How to become an expert in thermography without falling into the Dunning-Kruger effect.

The keys to advancing the application of thermography to health and sports in an objective and scientific manner without being an Dunning-Kruger person.

The Dunning-Kruger effect, coined by David Dunning and Justin Kruger from Cornell University (New York, USA) in 1999, refers to how people tend to overestimate their abilities due to excessive confidence when they lack knowledge or are just starting to learn about a subject. As they delve deeper into the topic, they realize how much they didn’t know and are unable to answer certain questions related to the subject, leading to a decrease in their perceived competence. It’s only when they attain in-depth knowledge and gain years of experience and practice with the technology that they acquire the skills and competencies to transfer knowledge effectively.

At ThermoHuman, we have been working on the application of thermography in health and sports since 2009, with over 59 published scientific articles, 9 defended doctoral theses, and professional experience in more than 40 countries. This experience allows us to humbly but proudly share our knowledge with the community.

Dunning-Kruger effect apply to thermography

When we apply the Dunning-Kruger effect to thermography, we may think of its use in the 70s-80s for breast cancer detection, which, due to poor results, gave thermography a controversial reputation for many years. This could be attributed, among other things, to professionals’ lack of knowledge in the technique and the technical limitations of cameras and software at that time.

To avoid falling into the Dunning-Kruger trap when applying thermography, it’s crucial to avoid making certain mistakes:

1. Initial focus on colors: It’s common to fixate on the colors in the thermographic images, where regions with more striking colors (such as red or white in the rainbow palette) catch attention. However, associating a problem solely based on colors is a major mistake. Colors in thermography do not correspond to any validated metric in scientific literature, so drawing conclusions solely from colors should be avoided.
2. Understanding the limitations: Without proper analysis using software, the only use of thermography is qualitative. However, relying solely on subjective interpretation without knowledge and experience can lead to high bias. It’s essential to analyze images using metrics that provide valuable information.
3. Using metrics for valuable insights: With the use of metrics, thermography can offer real applications. Asymmetry is a reliable and stable metric for analysis. By utilizing asymmetry, one can generate reports that help identify injury risks and monitor progress toward restoring balance.
4. Recognizing recurring patterns: Continued use of thermography allows professionals to recognize patterns and proportions that frequently occur in human biology. For instance, joints tend to have lower temperatures compared to muscular regions, and muscle injuries may exhibit hypothermia.

To follow a more optimized path through the Dunning-Kruger effect, one should seek guidance from experience, scientific knowledge, rigor in results, and recommendations from entities like ThermoHuman, who have a long-standing presence in thermography.

Understanding the reality of the learning curve in thermography

The process of learning and mastering thermography, while simple to start, requires comprehension of the learning curve. Basic analysis methodologies can be applied from the beginning, but gaining in-depth knowledge and optimizing methodologies takes time.

• Starting point: Self-learning from abundant online resources can provide a foundational understanding. However, formal training, like the 8-hour course offered by ThermoHuman, with filtered scientific literature, analysis of clinical cases, and comprehensive material, can be an ideal starting point.
• Familiarization: Over the first 2-3 weeks of using the software, individuals become familiar with individual and group analysis and the main views of the software. They can use thermal asymmetry as the primary information for athlete screening, both for prevention and injury monitoring.
• Standardization: Over the next month or two, professionals can establish evaluation standards, determine the right implementation timing, and collect individual athlete profiles to personalize the information for each of them.
• Implementation and adaptation: It takes a medium to long-term commitment, at least a season, to develop and adapt a personalized methodology, choose appropriate metrics, and generate key performance indicators (KPIs) to make informed decisions.