What factors are associated with informal carers’ psychological morbidity during end-of-life home care? A systematic review and thematic synthesis of observational quantitative studies
Notice bibliographique
Résumé
Background Family carers are central in supporting patients nearing end of life. As a consequence, they often suffer detrimental impacts on their own mental health. Understanding what factors may affect carers’ mental health is important in developing strategies to maintain their psychological well-being during caregiving. Aim To conduct a systematic review and thematic evidence synthesis of factors related to carers’ mental health during end-of-life caregiving. Method Searches of MEDLINE, CINAHL, PsychINFO, Social Sciences Citation Index, EMBASE, Cochrane Central Register of Controlled Trials and Database of Abstracts of Reviews of Effects 1 January 2009–24 November 2019. We included observational quantitative studies focusing on adult informal/family carers for adult patients at end of life cared for at home considering any factor related to carer mental health (anxiety, depression, distress and quality of life) pre-bereavement. Newcastle–Ottawa Quality Assessment Scale was used. Thematic analysis with box score presentation, and meta-analysis were done where data permitted. Results Findings from 63 included studies underpinned seven emergent themes. Patient condition (31 studies): worse patient psychological symptoms and quality of life were generally associated with worse carer mental health. Patient depression was associated with higher depression in carers (standardised mean difference = 0.59, 95% confidence interval 0.32 to 0.87, I 2 = 77%). Patients’ other symptoms and functional impairment may relate to carer mental health, but findings were unclear. Impact of caring responsibilities (14 studies): impact on carers’ lives, task difficulty and general burden had clear associations with worse carer mental health. Relationships (8 studies): family dynamics and the quality of the carer–patient relationship may be important for carer mental health and are worthy of further investigation. Finance (6 studies): insufficient resources may relate to carers’ mental health and warrant further study. Carers’ psychological processes (13 studies): self-efficacy and preparedness were related to better mental health. However, findings regarding coping strategies were mixed. Support (18 studies): informal support given by family and friends may relate to better carer mental health, but evidence on formal support is limited. Having unmet needs was related to worse mental health, while satisfaction with care was related to better mental health. Contextual factors (16 studies): older age was generally associated with better carer mental health and being female was associated with worse mental health. Limitations Studies were mainly cross-sectional (56) rather than longitudinal (7) which raises questions about the likely causal direction of relationships. One-third of studies had samples < 100, so many had limited statistical power to identify existing relationships. Conclusions and future work Future work must adopt a comprehensive approach to improving carers’ mental health because factors relating to carer mental health cover a broad spectrum. The literature on this topic is diverse and difficult to summarise, and the field would benefit from a clearer direction of enquiry guided by explanatory models. Future research should (1) further investigate quality of relationships and finances; (2) better define factors under investigation; (3) establish, through quantitative causal analyses, why factors might relate to mental health; and (4) utilise longitudinal designs more to aid understanding of likely causal direction of associations. Study registration This study is registered as PROSPERO registration 2019 CRD42019130279 at https://www.crd.york.ac.uk/prospero/. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme HSDR 18/01/01 and is published in full in Health and Social Care Delivery Research . See the NIHR Funding and Awards website for further award information.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,006 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 tête enseignante, 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 ».