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Essay Available:
4 pages/≈1100 words
4 Sources
Health, Medicine, Nursing
Article Critique
English (U.S.)
MS Word
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Qualitative Article Methods and Summary (Article Critique Sample)


Make sure your chosen article has been approved before you begin this assignment. Critiques of unapproved articles will receive zero points (absolutely no exceptions). Students are responsible for making sure they have met this requirement.
Length and Formatting
3.5 - 5 pages (not counting the title and reference pages)
APA 7th edition format (you do not need an Abstract)
Easiest to download and use this template: Summary template Download Summary template
The Summary should summarize the journal article section-by-section:
The summary of the Introduction should include details on the research questions or hypotheses, the important empirical and theoretical background information the authors included, and the rationale they gave for the study.
Note: Make sure you use the past tense and are clear when you are referring to something the authors did, said, or included. (Correct: "The authors discussed prior research that found self-concept predicted nursing self-efficacy." Incorrect: "Research suggests self-concept predicts nursing self-efficacy.")
The summary of the Methods section should include the research design, the sampling approach and sample characteristics, and the main variables and how they were measured. Without duplicating or quoting the article, explain what the researchers actually did in the study.
Note: Although you should summarize the research design, this may be beyond what we have learned in this class. You are not expected to summarize or evaluate these in great detail. However, you do need to understand the why the authors designed their study that way. I am happy to talk through this portion of your article with you.
In summarizing the Results section, pretend that you are the author reporting the results to students who have not read the article. Your summary of the results should enable a reader to see the main points and be able to interpret them without referring back to the article.
Note: Although you should summarize the relevant descriiptive statistics, some statistical analyses in your article may be beyond what we have learned in this class. You are not expected to summarize or evaluate these in great detail. However, you do need to understand the purpose of the analyses the authors did and what they found. I am happy to talk through this portion of your article with you.
In summarizing the Conclusions and Implications, detail each conclusion presented by the authors. These should parallel their research questions/hypotheses. What inferences did they draw from their results? Then summarize any implications they discussed based on these conclusions, including recommendations for policy or practice. Be sure to also list any limitations they included.
If the authors did not include some of the information above, explicitly state that they did not. (Be sure though! Sometimes things are mentioned in other sections of the article.)


Qualitative Article Summary
Student’s Name
Department of Nursing, Texas Woman's University
Instructor’s Name
Due Date
Qualitative Article Summary
Summary of Introduction
The majority of data analyses are pegged on models. Psychologists utilize statistical models to translate different variables that have been observed into meaningful psychological constructs. The authors discussed delved into cognitive models and response time models. In the article, the authors' main aim was to study the validity of the inferences that have been drawn from various cognitive models of response time data. The authors also argued that the validity of assumptions from these cognitive models could be influenced by other factors similar to those that affect statistical analysis CITATION Dut19 \l 2057 (Dutilh et al., 2019). According to the authors, cognitive models have become a standard measurement tool used to translate the accuracy and speed of participants' responses. The authors also look into the latent psychological factors of interest, such as the participants' response bias, their abilities, and whether they are cautious in their responses.
Cognitive models provide a clear account of the psychological processes involved during data analysis. According to the authors, a cognitive model is a formalized theory that mimics the cognitive processes that result in the observed data. The formalization process enables the researchers to derive specific predictions about the information that has been observed. It also makes it possible for the researcher to reverse engineer different variables that have been observed from the data or research CITATION Arn15 \l 2057 (Arnold, Bayen, & Broder, 2015). The cognitive models contain two main features: the ability to capture critical phenomena that behavioral data might have missed or ignored, and it reflects the magnitude of the assumed constructs CITATION Don11 \l 2057 (Donkin, Brown, & Heathcote, 2011). One of the most common cognitive models is Ratcliff's diffusion model, which transforms data accuracy and response times into constructs for various studies.
According to the article, other models are the evidence-accumulation models used to measure four main components. These components include boundary separations, non-decision times by the participants, accumulation rates, and starting points. Although the diffusion model is the most common model for response time data, researchers could utilize other alternative models. Some of these alternative models address the shortcomings of the diffusion model. They include the full diffusion model and linear ballistic accumulation (LBA) CITATION Dut19 \l 2057 \m Dut11 (Dutilh et al., 2019; Dutilh, Krypotos, & Wagenmakers, 2011). Like many of the other models used in statistical analysis, some of the shortcomings of cognitive models include undefined degrees of freedom for the researcher and discriminant and convergent validity.
Summary of Methods
The participants would shoot the direction of the apparent motion that several moving dots would constitute. Each stimulus contained 120 dots that were presented on a screen. During the first trial, all the dots were utilized randomly in an aperture. Afterward, the dots were then displaced at random intervals or according to the rules of the experiment.
For the easy stimuli, 20 percent of the dots were moved in the targeted direction. However, 90 percent of the dots were randomly placed in the aperture for the problematic stimuli, while the other 10 percent moved in the target direction. The set of stimuli had a duration of roughly 180 microseconds. The experiment also had an interval of between 0.5 and 1 second before the subsequent trial. To record the responses, the participants had to press buttons on a computer mouse.
The research involved 20 psychology students from the University of Basel, with 5 of them being male while the rest were females. The mean age of the participants was 26.7, while their standard deviation (SD) was 2.1. The 20 participants were required to perform a random dot motion task that utilized Python. This sampling method was picked because it allows a more accessible collection of data from the research and generalized results. The study design used three manipulations. The three manipulations included an accurate response to instructions, biasness, and difficulty or ease.
The manipulation trials were administered in blocks in which the total number of trials was 400 trials where they used five blocks of 80 trials each. This enabled the participants to familiarize themselves with response caution of the manipulations, bias, and stimuli. Before an upcoming block was displayed, the participants were allowed to get acquainted with the instructions. It required the participants to either pay attention to their accuracy and the total number of right and left stimuli.
Summary of Results
The first set of results indicated that the 17 contributors used the 17 procedures. However, the groups in the experiment did not use similar approaches to solve the problems at hand. Based on the results, there were high levels of agreement between the models. The diffusion models that were used had similar inferences along with the LBA models that were used. Despite the agreement within the models, there were differences between the diffusion and LBA models. It is critical to note that although there were different conclusions from the models, one could note that there was consensus in the inferences that were established. The diffusion model made 84 percent correct inferences. EZ2 indicated five false alarms and four misses from a group of 56 inferences. Therefore, the accuracy level was 71 percent.
The LBA models recorded an average inference

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