91Ó°ÊÓ

In a 2018 study reported in The New England Journal of Medicine, Halpern et al. randomly assigned smokers to one of five groups, including four smoking cessation interventions and usual care. Usual care consisted of access to information regarding the benefits of smoking cessation and to a motivational text-messaging service. The four interventions consisted of usual care plus one of the following: free cessation aids such as nicotine-replacement therapy or pharmacotherapy, free e-cigarettes, free cessation aids plus \(\$ 600\) in rewards for sustained abstinence, or free cessation aids plus \(\$ 600\) in redeemable funds deposited in an account for each participant, with money removed from the account if cessation milestones were not met. Researchers measured the percentage in each group who sustained smoking abstinence for six months. Results indicate that financial incentives added to free cessation aids resulted in a higher rate of sustained smoking abstinence than free cessation aids alone. Is this study an observational study or a controlled experiment? Explain. a. Is this study an observational study or a controlled experiment? Explain. b. Identify the treatment and response variables. c. Can a cause-and-effect conclusion be drawn from this study? Why or why not?

Step by step solution

01

Identify Type of Study

To identify whether it's a controlled experiment or an observational study, we have to look at whether the researchers intentionally apply treatments to the individuals or simply observe individuals and measure variables of interest without affecting them. Here, the researchers actively assigned subjects to different groups, which means it's a controlled experiment.

02

Identify Treatment and Response Variables

Next, treatment and response variables should be identified. The treatment variable is what the researchers purposely control or manipulate, in this case, that’s whether the smokers were given access to the motivational text-messaging service, free cessation aids, free e-cigarettes, cessation aids plus rewards, or cessation aids plus a funds deposit account. The response variable is what is measured as an outcome, in this case, that’s the percentage of subjects who managed to quit smoking for six months.

03

Determine If a Cause-and-Effect Conclusions Can Be Drawn

Due to the fact that the individuals in the study were randomly assigned to one of the five different treatment groups, it's possible to conclude that the differences in the outcome (abstinence rate) were indeed caused by the different treatments (interventions), suggesting a cause-and-effect relationship.

Unlock Step-by-Step Solutions & Ace Your Exams!

• Full Textbook Solutions

  Get detailed explanations and key concepts

• Unlimited Al creation

  Al flashcards, explanations, exams and more...

• Ads-free access

  To over 500 millions flashcards

• Money-back guarantee

  We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Observational Study vs Controlled Experiment

Understanding the difference between an observational study and a controlled experiment is crucial for students trying to grasp research methodologies. In an observational study, researchers simply observe and record data without intervening, much like a biologist watching birds to study their feeding habits. Conversely, a controlled experiment involves an active intervention by researchers to study the effects of a specific treatment on a subject group.

For instance, in the given exercise, researchers assigned smokers to various groups, administering different smoking cessation interventions, an approach that defines it as a controlled experiment. Such experiments are powerful because they allow researchers to control for extraneous variables, and, by randomizing subjects into groups, they can mitigate selection bias, providing a more reliable basis for drawing conclusions about cause and effect.

Treatment and Response Variables

Dissecting an experiment involves identifying two key elements: the treatment and response variables. A treatment variable is what the researcher changes or manipulates, hoping it will affect the study's outcome. It's like altering a recipe to see if the cake tastes better. The response variable is the outcome being measured, similar to the guests' reactions to the cake's taste.

In the context of our study, the treatment variables included different smoking cessation methods, such as free cessation aids or monetary incentives. The response variable was the percentage of participants who successfully quit smoking for six months. Clarifying these variables is fundamental as it determines the focus of the analysis and aids in interpreting the results.

Cause-and-Effect Relationship in Studies

Establishing a cause-and-effect relationship is the holy grail of many research studies. To infer causality, controlled experiments are often preferable over observational studies because they go beyond correlation, allowing researchers to manipulate one variable and observe the outcome.

In the smoking cessation study, due to the random assignment of subjects to treatments and the careful control over the experimental conditions, it's possible to deduce that any significant differences in the smoking abstinence rates can be attributed to the specific interventions, suggesting a cause-and-effect link. It's important for students to recognize that this level of inference is seldom possible in observational studies, where other variables may influence the outcome.