Suppr超能文献

就英国饮食失调临床研究网络中要收集的一系列生物心理社会变量达成共识:一项采用改良名义组技术的共识研究。

Agreeing a set of biopsychosocial variables for collection across the UK Eating Disorders Clinical Research Network: a consensus study using adapted nominal group technique.

作者信息

Jewell Tom, Smith Iona, Downs James, Carnegie Anna, Kakar Saakshi, Meldrum Laura, Qi Lu, Foye Una, Malouf Chelsea M, Baker Suzanne, Virgo Hope, Okoro Marilyn, Griffiths Jessica, Munblit Daniel, Herle Moritz, Schmidt Ulrike, Byford Sarah, Landau Sabine, Llewellyn Clare, Nicholls Dasha, Ayton Agnes, McNeil Sheryllin, Anderson Stephen, Breen Gerome, Allen Karina L

机构信息

Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care, King's College London, London, UK

Psychological and Mental Health Services, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.

出版信息

BMJ Ment Health. 2025 Jul 20;28(1):e301760. doi: 10.1136/bmjment-2025-301760.

Abstract

BACKGROUND

Eating disorders are serious psychiatric disorders associated with high levels of co-occurring physical and mental health conditions and poor treatment outcomes. The collection of standardised, routinely collected data within clinical services holds promise to improve patient care.

OBJECTIVE

To agree on a set of biopsychosocial variables for routine data collection within eating disorder services in the UK.

METHODS

Two online workshops were conducted using an adapted nominal group technique to agree on priorities for data collection in adult and child/adolescent eating disorder services. Workshop participants (n=43) consisted of people with lived experience, carers, clinicians and researchers. Two researchers independently conducted a reflexive thematic analysis of the workshop transcripts to identify qualitative priorities for data collection. Descriptive statistics were used to analyse the results of online voting.

FINDINGS

Thematic analysis identified four superordinate themes for data collection in eating disorder services: (1) a mutually valued and beneficial collaboration; (2) a holistic approach; (3) a balance between standardisation and individualisation; (4) doing no harm. Quantitative analysis of voting identified priorities across a range of domains, leading to a proposed biopsychosocial dataset.

CONCLUSIONS

This project agreed on a set of biopsychosocial variables for routine data collection in the UK Eating Disorders Clinical Research Network. Further research should evaluate the implementation success of these variables.

CLINICAL IMPLICATIONS

Patients, caregivers and clinicians support routine data collection in eating disorder services so long as the measures used are considered meaningful, not overly burdensome, non-stigmatising and collected in collaboration between patients and treatment providers.

摘要

背景

饮食失调是严重的精神疾病,常伴有多种身心健康问题,且治疗效果不佳。在临床服务中收集标准化的常规数据有望改善患者护理。

目的

就英国饮食失调服务中常规数据收集的一系列生物心理社会变量达成共识。

方法

采用改良的名义小组技术举办了两次在线研讨会,以确定成人及儿童/青少年饮食失调服务中数据收集的优先事项。研讨会参与者(n = 43)包括有实际经验的人、护理人员、临床医生和研究人员。两名研究人员独立对研讨会记录进行了反思性主题分析,以确定数据收集的定性优先事项。使用描述性统计分析在线投票结果。

结果

主题分析确定了饮食失调服务中数据收集的四个上级主题:(1)相互重视且有益的合作;(2)整体方法;(3)标准化与个性化之间的平衡;(4)不造成伤害。投票的定量分析确定了一系列领域的优先事项,从而形成了一个提议的生物心理社会数据集。

结论

该项目就英国饮食失调临床研究网络中常规数据收集的一组生物心理社会变量达成了共识。进一步的研究应评估这些变量的实施成效。

临床意义

只要所采用的措施被认为有意义、不过于繁重、不具污名化且是在患者与治疗提供者合作的情况下收集的,患者、护理人员和临床医生就支持在饮食失调服务中进行常规数据收集。

相似文献

5
Psychological therapies for women who experience intimate partner violence.针对遭受亲密伴侣暴力的女性的心理疗法。
Cochrane Database Syst Rev. 2020 Jul 1;7(7):CD013017. doi: 10.1002/14651858.CD013017.pub2.

本文引用的文献

1
Genetics of Anorexia Nervosa: Translation to Future Personalized Therapies.神经性厌食症的遗传学:向未来个性化治疗的转化
Psychiatr Clin North Am. 2025 Jun;48(2):293-309. doi: 10.1016/j.psc.2025.01.007. Epub 2025 Feb 28.
3
Using Progress Feedback to Enhance Treatment Outcomes: A Narrative Review.利用进展反馈改善治疗效果:一项叙述性综述
Adm Policy Ment Health. 2025 Jan;52(1):210-222. doi: 10.1007/s10488-024-01381-3. Epub 2024 May 11.
6
International consensus on patient-centred outcomes in eating disorders.国际共识:进食障碍患者为中心的结果
Lancet Psychiatry. 2023 Dec;10(12):966-973. doi: 10.1016/S2215-0366(23)00265-1. Epub 2023 Sep 25.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验