Psychosocial interventions that facilitate adult cancer survivors’ reintegration into daily life after active cancer treatment: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: This scoping review will map the extent and type of evidence related to psychosocial supports and interventions that facilitate adult cancer survivors' reintegration into daily life and activities after active cancer treatment. INTRODUCTION: Cancer and its treatment have substantial late and long-term adverse impacts on survivors despite enhanced prospects for survival. Cancer survivors have unmet psychosocial care needs, and recent studies show a lack of focus in survivorship research on outcomes important to survivors. Reintegration is an emerging concept, identified as important to cancer survivors, that focuses on returning to a "new normal" after cancer treatment. This study will explore the available evidence on psychosocial interventions that are targeted toward this outcome. INCLUSION CRITERIA: The population of interest is adult survivors (18 years and older at diagnosis) of any cancer type. Concepts of interest include psychosocial interventions targeting the outcome and reintegration into daily life after cancer treatment. Interventions addressing clinical depression or anxiety and interventions treating physical needs that are largely medically focused will be excluded. METHODS: A scoping review of the literature will be conducted in MEDLINE, CINAHL, and Embase. Gray literature will be searched using ProQuest Dissertations and Theses. Studies will be screened at the title/abstract and full-text levels, and data will be extracted by 2 independent reviewers. Disagreements that cannot be resolved will be settled by a third reviewer. Findings will be summarized narratively and in tabular format. SCOPING REVIEW REGISTRATION: Open Science Framework (https://osf.io/r6bmx).
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 | 0.081 | 0.072 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.057 | 0.011 |
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".