Annotated Bibliography, Social Science Assignment homework Help

  

Annotated BibliographySubmit: Annotated BibliographyThis week, you will submit the annotated bibliography introduced in Week 3.An annotated bibliography is a document containing selected sources accompanied by a respective annotation. Each annotation consists of a summary, analysis, and application for the purpose of conveying the relevance and value of the selected source. As such, annotations demonstrate a writer’s critical thinking about and authority on the topic represented in the sources.In preparation for your own future research, an annotated bibliography provides a background for understanding a portion of the existing literature on a particular topic. It is also a useful precursor for gathering sources in preparation for writing a subsequent literature review.The assignment:Locate six articles on a research topic of your interest—two quantitative research articles, two qualitative research articles, and two mixed methods research articles—published in peer-reviewed journals.Prepare an annotated bibliography that includes the following:A one-paragraph introduction that provides context for why you selected the research articles you did.A reference list entry in APA Style for each of the six articles that follows proper formatting. Follow each reference list entry with a three-paragraph annotation that includes:A summaryAn analysisAn application as illustrated in this exampleA one-paragraph conclusion that presents a synthesis of the six articles.Format your annotated bibliography in Times New Roman, 12-point font, double-spaced. A separate References list page is not needed for this assignment.Submit your Annotated Bibliography by Day 7.                                                                                     My Annotated bibliography introduction from Week 3.As a Health and PE teacher for the past fifteen years, I have noticed a decline in young people’s interest to live a healthy, active lifestyle.  I am interested in researching ways to motivate students to become vested in life-long health and fitness habits, especially in this digital age.Existing DatasetsOften researchers are not aware of the rich amount of existing data to support their research. Within our site, we want to support you in your efforts to explore these resources. We have listed some resources below to help you get started in considering and exploring secondary data.Tutorial on Secondary Data Analysis Accessing versus generating research dataSources of Data for ResearchWhat is the Participant Pool?The Participant Pool is a virtual bulletin board that connects researchers to participants. Walden researchers can post their studies on the site and those members of the Walden community who are interested in participating in research can visit the site to see if there are any studies in which they would like to participate. It is a great resource not only for researchers, as it provides access to a very diverse community, but also to participants as they have the opportunity to learn about research in general in addition to seeing the research being done by students and faculty within the university.The following self-paced tutorial provides an overview of the Participant Pool, explaining how both participants and researchers can use the site: Participant Pool (Students)Participant Pool (Faculty Only)Q. How do I find an article that reports on research that uses a specific methodology?You can find articles that report on research that uses a specific methodology by using methodology terms as search keywords in the Library databases. Useful keywords include:type of study, e.g. quantitative or qualitativemethods used to gather data, e.g. survey or interviewdata analysis type, e.g. ANOVA or t-testthe terminology used to describe the results, e.g. statistically significantSee the following Quick Answers for more specific search advice: How do I find a qualitative article?How do I find a quantitative article?How do I find a mixed-method article?How do I find a meta-analysis article?How do I find an integrative review?How do I find a systematic review?More Information:How do I find original or empirical research?Use SAGE Research Methods Online to learn more about methodology.Education Research: Methodology.Basics of Annotated BibliographiesAn annotated bibliography is a combination of the words annotation and bibliography. An annotation is a set of notes, comments, or critiques. A bibliography is the list of references that helps a reader identify sources of information. An annotated bibliography is a list of references that not only identifies the sources of information but also includes information such as a summary, a critique or analysis, and an application of those sources’ information.Review our resources on the following pages for more information about each component of an annotated bibliography. As always, read the instructions and any examples in your assignment carefully; some of what follows might not be required for your particular course.Components of an Annotated EntryDownload the following sample to see the components of an annotated bibliography. Follow the links to more information on formatting, summary, critique/analysis, application, and example in the left sidebar menu. Annotated Bibliography Sample DocumentA sample of an annotated bibliography illustrating its various components.The Last Article – Mixed Method 2 – Could not download this article!!!Adoption Decisions and Implementation  of a Community-Based Physical Activity  Program: A Mixed Methods StudySamantha M. Downey, BSc1 Joan Wages, MS2 Sharolyn Flaming Jackson,MS3 Paul A. Estabrooks, PhD1The purpose of this study was to determine the attributes of a community physical activity (PA) program that Kansas State Research & Extension System agents considered in the adoption decision-making process (DMP) and their understanding of evidence-based program principles. Ninety-nine percent of the eligible agents completed a survey that included quantitative and qualitative assessments of program attributes, delivery, and adaptations. The community PA program’s effectiveness, compatibility within the system, high reach, and ease of delivery most influenced the DMP. Success in other counties was also indicated as influential in the DMP by those who decided to deliver the program after its initial year. Concepts of group dynamics were accurately identified and adaptations were consistent with these principles. The results indicate that agents consider multiple factors during the adoption DMP for a PA program and are able to articulate and propose adaptations that align with the evidence-based principles.BACKGROUND The public health benefits of physical activity (PA) are abundant: PA reduces the risk of premature death, coronary heart disease, diabetes, and high blood pressure (Centers for Disease Control, 1996; Macera, Hootman, & Sniezek, 2003). At the population level, a relatively small change in PA for sedentary individuals can produce large reductions in disease risk (Blair, LaMonte, & Nichaman, 2004). Still, relatively few adults participate in the recommended amount of PA (<50%; Brownson, Boehmer, & Luke, 2005). The combined influence of the risk reduction properties of PA and the low prevalence has resulted in a large number of intervention studies that target increased PA. For example, the Community Guide for Preventive Services reviewed the body of work on PA interventions and strongly recommended community-wide interventions that include social support strategies to increase PA (Kahn et al., 2002). Yet there is little evidence that these programs have been translated into sustained practice (Glasgow, Klesges, Dzewaltowski, Bull, & Estabrooks, 2004). It has been suggested that the information necessary to determine the efficacy of a PA intervention may not be the same information that is used by community health professionals when deciding what programs, policies, or practices are implemented (Glasgow & Estabrooks, 2006). Indeed, there is a paucity of literature that examines the factors that could facilitate PA program adoption and delivery. Although there is some information on the personal characteristics of those who adopt versus those who do not adopt PA programs (Estabrooks, Bradshaw, Fox, Berg, & Dzewaltowski, 2004), there is no information, to our knowledge, that documents the attributes of PA interventions that could either facilitate or discourage adoption. Roger’s diffusion of innovations theory describes general attributes of interventions (i.e., innovations) that can either speed or slow adoption (Rogers, 2003). These characteristics include relative advantage; ease of implementation; compatibility with the systemic structure, mission, and values; and observability. Although these attributes may be important during the decision-making process (DMP), understanding the underlying functioning principles of any evidence-based program is critical to ensure that any adaptations considered during implementation do not have the unintended consequence of reducing effectiveness (Rogers, 2003). As defined by Rogers, a program’s underlying functioning principles refers to the processes by which the program achieves its effect. The purpose of this study was to determine (a) the perceptions of the attributes of an evidence-based PA program held by those who are intended to deliver the program (i.e., Cooperative Extension Agents), (b) which attributes were considered in the DMP to deliver the program, (c) potential differences between early adopters and those who adopted the program after its initial year, and (d) adopting agents’ understanding of the underlying principles of the program and if proposed adaptations aligned with those principles.METHOD Design This mixed methods study was completed within the Cooperative Extension System (CES) associated with land-grant universities. CES is available in every U.S. state and territory and provides a diffusion system with the potential to reach a large proportion of the population (United States Department of Agriculture, 2010). Kansas State Research and Extension introduced a PA program called Walk Kansas in 2002 (Estabrooks, Bradshaw, Dzewaltowski, & Smith-Ray, 2008). Approx imately 50% of the counties in Kansas offered the program during the 1st year of implementation, and by 2006 more than 90% of the counties offered the program (Estabrooks et al., 2008). Family and Consumer Science (FCS) agents were responsible for adopting and implementing the 8-week walking program. At the conclusion of Walk Kansas 2007, county agents were given a study description and asked to complete a brief survey. The survey assessed perceptions of Walk Kansas, the characteristics of the program that lead to the adoption decision, and understanding of the underlying functioning principles of the program. The study was approved by the Kansas State University IRB.ProgramWalk Kansas was developed using principles from group dynamics and social cognitive theory (Estabrooks et al., 2008). Specifically, the program was developed based on Carron and Spink’s (1993) team-building model, which proposes that PA participation is increased through improving group cohesion, targeting group processes such as interaction and communication, cooperation and friendly competition, developing a sense of distinctiveness within groups, and facilitating a group structure that includes norms and goals for participation (Estabrooks, 2008). Walk Kansas recruitment involved inviting teams, rather than individuals, to participate in the program. Volunteer team captains recruited five other team members with the group goal to collectively walk the distance of Kansas over an 8-week period. To achieve the group goal, the participants, on average, would complete 30 minutes of moderate PA 5 days per week—the recommended guidelines at the time of program development. Goal setting theory-based principles used in program development include the provision of health education information (weekly newsletters) and weekly feedback on goal achievement (Estabrooks et al., 2008).SampleIn 2007 there were 97 FCS agents serving 105 counties in the state of Kansas who had the responsibility of addressing health-related needs of the population. Ninety-six of the 97 FCS agents within the Kansas State University Research and Extension System completed the study. All had delivered Walk Kansas at least once. Thirty-five agents delivered the program for 6 years and were considered early adopters, whereas the remainder of the agents began delivery after the initial year of the program. Only a small minority had delivered the program only 1 or 2 years (<10%). All agents were women aged, on average, between 40 and 50 years, and more than 95% of the extension agents were Caucasian.MeasuresYears of program delivery. Agents were asked to indicate the years that they had delivered Walk Kansas. The range of possible responses was 0 to 6 years. Agent reports were confirmed by archival participant enrollment records that demonstrated all agents reported accurately.Program characteristics attributed to Walk Kansas. Six attributes were presented in a checklist format. Agents were encouraged to select all attributes that applied when considering the Walk Kansas program. The characteristics were based on Rogers’ proposed attributes and included: (a) Walk Kansas is easy to deliver (i.e., ease of delivery), (b) Walk Kansas is better than most other community PA programs (i.e., relative advantage), (c) Walk Kansas helps people start being more active and stick with it even after the program is finished (i.e., observability of effectiveness), (d) Walk Kansas fits the mission of Kansas State Research and Extension (i.e., compatibility with mission), (e) Walk Kansas attracts more county residents than any other Extension program (i.e., relative advantage related to reach), and (f) Walk Kansas was adapted from other programs to work specifically in Kansas (i.e., compatibility with structure).Program characteristics used in the decision-making process. The six attributes were again presented in a checklist format. Agents were encouraged to select all attributes that they considered when making the decision to offer Walk Kansas. A seventh category was added to this checklist: if the impact of the program in other counties influenced their DMP.Understanding functioning principles. Both quantitative and qualitative questions were used to determine agent understanding of the program’s functioning principles. Quantitative questions included asking agents if the program would work as well at increasing PA without the newsletter (i.e., no feedback), as individuals without the team (i.e., no group dynamics principles), and when increasing the team size to 8 or greater (i.e., altering the goal of meeting PA recommendation through equal distribution of walking the state of Kansas). In addition, agents were asked to indicate how frequently they provided feedback and by what method they provided feedback to participants. Questions to elicit open-ended responses were: In your opinion, what is it about Walk Kansas that helps people to do more PA? And please list suggestions that you have to make Walk Kansas a better program. These questions were used to assess agent understanding of the functioning principles and to determine if proposed changes were consistent with those principles.AnalysisThe proportion of agents who indicated the presence of a given attribute within Walk Kansas and who considered a given attribute in the DMP were calculated. Chi-squared analyses were used to determine if any proportional differences existed between agents who adopted Walk Kansas in the initial year when compared to those who began delivering it in subsequent years. Responses to the open-ended questions examining the understanding of functioning principles were reduced to meaning units (a word, phrase, or paragraph with a single meaning). Meaning units were grouped into categories, which were then grouped into themes. The emergent themes assessed what aspects of Walk Kansas increase PA (i.e., functioning principles) and suggestions for improving the program.RESULTSThe median number of characteristics attributed to Walk Kansas was 4, whereas the median number of characteristics used in the DMP was 3. The most endorsed characteristic of the program was that it was effective at increasing and maintaining PA (89%), and this is also the factor that the highest proportion of agents considered when deciding to deliver the program (77%). The compatibility of the program for Extension was the next most frequently selected attribute of Walk Kansas (83%), and this was also used in the DMP 73% of the time. Ease of delivery and a strong reach were identified as attributes of Walk Kansas by 70% and 69% of agents, respectively. In addition, about 60% considered both of these attributes in the DMP. Only the general relative advantage of the program (i.e., better than most other PA programs) and the specific adaptation for the geographic region were not considered by the majority of agents during the adoption DMP (40% and 25%, respectively). Figure 1, above, depicts attributes that the agents felt were indicative of Walk Kansas comparing early adopters to those who adopted after the 1st year. The figure demonstrates that a higher proportion of early adopters perceived that most of the attributes were present when compared to later adopters; however, only the proportion that identified that Walk Kansas had superior reach was significant (χ2 = 6.15, p = .01). Figure 2 depicts the proportion of early versus later adopters that considered each attribute as part of the adoption DMP. In this case, a significantly higher proportion of early adopters considered the reach of the program (χ2 = 6.76, p < .01) and its effectiveness (although,  this proportional difference was only marginally significant; χ2 = 2.45, p < .10). In contrast, but perhaps not surprisingly, a higher proportion of those who adopted the program after the 1st year indicated that seeing the impact in other counties influenced their decision (χ2 = 7.67, p = .01). When agents were asked if the program would work as well at increasing PA without the newsletter, as individuals without the team, and increasing the team size to eight or greater, 26%, 16%, and 38% of the agents agreed, respectively. Sixty-three percent of the agents provided weekly feedback, and the highest proportion of agents provided that feedback through e-mail and regular mail. Agents were asked about the mode of delivery for the newsletters and an overwhelming majority sent both hard copies and electronic versions (73%). Only 4% of the agents did not send newsletters. In terms of feedback on the teams’ progress, the modes used were e-mail or regular mail (50%), e-mail only (7%), regular mail only (5%), and website only (38%). However, some agents who indicated website only also indicated “provided no feedback” (20%). The mode by which agents gave feedback (i.e., website or e-mail) was significantly related to the frequency in which they gave their feedback (χ2 = 43.45, p < .001). If an agent simply directed participants to the website the frequency of “delivery” was low; however, if an agent provided hard copies or electronic versions, they were typically more frequent (i.e., weekly). Agents provided 223 meaning units in response to the question of factors that lead to Walk Kansas increasing participant PA. Of those, 164 responses referred to group concepts such as group cohesion, team goals, interactions and communication, competition, and norms. The remaining meaning units reflected aspects of the program that were related to specific program features, compatibility with busy participant lifestyles, and advertising. Table 1 includes the derived themes and categories with the number of meaning units provided for each and includes example meaning units for each category. The theme of group cohesion included the two most frequently identified categories—that participants felt accountable to the team and that the general team concept lead to the program’s success in changing PA. Although providing regular feedback was a key feature of the program, only 9 meaning units explicitly identified this as a key feature for increasing PA. Agents also provided 76 meaning units in response to the question of potential adaptations that could make the program better (Table 2). There were a number of general and specific responses related to ensuring that the program was dynamic and changed with the times to ensure continued relevance in the community (n = 30), such as changing the newsletter materials regularly, increasing media support, and adding new program features. In terms of adaptations, the primary area identified was the improvement of tools that helped speed or ease the effort of implementation (n = 22), such as reducing the time to deliver the program and improve automated features for tracking and feedback. There were also a small number of responses that highlighted program features that should be maintained (n = 11), which included the ease of program delivery and program T-shirts. Finally, there were a number of minor adaptations suggested (n = 6) that included both shortening and lengthening of the program, the addition of strength training more explicitly, and adding incentives.DISCUSSIONThe quantitative findings of our investigation demonstrated that the majority of cooperative extension agents believed that Walk Kansas was effective at increasing and maintaining PA, compatible with the mission of Kansas State Research and Extension, easy to deliver, and able to reach a large number of participants. In addition, information on each of these attributes was used by a majority of the agents in the DMP. Perhaps surprisingly, the general relative advantage of the program (i.e., better than most other PA programs) and the fact that the program was adapted for the geographic region were not considered by the majority of agents during the adoption DMP. Furthermore, early adopters were significantly more likely to consider the program’s potential reach when deciding whether or not to deliver the program. Finally, based on the quantitative responses on the frequency and delivery of feedback, it appears as though a high percentage of the agents provided some level of feedback to the participants and only a minority did not. Similarly, the qualitative responses suggest that the agents understood the basic functioning principles of the program and identified more program aspects that increase activity when compared to areas in need of improvement.These findings lead to a number of generalizations. First, delivery agents consider a number of program attributes in addition to the degree to which the program is effective; however, effectiveness is a prevalent consideration across agents suggesting that evidence is an important, but perhaps insufficient, criterion for adoption. Second, early adopters are more likely to use evidence of reach in addition to effectiveness in the DMP whereas those who adopt later are more likely to be convinced by observing the success of the program in other counties. Third, the proportion of agents that perceived a given attribute as consistent with Walk Kansas was always higher than the proportion of agents that used a given attribute in the DMP; thus, the perceived presence of a program attribute, even those that are thought to speed adoption, may not be influential during the DMP for all agents. The results suggest that the following attributes may enhance the likelihood that a PA intervention will be adopted within a community setting such as Cooperative Extension. One, an overwhelming majority of agents considered the effectiveness and potential reach of the program when making the adoption decision—indicative of a public health view. From a research perspective, this finding adds validity to the school of thought that both reach and effectiveness are critical indicators of translation of research into practice (Glasgow et al., 2004). Furthermore, our finding that differences in attributes considered in the DMP by early adopters and later adopters indicates that different marketing strategies to encourage agent adoption should be used at different times during the adoption process. Two, communicating information on the compatibility of the program to the organizational mission of potential delivery agencies and the ease of delivery may also be important indicators of adoption. These results reflect the characteristics that adopters found important in other behavioral intervention studies ranging from smoking cessation to nutritional interventions (Brownson et al., 2007; DeCherney, 1999; Hoelscher et al., 2001; Israel et al., 2006; Levine et al., 2006; Schrijvers, Oudendijk, & de Vries, 2003; Tripp-Reimer & Doebbeling, 2004). Once a program is adopted, fidelity to the underlying functioning principles is necessary to ensure that the program is effective (Green, 1995). Our findings suggested that the agents were likely to identify group-based principles as key in the effectiveness of the program, but only about two thirds used the frequency of feedback prescribed for the program. From the group dynamics perspective, many of the meaning units aligned closely with Carron and Spink’s framework for PA interventions (Carron & Spink, 1993). Furthermore, only two meaning units were provided that suggested changes to the program that would be inconsistent with the group dynamics approach (e.g., make the program available for individuals without teams). However, this request, although inconsistent with the Walk Kansas framework, could indicate the need for an integration of an individually targeted evidence-based PA program that could be used to enhance the reach of the program. Adaptations to the program, although covering many disparate areas, also aligned with some of the characteristics identified by Rogers that would enhance adoption. Specifically, many of the comments were related to mechanisms that would make the program easier to deliver and appear to have an advantage in content over the previous year. This suggests that although the delivery of Walk Kansas includes substantially less time and effort to implement than many other evidence-based PA programs (Wilcox et al., 2008), there are still opportunities to reduce delivery agent workload to improve satisfaction and sustained delivery. We conducted this study to provide preliminary information on agent perceptions of a PA program, their DMP, and understanding of key functioning principles and, therefore, this study is not without limitations. First, the results are specific to a Cooperative Extension System and may not be generalizable to other program delivery systems. However, even with different structures across states it is likely that these results could be generalized to other Cooperative Extension Systems (Israel et al., 2006). Furthermore, as most community and clinical health care setting providers and practitioners have similar responsibilities (Eakin, Glasgow, & Riley, 2000; Eakin, Lawler, Vandelanotte, & Owen, 2007), it is likely that the decision to adopt new programs, policies, or practices would follow a similar DMP. Second, the study included retrospective recall of a DMP that occurred, for some agents, a number of years previously and could be influenced by the success of the program in Kansas. Third, the attributes were identified using simple dichotomous response sets and it is likely that consideration of these variables and relative weighting are not clearly reflected by the proportion of agents that indicate an attribute was used in the DMP. Future studies should examine attributes using measures that can detect the degree to which each piece of information contributed to the adoption decision.CONCLUSIONThe results provide an indication of the broad range of program characteristics important in the adoption of community-based PA programs and demonstrate that marketing to delivery agents for early adoption of community PA programs may include a focus (e.g., highlight effectiveness and reach) different from when marketing in years after a program has been initially implemented (e.g., focus on results of peer implementation). Also, within the cooperative extension system, agents are able to communicate the underlying principles of a group dynamics–based intervention and are unlikely to make adaptations that are inconsistent with those principles. To better assess and predict characteristics that will facilitate PA program adoption, future studies should assess delivery agent perceptions of program characteristics at the beginning and periodically throughout the adoption  DMP. These assessments could then be used to develop predictive models for program adoption, thereby informing the program development process focusing on potential mediators of the adoption process.REFERENCES Blair, S. N., LaMonte, M. K., & Nichaman, M. Z. (2004). The evolution of physical activity recommendations: How much is enough? American Journal of Clinical Nutrition, 79, 913S-920S. Brownson, R. C., Boehmer, T. K., & Luke, D. A. (2005). Declining rates of physical activity in the United States: What are the contributors? Annual Review of Public Health, 26, 421-443. Brownson, R. C., Ballew, P., Dieffenderfer, B., Haire-Joshu, D., Heath, G., Kreuter, M. W., & Myers, B. A. (2007). Evidence-based interventions to promote physical activity: What contributes to dissemination by state health departments. American Journal of Preventive Medicine, 33(1 Suppl.), S66-S73. Carron, A. V., & Spink, K. S. (1993). Team building in an exercise setting. Sport Psychology, 7, 8-18. Centers for Disease Control and Prevention. (1996). Physical activity and health: At-A-Glance. A Report of the Surgeon General. Atlanta, GA: Author. DeCherney, G. S. (1999). Accelerating acceptance. Physician Executive, 25, 32-38. Eakin, E., Lawler, S., Vandelanotte, C., & Owen, N. (2007). Telephone interventions for physical activity and dietary behavior change: A systematic review. American Journal of Preventive Medicine, 32, 419-434. Eakin, E. G., Glasgow, R. E., & Riley, K. M. (2000). Review of primary care-based physical activity intervention studies: Effectiveness and implications for practice and future research. Journal of Family Practice, 49, 158-168. Estabrooks, P. A. (2008). Group integration interventions in exercise: Theory, practice and future directions. In M. Beauchamp & M. A. Eys (Eds.), Group dynamics in exercise and sport psychology: Contemporary themes (pp. 141-156). London, UK: Routledge. Estabrooks, P., Bradshaw, M., Fox, E., Berg, J., & Dzewaltowski, D. A. (2004). The relationships between delivery agents’ physical activity level and the likelihood of implementing a physical activity program. American Journal of Health Promotion, 18, 350-353. Estabrooks, P. A., Bradshaw, M., Dzewaltowski, D. A., & SmithRay, R. L. (2008). Determining the impact of Walk Kansas: Applying a team-building approach to community physical activity promotion. Annals of Behavioral Medicine, 36, 1-12. Retrieved from http://www.springerlink.com/content/w21404885lwx3424/ fulltext.pdfEstabrooks, P. A. & Glasgow, R., (2006). Translating effective clinicbased physical activity interventions into practice. American Journal of Preventive Medicine, 31(4 Suppl.), S45-S56. Glasgow, R. E., Klesges, L. M., Dzewaltowski, D. A., Bull, S. S., & Estabrooks, P. (2004). The future of health behavior change research: What is needed to improve translation of research into health promotion practice? Annals of Behavioral Medicine, 27, 3-12. Green, L. W. (1995). Participatory research in health promotion. Ontario, Canada: Royal Society of Canada. Hoelscher, D. M., Kelder, S. H., Murray, N., Cribb, P. W., Conroy, J., & Parcel, G. S. (2001). Dissemination and Adoption of the Child and Adolescent Trial for Cardiovascular Health (CATCH): A case study in Texas. Journal of Public Health Management Practice, 7, 90-100. Israel, B. A., Krieger, J., Vlahov, D., Ciske, S., Foley, M., Fortin, P., . . . Tang, G. (2006). Challenges and facilitating factors in sustaining community-based participatory research partnerships: Lessons learned from the Detroit, New York City and Seattle Urban Research Centers. Journal of Urban Health, 83, 1022-1041. Kahn, E. B., Ramsey, L. A. T., Brownson, R. C., Heath, G. W., Howze

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