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Factor analysis: When there are many interdependent survey responses to correlate and analyze, the data must be reduced into smaller sets of three to five factors. For instance, when studying a group of women their characteristics could include height, weight, hobbies, interests and activities. Factor analysis would reduce the five characteristics into two: size, combining height and weight and lifestyle, combining hobbies, interests and activities.
In short factor analysis is a way to take a mass data and shrinking in to a smaller data set that is more manageable and more understandable.
It is used to create a set of variables for similar items in the set (these sets of variables are called dimensions). It can be a very useful tool for complex set of data involving psychological, studies, socioeconomic status and more involved concepts.
multilevel analysis: Many kinds of data, including observational data collection in the human and biological sciences, have a hierarchical or clustered structure. For example, children with same parents tend to be more alike in their physical and mental characteristics than individual at random from population at large. Individual may be further nested within geographical areas or institutions such as schools or employers. Multilevel data also arise in longitudinal studies where an individual response over time are correlated with each other. Multilevel models recognize the existence of such data hierarchies by allowing for residual components at each level in the hierarchy example a two-level model which allows for grouping of child outcomes within schools would include residuals at the child and school level.
Multilevel models can also be used to non- hierarchical structures. For example, children might be nested within a cross classification of neighborhoods or residence and schools.
Multilevel models have been used in education research or geographical research, to estimate separately the variance between pupils within the same school, and the variance between schools. In psychological applications, the multiple level are items is an instrument, individuals and families. In sociological applications, multilevel models are used to examine individuals embedded within regions or countries. In organizational psychology research data from individuals must often be nested within teams or other functional units.
Ans 2) The adults for instance are the primary audience for information on the quality of Medicare plans. Also, some sponsors start out with well-defined target audience example patients with diabetes and then determine what information would be useful to them. While some primary audiences are fairly narrow example the employees of a specific set of employers or patients with a specific health condition. Your primary audience may be very broad e.g. all consumers in the state. One key downside of a broad audience is that it is hard to design a report that works for everyone. The most significant audience could be the segment that represents
- The most motivated readers
- The readers most in need of the information
- The readers that wield the most influence.
If your primary audience is people with Medicare, secondary audiences include the adult children, who may be helping their parents make health care decisions, or the insurance counselling services that help beneficiaries identify and understand their options. If you are a business coalition producing a report on behalf of member employers, the health benefits managers at those companies are an important secondary audience for information aimed at the employees. Physicians are often a secondary audience for quality reports on hospitals or nursing homes.
Methods used to communicate research result to audiences:
Communication techniques: Government agencies and institutions, advocacy groups, media organizations, researchers, and other interested stakeholders can all carry out communication activities. They use various techniques to communicate evidence so that target audiences can understand it better. Hence communication techniques fall into the broad area of health communication and focus on making evidence interpretable, persuasive, and actionable.
Dissemination is the targeted distribution of information and intervention materials to a specific public health or clinical practice audience. The intent is to spread knowledge and associated evidence-based interventions. Dissemination has several very broad goals 1) to increase the reach of evidence 2) to increase people motivation to use and apply evidence. 3) to increase people ability to use and apply evidence.
Uncertainty is inherent in health and health care evidence and can limit its use. Uncertainty creates multiple challenges, including difficulties 1) determining whether preventive services and treatments should be implemented in clinical practice. 2) determining for whom in what settings preventive services and treatments should be implemented 3) communicating evidence so that consumers can make informed decisions. By optimizing the presentation of uncertainty, evidence, creators, synthesizers, and disseminators can enable people to make the best possible decisions.
Strategies to disseminate evidence that will:
- Increase reach of the evidence example telephone: postal mail/email; electronic/digital media, social media,, mass, media: interpersonal outreach.
- Increase people ability to use and apply the evidence (example opinion leaders, champions, social networks)