Objective: To explore predictors of dropout of patients with chronic musculoskeletal pain from an interdisciplinary chronic pain management programme, and to develop and validate a multivariable prediction model, based on the Extended Common- Sense Model of Self-Regulation (E-CSM). Methods: In this prospective cohort study consecutive patients with chronic pain were recruited and followed up (July 2013 to May 2015). Possible associations between predictors and dropout were explored by univariate logistic regression analyses. Subsequently, multiple logistic regression analyses were executed to determine the model that best predicted dropout. Results: Of 188 patients who initiated treatment, 35 (19%) were classified as dropouts. The mean age of the dropout group was 47.9 years (standard deviation 9.9). Based on the univariate logistic regression analyses 7 predictors of the 18 potential predictors for dropout were eligible for entry into the multiple logistic regression analyses. Finally, only pain catastrophizing was identified as a significant predictor. Conclusion: Patients with chronic pain who catastrophize were more prone to dropout from this chronic pain management programme. However, due to the exploratory nature of this study no firm conclusions can be drawn about the predictive value of the E-CSM of Self-Regulation for dropout.
Background: In postoperative pain treatment patients are asked to rate their pain experience on a single uni-dimensional pain scale. Such pain scores are also used as indicator to assess the quality of pain treatment. However, patients may differ in how they interpret the Numeric Rating Scale (NRS) score. Objectives: This study examines how patients assign a number to their currently experienced postoperative pain and which considerations influence this process. Methods: A qualitative approach according to grounded theory was used. Twenty-seven patients were interviewed one day after surgery. Results: Three main themes emerged that influenced the Numeric Rating Scale scores (0–10) that patients actually reported to professionals: score-related factors, intrapersonal factors, and the anticipated consequences of a given pain score. Anticipated consequences were analgesic administration—which could be desired or undesired—and possible judgements by professionals. We also propose a conceptual model for the relationship between factors that influence the pain rating process. Based on patients’ score-related and intrapersonal factors, a preliminary pain score was ‘‘internally’’ set. Before reporting the pain score to the healthcare professional, patients considered the anticipated consequences (i.e., expected judgements by professionals and anticipation of analgesic administration) of current Numeric Rating Scale scores. Conclusions: This study provides insight into the process of how patients translate their current postoperative pain into a numeric rating score. The proposed model may help professionals to understand the factors that influence a given Numeric Rating Scale score and suggest the most appropriate questions for clarification. In this way, patients and professionals may arrive at a shared understanding of the pain score, resulting in a tailored decision regarding the most appropriate treatment of current postoperative pain, particularly the dosing and timing of opioid administration.
Objective To develop and internally validate a prognostic model to predict chronic pain after a new episode of acute or subacute non-specific idiopathic, non-traumatic neck pain in patients presenting to physiotherapy primary care, emphasising modifiable biomedical, psychological and social factors. Design A prospective cohort study with a 6-month follow-up between January 2020 and March 2023. Setting 30 physiotherapy primary care practices. Participants Patients with a new presentation of non-specific idiopathic, non-traumatic neck pain, with a duration lasting no longer than 12 weeks from onset. Baseline measures Candidate prognostic variables collected from participants included age and sex, neck pain symptoms, work-related factors, general factors, psychological and behavioural factors and the remaining factors: therapeutic relation and healthcare provider attitude. Outcome measures Pain intensity at 6 weeks, 3 months and 6 months on a Numeric Pain Rating Scale (NPRS) after inclusion. An NPRS score of ≥3 at each time point was used to define chronic neck pain. Results 62 (10%) of the 603 participants developed chronic neck pain. The prognostic factors in the final model were sex, pain intensity, reported pain in different body regions, headache since and before the neck pain, posture during work, employment status, illness beliefs about pain identity and recovery, treatment beliefs, distress and self-efficacy. The model demonstrated an optimism-corrected area under the curve of 0.83 and a corrected R2 of 0.24. Calibration was deemed acceptable to good, as indicated by the calibration curve. The Hosmer–Lemeshow test yielded a p-value of 0.7167, indicating a good model fit. Conclusion This model has the potential to obtain a valid prognosis for developing chronic pain after a new episode of acute and subacute non-specific idiopathic, non-traumatic neck pain. It includes mostly potentially modifiable factors for physiotherapy practice. External validation of this model is recommended.
