Overview
Issues with data privacy and cybersecurity are fast-expanding concerns that affect many different types of internet users. Cyberattacks and unauthorized data use, ranging from significant data breaches to individual account intrusions, put millions of people’s safety and privacy in danger every year. In countering these dangers, it is essential to comprehend user viewpoints, knowledge, attitudes, and real actions connected to cybersecurity and privacy. Therefore, it is important to understand what attitudes, actions, needs, and obstacles regular internet users have when it comes to implementing suggested online security and privacy measures.
Proposed Research Design and Methods
To begin with, the main method of data collection for this project will be one-on-one, remote, semi-structured interviews with between 30 and 50 adult internet users from various backgrounds. Through interviews, participants’ rich, detailed insights into their viewpoints and experiences may be gathered in their own words. In order to gather detailed user-centred data relevant to the study questions—which need “how” and “what” type investigations suggested for qualitative designs—a qualitative interview-based technique was judged to be the most suitable (Lobe et al., 2020). In addition, structured surveys or quantitative data could not easily gather firsthand narrative reports of user views and actions. Also, interviews will provide participants with the freedom and amount of information required to explain their ideas on cybersecurity and privacy, as well as their real practices, obstacles, and areas in need of development.
Theoretical Framework
The Theory of Planned Behavior (TPB) will serve as the conceptual framework and methods guide. TPB takes into account the ways in which attitudes toward a behaviour, arbitrary norms and standards, and perceived control affect intentions and behaviours. Again, these essential elements will support the interview process. Also, users’ knowledge, opinions, societal influences, and sense of control over cybersecurity and privacy safeguards will all be questioned. Feedback may be used to enhance adoption strategies and provide an explanation of current use levels (Alomari & Jenkins, 2021). The study’s applied aims are aligned with TPB’s assumption that correcting knowledge gaps or harmful attitudes might favourably influence behaviours.
Method of Sampling
Furthermore, adult internet users in the United States who are over 18 and come from a variety of backgrounds make up the target market. This demographic represents the dangerous landscape of cybersecurity for the general public. Besides, participants will be sought out throughout the country via advertisements on social media and online discussion boards. For example, Etikan et al. (2016) say that the non-probabilistic purposive sampling method lets you choose interesting people on purpose based on their age, gender, race or ethnicity, where they live, and other factors that take into account differences. According to Mason (2010), the sample size objective of 30–50 came about as a result of estimations found in qualitative methodological sources for approaching data saturation, which is the point at which gathering more data adds nothing to the interpretative value.
Procedures for Gathering Data
Moreover, Zoom software was used to conduct remote, 60-to-90-minute semi-structured video interviews with participants, which served as the main source of data. The interview methodology comprises open-ended questions on cybersecurity and privacy practices and attitudes that are designed around the main TPB factor categories (Kumar et al., 2020). In addition, inquiries pertaining to the goals of the study will provide depth and specifics (Etikan et al., 2016). In the event that permission is obtained, the sessions will be videotaped for later de-identified text transcription, coding, and analysis. Hence, by giving participants the opportunity to examine summaries of the results, member checking will also aid in the validation of interpretations.
Plan for Data Analysis
NVivo, a qualitative data analysis program, will be used to import the transcripts of the interviews. From there, inductive thematic coding will be utilized to categorize the replies in accordance with the main topic areas, emerging ideas, and analytical TPB frames (Elliott, 2018). Also, dialogue snippets are analyzed by repeatedly classifying them into core nodes that stand in for the user’s attitudes and beliefs, present actions or difficulties, outside influences, wishes, and suggestions. By comparing and synthesizing patterns across instances, one can find meta-themes pertaining to study issues about user habits, motives, and necessary actions. The frequency of themes will also be measured using descriptive statistics.
Moral Aspects to Take into Account
Nevertheless, institutional university approval ensures that participant consent processes adhere to ethical standards. Also, the confidentiality precautions that may be implemented in a remote setting, such as de-identified data and safe storage, will be explained to interview respondents (Lobe et al., 2020). Subjects are free to exit the research at any time or to skip any questions; participation is entirely optional. Again, the dangers are low, but people may feel uncomfortable talking about cybersecurity. If that happens, therapy recommendations will be given. Contributing knowledge to advance user welfare in terms of security and privacy is one benefit.
Possible Restrictions and Alleviations
Since this was a qualitative study, conclusions may only apply to other contexts with further research. Self-reported data may contain recollection errors or social desirability biases that lead respondents to give false information or withhold information; however, the anonymity of the data reduces this risk (Latkin et al., 2017). To optimize robustness, it would be best to triangulate these direct user stories with quantitative behaviour surveys from secondary cybersecurity research. Notwithstanding their drawbacks, unfiltered one-on-one interviews provide insightful, in-depth portraits of user orientations that are essential for the creation of downstream solutions.
In conclusion
To sum up, this suggested interview-based study strategy fulfils important preliminary phases of investigation that are meant to collect detailed user viewpoints and experiences in order to inform remedies regarding privacy and public cybersecurity concerns. Approximately 30 to 50 varied adult internet users participated in semi-structured remote interviews, which provide a rich qualitative technique for describing consumer attitudes, real-world activities, challenges, and demands. Multidimensional insights may show why some security measures are used or not used by directly asking firsthand, open-ended questions about use, attitudes, and motivations based on a well-known behavioural theory paradigm. Additionally, descriptive patterns that translate ideas into actions will highlight key leverage points for safety-promoting initiatives. Even though exploratory qualitative research cannot always be used to find answers that apply to everyone, this user-centred approach to research could help find important problems and factors that affect decisions that will help create custom solutions in future projects. Although it is beyond the present purview to verify particular theories, highlighting the decision-making processes gives security professionals and developers a solid foundation on which to operate in order to improve public welfare in relation to online risks. Additional integrations with data obtained through surveys or other triangulation techniques would strengthen these human-centred discoveries and boost support for significant cybersecurity initiatives. However, a solid understanding of user viewpoints serves as a sympathetic springboard for bringing about significant change in this area of concern.
References
ALOmari, M. O., & Jenkins, J. (2021). Exploring the attitudes of patients towards using the seha application (Telehealth) in Saudi Arabia during the coronavirus epidemic ABC Journal of Advanced Research, 10(1), 9–22.
Elliott, V. (2018) Think about the coding process in qualitative data analysis. Qualitative report, 23(11)
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling American Journal of Theoretical and Applied Statistics, 5(1), 1-4.
Kumar, S., Kumar, R. S., & Prabhu, M. G. N. (2020). sampling framework for personal interviews in qualitative research. PalArch’s Journal of Archaeology of Egypt/Egyptology, 17(7), 7102–714.
Latkin, C. A., Edwards, C., Davey-Rothwell, M. A., & Tobin, K. E. (2017). The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland. Addictive Behaviors, 73, 133–136.
Lobe, B., Morgan, D., & Hoffman, K. A. (2020). Qualitative data collection in an era of social distancing International journal of qualitative methods, 19, 1609406920937875
Mason, M. (2010, August). Sample size and saturation in PhD studies using qualitative interviews Forum qualitative Sozialforschung/Forum: qualitative social research (Vol. 11, No. 3).
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