(321) CONTRIBUTIONS OF DYADIC APPROACHES TO THE PSYCHOSOCIAL ADAPTATION OF COUPLES TO PROSTATE CANCER: A SCOPING REVIEW PROTOCOL
Bibliographic record
Abstract
Abstract Objectives Prostate cancer is the second most prevalent cancer diagnosed in men around the world. The available treatments have negative side effects on the mental and sexual health of patients, but also their partners. There is evidence of the relevance of taking dyadic approaches to the study of relational stress that chronic diseases bring to couples’ dynamics. Although, less is known about the application of dyadic approaches to the psychosocial adaptation to prostate cancer. Despite the recent increase of studies conducted with both patients and partners, there are different approaches used. The goal of this scoping review is to map and summarize the evidence of existing dyadic studies that examine the psychosocial adaptation of couples to prostate cancer. Methods To this end, we are conducting a systematic search of studies published from 2005 to September 2022 on electronic databases (Scopus, Web of Science, PubMed, Cochrane, and EBSCOHost), with the following search terms “prostat* cancer” OR “prostat* carcinoma” OR “prostat* tumor” OR “prostat* adenocarcinoma” OR “prostat* neoplasia” OR “pca” AND “dyad*” OR “couple*” OR “partner*” OR “spouse” OR “caregiver*” OR “APIM” OR “Actor Partner Interdependence Model” OR “Actor Partner” OR “Actor Partner Model” AND “psychosocial” OR “pychology*” OR “impact” OR “mental health” OR “sexual health” OR “adaptati*”. This review follows the PRISMA guidelines. Results This work will give, researchers on prostate cancer and professionals working on oncological care, an overview of the potential use of dyadic approaches to help with the psychosocial adaptation of couples’ mental and sexual health during prostate cancer. Conclusions The present work strengthens the need to do more research on how couples adapt together to prostate cancer diagnosis and treatments and to raise awareness among professionals to include both patients and partners and their needs in the interventions to promote mental and sexual health recovery after the prostate cancer journey. Conflicts of Interest All the authors declare no known conflict of interest. This project is funded by Horizonte Europa (NORTE-01-0145-FEDER-000057) and by Fundação para a Ciência e Tecnologia (2022.11670.BD.).
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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 | 0.069 | 0.072 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.018 |
| Bibliometrics | 0.025 | 0.018 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.075 | 0.009 |
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".