School of Health Sciences, Queen Margaret University, Edinburgh, EH21 6UU, UK.
BMC Geriatr. 2021 Oct 30;21(1):613. doi: 10.1186/s12877-021-02546-7.
Assistive Technology for people with dementia living at home is not meeting their care needs. Reasons for this may be due to limited understanding of variation in multiple characteristics of people with dementia including their safety and wandering risks, and how these affect their assistive technology requirements. This study therefore aimed to explore the possibility of grouping people with dementia according to data describing multiple person characteristics. Then to investigate the relationships between these groupings and installed Assistive Technology interventions.
Partitioning Around Medoids cluster analysis was used to determine participant groupings based upon secondary data which described the person characteristics of 451 people with dementia with Assistive Technology needs. Relationships between installed Assistive Technology and participant groupings were then examined.
Two robust clustering solutions were identified within the person characteristics data. Relationships between the clustering solutions and installed Assistive Technology data indicate the utility of this method for exploring the impact of multiple characteristics on Assistive technology installations. Living situation and caregiver support influence installation of assistive technology more strongly than level of risk or cognitive impairment. People with dementia living alone received different AT from those living with others.
Results suggest that caregiver support and the living situation of the person with dementia influence the type and frequency of installed Assistive Technology. Reasons for this include the needs of the caregiver themselves, the caregiver view of the participants' needs, caregiver response to alerts, and the caregiver contribution to the assistive technology assessment and selection process. Selection processes should be refined to account for the needs and views of both caregivers and people with dementia. This will require additional assessor training, and the development of validated assessments for people with dementia who have additional impairments. Policies should support the development of services which provide a wider range of AT to facilitate interventions which are focused on the needs of the person with dementia.
居家痴呆症患者的辅助技术无法满足他们的护理需求。造成这种情况的原因可能是由于对痴呆症患者的多种特征(包括他们的安全和走失风险)的变化了解有限,以及这些特征如何影响他们的辅助技术需求。因此,本研究旨在探索根据描述多种人员特征的数据对痴呆症患者进行分组的可能性。然后研究这些分组与已安装的辅助技术干预之间的关系。
使用基于中位数的分区聚类分析方法,根据描述 451 名有辅助技术需求的痴呆症患者个体特征的次要数据,确定参与者分组。然后检查已安装的辅助技术与参与者分组之间的关系。
在个体特征数据中确定了两个稳健的聚类解决方案。聚类解决方案与安装的辅助技术数据之间的关系表明,该方法可用于探索多种特征对辅助技术安装的影响。居住情况和照顾者支持对辅助技术的安装比风险或认知障碍程度的影响更大。独居的痴呆症患者比与他人同住的患者获得不同的辅助技术。
结果表明,照顾者支持和痴呆症患者的居住情况会影响已安装辅助技术的类型和频率。造成这种情况的原因包括照顾者自身的需求、照顾者对参与者需求的看法、照顾者对警报的反应,以及照顾者对辅助技术评估和选择过程的贡献。选择过程应加以完善,以考虑到照顾者和痴呆症患者的需求和意见。这将需要更多的评估员培训,以及为有额外障碍的痴呆症患者开发经过验证的评估方法。政策应支持提供更广泛的辅助技术服务的发展,以促进以痴呆症患者的需求为重点的干预措施。