Assignment task:
With this plan, you are taking on far more than is recommended for this 8-week course. Did you listen to the lectures? I warn against thinking of all possible work you can do and instead focusing on the realistic. A self-controlled pre/post test examination of a single variable or maybe two is ideal. Stratified random sampling is beyond the scope of this course with all those variables. Generally we will study the whole population without evaluating those different criteria.
Various research methods could help assess the capabilities of Mental Health America programs aimed at reducing stigma and ensuring more people have access to mental health support. A mixed methods strategy can be suitable based on the complicated nature of mental health solutions and the necessity to capture quantitative and qualitative results.
A quasi-experimental design would be helpful for a program on reduction of stigma. This design will enable a comparison between places where MHA implements such projects and places where it does not, recognizing that randomization might not be possible in real life. Attitudes regarding mental illness could also be recorded before and after the intervention with the help of surveys and interviews (Fink, 2015). Those data would offer a mix of quantitative and qualitative findings on the change process. Such an approach is consistent with the evaluation question: "How effectively does MHA employ the strategies in reducing the public's stigma against persons with mental illness and discrimination against them?"
The program focused on improving the accessibility of mental healthcare requires the employment of the longitudinal study method. Many of the changes to the access algorithms would be assessed while measuring instant and long-term effects associated with the MHA's solutions (Torjesen, 2022). The design would help incorporate regular data collection points to help monitor changes in the utilization of the services, waiting times, and demographic reach. Such a strategy helps address the assessment question regarding the MHA's contribution to the improvement of access for hard-to-reach populations.
Stratified random sampling is the most functional technique in terms of sampling procedures. It helps ensure a balanced representation across all social strata, weighting more even marginalized ones, which has become the primary objective of the MHA (Fink, 2015). It could include stratification based on factors like age, income, location, and previous contact with mental health facilities to ensure the inclusion of all target population groups. The method helps ensure that the collected data represents different communities served by the MHA while helping maintain statistical validity.
For instance, in the evaluation of the stigma reduction program. The population is put under strata such as community features like urban/rural, socioeconomic status, and any previous exposure to mental health. It helps ensure the evaluation demonstrates the program's effects across the different community setups (Fink, 2015). Equally, in the case of a healthcare access program, stratifying groups could invite various geographical distances from healthcare services, having insurance or not, and how these factors vary with individuals to access care.
There are several benefits to stratified random sampling within this research. Most importantly, it offers accurate and representative data regarding how diverse subgroups respond to MHA's interventions, permitting more targeted program improvements. It is aligned with evidence-based strategy and supports the organizational objective of serving different populations successfully while at the same time ensuring the maintenance of ethical standards of assessment.
References:
Fink, A. (2015). Evaluation fundamentals: Insights into program effectiveness, quality, and value (3rd ed.). Thousand Oaks, CA: Sage.
Torjesen, I. (2022). Access to community mental health services continues to deteriorate, survey finds. BMJ: British Medical Journal (Online), 379, o2585.