| Title |
Examining the role of a community coalition in facilitating policy and environmental changes to promote physical activity: the case of Get Fit Kaua'i
|
|---|---|
| Published in |
Translational Behavioral Medicine, December 2015
|
| DOI | 10.1007/s13142-015-0379-z |
| Pubmed ID | |
| Authors |
Lehua B. Choy, Jay E. Maddock, Beverley Brody, Katherine L. Richards, Kathryn L. Braun |
| Abstract |
Community coalitions help to generate policy and environmental changes that address community health problems. This qualitative study examined how one community coalition, Get Fit Kaua'i, catalyzed built environment (BE) policy and infrastructure changes in a rural county in Hawai'i. The purpose was to develop a theory that explained the process by which the community coalition facilitated BE changes to support physical activity. Using a grounded theory approach, semi-structured interviews were conducted with a purposeful sample of 25 stakeholders engaged in the coalition's BE activities. The model to emerge from the coalition interviews consisted of five phases: (1) coalition formation, (2) capacity building, (3) policy development, (4) policy passage, and (5) policy implementation. Community context influenced all of these phases. Although community context limits generalizability, other community coalitions pursuing BE changes can learn from the process of the coalition under study. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 66 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 26% |
| Student > Master | 9 | 14% |
| Student > Doctoral Student | 7 | 11% |
| Student > Ph. D. Student | 6 | 9% |
| Student > Bachelor | 3 | 5% |
| Other | 8 | 12% |
| Unknown | 16 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 12 | 18% |
| Social Sciences | 9 | 14% |
| Medicine and Dentistry | 8 | 12% |
| Agricultural and Biological Sciences | 4 | 6% |
| Psychology | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 23 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 December 2015.
All research outputs
#13,961,191
of 22,836,570 outputs
Outputs from Translational Behavioral Medicine
#646
of 990 outputs
Outputs of similar age
#197,817
of 390,592 outputs
Outputs of similar age from Translational Behavioral Medicine
#19
of 30 outputs
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