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Record W4294739095 · doi:10.11124/jbies-21-00438

Psychosocial interventions that facilitate adult cancer survivors’ reintegration into daily life after active cancer treatment: a scoping review protocol

2022· review· en· W4294739095 on OpenAlexafffund
Sarah Murnaghan, Sarah Scruton, Robin Urquhart

Bibliographic record

VenueJBI Evidence Synthesis · 2022
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsNova Scotia Health AuthorityDalhousie University
FundersCanadian Institutes of Health Research
KeywordsPsychosocialCINAHLPsychological interventionSurvivorship curveCancer survivorMedicineMEDLINEQuality of life (healthcare)AnxietyPsycho-oncologyGerontologyCancerPsychologyPsychiatryNursing

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.683
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.000

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.

Opus teacher head0.113
GPT teacher head0.452
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2022
Admission routes2
Has abstractyes

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