Validation of a complex needs indicator for veterans in the UK using a composite indicators' method - Anastasia Fadeeva; Marco Tomietto; Ajay Tiwari; Emily Mann; Giuseppe Serra; Matthew D. Kiernan (Elsevier, 2024)
Objective: To construct an indicator for assessing the complexity of UK veterans' needs. Study design: Cross-sectional, secondary analysis. Methods: The study applied principal component (PCA) analysis as the method to determine the weights of different needs based on their interactions with each other, the effectiveness of the model was evaluated using bootstrapping. The dataset on UK veterans' support provided by the "Soldiers, Sailors, Airmen and Families Associations" (SSAFA) (N = 35,208) was considered. The grant applications for different categories of support were used as indicators of different needs. The dimensions of breadth (number of different needs) and depth (number of grant applications to address the need) were incorporated in the assessment of complexity. Results: The complex needs indicator for the current sample was validated. The majority of cases had a complexity score of 1 or less. Conclusions: The research suggested and tested an assessment method for the complexity of veterans' needs, that may be positively associated with higher risk of adverse health outcomes. This indicator can be used by decision-makers for risk stratification of the veteran population, thus supporting the allocation of resources in a more effective way.