CHRONIC PAIN A study on patients with chronic pain: What characteristics/variables lie behind the fact that a patient does not respond well to treatment?
Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
The primary purpose of this study was to find out which variables lie behind the fact that patients who respond well to treatment of chronic pain differs from those who do not. We used logistic regression to predict group belonging based on the self-reported health surveys, i.e if different answers in the surveys can predict whether a patient is “responsive” or “unresponsive”. By bootstrapping 176 samples, and aggregating the results from 176 logistic regressions based on the sub-samples, we calculate an averaged model. The variables anxiety and physical health were significant in 76% and 70% of the models respectively, while depression was significant in 30% of the models. Gender was significant in 15% of the models and health status in 0,006%. The averaged model correctly classified the most unresponsive patients at cut-off value 0.5. As the cut –off value was increased, the number of correctly classified unresponsive patients decreased while the number of correctly classified responsive patients increased, as well as unresponsive patients classified as responsive. We concluded that the model did not discriminate enough between the two groups.
We were also interested in finding out how the variables anxiety, depression, heath status, willingness to participate in activities as well as engagement in activities, mental and physical health relate with one another. The results from confirmatory factor analysis showed that a patient’s health status is highly related to their physical health and activity engagement while pain willingness and engagement in activity were least related. Furthermore, the analysis showed that mental health is highly related with anxiety and health status, indicating that mental health is indeed important to reflect upon when considering the health status of a patient.
Place, publisher, year, edition, pages
2015. , 46 p.
Chronic pain, Logistic regression, Confirmatory factor analysis, imbalanced data
Social Sciences Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:uu:diva-254493OAI: oai:DiVA.org:uu-254493DiVA: diva2:818458
Smärtcentrum, Akademiska sjukhuset
Subject / course