#85: Bad Data = Bad Decisions? Fix It with This Simple Concept
Misleading research can have serious consequences.
You're about to discover the "Intention-to-Treat Error" and its impact on everything from healthcare to business. You'll learn how to correct this bias for better, more informed choices. #problemsolving #datadriven #decisionmaking
IN TODAY'S ARTICLE
1. The Intention-to-Treat Error
2. Reinforce What You Learn
3. Recommended Critical Thinking Books
4. Next Friday: #86 Because Justification Bias
5. The Other 84 Cognitive Biases Covered On The Way to 200!
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1. THE INTENTION-TO-TREAT ERROR
??Understanding | ??Harmful Effects | ??Susceptibility | ??Avoiding | ??Benefiting
??UNDERSTANDING THE INTENTION-TO-TREAT ERROR
The Intention-to-Treat Error bias occurs when researchers analyze clinical trial data based on the initial treatment assignment, regardless of whether participants actually completed the assigned treatment.
The Intention-to-Treat (ITT) error bias refers to a common issue in clinical trials where the analysis includes all participants based on the initial treatment assignment, regardless of whether they completed the treatment as planned. This method is intended to preserve the randomization process and provide a conservative estimate of treatment effectiveness. However, it introduces bias because participants who do not follow the assigned treatment protocol can dilute the true effect of the treatment, leading to misleading conclusions about its efficacy. This bias can arise from various reasons, such as non-compliance, dropout, or protocol deviations, affecting the reliability of the study's findings.
Going Deeper:
The Intention-to-Treat (ITT) principle, has its roots in the development of clinical trial methodology, but it's not typically referred to as a "bias" in the scientific literature. Instead, it's considered a methodological approach to analysis.
One of the earliest and most influential papers on the topic was published in 1961 by Austin Bradford Hill, a British statistician and epidemiologist. Hill is often credited with formalizing many principles of modern clinical trials, including the concept of randomization.
In his 1961 paper "The Clinical Trial," published in the New England Journal of Medicine, Hill discussed the importance of analyzing all randomized subjects according to their original group assignment, regardless of whether they actually received the treatment. This is essentially the core principle of Intention-to-Treat analysis.
Examples of the Intention-to-Treat Error:
1?? CLINICAL TRIAL MEDICATION ADHERENCE
In a clinical trial, some participants do not take their medication as prescribed, but their outcomes are still analyzed with those who followed the regimen. This skews the results, making the medication appear less effective than it might actually be. Imagine a trial for a new diabetes medication where several participants skip doses or stop taking the medication entirely.
2?? WEIGHT LOSS PROGRAM
Participants in a weight loss program are assigned to different diet plans. Some participants do not follow their assigned diet but continue to be analyzed as if they had. This leads to an underestimation of the true effectiveness of the diets. For instance, some participants indulge in high-calorie foods despite being assigned a low-carb diet.
3?? EXERCISE INTERVENTION STUDY
In a study aimed at assessing the impact of a new exercise regimen on cardiovascular health, some participants do not follow the exercise schedule but are still included in the analysis. This reduces the perceived benefits of the exercise program. Picture participants skipping workouts or doing different exercises than prescribed.
4??SMOKING CESSATION PROGRAM
In a smoking cessation program, participants are given different methods to quit smoking, such as patches or counseling. Some participants do not follow their assigned method but continue to be part of the analysis. This diminishes the apparent effectiveness of the intervention. Visualize participants occasionally smoking or using alternative methods not included in the study.
5?? EDUCATIONAL INTERVENTION STUDY
?In a study to measure the effectiveness of a new teaching method, some students do not attend the sessions regularly or engage with the materials as required. These students are still included in the final analysis, making the teaching method appear less effective. Think of students missing classes or not completing assignments.
6??DRUG REHABILITATION PROGRAM
Participants in a drug rehabilitation program are assigned different therapy methods. Some do not adhere to their assigned therapy but remain in the analysis group, which affects the perceived success rates of the therapies. Imagine participants relapsing or skipping therapy sessions.
??HARMFUL EFFECTS OF THE INTENTION-TO-TREAT ERROR
The intention-to-treat error can be a real headache because it distorts the results of studies, making them misleading and unreliable. It's like trying to judge a book by its cover – you might miss out on some important details inside.
Here are three potential negative consequences:
1?? MISLEADING TREATMENT EFFICACY
Misleading results can occur when the effectiveness of a treatment is underestimated due to non-adherence.
For example, in a clinical trial for a new drug, if many participants do not follow the prescribed dosage, the drug may appear less effective than it truly is, leading to its dismissal.
2?? WASTED RESOURCES AND EFFORT
Resources and effort can be wasted if interventions are based on inaccurate data.
For instance, if a public health campaign is designed around a weight loss program that appears ineffective due to ITT error, significant time and money may be spent on a flawed strategy.
3?? COMPROMISED PATIENT CARE
Patient care can be compromised if healthcare providers make decisions based on inaccurate efficacy data.
For example, doctors might choose less effective treatments for patients with chronic diseases if the data they rely on is biased by ITT error.
???MOST SUSCEPTIBLE: ARE YOU PRONE TO THE INTENTION-TO-TREAT ERROR?
The intention-to-treat error can trip up anyone involved in research or data analysis, but certain types of people might be more prone to it. Think of those who are a bit too focused on the details, or maybe those who get caught up in their own expectations.
So, who's most susceptible?
1?? STRICT ADHERENCE TO PROTOCOLS
Individuals who strictly adhere to research protocols might overlook deviations and non-compliance among participants, leading to ITT errors.
For instance, a clinical trial coordinator who insists on including all participants in the final analysis, regardless of whether they followed the treatment plan.
2?? DATA INTEGRITY FOCUS
Those who focus heavily on maintaining data integrity may prioritize keeping all participants in the analysis to preserve the original sample size, even when participants do not adhere to the treatment.
For example, a biostatistician who includes all participants in the analysis to avoid introducing bias from dropouts, despite significant non-compliance.
3??OUTCOME BIAS
Individuals with a strong belief in the efficacy of an intervention may include all participants in the analysis to ensure that the results reflect the intended treatment effects, potentially ignoring non-adherence.
Consider a pharmaceutical researcher who wants to demonstrate the drug's effectiveness and thus includes non-compliant participants in the final results.
??WAYS TO AVOID THE HARMFUL EFFECTS OF THE INTENTION-TO-TREAT ERROR
Avoiding the Intention-to-Treat (ITT) error is crucial for maintaining the integrity of research and clinical trials. The main goal is to ensure that the analysis accurately reflects the adherence and outcomes of the participants.
Here are three top ways to avoid ITT error:
1?? ROBUST PARTICIPANT MONITORING
Regularly monitor participants to ensure adherence to the treatment protocol. This involves frequent check-ins, reminders, and support to help participants follow the prescribed treatment plan. For example, in a clinical trial, coordinators can use electronic reminders and periodic consultations to keep participants on track.
2??DETAILED PROTOCOL DEVIATION RECORDING
Record any deviations from the treatment protocol in detail. This helps in identifying patterns of non-adherence and understanding their impact on the study outcomes. For instance, in a weight loss program, keeping a log of participants' diet and exercise deviations provides insights into adherence levels.
3?? USE OF PER-PROTOCOL ANALYSIS
Complement ITT analysis with per-protocol analysis to compare results. This involves analyzing only the data from participants who fully adhered to the treatment plan. For example, in a smoking cessation study, comparing the outcomes of those who strictly followed the quitting methods with the ITT results gives a clearer picture of effectiveness.
领英推荐
?? Have you ever encountered a situation where a study's results seemed too good to be true, only to later discover flaws in the analysis? How did this experience impact your trust in research findings?
??USE THE INTENTION-TO-TREAT ERROR FOR GOOD
While it's important to be aware of this bias in research, we can apply some of its principles ethically in our daily lives to benefit those around us. The key is to focus on inclusivity and considering the bigger picture, much like how ITT analysis aims to include all participants. Here are a few ways we can do this:
1?? INCLUSIVE FAMILY PLANNING?
Considering everyone's preferences and needs when making family decisions can lead to better outcomes and stronger relationships.?
How To: Create a family suggestion box where all members can contribute ideas for activities or improvements, regardless of how often they participate in family events.
2?? WORKPLACE INCLUSIVITY?
Valuing input from all team members, regardless of their level of involvement in a project, can lead to more innovative solutions.
?How To: Implement a system where all team members are invited to brainstorming sessions, even if they're not directly involved in the project, to gather diverse perspectives.
3?? COMMUNITY ENGAGEMENT?
Including all community members in decision-making processes, even those who may not always participate, can lead to more representative outcomes.?
How To: Organize town halls with multiple time slots and online options to ensure everyone has a chance to voice their opinions, regardless of their usual level of engagement.
By applying these principles, we can create more inclusive and considerate environments in our personal and professional lives, much like how the Intention-to-Treat analysis aims to provide a more comprehensive view in research.
??Have you ever experienced a situation where someone's opinion was excluded or overlooked simply because they weren't always present or fully engaged? How did this exclusion affect the outcome?
2. REINFORCE WHAT YOU LEARNED
???Glance Over the Poem
"Stay on Track and Be Exact"
In a trial, we set the stage,
Assign a plan for every age.
But some may stray, not do their part,
This can skew the science art.
Intention-to-Treat, we must beware,
Include them all, handle with care.
But if they don't stick to the plan,
Results may differ from what we began.
To avoid this error, here's the key,
Monitor closely, see what you see.
Record each step, who follows through,
And analyze what's really true.
Stay on track, follow through,
In every study, it's what you do.
For clear results and honest views,
This is the path, the way to choose.
3. RECOMMENDED CRITICAL THINKING BOOKS
Don't have time to read a book, but want to apply its core concepts? Check out Idea Express to learn three (3) book derived concepts and how to apply them today:
Mistakes Were Made (But Not by Me) by Carol Tavris and Elliot Aronson
Outsmart Your Brain by Daniel T. Willingham
Predictably Irrational by Dan Ariely
The A-Ha! Method by Brandon Williams
The Book of Risk by Dan Borge
The Scout Mindset by Julia Galef
Thinking in Time by Richard E. Neustadt and Ernest R. May
Focuses on applying historical thinking and critical analysis to decision-making processes, emphasizing the importance of context, precedent, and strategic foresight
You Are Not So Smart by David McRaney
Our article about "You Are Not So Smart" by David McRaney provides actionable insights into common cognitive biases and how they affect our thinking and decision-making. The book reveals how our brains trick us into believing we are more rational and logical than we actually are.
4. ???UP NEXT: #86 Because Justification Bias
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5. COGNITIVE BIASES WE'VE COVERED (SO FAR)
Find them here: