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运用群组概念映射法为重度精神疾病成年人开发住房及社区居住环境的概念模型。

Using Group Concept Mapping to Develop a Conceptual Model of Housing and Community-Based Residential Settings for Adults With Severe Mental Illness.

作者信息

Felx Amélie, Kane Mary, Corbière Marc, Lesage Alain

机构信息

Research Centre, Institut universitaire en santé mentale de Montréal (IUSMM), Montreal, QC, Canada.

Mental Health and Addiction Programs, Douglas Mental Health University Institute, Montreal, QC, Canada.

出版信息

Front Psychiatry. 2020 Jun 19;11:430. doi: 10.3389/fpsyt.2020.00430. eCollection 2020.

DOI:10.3389/fpsyt.2020.00430
PMID:32636764
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7319103/
Abstract

BACKGROUND

Most existing conceptual models of residential environments and housing programs were developed over a decade ago or lack comprehensiveness. The attributes to be used to describe housing programs with adequate specification remain unclear including the attributes that mediate service user outcomes. In this study, group concept mapping was used to develop a conceptual model of housing and community-based residential settings for adults with severe mental illness based on stakeholder perceptions and values.

METHODS

Participants were selected through purposive sampling and included service users, family members, staff working in residential facilities, mental health workers and managers. Participants (n=221) generated 1,382 statements describing attributes of housing and community-based residential settings for adults with severe mental illness (99% saturation). Thematic content analysis was conducted to analyze the statements and create a list of 140 selected statements. Participants then rated (n=416) and sorted into categories (n=73) the selected statements. Descriptive statistics were computed for each statement relative importance. Multidimensional scaling and hierarchical cluster analysis were used to produce the conceptual model (maps). Stakeholders (n=12) were also involved in the interpretation of the maps.

RESULTS

The findings show overall concordance between stakeholders in relation to statements perceived importance (rating) and the statements inter-relationships (sorting). The stress value of 0.23 indicates that the two-dimensional solution of the multidimensional scaling analysis fits the data set (goodness of fit). The final conceptualization includes 12 clusters: (1) A balanced and healthy housing system; (2) Quality and management practices (facility/local level); (3) Physical external environment; (4) Services tailored to needs and preferences; (5) Services and interventions provided (linkage); (6) Equality, policies and availability of activities; (7) Organizational structure and staff qualities; (8) Services and interventions (learning skills); (9) Services and interventions (daily living support); (10) Personal space and right to privacy; (11) Physical interior environment; (12) Respect, functioning and atmosphere.

CONCLUSION

The results illustrate the multifaceted and multilevel nature of community-based residential settings through a visual representation. They articulate a number of attributes, clusters and dimensions that could be included in a common conceptual model of community-based residential settings and housing for adults with severe mental illness.

摘要

背景

大多数现有的居住环境和住房项目概念模型是在十多年前开发的,或者缺乏全面性。用于充分描述住房项目的属性仍不明确,包括介导服务使用者结果的属性。在本研究中,基于利益相关者的认知和价值观,采用小组概念映射法为患有严重精神疾病的成年人开发了一个住房和社区居住环境的概念模型。

方法

通过目的抽样选择参与者,包括服务使用者、家庭成员、居住设施工作人员、心理健康工作者和管理人员。参与者(n = 221)生成了1382条描述患有严重精神疾病的成年人的住房和社区居住环境属性的陈述(饱和度99%)。进行主题内容分析以分析这些陈述,并创建了一份包含140条选定陈述的列表。然后,参与者对选定的陈述进行评分(n = 416)并分类(n = 73)。计算每条陈述的描述性统计数据以确定其相对重要性。使用多维尺度分析和层次聚类分析来生成概念模型(地图)。利益相关者(n = 12)也参与了对地图的解读。

结果

研究结果表明,利益相关者在陈述的感知重要性(评分)和陈述的相互关系(分类)方面总体一致。压力值0.23表明多维尺度分析的二维解决方案与数据集拟合良好(拟合优度)。最终的概念化包括12个聚类:(1)平衡且健康 的住房系统;(2)质量和管理实践(设施/地方层面);(3)外部物理环境;(4)根据需求和偏好定制的服务;(5)提供的服务和干预措施(联系);(6)平等、政策和活动的可获得性;(7)组织结构和员工素质;(8)服务和干预措施(学习技能);(9)服务和干预措施(日常生活支持);(10)个人空间和隐私权;(11)内部物理环境;(12)尊重、功能和氛围。

结论

研究结果通过直观的呈现方式说明了社区居住环境的多方面和多层次性质。它们阐明了一些属性、聚类和维度,这些可以纳入一个针对患有严重精神疾病的成年人的社区居住环境和住房的通用概念模型中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15fa/7319103/47317d52536b/fpsyt-11-00430-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15fa/7319103/1e7970b72f55/fpsyt-11-00430-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15fa/7319103/47317d52536b/fpsyt-11-00430-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15fa/7319103/1e7970b72f55/fpsyt-11-00430-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15fa/7319103/47317d52536b/fpsyt-11-00430-g002.jpg

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