Background Chronic pain is a complex disease with high prevalence rates, and many individuals who are affected do not receive adequate treatment. As a complement to conventional therapies, eHealth interventions could provide many benefits to a multimodal treatment approach for patients with chronic pain, whereby future use is associated with the acceptance of these interventions. Objective This study aims to assess the acceptance of eHealth pain management interventions among patients with chronic pain and identify the influencing factors on acceptance. A further objective of the study is to evaluate the viability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and compare it with its extended version in terms of explained variance of acceptance. Methods We performed a cross-sectional web-based study. In total, 307 participants with chronic pain, as defined according to the International Association for the Study of Pain criteria, were recruited through flyers, posters, and web-based inquiries between December 2020 and July 2021. In addition to sociodemographic and medical data, the assessment included validated psychometric instruments and an extended version of the well-established UTAUT model. For statistical analyses, group comparisons and multiple hierarchical regression analyses were performed. Results The acceptance of eHealth pain management interventions among patients with chronic pain was overall moderate to high (mean 3.67, SD 0.89). There was significant difference in acceptance among age groups (W=9674.0; r=0.156; P=.04). Effort expectancy (β=.37; P<.001), performance expectancy (β=.33; P<.001), and social influence (β=.34; P<.001) proved to be the most important predictors of acceptance. The extended UTAUT (including the original UTAUT factors as well as sociodemographic, medical, and eHealth-related factors) model explained 66.4% of the variance in acceptance, thus supporting the viability of the model. Compared with the original UTAUT model (performance expectancy, effort expectancy, and social influence), the extended model explained significantly more variance (F25,278=1.74; P=.02). Conclusions Given the association between acceptance and future use, the knowledge of the influencing factors on acceptance should be used in the development and promotion of eHealth pain management interventions. Overall, the acceptance of eHealth pain management interventions was moderate to high. In total, 8 predictors proved to be significant predictors of acceptance. The UTAUT model is a valuable instrument for determining acceptance as well as the factors that influence acceptance of eHealth pain management interventions among patients with chronic pain. The extended UTAUT model provided the greatest predictive value for acceptance.

Background While the COVID‐19 pandemic is affecting people's well‐being worldwide, it may place a particularly high burden on people with chronic pain, as pain is known to be influenced by societal and psychological conditions. Methods In this observational study, we conducted telephone interviews with 196 patients with chronic pain to assess the impact of the pandemic on various aspects of their pain and everyday life. The initial interviews were conducted between April and May 2020 and were followed up by a second interview between August and December 2020. Results A substantial percentage of patients (39% at the first and 32% at the second interview) reported an increase in pain intensity due to the pandemic. Exploratory analyses revealed that patients who already suffered from greater pain and who experienced greater restrictions due to the pandemic were more likely to express a pain worsening. Psychological factors such as negative expectations about the development of their pain and pain treatment and a high external locus of control were also associated with increases in pain. Conclusions These findings illustrate the complexity of chronic pain, suggesting that not only the impact of the pandemic on various areas of life but also the severity of the pain‐symptoms themselves and psychological factors influence the course of patients’ symptoms during the pandemic.

Motor chunking, the grouping of individual movements into larger units, is crucial for sequential motor performance. The presupplementary motor area (preSMA) is involved in chunking and other related processes such as task switching, response selection, and response inhibition that are crucial for organizing sequential movements. However, previous studies have not systematically differentiated the role of preSMA in motor chunking and hand switching, thus leaving its relative contribution to each of these processes unclear. The aim of this study is to demonstrate the differential role of preSMA in motor chunking and hand switching. We designed motor sequences in which different kinds of hand switches (switching toward the right or left hand or continuing with the right hand) were counterbalanced across between- and within-chunk sequence points. Eighteen healthy, right-handed participants practiced four short subsequences (chunks) of key presses. In a subsequent task, these chunks had to be concatenated into one long sequence. We applied double-pulse transcranial magnetic stimulation (TMS) over left preSMA or left M1 areas at sequence initiation, between chunks, or within chunks. TMS over the left preSMA significantly slowed the next response when stimulation was given between chunks, but only if a hand switch toward the contralateral (right) hand was required. PreSMA stimulation within chunks did not interfere with responses. TMS over the left M1 area delayed responses with the contralateral hand, both within and between chunks. Both preSMA and M1 stimulation decreased response times at sequence initiation. These results suggest that left preSMA is not necessary for chunking per se, but rather for organizing complex movements that require chunking and hand switching simultaneously.

Zusammenfassung Hintergrund Chronische Rückenschmerzen sind eine schwerwiegende und global sehr häufig auftretende Erkrankung mit enormen persönlichen sowie sozioökonomischen Auswirkungen. Die interdisziplinäre multimodale Schmerztherapie (IMST) ist eines der wenigen evidenzbasierten Behandlungsverfahren für chronische Schmerzen. Obwohl bekannt ist, dass Schmerzen sowie deren Chronifizierung und Behandlung von den persönlichen Erwartungen der Patienten beeinflusst werden, gibt es wenige etablierte Interventionen oder Richtlinien für eine aktive Modulation dieses Effekts. Ziel der Arbeit Wir möchten mit dieser Arbeit die Rolle der Erwartung als Prädiktor für Schmerzen sowie schmerzbezogene Beeinträchtigung in der klinischen Praxis verdeutlichen und präsentieren hierzu beispielhaft explorative Pilotdaten einer Beobachtungskohorte unserer Klinik. Material und Methoden Die Untersuchung zeigt erste Daten einer prospektiven longitudinalen Beobachtungsstudie bestehend aus bis zu 41 Patienten mit chronischen Rückenschmerzen, die im Setting einer IMST am Essener Rückenschmerz-Zentrum behandelt wurden. Es wurden Daten zum Zeitpunkt der Aufnahme (T0) und der Entlassung (T1) sowie drei Monate nach Therapieende (T2) erhoben. Primäre Endpunkte waren die Schmerzintensität und die Schmerzbeeinträchtigung. Zusätzlich erfassten wir die Therapieerwartung zum Zeitpunkt der Aufnahme als möglichen Prädiktor. Die Bedeutung der vor der Therapie erhobenen Therapieerwartung wurde mittels linearer Regression erfasst. Ergebnisse Die IMST führte zu einer signifikanten Besserung in Bezug auf die Schmerzintensität und -beeinträchtigung. Der Effekt auf die Schmerzintensität war über den Zeitraum von drei Monaten nach Therapieende anhaltend und die Beeinträchtigung sank in diesem Zeitraum weiter signifikant. Diskussion Erwartung war ein signifikanter Prädiktor für die Abnahme der Schmerzintensität und erklärte ca. 15 % der Varianz. In der klinischen Praxis sollten daher valide Methoden etabliert werden, negative Erwartungen zu reduzieren und positive Erwartungen zu fördern.