Fadeeva Anastasia, Tomietto Marco, Tiwari Ajay, Mann Emily, Serra Giuseppe, Kiernan Matthew D
Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, United Kingdom.
Violence and Society Centre, City, University of London, London, United Kingdom.
Public Health Pract (Oxf). 2024 Jan 5;7:100464. doi: 10.1016/j.puhip.2024.100464. eCollection 2024 Jun.
To construct an indicator for assessing the complexity of UK veterans' needs.
Cross-sectional, secondary analysis.
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.
The complex needs indicator for the current sample was validated. The majority of cases had a complexity score of 1 or less.
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.
构建一个用于评估英国退伍军人需求复杂性的指标。
横断面研究,二次分析。
该研究采用主成分分析(PCA)方法,根据不同需求之间的相互作用来确定其权重,并使用自抽样法评估模型的有效性。研究考虑了由“陆海空三军军人及其家属协会”(SSAFA)提供的关于英国退伍军人支持的数据集(N = 35208)。不同类别支持的资助申请被用作不同需求的指标。在复杂性评估中纳入了广度(不同需求的数量)和深度(满足需求的资助申请数量)维度。
当前样本的复杂需求指标得到验证。大多数案例的复杂性得分在1分及以下。
该研究提出并测试了一种退伍军人需求复杂性的评估方法,该方法可能与不良健康结果的较高风险呈正相关。该指标可供决策者用于退伍军人人群的风险分层,从而以更有效的方式支持资源分配。