Getting Started: An Empirically Derived Logic Model for Age-Friendly Community Initiatives in the Early Planning Phase

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11 Scopus citations

Abstract

Age-friendly community initiatives (AFCIs) foster efforts across stakeholders to make localities more supportive and inclusive of older adults, and potentially better for residents of all ages. This study drew on in-depth interviews with leaders of nine newly forming AFCIs in northern New Jersey to develop an empirically based logic model for the initiatives in the early planning phase. The results obtained from a conventional content analysis indicated three main activities in the early planning phase: assessing the community; meeting; and communicating with stakeholders; and facilitating communitywide communications. These activities worked toward two outputs: increased understanding of aging in the community and more engaged stakeholders in aging. Participants described leveraging the contributions of lead staff, consultants, elected officials, organizational partners, volunteers, interns, funders, and other AFCIs to engage in their focal activities. Based on these findings, a logic model for AFCIs in the early planning phase is presented. AFCI leaders can draw on this model to evaluate AFCI processes and outcomes in their formative stages, as well as to strategically plan for the start of an AFCI within a given locality. Findings also suggest important directions for future research on the development of AFCIs and the community changes that they seek to influence.

Original languageEnglish (US)
Pages (from-to)295-312
Number of pages18
JournalJournal of Gerontological Social Work
Volume61
Issue number3
DOIs
StatePublished - Apr 3 2018

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Nursing (miscellaneous)

Keywords

  • Community
  • age-friendly
  • aging-friendly
  • community development
  • community intervention
  • community practice
  • evaluation
  • logic model
  • macro-practice
  • program theory
  • qualitative methods

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