Effectiveness of Acceptance and Commitment Therapy (ACT) for the Management of Postsurgical Pain: Study Protocol of a Randomized Controlled Trial (SPINE-ACT Study).
Juan R Castaño-AsinsJuan P Sanabria-MazoJuan V LucianoAlberto Barceló-SolerLuis M Martín-LópezAlejandro Del Arco-ChurrucaJesús Lafuente-BarazaAntonio BulbenaVíctor Pérez-SolàAntonio Montes-PérezPublished in: Journal of clinical medicine (2023)
Research on the use of Acceptance and Commitment Therapy (ACT) for patients with degenerative lumbar pathology awaiting surgery are limited. However, there is evidence to suggest that this psychological therapy may be effective in improving pain interference, anxiety, depression, and quality of life. This is the protocol for a randomized controlled trial (RCT) to evaluate the effectiveness of ACT compared to treatment as usual (TAU) for people with degenerative lumbar pathology who are candidates for surgery in the short term. A total of 102 patients with degenerative lumbar spine pathology will be randomly assigned to TAU (control group) or ACT + TAU (intervention group). Participants will be assessed after treatment and at 3-, 6-, and 12-month follow-ups. The primary outcome will be the mean change from baseline on the Brief Pain Inventory (pain interference). Secondary outcomes will include changes in pain intensity, anxiety, depression, pain catastrophizing, fear of movement, quality of life, disability due to low back pain (LBP), pain acceptance, and psychological inflexibility. Linear mixed models will be used to analyze the data. Additionally, effect sizes and number needed to treat (NNT) will be calculated. We posit that ACT may be used to help patients cope with the stress and uncertainty associated with their condition and the surgery itself.
Keyphrases
- chronic pain
- minimally invasive
- pain management
- neuropathic pain
- randomized controlled trial
- sleep quality
- multiple sclerosis
- depressive symptoms
- chronic kidney disease
- end stage renal disease
- type diabetes
- spinal cord injury
- machine learning
- cerebrospinal fluid
- metabolic syndrome
- high intensity
- physical activity
- stem cells
- deep learning
- skeletal muscle
- coronary artery disease
- postoperative pain
- bone marrow
- replacement therapy
- cell therapy
- smoking cessation
- patient reported