Data · dataset · 2026
Cognitive-affective and behavioural pain mechanisms in individuals with chronic low back pain: a network analysis
Listed in IISH Dataverse
Various cognitive-affective and behavioral factors contribute to the maintenance of low back pain, but these factors are often evaluated in isolation.
Description
The network approach provides an avenue to evaluate multiple cognitive-affective and behavioral factors at once and across time. This study explored the relationship between pain, expectancies, avoidance, and related cognitive-affective and behavioral factors using network analysis.
A total of 30 individuals with chronic low back pain completed ecological momentary assessments regarding their physical symptoms and related cognitive-affective and behavioral factors 5 times per day for a duration of 2 weeks. Temporal and contemporaneous networks were estimated using vector autoregressive models on a group and individual level. Networks show that the relationship among cognitive-affective and behavioral factors reinforces each other within the same time frame as well as across time.
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The strongest temporal connections were found between pain and attention, while the strongest contemporaneous connections were found between fear and attention at the group level. On an individual level, different variations of network structures can be found, suggesting that a more individualized approach is needed for better treatment outcomes. Further research is warranted to confirm the causal relations between cognitive-affective and behavioral factors in the maintenance of chronic pain.
The network approach may be a useful tool to develop more effective individualized treatment to manage chronic pain.
Links
Where it is published
- Dataverse dataset page dataverse.nl/dataset.xhtml?persistentId=doi%3A10.34894%2FJMTTTM ↗
landing page · from datasets iisg amsterdam
- DOI doi.org/10.34894/jmtttm ↗
DOI / persistent id · from datasets iisg amsterdam
Catalogue records · 1
- Dataverse API dataverse.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2FJMTT… ↗
metadata API · from datasets iisg amsterdam
Topics
- Stated by source
- Social Sciences
- From keywords
- Social Science
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IISH Dataverse | doi:10.34894/JMTTTM | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].dataverse_subject:social-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| created_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| description | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /description |
| publication_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| title | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /name |
| updated_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| version_label | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 |