activities regularly.

Cusp catastrophe modeling analysis

Although the idea is attractive, there is a lack of right method to test the idea. It was until 2009 when I met with Dr. Stephen Guastello from Marquette University, I got to know a method to analyze both the continuous and the discrete part of a behavior using one model – cusp catastrophe modeling analysis.

More importantly, the complex cusp model can be solved using the conventional regression method.

I have conducted a series of research and published several papers to investigate adolescent behaviors that are directly related to health, particularly tobacco use.

With the method developed by Dr. Guastello and colleagues, I have conducted a series of research and published several papers to investigate adolescent behaviors that are directly related to health, particularly tobacco use.

A comparison of these results leads us to conclude that it is the limitation of the conventional analytical approach, not the behavior theory that has limited us to better understand human health behavior, particularly health behavior among adolescents.

The research we recently published in Global Health Research and Policy involves the application of the Protection Motivation Theory (PMT) in understanding cigarette smoking behavior among adolescents.

What did we do?

The study was conducted using data collected among a sample of vocational high school students. Vocational high school students consist of an at-risk adolescent population for substance use and many other unhealthy behaviors.

Understanding their behavior is a pre-requisite for effective intervention.

Understanding their behavior is a pre-requisite for effective intervention. Results from our analysis indicated that PMT can explain 82% of the variance in reported smoking. If the same data were analyzed using linear or logistic regression, the PMT theory can only explain up to 20-25% of the variance, as we reported in this and another study published in Addictive Behavior in 2014.

According to our findings from cusp catastrophe modeling analysis, effective behavioral intervention to prevent adolescents from smoking must provide adequate education on tobacco harm to enhance perceived health threat from smoking, which serves as the foundation for behavior change; emphasize training on coping skills, including self-efficacy for not smoking, health and social costs from smoking and thirdly social and health benefits from not smoking, which consists of a driving force to promote sudden (quantum) change not to smoke.

Many behavioral interventions either failed or do not achieve the effect size as expected because of the lack of power of the intervention to promote quantum change.

Application of cusp modeling method in analyzing health behavior represents an important direction in public health and epidemiological research.

Application of cusp modeling method in analyzing health behavior represents an important direction in public health and epidemiological research. Our health is determined, to a great extent, by our own behavior.

My continuous work on quantum change in health risk behavior enabled me to obtain a large five year research grant from the US National Institute of Health in 2013 to formally establish and test the cusp modeling methods in analyzing HIV risk behavior among adolescents. We look forward to more studies with a focus on quantum change using advanced analytical methods.