A nurse and a community team are deciding on methods to use for data analysis to assist with prioritizing community needs. Which of the following data analysis methods uses a questionnaire?

Choice A reason: Establish one group that can focus on a shared vision
Establishing a group that focuses on a shared vision is crucial for overcoming barriers in community health initiatives. A shared vision helps align the goals and efforts of all team members, fostering collaboration and unity. When everyone is working towards the same objectives, it becomes easier to address challenges and implement effective solutions. This approach ensures that all members are committed to the same outcomes, enhancing the overall effectiveness of the initiatives.

Choice B reason: Allow for the division into subgroups based on cultural similarities
While recognizing cultural similarities can be beneficial, dividing the team into subgroups based on these similarities may lead to fragmentation and reduce the overall cohesiveness of the group. It is important to promote inclusivity and ensure that diverse perspectives are integrated into the planning and implementation process. This approach helps in addressing the needs of the entire community rather than focusing on specific cultural groups.

Choice C reason: Encourage the creation of subgroups based on similar values
Encouraging the creation of subgroups based on similar values can also lead to fragmentation. While shared values are important, it is essential to maintain a unified team that can work together towards common goals. Creating subgroups may result in isolated efforts that do not fully address the broader community needs. A cohesive team with diverse values can provide a more comprehensive approach to community health initiatives.

Choice D reason: Ensure the group is limited to members with similar professional backgrounds
Limiting the group to members with similar professional backgrounds can hinder the effectiveness of community health initiatives. A diverse team with varied professional expertise can offer a broader range of perspectives and solutions. Including members from different backgrounds ensures that all aspects of community health are considered, leading to more innovative and effective interventions. Collaboration among professionals from different fields can enhance the overall impact of the initiatives.

Choice A: Prevalence Rate
The prevalence rate measures the total number of cases of a disease or health condition in a population at a specific point in time or over a specified period. It is expressed as a proportion of the population. While useful for understanding the burden of disease, the prevalence rate does not provide information on the number of deaths, making it unsuitable for calculating mortality data.

Choice B: Case Fatality Rate
The case fatality rate (CFR) is the proportion of individuals diagnosed with a particular disease who die from that disease within a specified period. It is expressed as a percentage. While CFR provides insight into the severity of a disease, it does not give the overall number of deaths in a population, nor does it specify the age group affected.

Choice C: Age-Specific Mortality Rate
The age-specific mortality rate is the number of deaths in a specific age group per 100,000 population in that age group over a given period. This measure is ideal for calculating the number of deaths among school-age children, as it provides detailed mortality data specific to that age group. By using this rate, the nurse can accurately determine the mortality rate for school-age children in the county.

Choice D: Cause-Specific Mortality Rate
The cause-specific mortality rate is the number of deaths from a specific cause per 100,000 population in a given year. While this measure is useful for understanding the impact of specific diseases or conditions, it does not provide a comprehensive view of mortality across different age groups. Therefore, it is not the best choice for calculating the overall number of deaths among school-age children.