Social Support, Insomnia, and Adherence to Cognitive Behavioral Therapy for Insomnia After Cancer Treatment
Bibliographic record
Abstract
OBJECTIVE/BACKGROUND: While cognitive-behavioral therapy for insomnia (CBT-I) has been shown to be efficacious in treating cancer survivors' insomnia, 30-60% of individuals have difficulty adhering to intervention components. Psychosocial predictors of adherence and response to CBT-I, such as social support, have not been examined in intervention studies for cancer survivors. PARTICIPANTS: Data from a randomized placebo-controlled 2 x 2 trial of CBT-I and armodafinil (a wakefulness promoting agent) were used to assess adherence. Ninety-six cancer survivors participated in the trial (mean age 56, 86% female, 68% breast cancer). METHODS: CBT-I and armodafinil were administered over the course of seven weeks, and participants were assessed at baseline, during intervention, postintervention, and at a three-month follow-up. Social support was assessed using a Functional Assessment of Chronic Illness Therapy subscale, insomnia severity was assessed using the Insomnia Severity Index, and adherence was measured based on CBT-I sleep prescriptions. RESULTS: At baseline, social support was negatively correlated with insomnia severity (r = -0.30, p = 0.002) and associations between social support, CBT-I, and insomnia were maintained through the three-month follow-up. Social support was positively associated with adherence to CBT-I during intervention weeks 3, 4, and 5, and with overall intervention adherence. At postintervention, both social support and treatment with CBT-I independently predicted decreased insomnia severity (p < 0.01) when controlling for baseline insomnia severity. CONCLUSIONS: Higher social support is associated with better intervention adherence and improved sleep independent of CBT-I. Additional research is needed to determine whether social support can be leveraged to improve adherence and response to CBT-I.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".