QST of PPTs demonstrated good ability to differentiate between people with OA and healthy controls. Lower PPTs in people with OA in affected sites may suggest peripheral, and in remote sites central, sensitisation. PPT measurement merits further evaluation as a tool for phenotyping OA pain.

ObjectiveMultiple mechanisms are involved in pain associated with osteoarthritis (OA). The painDETECT and Self‐Report Leeds Assessment of Neuropathic Symptoms and Signs (S‐LANSS) questionnaires screen for neuropathic pain and may also identify individuals with musculoskeletal pain who exhibit abnormal central pain processing. The aim of this cross‐sectional study was to evaluate painDETECT and S‐LANSS for classification agreement and fit to the Rasch model, and to explore their relationship to pain severity and pain mechanisms in OA.MethodsA total of 192 patients with knee OA completed questionnaires covering different aspects of pain. Another group of 77 patients with knee OA completed questionnaires and underwent quantitative sensory testing for pressure–pain thresholds (PPTs). Agreement between painDETECT and S‐LANSS was evaluated using kappa coefficients and receiver operator characteristic (ROC) curves. Rasch analysis of both questionnaires was conducted. Relationships between screening questionnaires and measures of pain severity or PPTs were calculated using correlations.ResultsPainDETECT and S‐LANSS shared a stronger correlation with each other than with measures of pain severity. ROC curves identified optimal cutoff scores for painDETECT and S‐LANSS to maximize agreement, but the kappa coefficient was low (κ = 0.33–0.46). Rasch analysis supported the measurement properties of painDETECT but not those of S‐LANSS. Higher painDETECT scores were associated with widespread reductions in PPTs.ConclusionThe data suggest that painDETECT assesses pain quality associated with augmented central pain processing in patients with OA. Although developed as a screening questionnaire, painDETECT may also function as a measure of characteristics that indicate augmented central pain processing. Agreement between painDETECT and S‐LANSS for pain classification was low, and it is currently unknown which tool may best predict treatment outcome.

We examine the extent to which retrieval from very long-term autobiographical memory is similar when participants are asked to retrieve from widely differing periods of time. Three groups of 20 participants were given 4 min to recall autobiographical events from the last 5 weeks, 5 months, or 5 years. Following recall, the participants dated their events. Similar retrieval rates, relative recency effects, and relative lag-recency effects were found, despite the fact that the considered time scales varied by a factor of 52. These data are broadly consistent with the principle of recency, the principle of contiguity (Howard & Kahana, 2002), and scale similarity in the rates of recall (Brown, Neath, & Chater, 2007; Maylor, Chater, & Brown, 2001). These findings are taken as support for models of memory that predict time scale similarity in retrieval, such as SIMPLE (Brown et al., 2007) and TCM (Howard & Kahana, 2002).

SummaryObjectivesThe Intermittent and Constant Osteoarthritis Pain (ICOAP) questionnaire was developed to assess two forms of pain reported by people with osteoarthritis: intermittent and constant pain. Studies examining its measurement qualities have provided some support for its use as separate and total scales. However, it has not been previously evaluated using Rasch analysis. The current study examined the fit between data obtained from the ICOAP questionnaire and the Rasch model to determine whether it meets the requirements of interval-level measurement.DesignICOAP responses from 175 participants with knee osteoarthritis were collected in a cross-sectional questionnaire study. Participants were recruited from hospital clinics and a group who had taken part in previous research. The questionnaires were completed at home and returned by pre-paid envelope and the data were analysed using RUMM2020.ResultsFit to the Rasch model was achieved for both the Constant and Intermittent subscales following removal of a small number of items. The Total scale initially resulted in substantial misfit to the model, but fit was improved by removing four items that misfit the model. However, several participants presented with high fit residuals, which is consistent with misfit.ConclusionsThe results support the use of Constant and Intermittent subscales as unidimensional measures of pain. The Total scale can be adapted to improve fit to the Rasch model, but there are concerns over participant misfit.