Researchers from the University of Malaga, Spain, have developed a new tool to help clinicians assess the impact of chronic pain on daily activities, according to a study published in the April issue of The Journal of Pain.
New self-report measure includes 8 factors related to avoidance, persistence, and pacing.
Known as the Activity Patterns Scale (APS), the self-report measure breaks down 3 general activities (avoidance, persistence, and pacing) into 8 more specific patterns:
- pain avoidance,
- activity avoidance,
- task-contingent persistence,
- excessive persistence,
- pain-contingent persistence,
- pacing to increase activity,
- pacing to conserve energy, and
- pacing to reduce pain.
Patients with chronic pain often have to modify how they perform activities of daily living, which can impact their sense of wellbeing and quality of life.
Construction and Validation
Confirmatory factor analysis supported the validity of a 24-item APS with 8 subscales for related factors. The new version was found to be slightly superior to the 6-factor structure, indicating that avoidance, persistence, and pacing should be thought of as multidimensional constructs.
The APS was constructed and validated in 2 studies.
Results showed an association between activity avoidance and daily functioning and impairment.
Negative affect was positively associated with activity avoidance and excessive persistence, and negatively associated with task-contingent persistence; the latter was also positively associated with positive affect.
“[A]lthough further research is needed, this study provides evidence that the APS, which assesses 8 activity patterns with a relatively low number of items, is a promising instrument for clinical practice and research,” the authors write.
Clinical Pain Advisor had the opportunity to discuss the APS in greater detail via e-mail with lead author Rosa Esteve, PhD.
- Clinical Pain Advisor: What led you and your colleagues to develop the APS and how did it evolve?
The Kindermans et al. article used exploratory factor analyses of various activity patterns self-report measures and identified 6 patterns: pain avoidance, activity avoidance, task-contingent persistence, excessive persistence, pain-contingent persistence, and pacing.2
The articles by Nielson et al. suggested that existing measures did not include some key pacing subdomains and that future measures should be developed that address specific pacing behaviors based on the goal of the pacing
- Clinical Pain Advisor: In validating the APS, what was your key finding?
Our key finding is that the goals of avoidance, persistence, and pacing behaviors are crucial factors that influence disability and wellbeing, rather than being considered intrinsically adaptive or maladaptive.
This distinction between functional and dysfunctional forms of avoidance, persistence, and pacing could contribute to refining the treatment instructions aimed at regulating patients’ activity and in providing a more individualized approach to care.
- Clinical Pain Advisor: Any area for future development or refinement of the scale?
At the same time, they are investigating the validity of the dimensions of the APS activity patterns by studying if their relationship with measures of psychosocial functioning differs from that of existing activity patterns measures. In addition to this research, future research should test the construct validity of the dimensions included in the instrument using objective measures, rather than just relying on self-reports.
Self-reports are notoriously unreliable, especially when it involves such subjective intangibles like levels of “stress” or “discomfort” or “anxiety”.
This seems to be a great deal of fuss over a new psychological “measuring toy” with which they believe they can get closer to “measuring” pain.
- Clinical Pain Advisor: How do you see the scale being used in clinical practice?
For clinicians, the instrument offers the possibility of a more detailed description of activity patterns and of making more specific predictions of the relationship of activity patterns with wellbeing using exploratory factor analyses of various activity patterns self-report measures.
Having this information can enable clinicians to make treatment instructions more specific.
Nevertheless, at this moment, the instrument should be used cautiously because it is still in the initial stages of development