Aim <p>To construct a competency index system for Community-Based Gerontological Nurse Specialists.</p> Background <p>Global population aging has created urgent demand for specialized geriatric nursing competencies, particularly in community settings. While international competency frameworks exist, a standardized competency index system for community-based gerontological nurse specialists (CGNS) that aligns with Chinese healthcare realities and policy priorities is lacking.</p> Methods <p>A literature review and semi-structured interviews were conducted to develop an initial framework. A two-round Delphi survey was employed to build the index system for Community-Based Gerontological Nurse Specialists.</p> Results <p>The final validated competency index system included 4 first-level indicators (knowledge, skills, abilities, motivation/traits), 13&#xa0;s-level indicators and 40 third-level indicators. The effective response rates of the two expert consultation rounds were 100%. The expert authority coefficients were 0.888. The coefficients of variation were 0.1192 and 0.0961, and the Kendall’s coefficient of concordance were 0.254 and 0.382, respectively (<i>P</i> &lt; 0.05).</p> Conclusion <p>The competency index system of community gerontological specialist nurses constructed through the competency onion model is scientific and practical, which can provide a reference for the training, assessment and evaluation of senior community geriatric nursing talents.</p>

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Construction of a competency index system for Community-Based Gerontological Nurse Specialists: a Delphi study

  • HuiFen Zhao,
  • Xiaolan Lai,
  • XinYu Li,
  • BingJie Chen,
  • Rong Hu,
  • Hong Li

摘要

Aim

To construct a competency index system for Community-Based Gerontological Nurse Specialists.

Background

Global population aging has created urgent demand for specialized geriatric nursing competencies, particularly in community settings. While international competency frameworks exist, a standardized competency index system for community-based gerontological nurse specialists (CGNS) that aligns with Chinese healthcare realities and policy priorities is lacking.

Methods

A literature review and semi-structured interviews were conducted to develop an initial framework. A two-round Delphi survey was employed to build the index system for Community-Based Gerontological Nurse Specialists.

Results

The final validated competency index system included 4 first-level indicators (knowledge, skills, abilities, motivation/traits), 13 s-level indicators and 40 third-level indicators. The effective response rates of the two expert consultation rounds were 100%. The expert authority coefficients were 0.888. The coefficients of variation were 0.1192 and 0.0961, and the Kendall’s coefficient of concordance were 0.254 and 0.382, respectively (P < 0.05).

Conclusion

The competency index system of community gerontological specialist nurses constructed through the competency onion model is scientific and practical, which can provide a reference for the training, assessment and evaluation of senior community geriatric nursing talents.