Analyzing Articles on Data Collection Using Unobtrusive Measures

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

Table of Contents

Article Critique
Article Summary
Arguments
Critique
Conclusion
References

Article Critique

Typically, during research, an investigator has to be physically present to collect data; this can influence the respondents response and behavior. The consequence of the participants responses is altered or biased results. Unobtrusive information collection methods may be used to resolve some of these data errors. The purpose of this paper is to review an article on data collection using unobtrusive measures. The writing first provides an overview of the study and a brief critique of the arguments made by the researcher.

Article Summary

The article first outlines the major types of unobtrusive methods and provides a comprehensive listing of data sources for each measure. Physical trace analysis refers to studying substances or deposits produced by human activities during the occurrence of an event. Archives relate to studying the official historical records through investigating mass media contents (content analysis) or reanalyzing data collected for other purposes (secondary analysis). In simple observation, the researcher distances himself or herself from the research subjects but carefully observes their behaviors and activities. On the other hand, disguised analysis refers to the procedure of disguising or misrepresenting ones persona to study human behavior while simulation alludes to imitating a realistic situation. The main drawback associated with unobtrusive methods includes ethical issues regarding privacy and data confidentiality. Data collection may be time-consuming, and it lacks generalizability and transferability to the larger population. The advantages of unobtrusive measures include the fact that the data collected is unreactive, natural, and cost-effective.

Arguments

Study subjects are less likely to exhibit deflective behaviors when they are unaware that they are being observed.
The use of available data and public observations may overcome the challenges experienced by other obtrusive measures.
The best way to test the validity of data from the content analysis approach is through its replicability.
The emphasis of meta-analyses on quantifying data maximizes precision and replicability.
Observation is a reliable source of data collection as it does not rely on the accuracy of those being observed.

Critique

Because of the Hawthorne effect, study respondents are likely to alter behaviors. However, unobtrusive research can facilitate the collection of unbiased data by allowing one to study the respondents without alerting them of your presence. A study conducted by Roberts et al. (2019) affirmed the authors stance that testing the replicability of data from content analyses is the best way to test the datas validity. The study demonstrated that although time-consuming, reliability testing can ensure the accurate description of thematic analyses. Thematic analyses are a form of content analysis that are used to recognize patterns in qualitative surveys.

Given that archived data and physical trace analyses may be susceptible to data omission, the authors argument that observation can resolve some of the unobtrusive issues holds to be true. Data from observations are not subject to verbal or biased narrations that are characteristic of other unobtrusive measures. However, Rao et al. (2017) contradicted the authors stance that observation can address some obtrusive challenges. The study showed that the analysis of results from meta-analyses is subject to misinterpretation and misapplication that may lead to data errors.

Conclusion

The unobtrusive approach is a strategy used to deflect artificial behaviors of study subjects when they are knowledgeable of the fact that they are being surveyed. The major types of unobtrusive methods include physical trace analysis, simple observation, simulation, archives/existing data, and disguised observation. Each of these unobtrusive methods has its strengths and limitations. Researchers should always strive to combine multiple unobtrusive measures to add diversity to their research, answer hypothetical questions, build their case, and identify criminal trends and patterns.

References

Rao, G., Lopez-Jimenez, F., Boyd, J., DAmico, F., Durant, N. H., Hlatky, M. A., & Wessel, J. (2017). Methodological standards for meta-analyses and qualitative systematic reviews of cardiac prevention and treatment studies: a scientific statement from the American Heart Association. Circulation, 136(10), e172 e194.

Roberts, K., Dowell, A., & Nie, J.-B. (2019). Attempting rigour and replicability in thematic analysis of qualitative research data; a case study of codebook development. BMC Medical Research Methodology, 19(66), 1 8.

Click Here To Order Now!

Analyzing Articles on Data Collection Using Unobtrusive Measures

Do you need this or any other assignment done for you from scratch?

We have qualified writers to help you.

We assure you a quality paper that is 100% free from plagiarism and AI.

You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)