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Psychometric properties of a new intake questionnaire for visually impaired young adults: The Participation and Activity Inventory for Young Adults (PAI-YA)

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  • Ellen Bernadette Maria Elsman
  • Gerardus Hermanus Maria Bartholomeus van Rens
  • Ruth Marie Antoinette van Nispen

Abstract

Background: To be able to identify and monitor personal needs and goals of visually impaired young adults before and during rehabilitation trajectories, the Participation and Activity for Young Adults (PAI-YA) was developed involving young adults (18–25 years) and professionals as stakeholders. The psychometric properties of this new patient-reported outcome measure were investigated in order to develop an improved version. Methods: Young adults registered at two low vision rehabilitation centers in the Netherlands were invited to complete the 141-item PAI-YA (n = 186) in a test-retest design. To select the best items for the PAI-YA, response frequencies were assessed and a graded response model (GRM) was fitted. Item reduction was informed by response frequencies, insufficient item information, and participants’ comments. Fit indices, item and person (theta) parameters were computed, after which known-group validity, concurrent validity, test-retest reliability and feasibility were studied. Results: Response frequencies, violation of assumptions and item information informed the elimination of 81 items, resulting in a unidimensional PAI-YA showing satisfactory fit to the GRM. Known-group validity showed significant differences for visual impairment, financial situation, sex, educational situation and employment situation. Concurrent validity with (scales of) other questionnaires showed moderate to strong expected correlations. Test-retest reliability was satisfactory for all items (kappa 0.47–0.87), as was agreement (63.1–92.0%). Four items and one response option were added to increase feasibility. Conclusions: This study contributes to the development and assessment of psychometric properties of the PAI-YA, which resulted in an improved 64-item version. Evidence was provided for construct validity, known-group validity, concurrent validity and test-retest reliability. These results are an important step in the development of a feasible instrument to investigate and monitor rehabilitation needs of visually impaired young adults, to structure the intake procedure at low vision rehabilitation services and to evaluate the effectiveness of rehabilitation.

Suggested Citation

  • Ellen Bernadette Maria Elsman & Gerardus Hermanus Maria Bartholomeus van Rens & Ruth Marie Antoinette van Nispen, 2018. "Psychometric properties of a new intake questionnaire for visually impaired young adults: The Participation and Activity Inventory for Young Adults (PAI-YA)," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-24, August.
    • Handle: RePEc:plo:pone00:0201701
    DOI: 10.1371/journal.pone.0201701
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    1. Robert Tsutakawa & Jane Johnson, 1990. "The effect of uncertainty of item parameter estimation on ability estimates," Psychometrika, Springer;The Psychometric Society, vol. 55(2), pages 371-390, June.
    2. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    3. Rizopoulos, Dimitris, 2006. "ltm: An R Package for Latent Variable Modeling and Item Response Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i05).
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