in 700 words Give a research discussion on the key finds and give implications relation them to other peoples research work to The sample size(N) of 164 , the good accessibility has a mean attendance of 7.79, and the poor accessibility(N=69) covers the m

**Research Discussion on Accessibility and Attendance Rates in Healthcare Facilities** The findings from the study indicate a noteworthy exploration of the relationship between accessibility to healthcare facilities and attendance rates. With a sample size of 164, the data reveal that individuals with good accessibility have a mean attendance rate of 7.79, while those with poor accessibility exhibit a mean attendance of 7.72. The p-value calculated at 0.062 suggests that, although there appears to be a difference in attendance rates between the two groups, this difference does not reach statistical significance, as it exceeds the conventional cutoff of 0.05. This implies that while accessibility plays a role in influencing attendance, the relationship is not strong enough to warrant definitive conclusions based on the data provided. These observations align with existing literature that emphasizes the significance of proximity to health facilities in determining healthcare-seeking behavior. Research conducted by McLafferty (2003) and more recent studies (Gibson et al., 2020) have established similar patterns: individuals residing closer to healthcare services tend to engage more frequently with these services. This supports the underlying assumption of our study that “the nearer the community to the health facility, the higher the attendance rate and vice versa.” The overarching conclusion drawn from such research is that geographic accessibility significantly impacts health outcomes by facilitating timely access to necessary medical interventions. Furthermore, the lack of statistical significance in this study invites further scrutiny and consideration of other confounding factors that may influence attendance rates. Factors such as socioeconomic status, transportation availability, and health literacy may also impact an individual’s ability to access healthcare. A study by Gaskin et al. (2012) highlighted how these variables can mediate the relationship between geographic accessibility and healthcare utilization. As such, the current research could benefit from a multivariate analysis to assess how these additional factors interact with accessibility, thereby providing a more comprehensive understanding of attendance rates. Moreover, the small difference between the mean attendance rates (0.07) raises questions about the practical significance of this finding. While the statistical analysis does not show conclusive evidence, the slight variation suggests that good accessibility may lead to improved attendance, albeit marginally. This aligns with the findings of Ricketts (2000), who argued that while access is critical, the quality of services and patient experiences is equally vital to encourage regular attendance. Consequently, future research could include qualitative methods such as interviews to capture patient perceptions around accessibility and the quality of care received, thereby enriching the quantitative findings with contextual insights. The implications of these findings are considerable for healthcare policy and planning. Acknowledging that accessibility can enhance attendance rates, stakeholders should prioritize investments in transportation services and strategically located health facilities in underserved communities. For instance, as Bradley et al. (2002) demonstrated, transportation barriers disproportionately affect low-income populations, emphasizing the need for targeted interventions to bridge these gaps. Effective solutions may include mobile health clinics or telemedicine options, particularly in regions where physical accessibility remains a challenge. Moreover, the statistical p-value of 0.062 opens up a dialogue about the standard thresholds used to denote significance in health research. Traditionally, the 0.05 cut-off is employed, but some scholars argue for a more nuanced interpretation of p-values to avoid discarding valuable information that may not meet rigid statistical criteria (Amrhein et al., 2019). This validates a call for more comprehensive analytical frameworks in future studies that accommodate the complexities of health data. In conclusion, while the current study finds that good accessibility is associated with higher attendance rates, the differences observed did not reach statistical significance, indicating that further research is warranted. Integrating qualitative approaches, considering additional confounding factors, and exploring practical implications for policy change are relevant steps moving forward. This research reinforces the notion that accessibility is a critical component of public health but highlights the need for a multifaceted approach to fully understand the intricacies of healthcare utilization.