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Enregistrement W4389082976 · doi:10.11124/jbies-23-00044

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

2023· review· en· W4389082976 sur OpenAlexafffund
Sarah Murnaghan, Sarah Scruton, Robin Urquhart

Notice bibliographique

RevueJBI Evidence Synthesis · 2023
Typereview
Langueen
DomaineMedicine
ThématiqueCancer survivorship and care
Établissements canadiensNova Scotia Health AuthorityDalhousie University
Organismes subventionnairesCanadian Institutes of Health ResearchDalhousie University
Mots-clésPsychosocialPsychological interventionCINAHLSurvivorship curvePsycINFOMedicineCancer survivorMEDLINECancerSocial supportGerontologyQuality of life (healthcare)PsychologyPsychiatryPsychotherapistNursing

Résumé

récupéré en direct d'OpenAlex

OBJECTIVE: This review explored psychosocial interventions targeting adult cancer survivors' reintegration following active cancer treatment. This included the types of interventions tested and the tools used to measure reintegration. INTRODUCTION: Cancer survivors face lingering health issues following the completion of cancer treatment. Many cancer survivors still experience unmet psychosocial care needs despite receiving follow-up care. Further, many survivorship interventions do not specifically address outcomes important to survivors. A number of primary studies have identified reintegration as an outcome important to cancer survivors. Reintegration is a concept that focuses on returning to normal activities, routines, and social roles after cancer treatment; however, it is emerging and abstract. INCLUSION CRITERIA: Studies involving adult cancer survivors (18 years or older at diagnosis) of any cancer type or stage were included in this review. Studies with psychosocial interventions targeted at reintegrating the person into daily life after cancer treatment were included. Interventions addressing clinical depression or anxiety, and interventions treating solely physical needs that were largely medically focused were excluded. METHODS: A literature search was conducted in MEDLINE (Ovid), CINAHL (EBSCOhost), and Embase. Gray literature was searched using ProQuest Dissertations and Theses (ProQuest). Reference lists of included studies were searched. Studies were screened at the title/abstract and full-text levels, and 2 independent reviewers extracted data. Manuscripts in languages other than English were excluded due to feasibility (eg, cost, time of translations). Findings were summarized narratively and reported in tabular and diagrammatic format. RESULTS: The 3-step search strategy yielded 5617 citations. After duplicates were removed, the remaining 4378 citations were screened at the title and abstract level, then the remaining 306 citations were evaluated at the full-text level by 2 independent reviewers. Forty studies were included that evaluated psychosocial interventions among adult cancer survivors trying to reintegrate after active cancer treatment (qualitative n=23, mixed methods n=8, quantitative n=8, systematic review n=1). Included articles spanned 10 different countries/regions. Over half of all included articles (n=25) focused primarily on breast cancer survivors. Many studies (n=17) were conducted in primary care or community-based settings. The most common types of interventions were peer-support groups (n=14), follow-up education and support (n=14), exercise programs (n=6), and multidisciplinary/multicomponent programs (n=6). While the majority of included studies characterized the outcome qualitatively, 9 quantitative tools were also employed. CONCLUSIONS: This review identified 6 types of interventions to reintegrate survivors back into their daily lives following cancer treatment. An important thread across intervention types was a focus on personalization in the form of problem/goal identification. Given the number of qualitative studies, future research could include a qualitative systematic review and meta-aggregation. Quantitative tools may not be as effective for evaluating reintegration. More primary studies, including mixed methods studies, utilizing consistent measurement tools are required. Furthermore, this work provides a basis for future research to continue examining the complexity of implementing such interventions to successfully achieve reintegration. To do so, primary studies evaluating interventions from an implementation science and complex systems perspective would be useful. REVIEW REGISTRATION: Open Science Framework https://osf.io/r6bmx.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,030
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,034

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,030
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0050,005
Bibliométrie0,0080,008
Études des sciences et des technologies0,0010,001
Communication savante0,0040,002
Science ouverte0,0020,001
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,099
Tête enseignante GPT0,442
Écart entre enseignants0,344 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations22
Publié2023
Routes d'admission2
Résumé présentoui

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