Design and evaluate a nurse-led digital intervention for chronic pain management

Thesis Abstract

Chronic pain remains a pervasive health challenge, significantly impairing quality of life and posing substantial burdens on healthcare systems worldwide. Despite advances in pain management, many patients continue to experience inadequate control due to limited access to specialized interventions and the underutilization of innovative therapeutic modalities. This study aims to design, implement, and evaluate a nurse-led digital intervention tailored for individuals experiencing chronic pain, with the objective of improving pain management outcomes and enhancing patient self-efficacy. The specific objectives include (1) developing a theoretically grounded digital platform incorporating cognitive-behavioral strategies based on the Health Belief Model and Self-Efficacy Theory, (2) assessing the usability and acceptability of the digital intervention among chronic pain patients, (3) evaluating its effectiveness in reducing pain intensity and improving functional outcomes, and (4) exploring patient and nurse perceptions of the intervention's impact on pain management practices. Methodologically, the study adopts a mixed-methods design comprising a quasi-experimental pretest-posttest controlled trial complemented by qualitative interviews. The target population encompasses adult patients aged 18-65 with a clinical diagnosis of chronic musculoskeletal pain attending outpatient clinics in a metropolitan tertiary hospital. A stratified random sampling technique will be employed to recruit 120 participants—60 assigned to the intervention group and 60 to the control group receiving standard care. Data collection instruments include the Numeric Pain Rating Scale (NPRS), the Pain Disability Index (PDI), the General Self-Efficacy Scale (GSE), and a customized usability questionnaire validated through cognitive interviews. Qualitative data will be obtained through semi-structured interviews with 15 participants and 10 nurses involved in the intervention, with thematic analysis conducted using NVivo software to explore perceptions and experiences. Quantitative data will be analyzed using descriptive statistics, paired and independent t-tests, and multiple regression analyses to determine the intervention’s effect on pain and functional outcomes, controlling for baseline characteristics. Thematic analysis of qualitative data will identify core themes relating to usability, acceptability, and perceived impact on pain management practices. A multiple linear regression model will be specified to assess the predictors of pain reduction, informed by the theoretical frameworks guiding the intervention development. Anticipated findings suggest that the nurse-led digital intervention will significantly reduce pain intensity, improve functional capacity, and enhance self-efficacy compared to standard care, with high levels of user acceptability and satisfaction. Furthermore, qualitative insights are expected to reveal improved nurse-patient communication, increased patient empowerment, and the feasibility of integrating digital tools into routine nursing practice. These results are poised to contribute to the body of knowledge by demonstrating the efficacy of nurse-led digital interventions grounded in behavioral theories for chronic pain management, addressing identified gaps related to scalability and personalization of pain care. The study concludes that a nurse-led digital intervention is a promising adjunct to conventional pain management strategies, offering a scalable and accessible approach to improve patient outcomes. Recommendations include integrating such digital tools into clinical practice, training nurses in digital health competencies, and conducting longitudinal studies to evaluate long-term effects. Overall, the study advocates for policymakers and healthcare providers to harness digital health innovations to enhance chronic pain management, emphasizing the pivotal role of nursing in leading evidence-based digital interventions.