91Ó°ÊÓ

Late-Onset Schizophrenia Treatment Very late onset schizophrenia affects people who are at least 60 years old. In a 2018 study reported in The Lancet Psychiatry, researchers conducted a double-blind controlled experiment to study the effect of the drug amisulpride on these patients (Howard et al., 2018). The experiment was divided into two stages, and subjects were randomly assigned to one of three groups: Group 1 received the drug for both stages, Group 2 received the drug for stage 1 and the placebo for stage 2 , and Group 3 received the placebo for state 1 and the drug for stage 2. Researchers found that those subjects receiving the drug showed reduced psychosis symptoms compared with those receiving the placebo. a. Identify the treatment and response variables. b. Restate the conclusion of the study in terms of a cause-and-effect conclusion. Why can a cause-and-effect conclusion be made from this study?

Step by step solution

01

Identifying treatment and response variables

First, in this experiment, the treatment variables, also known as independent variables, are the application of the drug amisulpride and the placebo. For Group 1, the drug was applied in both stages. For Group 2, they received the drug in stage 1 and a placebo in stage 2. For Group 3, they were administered a placebo in stage 1 and the drug in stage 2. The response variable, also known as the dependent variable, is the reduction of psychosis symptoms. It is considered dependent because the level of psychosis symptoms depends on the administration of the drug.

02

Restate the conclusion of the study in terms of a cause-and-effect conclusion

The conclusion in terms of a cause-and-effect relationship would be: administration of the drug amisulpride reduces psychosis symptoms in patients suffering from very late onset schizophrenia. This is derived from the data showing that subjects who received the drug showed reduced psychosis symptoms compared to those receiving the placebo.

03

Reasoning for cause-and-effect conclusion

A cause-and-effect conclusion can be made from this study because it is a randomized controlled trial. Random assignment of subjects into groups helps to ensure that any observed differences in outcomes are due to the treatment (amisulpride vs placebo) rather than other confounding variables. Also, the double-blind nature of the experiment, where neither the test subjects nor the researchers knew who was receiving which treatment, further reduces bias and provides stronger evidence that the observed effect is due to the treatment.

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.

Randomized Controlled Trial

Randomized Controlled Trials (RCTs) are considered the gold standard in clinical research. They provide strong evidence for the effectiveness of medical interventions. In an RCT, participants are randomly assigned to groups, minimizing selection bias. This means everyone has an equal chance to receive any of the treatments being tested.
Key components of RCTs include:

• Random assignment: Helps ensure groups are comparable.
• Use of control groups: Usually receive a placebo or standard treatment for comparison.

In the schizophrenia study, randomization ensured that differences in psychosis symptoms could be attributed to amisulpride rather than other factors. Thus, RCTs play a crucial role in validating new medical treatments.

Independent and Dependent Variables

In any scientific study, identifying the independent and dependent variables is vital. These terms help clarify the cause-and-effect relationship of an experiment.

• Independent variable: This is what the researcher changes or controls. In the given study, it is the administration of the drug amisulpride or a placebo. This variable stands alone and does not change based on other variables in the experiment.
• Dependent variable: This is what the researcher measures. The dependent variable depends on the independent variable. In the study, the dependent variable is the reduction in psychosis symptoms. It changes in response to the drug administration.

Understanding these variables provides the foundation for establishing cause-and-effect relationships in scientific research.

Cause-and-Effect Relationship

A cause-and-effect relationship outlines how one event (the cause) directly affects another event (the effect). In the scope of clinical trials, understanding this relationship is essential to deduce whether a treatment leads to a specific outcome. In the schizophrenia study, the administration of amisulpride is the cause, while the reduction in psychosis symptoms is the effect. The study's results showed that patients receiving the drug experienced fewer symptoms.
Hence, we can infer a cause-and-effect relationship, indicating that the drug effectively reduces symptoms. This strong conclusion is feasible because of the study’s randomized controlled and double-blind design, which minimizes bias and strengthens the validity of the findings.

Double-Blind Study

A double-blind study is a research design where neither the participants nor the experimenters know who is receiving a particular treatment. This approach minimizes bias, ensuring the study results are due to the treatment itself and not other influencing factors. By blinding both parties, expectations do not influence the outcome, making the results more reliable. In the context of the schizophrenia study, the double-blind approach meant that neither researchers nor patients knew who received amisulpride or the placebo. This setup helps to affirm that observed symptom reductions were solely due to the drug and not influenced by placebo effects or researchers' biases.

Psychosis Symptoms Measurement

In clinical trials concerning mental health, measuring symptoms accurately is paramount. Psychosis symptoms are varied, including hallucinations, delusions, and disorganized thinking, which can greatly affect a patient's well-being.
Accurate measurement helps determine a treatment’s effectiveness. In the studied trial, researchers used specific criteria and scales to gauge the severity of psychosis symptoms effectively before and after treatments.
This precise measurement was crucial to establish that amisulpride led to a reduction in psychosis symptoms, offering evidence of its efficacy. By defining and measuring these symptoms clearly, researchers can provide clearer conclusions about the treatment benefits.