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Feasibility And Validity Of Research

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Feasibility and Validity Notwithstanding the importance of such studies, they’re not void of challenges given the complex nature of the behavior. Therefore, considerable attention was applied to the issue of feasibility to include the length of study, ethical constraints (see Methodology), respondent cooperation, and research cost (Trochim, Donnelly, & Arora, 2016). In efforts to avert such concerns without compromising the sought after qualitative and quantitative data, it was pivotal to identify the target audience, as well as secure access to this very specific audience. In securing the cooperation from the owners of local gay bars/nightclubs, we have unlimited and free access to the desired audience. Thus, the length of time to…show more content…
To that end, change behavior advances individuals in the direction of not only safe sexual practices but also improved sexual health. Methodology As alerted to previously, Metro Phoenix has a lesbian, gay, bisexual, and transgender (LGBT) population exceeding 63,222, of which 49 percent or 30,978 identify as MSM (ADHS, 2015). Thus, the theoretical population exceeds 30,978 (63,222 x 49% = 30,978); however, access constraints make it impossible to survey all MSM residing in MP. Therefore, it became necessary to determine an appropriate sample size, a task achieved by calculating the MSM population at 30,978 (rounded to 30,980), a confidence level of 99 percent, and a two percent margin of error, the required sample totals 3,658. However, when factoring in an estimated response rate of 50 percent, 7,316 MSM must be approached for participation to achieve the necessary sample size based on the expected response rate. Important to note, if researching the expected frequency of behavior alone, the sample size drops to 1,980; however, given this is a two-fold cross-sectional study (expected frequency and attitudes) it requires the larger sample. When considering the survey design and research question this method avoids saturation while procuring rich (quality) and thick (quantity) data, which is multifaceted, detailed, intricate, and nuanced (Fusch & Ness, 2015).
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