Evaluating Studies  

Selected Gallup Poll

The Gallup poll that is selected for the evaluation is (U.S. Employee Engagement Needs a Rebound in 2023) (Inc, 2023).

Purpose and Summary of Selected Gallup Poll

The title of the selected study is U.S. Employee Engagement Needs a Rebound in 2023(https://www.gallup.com/workplace/468233/employee-engagement-needs-rebound-2023.aspx). This study deals with the population who will be more likely to be the workers belonging to several organizations. A survey is organized for the workers of different organizations. The selected population must be under the chosen sample to universalize the findings.

MAT FPX 2001 Assessment 5 Evaluating Studies

This study deals with the influence of employee interaction on business outcomes. According to the survey, 36% of the engagement of the employees declined in a decade. This study is focused on the samples collected randomly from 15,000 US full and part-time employees. The results of the Gallup survey suggested that organizations are working these days to settle into the new normal hybrid work arrangements. 21% of these remote-ready jobs are functionally on-site too. 53% of the employees work in hybrid arrangements while 26% work remotely. This stabilization means ways of working in the future are more predictable, but it also demands a high level of coordination.

The organization maintained this level of engagement by using its organizational culture and values to guide business decisions and by embracing hybrid work. They also maintained strong connections between managers and employees.

Appropriateness of Sample

The Gallup poll illustrated the main results which include that ratio of actively engaged to disengaged workers in the US can be stated as 1.8 to 1 down from 2.1 to 1 in the year 2021 and 2.6 to 1 in the year 2020. This is considered the lowest ratio for disengaged workers in the United States.

According to the sample data, the range of the fall of the valid population parameter is the range for the margin of error. With the increase of the size of the sample, the margin of the error decreases owing to the reason that more details are given by the larger sample, therefore, decreasing the impact of random error of sampling. The size of the sample reduces, and the increase in the margin of error takes place due to the less provision of information. The margin of error is changed by the other factors as well which includes the variations in data and confidence level. Hence these certain factors must be evaluated while interpreting the results of the survey (Story & Tait, 2019).

The Rationale for Sampling Technique

The type of research question, the traits of the population under study, and accessible resources are the factors responsible for the rationale for a specific technique. Sampling techniques vary in strengths and weaknesses. For instance, sampling which is done randomly involves a random subset of individuals within the same population. This technique applies to the homogeneous population. Therefore, for a diverse population, this technique may not be applicable. This survey deals with the random sampling of the working population about the elements of the workspace which includes customer service and productivity.

The division of populations into groups is included in the cluster sampling. For instance, geographical regions and random selection of groups are involved in it. A researcher may find this technique appropriate when the population is geographically dispersed or if he or she wants to reduce travel or data collection costs. However, if clusters are not representative of the population or there is a lot of variability within clusters, it may not be appropriate. Therefore this Gallup study evaluates the various elements of the workplace which involves the level of compliance of clients regarding their clarity of expectations and chances for their growth.

Comparison With Other Techniques

The random techniques for sampling have been applied by the researchers which is better than cluster, stratified, and simple sampling. The stratified sampling cannot be related to the overall population. The sample size is necessary to determine the related population. Most of the time larger samples are proven beneficial. Random Sampling deals with the technique in which each sample is observed equally. It leads to the unbiased representation of the entire population (Lakens, 2022). Therefore random sampling is adopted in this Gallup survey which is better than all other approaches 

Interpretation of Confidence Interval

Confidence intervals are a range of values indicating certainty or probability that the population parameter exists within that range. In the survey outcomes, a confidence interval deals with the scope of values for the specific population. For example, according to the given survey, the engagement among young workers was more impacted than that among older workers. The engagement of young workers decreased by four points, while active disengagement increased by four points.

MAT FPX 2001 Assessment 5 Evaluating Studies

The accuracy of the survey can be represented by the margin of the survey. The sampling error can be determined that might have occurred from the sample instead of the whole population. The sample size mostly affects the margin of the errors. As the greater samples lead to smaller margins of error and vice versa. Moreover, the larger the marginal error the wider will be the confidence interval. Similarly the smaller the marginal error the smaller will be the confidence interval. The modifications in the design of the study, sampling technique, and sample size determine the margin of error. For instance, a biased survey question may enhance the errors and decrease the validity of the outcomes. 

Effect of Study Design on Margin of Error

           The random changes in the sampling process affect the margins of the errors. Most of the time a prominent size of the sample deals with the lesser margin of error and lesser confidence interval. The modifications in the design of the study lead to changes in the marginal errors. In case the sample is not relevant to the population, the marginal error becomes consequential as the sample is unlikely to highlight the proportion of the population precisely (Etikan & Babatope, 2019).

Impact of Question-Wording

The impact of question-wording on the participants is quite significant in the surveys. The accuracy of the results can be affected merely by the phrases of the questions. The inaccurate questions lead to inaccurate results. Though the questions are represented in a way that deals with the promotion of learning in their specific workplace. It may lead to a partial response as it because the respondents might feel pressure to coordinate with the statement Therefore phrases of questions must be selected accordingly (Henriques et al., 2019).

Impact of Question-Wording on Statistical Results

The phrases of the questions have keenly affected the outcomes of the surveys. The answers of the respondents depend on the statement of the question. Several types of questions are included in the surveys which can be multiple-choice, open-ended, and ratio scale queries. The open-ended type of questions provides discernment into the thoughts of the respondents regarding a certain situation. The given survey deals with the question, What is employee engagement, really? Hence the phrases of the questions directly affect the statistical results. The selection of wording should be following the desired consequences of the survey (DeJonckheere & Vaughn, 2019).

Evaluation of Biasness

According to the given information, it is arduous to get to know that either the study is partial or not. Therefore, it is mandatory to review the possible sources of bias that might have impacted the consequences. The sampling method which involves only the selected participants a biased source of sampling. This survey deals with random sampling. Therefore, to make certain an unbiased survey random sampling can be done (Kyriazos, 2018).

Avoidance of Biasness

The wording of the question as discussed earlier, and the survey design are other factors for the biased source. Ambiguous questions lead to the partial response of the participants. To shun this impartiality a well-established survey questionnaire was prepared for the specific population. The introduction of neutral questions led to precise answers. The obtained outcomes were verified with the other sources. The possible sources of biases were taken into consideration for better output (Boutron et al., 2019).

Conclusion

In a nutshell, we can say that the study US Employee Engagement Needs a Rebound in 2023 has given explicit insight into actively engaged and disengaged employees. The study dealt with a well-organized questionnaire. Descriptive Statistics were used for the evaluation of the quantitative and qualitative data. The study has avoided biases in surveys by taking rational questions. In general, a study has provided reliable information for the sources. The outcomes have highlighted the importance of working in a hybrid arrangement.

MAT FPX 2001 Assessment 5 Evaluating Studies

References

Boutron, I., Page, M. J., Higgins, J. P., Altman, D. G., Lundh, A., & Hróbjartsson, A. (2019). Considering bias and conflicts of interest among the included studies. Cochrane Handbook for systematic reviews of Interventions, 177–204. https://doi.org/10.1002/9781119536604.ch7 

DeJonckheere, M., & Vaughn, L. M. (2019). Semistructured interviewing in primary care research: A balance of relationship and rigor. Family medicine and community health, 7(2). Bmj.

Etikan, I., & Babatope, O. (2019). A basic approach in sampling methodology and sample size calculation review article. MedLife Clinics, 1, 1006. http://www.medtextpublications.com/open-access/a-basic-approach-in-sampling-methodology-and-sample-size-calculation-249.pdf 

 Henriques, A., Silva, S., Severo, M., Fraga, S., & Ramos, E. (2019). The influence of question-wording on interpersonal trust. Methodology, 15(2), 56–66. https://doi.org/10.1027/1614-2241/a000164 

Inc, G. (2023, January 25). U.S. Employee engagement needs a rebound in 2023. Gallup.com. https://www.gallup.com/workplace/468233/employee-engagement-needs-rebound-2023.aspx 

Kyriazos, T. A. (2018). Applied psychometrics: Sample size and sample power considerations in factor analysis (efa, cfa) and sem in general. Psychology, 09(08), 2207–2230. https://doi.org/10.4236/psych.2018.98126 

Lakens, D. (2022). Sample size justification. Collabra: Psychology, 8(1), 33267. https://doi.org/10.1525/collabra.33267 

Story, D. A., & Tait, A. R. (2019). Survey research. Anesthesiology, 130(2), 192–202. https://doi.org/10.1097/aln.0000000000002436