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Cited by 40Musculoskeletal pain and rehabilitationDigital Mental Health InterventionsPediatric Pain Management Techniques

The DOI matches its Crossref record; 54 of the 56 references it cites were found in a registry or an index.

The Pain Course: exploring predictors of clinical response to an Internet-delivered pain management program

Dear, B.F., Gandy, M., Karin, E., Ricciardi, T., Langman, N., Staples, L.G., Fogliati, V.J., Sharpe, L., McLellan, L.F., Titov, N.·2016·Pain
DOI 10.1097/j.pain.0000000000000639
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Abstract

There is significant interest in the potential of Internet-delivered pain management programs for adults with chronic pain. Understanding the characteristics of people who do and do not benefit from Internet-delivered programs will help to guide their safe and effective use. Using a large sample from a previous randomised controlled trial of an established Internet-delivered pain management program, the Pain Course, this study (n = 463) examined whether several demographic, clinical, psychological, and treatment-related variables could be used to predict clinical response in levels of disability, depression, anxiety, or average pain. Multiple univariate and multivariate stepwise logistic regressions were used to identify unique predictors of clinical improvement, which, consistent with recommendations, was defined as a ≥30% reduction in symptoms or difficulties from baseline. Several unique predictors of clinical improvement were found. However, no particularly decisive or dominant predictors emerged that were common across time points or across the outcome domains. Reflecting this, the identified predictors explained only 18.1%, 13.7%, 7.6%, and 9.5% of the variance in the likelihood of making a clinical improvement in disability, depression, anxiety, and average pain levels, respectively. The current findings suggest that a broad range of patients may benefit from emerging Internet-delivered pain management programs and that it may not be possible to predict who will or will not benefit on the basis of patients' demographic, clinical, and psychological characteristics.

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Metadata

Authors
Dear, B. F., Gandy, M., Karin, E., Ricciardi, T., Langman, N., Staples, L. G., Fogliati, V. J., Sharpe, L., McLellan, L. F., & Titov, N.
Affiliations
  • Macquarie University (AU)
  • The University of Sydney (AU)
Corresponding author
Dear, B.F.
ORCID
Venue
Pain
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2016-05-31
Volume
157
Issue
10
Pages
2257-2268
ISSN
  • 0304-3959 (ISSN-L)
  • 1872-6623
DOI
10.1097/j.pain.0000000000000639
OpenAlex
W2415210715
Cited by
40
References
56
Citations by year
2026: 2 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 3 · 2021: 4 · 2020: 2 · 2019: 4 · 2018: 9 · 2017: 4 · 2016: 3
FWCI
5.40
Type
journal article
Language
en
Open access
closed
Locations
  • Pain (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Musculoskeletal pain and rehabilitation
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pediatric Pain Management Techniques
Keywords
chronic pain, predictors of treatment response, disability, depression, anxiety, pain intensity, online psychological intervention
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Anxiety, Disability Evaluation, Female, Humans, Male, Middle Aged, Pain, Predictive Value of Tests, Psychotherapy, Surveys and Questionnaires, Logistic Models, Treatment Outcome, Internet, Young Adult, Pain Management

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