Interventions for Managing a Symptom Cluster of Pain, Fatigue, and Sleep Disturbances During Cancer Survivorship: A Systematic Review

Sheikh-Wu, Sameena F.; Downs, Charles A.; Anglade, Debbie

doi:10.1188/20.onf.e107-e119

Cited by 23 publications

(25 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Symptom clusters are commonly seen across cancer populations and may have similar underlying etiology as a single symptom, even though symptom clusters may produce different outcomes (Albusoul et al, 2017; Sheikh-Wu et al, 2020). We examined whether positive psychology moderates the relationship between symptom(s) characteristics and quality of life among CRC survivors.…”

Section: Discussionmentioning

confidence: 99%

“…Quality of life is a person’s perceived state of well-being that has physical and psychosocial implications on ones’ long-term health maintenance and survival (Drury, 2022; World Health Organization, 2020). Among cancer survivors, those reporting lower levels of quality of life showed an increase in mortality rates (DuMontier et al, 2018; Sheikh-Wu et al, 2020). However, in recent years, when asked survivors report positive changes (e.g., life satisfaction and appreciation, positive and stronger social connections) associated with their cancer diagnosis, referred to as positive psychology (Gesselman et al, 2017; Jansen et al, 2011; Mosher et al, 2017; Park & Sinnott, 2018; Walsh et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Relationships Between Colorectal Cancer Survivors’ Positive Psychology, Symptoms, and Quality of Life

et al. 2022

Self Cite

View full text Add to dashboard Cite

This cross-sectional study examined colorectal cancer (CRC) survivors’ symptom and symptom cluster characteristics (occurrence, frequency, and severity), positive psychology (benefit-finding and post-traumatic growth), and quality of life (QoL), and determined whether positive psychology moderates symptoms and QoL relationship during acute cancer survivorship, time from diagnosis to treatment completion. A total of 117 CRC survivors completed demographics, symptoms, QoL, and positive psychology questionnaires. Descriptive statistics, multiple linear regression, and moderation analyses were performed. Participants reported high QoL (94%, M = 5.15) and moderate-high positive psychology (75%, M = 3.21). Nineteen symptoms and five symptom clusters were inversely related to QoL ( p < .05). Positive psychology ( M = ~≥3.24) moderated the relationship of QoL ( p < .05) with symptoms occurrence ( n = 10), symptom severity ( n = 1), and with the generalized symptom cluster (weakness, fatigue, dizziness, drowsy, sleep disturbances, and pain). Positive psychology aids in symptom management and improves QoL. Nurses are poised to identify, prevent, promote, and advocate self-management skills to improve health-related outcomes.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Relationships Between Colorectal Cancer Survivors’ Positive Psychology, Symptoms, and Quality of Life

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Par exemple, il arrive que les survivants présentent des symptômes causés par le cancer et ses traitements (ex. dépression, trouble de l'image corporelle, dysfonctionnement sexuel, neuropathie des mains et des pieds) qui peuvent s'exacerber avec le temps (Deshields et al, 2014;Fan et al, 2007;Sheikh-Wu et al, 2020;Sheikh-Wu et al, 2021). Si ces symptômes ne sont pas pris en charge, les survivants risquent d'éprouver de l'incertitude et de la détresse; ils perçoivent alors plus négativement leur état de santé et leur qualité de vie, ce qui, en fin de compte, augmente la mortalité (DuMontier et al, 2018;Sheikh-Wu et al, 2020).…”

Section: Résuméunclassified

Modèle de survie au cancer appliqué aux soins holistiques et à la recherche

Sheikh-Wu¹,

Anglade²,

Downs³

2023

CONJ

View full text Add to dashboard Cite

Les progrès réalisés dans la lutte contre le cancer ont augmenté les taux de survie, entraînant un tel changement de paradigme que le cancer est maintenant considéré comme une maladie chronique; il nous faut donc évaluer notre connaissance de la survie au cancer (SC). C’est dans cette optique que les auteurs ont procédé à une recension exhaustive des écrits dans les référentiels CINAHL, MEDLINE et PUBMED de 2000 et 2021. En s’appuyant sur les concepts étudiés dans la littérature, ils ont répertorié les principaux facteurs qui influencent la survie au cancer dans l’ensemble des populations atteintes et ont proposé un modèle. Le présent article décrit ce modèle de survie au cancer (MSC). Le MSC prend en compte les facteurs prédisposant à la survie ainsi que les facteurs d’influence en jeu dans les trois phases de survie (aiguë, prolongée et permanente), à savoir le traitement et le traitement d’entretien (soins médicaux et psychosociaux), le bien-être, et d’autres éléments d’influence (expériences entraînant de profonds changements, incertitude, établissement de priorités, gestion du bien-être et conséquences indirectes) de même que les facteurs liés aux relations sociales qui jouent sur le fardeau des symptômes des survivants ainsi que l’expérience globale de la survie (état de santé et qualité de vie). Une étude de cas a d’ailleurs montré l’utilité du MSC. L’application du modèle est prometteuse pour l’avenir, tant pour améliorer la qualité de la survivance que pour guider la recherche et la pratique clinique en vue de favoriser et d’optimiser la bonne santé des survivants à long terme.

show abstract

“…Cancer survivors are defined [42] as persons who have completed primary treatments for cancer, and are apparently free of recurrent or persistent cancer. More specifically, we will consider the period after the end of primary treatment, when there is a lower risk of recurrence [43]: [1][2][3][4][5] years after the end of primary cancer treatments.…”

Section: Study Populationmentioning

confidence: 99%

“…Cancer survivors may face different physical and/or psychosocial sequelae caused by the illness or the treatments. Frequently, these patients report symptoms such as pain, fatigue, cognitive impairment, sexual dysfunction, sleep disturbances, distress, anxiety, or depression [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

A prospective observational study for a Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment (FAITH): study protocol

et al. 2022

View full text Add to dashboard Cite

Background Depression is a common condition among cancer patients, across several points in the disease trajectory. Although presenting higher prevalence rates than the general population, it is often not reported or remains unnoticed. Moreover, somatic symptoms of depression are common in the oncological context and should not be dismissed as a general symptom of cancer. It becomes even more challenging to track psychological distress in the period after the treatment, where connection with the healthcare system typically becomes sporadic. The main goal of the FAITH project is to remotely identify and predict depressive symptoms in cancer survivors, based on a federated machine learning (ML) approach, towards optimization of privacy. Methods FAITH will remotely analyse depression markers, predicting their negative trends. These markers will be treated in distinct categories, namely nutrition, sleep, activity and voice, assessed in part through wearable technologies. The study will include 300 patients who have had a previous diagnosis of breast or lung cancer and will be recruited 1 to 5 years after the end of primary cancer. The study will be organized as a 12-month longitudinal prospective observational cohort study, with monthly assessments to evaluate depression symptoms and quality of life among cancer survivors. The primary endpoint is the severity of depressive symptoms as measured by the Hamilton Depression Rating Scale (Ham-D) at months 3, 6, 9 and 12. Secondary outcomes include self-reported anxiety and depression symptoms (HADS scale), and perceived quality of life (EORTC questionnaires), at baseline and monthly. Based on the predictive models gathered during the study, FAITH will also aim at further developing a conceptual federated learning framework, enabling to build machine learning models for the prediction and monitoring of depression without direct access to user’s personal data. Discussion Improvements in the objectivity of psychiatric assessment are necessary. Wearable technologies can provide potential indicators of depression and anxiety and be used for biofeedback. If the FAITH application is effective, it will provide healthcare systems with a novel and innovative method to screen depressive symptoms in oncological settings. Trial registration Trial ID: ISRCTN10423782. Date registered: 21/03/2022.

show abstract

Interventions for Managing a Symptom Cluster of Pain, Fatigue, and Sleep Disturbances During Cancer Survivorship: A Systematic Review

Cited by 23 publications

References 42 publications

Relationships Between Colorectal Cancer Survivors’ Positive Psychology, Symptoms, and Quality of Life

Relationships Between Colorectal Cancer Survivors’ Positive Psychology, Symptoms, and Quality of Life

Modèle de survie au cancer appliqué aux soins holistiques et à la recherche

A prospective observational study for a Federated Artificial Intelligence solution for moniToring mental Health status after cancer treatment (FAITH): study protocol

Contact Info

Product

Resources

About