{
  "abstract": "Predictive modelling has been recognised in nursing since Hinshaw et al’s 1983 editorial, which demonstrated how modelling could assess the impact of a perioperative teaching programme on patient outcomes such as anxiety, pain and recovery.1 In the era of artificial intelligence (AI), predictive modelling has become central to forecasting outcomes such as falls, pressure injuries, readmissions and deterioration, supporting proactive clinical decision-making.2 3 Yet adoption in nursing remains slower than in other fields, often due to perceived complexity or lack of interdisciplinary collaborations. This article offers a practical guide to developing, interpreting, validating and ethically applying predictive models to support transparent, evidence-based nursing practice and research.",
  "authors": [
    {
      "affiliations": [
        "Nursing & Midwifery Research Department, Hamad Medical Corporation, Doha, Doha, Qatar"
      ],
      "name": "Abdulqadir J Nashwan"
    },
    {
      "affiliations": [
        "Nursing Department, Hamad Medical Corporation, Doha, Doha, Qatar"
      ],
      "name": "Ahmad A Abujaber"
    }
  ],
  "title": "Developing predictive models in nursing research and clinical practice",
  "uid": "c1b1aefe-ff8c-5bce-b445-2f86ec8c7c7c"
}