Identifying Major Depressive Symptoms and Major Depressive Episodes in Adolescents with Cancer
Notice bibliographique
Résumé
Cancer is the leading cause of death from disease among adolescents in Canada. Although cancer is a well-researched disease process in the medical and nursing literature, adolescence is relatively understudied, with minimal evidence on strategies to promote healthy emotional adjustment throughout the disease trajectory. Current literature on major depressive episodes (MDE) in adolescents diagnosed with cancer suggests limited evidence in screening and diagnosing MDEs. Furthermore, current practice in pediatric oncology centres do not include routine psychosocial assessments of adolescents with cancer, but rather, rely on individual clinician discretion on individuals who may benefit from referrals to a psychosocial and/or psychiatric team. Existing instruments used to screen for depression in adolescents have not previously been tested for clinical utility in pediatric oncology patients, which is problematic due to the significant overlap in MDE symptoms and adverse side effects of cancer disease and treatment. Research on adult cancer survivors suggests that age, gender, and anxiety are significantly related to depression, but this has not previously been examined among Canadian adolescent cancer patients. This study employed a cross-sectional descriptive design to examine and compare the feasibility of utilizing the Children’s Depression Inventory (CDI) and the Diagnostic Interview for Children and Adolescents (DICA-IV) to screen for MDEs, and to examine the relationships among age, gender, and anxiety and a MDE in adolescents with cancer. Of the twenty five eligible participants, fourteen adolescent patients with either a malignant cancer or tumour requiring chemotherapy treatment or a hematological disorder requiring a blood or bone marrow transplant were recruited from an outpatient pediatric oncology clinic. The CDI was found to be a feasible tool that can be used in busy clinical settings, as it was less time-intensive compared to the DICA-IV. Further comparison of the CDI and DICA-IV indicated that there was no evidence that participants were more willing to disclose their symptoms on a self-report questionnaire compared to a face-to-face interview. As for recruitment issues, females were more willing to participate in the study than males, but overall, adolescents as a group were a difficult population to engage in the study, with only a 56% participation rate in this study. Future research will need to address these recruitment challenges. Finally gender (p=0.013) and anxiety (p=0.003) were significantly correlated with a MDE.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».