Identify The Independent And Dependent Variables

Identify the independent variable and dependent variable

The independent variable in the described insomnia study is the type of instruction given to participants about the pill. It has three levels: (1) told the pill will make them sleepy, (2) told the pill will make them feel alert, and (3) no information given about the effects of the pill. These levels represent different conditions manipulated to observe their effect on sleep onset latency.

The dependent variable is the measure of the outcome, which is the amount of time it took participants to fall asleep after taking the pill. This variable indicates the effect of the different instructions on sleep latency.

There is one independent variable with three levels, reflecting the different information conditions given to the participants, and one dependent variable measuring sleep onset time.

Indicate the research design type and reasoning

The study employed a between-participants design. This conclusion is based on the fact that each participant was assigned to only one instruction condition—either told the pill would make them sleepy, make them alert, or given no information—and they experienced only that one condition. Different groups of participants were exposed to each of the three instructional conditions, ensuring that each person's sleep latency was measured under a single, specific set of instructions, characteristic of a between-subjects design (Cohen, Swerlik & Camrin, 2018).

Adding a third condition and interpreting ANOVA significance

If a third condition was added where participants received no information about the effects of the pill, this would create a more comprehensive experimental setup involving three levels: explicitly told sleepy, explicitly told alert, and no info. Conducting an analysis of variance (ANOVA) on the sleep latency data across these three groups would help determine whether the different instructions have a statistically significant effect on how quickly participants fall asleep.

If the F statistic from the ANOVA is significant, it would indicate that there are meaningful differences in sleep onset times among the three instructional conditions. Specifically, a significant F value suggests that at least one group's mean sleep latency differs from the others, implying that the type of information provided about the pill influences sleep behavior (Keselman, 2003). This could suggest that participants' expectations, shaped by instructions, have a measurable effect on sleep latency, supporting the notion that psychological factors play a role in sleep onset and that placebo effects can be influential.

Conclusion

Overall, this experimental design exemplifies how manipulation of informational cues, an independent variable, can impact sleep outcomes, as measured by the dependent variable. The use of a between-participants design minimizes potential carryover effects, preserving the validity of the findings. A significant F within an ANOVA supports the hypothesis that expectations or beliefs about the pill can influence sleep latency, emphasizing the importance of psychological processes in physiological responses (Kirsch, 2019). This understanding can inform clinical approaches to insomnia treatment, including the application of placebo effects and expectation management.

References

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