Differences in Assistive Technology Installed for People With Dementia Living at Home Who Have Wandering and Safety Risks

Differences in Assistive Technology Installed for People With Dementia Living at Home Who Have Wandering and Safety Risks | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Differences in Assistive Technology Installed for People With Dementia Living at Home Who Have Wandering and Safety Risks Eleanor Curnow, Robert Rush, Sylwia Gorska, Kirsty Forsyth This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-95753/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2021 Read the published version in BMC Geriatrics → Version 1 posted 10 You are reading this latest preprint version Abstract Background : 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. 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. Methods : 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. Results : 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. Conclusions : 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. Geriatrics & Gerontology living situation caregiver support secondary data analysis living alone Figures Figure 1 Figure 2 Figure 3 Background Assistive technology (AT) has been proposed as an intervention which can reduce the risk of adverse outcomes related to safety and wandering, by meeting the needs of people with dementia. However, there is an acknowledged gap between required care and the AT services provided for people with dementia (1), and evidence for their effectiveness remains inconsistent (2). The reasons for this are unclear but perhaps include incomplete awareness of differences in the requirements of people with dementia in the real world (3), insufficient assessment of their circumstances (4,5), and limited availability of AT interventions (6,7). Variations of the model of healthcare utilisation indicate that many characteristics have an impact upon health service use (8-10). However, the relative importance of each characteristic, their impact, together with the heterogeneity of user requirements and other person characteristics restricts understanding of their relationship to AT interventions (11-14). Research into the effects of multiple variables on the provision of AT is scarce (11). Need factors have traditionally been viewed as the most immediate cause of health service use (15). However, predisposing characteristics including the relationship between the person with dementia and their caregiver are important predictors of health care utilisation (10). Additionally, enabling resources such as caregiver support can facilitate or inhibit the use of healthcare services (16). Unmet needs and risks are strongly associated with adverse outcomes (17,18) , and wandering and safety risks have been identified as primary concerns for caregivers of people with dementia (19,20). As there is evidence that these risks can be modified, this study will focus upon AT installed to reduce risks in these areas (18). In order to provide people with dementia with effective, client centred AT interventions service providers must understand patterns of need for people with dementia and how these relate to specific AT interventions (11,21,22). Hence, there is a need to explore the relationship between multiple variables and AT use. This research aims to investigate patterns in person characteristics of people with dementia living at home, specifically: wandering and safety risks; Mini Mental State Examination scores (MMSE) (23); living situation; caregiver support; and how these relate to installed AT. Methods This study used secondary analysis of data collected from the ATTILA RCT investigating the impact of AT on institutionalisation for people with dementia living at home in 11 Council with Adult Social Service Responsibilities (CASSR) areas across England ( 24 ). Population Characteristics Three categories of population characteristics have been shown to have an impact upon healthcare utilisation namely predisposing, enabling and need categories ( 9 ). These data included participant risk of wandering and safety categorised for the primary study according to the number of incidents previously experienced by the person with dementia. A low rating indicates no or very few relevant incidents, occasional incidents would be classified as moderate, and a high-risk rating indicates very frequent or very serious incidents. Level of caregiver support was categorised according to the amount of times the caregiver was present; ( 1 ) live-in caregiver, ( 2 ) caregiver visits at least once / day, or ( 3 ) caregiver visits less than once/ day. Living situation was categorised as ( 1 ) living with spouse/ partner, ( 2 ) living alone or ( 3 ) Other. All participants categorised as “other” were living with another person who was not their spouse or partner, generally another relative. MMSE was scored on a scale which ranged from 0 to 30, where 30 indicates no dementia; scores of 26–29 indicate questionable dementia; 21–25 indicates mild dementia; 11–20 suggests moderate dementia and a score of 0–10 indicates severe dementia ( 25 ). Assessment of need was conducted in line with normal CASSR practice to determine level of need and required AT services. AT considered in this study was installed within six months of recruitment. The list of installed AT categories is provided in Table 1 ( 26 ). The installation of AT reflects normal CASSR practice and was not funded, assessed or installed by the RCT ( 24 ). Table 1 Categories of Assistive Technology Basic AT Pendant alarm Non-monitored smoke detector Non-monitored carbon monoxide Key safe Activity monitors assessment only Other devices Reminder or prompting devices Date and time reminders Item locator devices Medication reminders/dispensers Voice recorders and memo minders Other reminder/prompting devices Devices to promote safety Activity monitors - on-going monitoring Fall detectors Continence management devices Alarm and pager units Flood detectors and water temperature monitor Gas detectors Monitored carbon monoxide detectors Monitored smoke detectors Monitored extreme temperature sensors Lighting devices Other safety and security devices Safer walking technologies To locate the user To alert the responder to movement Communication devices Intercoms Telephones Communication aids Other communication devices Devices that support meaningful use of leisure time Computer aids Dementia friendly TV/radio/music players Electronic photo albums/electronic reminiscence aids Electronic games Other devices -support meaningful use of leisure time Methodology To identify groups of people with dementia who have similar AT needs this study employed cluster analysis. This technique is essentially concerned with discovering intrinsic discrete groups within data ( 27 – 29 ). Reduction of a heterogeneous sample into a number of more homogeneous groups provides a means to organise large quantities of information and facilitates consideration of multiple characteristics ( 30 ). A Partitioning Around Medoids (PAM) algorithm for clustering data was employed due to its toleration of Gower distance to measure dissimilarity ( 31 ). Gower distance assesses partial dissimilarities and can accommodate mixed data types ( 32 ). The number of clusters was determined through examination of the silhouette coefficient ( 33 ). Observations with large silhouette width (almost 1) can be considered well clustered. Silhouette width was used as a means to evaluate the clustering solution relative to other possible clustering solutions and facilitated the selection of the most robust solution. Utility of the clustering solutions was tested through exploration of their relationship with installed AT. Installed AT data was stratified according to each of the clustering solutions in turn. The wandering cluster solution included data describing caregiver support, living situation, MMSE and level of risk of wandering of the participants. Similarly, the safety cluster solution included data describing caregiver support, living situation, MMSE and level of safety risk of the participants. Installed AT data was also stratified according to wandering risk, and safety risk for comparison purposes. Where data was available the strength of these associations between installed AT and level of wandering, safety risk and clustering solutions were tested using Chi square analyses ( 34 ). These analyses were conducted using R Studio Software ( 35 , 36 ), and the Cluster package ( 37 ). Ethics Approval for this secondary data analysis study was obtained from Queen Margaret University Ethics Committee. FIGURE 1 NEAR HERE Results The dataset contained anonymised information on 451 participants with dementia or suspected dementia living at home in England who had a documented needs assessment available for analysis (Fig. 1). Fifty-six participants did not have documented MMSE scores for unspecified reasons (Table 2 ) and were excluded from the analysis. These excluded participants were more likely to have high risk of wandering and high safety risk when compared with the remaining population. The relationship between MMSE and wandering or safety risk were not significant although participants with low risk of wandering had higher MMSE scores (M = 19.05 (SD = 6.1)) than participants with high risk of wandering (M = 14.35 (SD = 7.1)). Similarly, participants with low safety risk had higher MMSE score (M = 18.35 (SD = 6.66)) than participants with high safety risk (M = 16.15 (SD = 8.35)). This indicates that participants with increased cognitive impairment experience higher levels of wandering and safety risks. Table 2 Population with and without Mini Mental State Examination Score Without MMSE With MMSE n (%) 56(12.4) 395(87.6) Gender = Female 35 (62.5) 229 (57.97) Living Situation Living alone 21 (37.5) 182 (46.1) Living with spouse/partner 21 (37.5) 160 (40.5) Other 14 (25.0) 53 (13.4) Caregiver Support Caregiver visits at least once per day 16 (28.6) 95 (24.1) Caregiver visits less than once per day 11 (19.6) 107 (27.1) Live-in caregiver 29 (51.8) 193 (48.9) Risk of Wandering Low 35 (62.5) 293 (74.2) Moderate 14 (25.0) 76 (19.2) High 7 (12.5) 26 ( 6.6) Safety Risk Low 19 (33.9) 211 (53.4) Moderate 28 (50.0) 158 (40.0) High 9 (16.1) 26 ( 6.6) Note . N = 451, MMSE = Mini Mental State Examination ( 23 ), M = Mean, SD = Standard Deviation Overall, 1335 AT devices were installed during the 6-month period after baseline. Participants with MMSE scores (n = 395) included within this analysis, had 1217 AT devices installed during this period (Fig. 1). Clustering solutions including both safety and wandering risk data together with caregiver support, living situation and MMSE score had an average silhouette width below 0.5 indicating that these structures were not robust. Therefore, two separate clustering solutions were developed based on the following data variables: Risk of Wandering or Safety Risk, Caregiver Support, Living Situation and MMSE score. These will now be described in turn. Table 3 provides a summary of the characteristics of the participants included in each of the three clusters based upon caregiver support, MMSE, living situation and risk of wandering data. Clusters were named to reflect dominant characteristics of participants within that cluster ( 29 ): ( 1 ) “Living with Spouse/ Partner”, ( 2 ) “Living with Other” and ( 3 ) “Living alone”. FIGURE 2 NEAR HERE Six participants included in this third cluster exhibited negative silhouette width ( 33 ) (Fig. 2 ). These participants were unusual within this dataset as they lived with spouse or partner or other yet did not have a live-in caregiver. Due to their small number it was not possible to draw conclusions regarding the Assistive Technology installations for these participants. This clustering solution had an average silhouette width of 0.63 indicating that a reasonable structure has been found ( 38 ). Medoids or exemplars are also presented for each cluster. Table 3 Partitioning Around Medoids (PAM) Summary for Wandering Cluster Cluster Caregiver Support n (%) MMSE Living Situation n (%) Risk of Wandering n (%) 1. Living with Spouse/ Partner ( n = 156) Live-in caregiver: 147(94.2) Caregiver visits at least once per day: 8(5.1) Caregiver visits less than once per day: 1(0.6) Min: 0.0 1st Qu.: 13.0 Median:19.0 M : 17.6 3rd Qu.: 24.0 Max: 28.0 Living alone: 0(0) Living with Spouse/ Partner: 156(100.0) Other: 0(0) Low:112(71.8) Mod: 34(21.8) High: 10(6.4) 2. Living with Other ( n = 51) Live-in caregiver: 46(90.2) Caregiver visits at least once per day: 4(7.84) Caregiver visits less than once per day: 1(1.78) Min: 0.0 1st Qu.: 14.5 Median: 18.0 M : 17.6 3rd Qu.: 24.0 Max: 29.0 Living alone: 0(0) Living with Spouse/ Partner: 0(0) Other: 51(100.0) Low: 36(70.6) Mod: 10(19.6) High: 5(9.8) 3. Living Alone ( n = 188) Live-in caregiver: 0(0) Caregiver visits at least once per day: 83(44.2) Caregiver visits less than once per day: 105(55.8) Min: 0.0 1st Qu.: 15.0 Median:20.0 M : 18.8 3rd Qu.: 23.0 Max: 28.0 Living alone: 182(96.8) Living with Spouse/ Partner: 4(2.1) Other: 2(1.1) Low:145(77.1) Mod: 32(17.0) High: 11(9.0) Medoids for Wandering Clusters 1. Living with Spouse/ Partner Live-in caregiver 19 Living with spouse/partner Low 2. Living with Other Live-in caregiver 18 Other Low 3. Living Alone Caregiver visits less than once per day 20 Living alone Low Note . N = 395, PAM = Partitioning Around Medoids, MMSE = Mini Mental State Examination ( 23 ), Min = Minimum, Qu = Quarter, M = Mean, Max = Maximum. Table 4 provides a summary of the characteristics of the participants based upon caregiver support, MMSE, living situation and safety risk data. Clusters were named ( 1 ) “Live with Someone”, and ( 2 ) “Live-out Caregiver” to reflect characteristics of their participants ( 29 ). FIGURE 3 NEAR HERE All participants had positive silhouette widths in this solution (Fig. 3 ). This average silhouette width of 0.59 indicates that a reasonable structure has been identified ( 38 ). Again, medoids are presented for each cluster. Table 4 Partitioning Around Medoids (PAM) Summary for Safety Cluster Cluster Caregiver Support n (%) MMSE Living Situation n (%) Safety Risk n (%) 1. Live with Someone ( n = 208) Live-in Caregiver: 193(92.79) Caregiver visits at least once per day: 12(5.77) Caregiver visits less than once per day: 3(1.44) Min.:0.00 1st Qu.:14.00 Median:18.00 M : 17.66 3rd Qu.:24.00 Max.:29.00 Living alone: 0(0.0) Living with spouse/ partner: 158(75.96) Other: 50(24.04) Low: 121(58.17) Moderate:70(33.65) High: 17 (8.17) 2. Live out Caregiver ( n = 187) Live-in Caregiver: 0(0.0) Caregiver visits at least once per day: 83(44.38) Caregiver visits less than once per day: 104(55.61) Min. 0.00 1st Qu.:15.00 Median:20.00 M : 18.72 3rd Qu.:23.00 Max.:28.00 Living alone:182(97.33) Living with spouse/ partner: 2(1.07) Other: 3(1.60) Low: 90(48.13) Moderate:88(47.06) High: 9(4.81) Medoids for Safety Clusters 1. Live with Someone Live-in Caregiver 18 Living with spouse/ partner Low 2. Live out Caregiver Caregiver visits less than once per day 20 Living alone Moderate Note . N = 395, PAM = Partitioning Around Medoids, MMSE = Mini Mental State Examination ( 23 ), Min = Minimum, Qu = Quarter, M = Mean, Max = Maximum. Associations between the clusters and categories of installed AT are presented in Table 5 , together with associations identified between installed AT and risk of wandering or safety risk. Table 5 Associations with Installed Assistive Technology Risk Low Moderate High Wandering (N = 451) Medication Reminders and Dispensers ( χ² = 13.18, ** p = .001) Pendant Alarms ( χ² = 7.79, ** p = .020) Activity Monitors for Ongoing Monitoring ( χ² = 15.78, *** p = .0003) Safer Walking Technologies to Locate the User ( χ² = 39.04, *** p < .00001) Intercoms ( χ² = 27.90, *** p < .00001) Safer Walking Technologies to alert a Responder of Movement ( χ² = 40.40, *** p < .00001) Telephones ( χ² = 13.51, ** p = .001) Safety (N = 451) Safer Walking Technologies to Locate the User ( χ² = 13.41, ** p = .001) NA Fall Detectors ( χ² = 68.62, *** p < .00001) Wandering Cluster (N = 395) Living with Spouse/ partner Living with Other Living Alone Fall Detectors ( χ² = 6.94, * p = .03) Safer Walking Technologies to alert a responder of movement ( χ² = 7.33, * p = .02) Medication Reminders and Dispensers ( χ² = 15.91, *** p = .0003) NA Safety Cluster (N = 395) Live with Someone Live Out Caregiver Safer Walking Technologies to alert a Responder of Movement ( χ² = 19.67, *** p = .000009) Safer Walking Technologies to Locate the User ( χ² = 21.96, *** p = .000003) Monitored Smoke Detectors ( χ² = 7.58, ** p = .006) Pendant Alarms ( χ² = 10.42, ** p = .001) Note . AT = Assistive Technology, NA = Not available, * p < .05, ** p < .01, *** p < .001, associations are presented under group which most frequently received this category of AT. Risk of wandering was associated with installation of safer walking technologies to alert a responder of movement χ ² (2, N = 451) = 40.40, p = < .00001), safer walking technologies to locate the user χ ² (2, N = 451) = 39.04, p < .00001, medication reminders and dispensers χ ² (2, N = 451) = 13.18, p = .001, telephones χ ² (2, N = 451) = 13.51, p = .001, intercoms χ ² (2, N = 451) = 27.90, p < .00001, pendant alarms χ ² (2, N = 451) = 7.79, p = .02 and activity monitors for ongoing monitoring χ² (2, N = 451) = 15.78, p = .0003) (Table 5 ). Pendant alarms and medication reminders and dispensers were most frequently installed for participants with low risk of wandering. Activity Monitors for Ongoing Monitoring and Safer walking technologies to locate the user were most frequently installed for participants with moderate risk of wandering. Intercoms, Telephones and Safer Walking Technologies to alert a Responder of Movement were most frequently installed for participants with high risk of wandering. Safety risk was associated with installation of safer walking technologies to locate the user χ ² (2, N = 451) = 13.41, p = .001 most frequently installed for people with low safety risk; and fall detectors χ² (2, N = 451) = 68.62, p < .00001 which were most frequently installed for people with high safety risk. The wandering cluster solution was associated with installation of fall detectors χ ² (1, N = 395) = 6.94, p = .03, safer walking technologies to alert a responder of movement χ ² (2, N = 395) = 7.33, p = .02 and medication reminders and dispensers χ ² (2, N = 395) = 15.91, p = .0003. The safety cluster solution was associated with safer walking technologies to alert a responder of movement χ² (1, N = 395) = 19.67, p = .000009 and safer walking technologies to locate the user χ ² (1, N = 395) = 21.96, p = .000003. Both types of safer walking technologies were most frequently installed for participants “living with someone”. Monitored smoke detectors χ² (1, N = 395) = 7.58, p = .006 and pendant alarms χ² (1, N = 395) = 10.42, p = .001) were also associated with the safety cluster solution and were most frequently installed for participants in the “live out caregiver” cluster. Discussion This study has developed understanding of the interaction of heterogeneous person characteristics including predisposing characteristics, needs and enabling resources, and their impact upon installed AT interventions in current practice. Results demonstrate that robust clusters created from data describing the characteristics of people with dementia can provide a basis for the exploration of the impact of multiple factors upon AT installations for this population. Subsequently this study validated these cluster solutions through demonstration of their applicability to data describing AT installed for people with dementia living at home. Cluster analyses appear to have grouped people with dementia according to their caregiver support and living situation, although MMSE and risk of wandering or safety risk were also considered. Subsequent analysis of the relationship between the cluster solutions and installed AT illustrated differences in patterns of AT installation in regard to safety and wandering risk indicating that these are associated with contrasting areas of concern. AT provided to mitigate safety risk suggests consideration of mobility issues, including falls. Whereas, installed AT associated with level of wandering risk is more varied perhaps because of a wider area of interest. Associations between installed AT and clustering solutions in this study indicate that the relationship between the person with dementia and their caregiver or support network may also influence AT provision in a number of ways. These include that; ( 1 ) AT is provided to meet the needs of the caregiver; ( 2 ) input from the caregiver is required to obtain, maintain or monitor AT; and/ or ( 3 ) the caregiver provides a different view of the needs of the person with dementia resulting in a change in AT provision. These will now be discussed in turn. Installation of safer walking technologies to alert a responder of movement were associated with the “living with spouse/ partner”, or the “live with someone” clusters. Additionally, installation of safer walking technologies to locate the user was associated with the “live with someone” cluster. This type of AT may be used by caregivers to track people with dementia who are perceived to have lower risk of becoming lost and as a back up to caregiver support ( 39 ). However, as GPS technologies are generally used to back-up other forms of support and rarely facilitate independent walking for the person with dementia ( 39 ), results indicate that AT provision may be influenced by the needs of caregivers, such as fear of losing the person with dementia, to improve quality of life, and reduce stress ( 40 ). This confirms previous studies indicating a reduction in caregiver anxiety following the installation of AT ( 40 , 41 ). Safety is a known concern for caregivers even when the person with dementia is unable to leave the home ( 39 ), and often leads to restrictions being placed upon the independent activity of the participant. Caregivers prioritise the safety of the person with dementia even above their autonomy or privacy ( 42 ). If safer walking technologies are primarily installed to alleviate caregiver anxiety, this explains why this type of AT was less likely to be provided for people with dementia living alone. Caregiver anxiety is associated with the institutionalisation of the person with dementia; hence caregiver stress reduction has direct benefit for them and may be the reason for their acceptance of AT which restricts their autonomy ( 8 ). This may not be the case for people with dementia living alone. AT providers are therefore required to balance the needs and rights of people with dementia, whilst also considering the needs of the caregiver ( 43 ). Participants living with others were more likely to receive installations of fall detectors, safer walking technologies to alert a responder of movement and safer walking technologies to locate the user. Whereas, participants living alone received more basic AT items such as monitored smoke detectors, and carbon monoxide detectors. Reasons for these differences are unclear but in addition to the absence of caregivers’ concerns, may include there being no-one to adapt, monitor or respond to AT on their behalf ( 44 ). Caregivers who live with the person with dementia are likely to be able to respond more quickly to alerts than monitoring centres. As, wandering incidents may occur frequently, they can require high levels of response which are unavailable from formal response teams. Familiar caregivers will also have more understanding of the particular requirements of the person with dementia ( 45 ). Further, caregivers and co-residents may influence the assessment process, and therefore the AT installed for people living with others. Decisions to use tracking technologies have been shown to be informed by the caregivers’ personal assessment of the safety of the participant ( 39 ). Additionally, caregivers report higher levels of need than people with dementia report themselves ( 21 ). Results indicate a focus on the priorities of caregivers rather than people with dementia. People with dementia identify daily activities and socialising as their priority ( 46 ). Focussing on activities which increase participation can increase wellbeing, and reduce anxiety related behaviour such as wandering ( 22 ). In such incidences, people with dementia living with others are more likely to have a caregiver who is able to provide an overview of their needs and abilities on their behalf ( 47 , 48 ). Results of this study indicate that there are factors other than safety or wandering risk, which can affect installation of AT. Factors which may not be considered during the AT needs assessment include the impact of caregiver needs, the caregiver’s view of the person with dementia’s needs or the support received from informal caregivers. This may reflect limitations in the skills and knowledge of staff conducting the assessment of need ( 19 , 48 ). People living alone are less likely to be diagnosed with dementia, and clinicians often struggle to identify their needs ( 47 , 48 ). Additionally, people with more severe impairment often have less documented assessment than people with milder cognitive impairment ( 4 ). People with moderate to severe dementia may have difficulty understanding questions in assessment tools ( 49 ). Poor vision and hearing, deficient schooling and consequences of stroke or tremor may also make the completion of assessments difficult ( 50 ). Overall, this suggests that needs which are perhaps considered difficult to assess or cannot be directly observed such as psychological needs often remain unassessed ( 4 ). People with dementia living with others may be more likely to have a caregiver who can provide an overview of their needs and abilities. Whereas, the reduced level of understanding of the needs of particular groups such as people with dementia living alone, results in them being less likely to receive services, despite being identified as a high-risk group ( 51 ). In order to account for the AT needs of people at all stages of dementia there is a requirement for the development of skilled assessors, validated assessment tools and alternative methods of assessment. Further, these groups are also less likely to be included in research which would advance understanding of their intervention requirements ( 47 ). As caregivers have been identified as key actors in ensuring the safety of people with dementia ( 52 ), it is important to consider their views during the assessment of the person with dementia. Caregivers often monitor and maintain AT on behalf of the person with dementia. Additionally, AT is often provided for the reassurance and support of caregivers ( 53 ). It is therefore, difficult to distinguish between the needs of people with dementia and their caregivers as these are interwoven in a complex manner due to multiple interdependencies between these groups ( 10 ). Consideration of the views, needs and capabilities of the person with dementia and their caregiver or people they live with, during the assessment process will provide a target for the tailoring of interventions and increase the ability to meet needs. This study indicates limitations in the needs assessment of people with dementia. Staff appear to lack confidence in assessment of people with moderate or severe dementia, or dementia and other impairments which may restrict communication. There is a requirement to develop validated assessment tools which consider the needs of people with dementia and communication difficulties. Additional training in the assessment of people with dementia should be available to clinicians working in this field to facilitate the development of expertise. Results also indicate assessors have limited understanding of the relationship between personal characteristics and AT ( 20 ), which may be due to organisational policy, or limitations of time, support, training, knowledge and resources ( 54 ). Additionally, a supply led allocation process or preoccupation with risk generated interventions restricts choice and may increase distress ( 4 , 55 ). Policies, staff training and resources should be reviewed to ensure that they support person centred care. Assessment should focus on the individuality of the person with dementia and their circumstances, thereby increasing the acceptability of person centred rather than supply led AT interventions ( 4 ). Stakeholders will need to ensure access to sufficient AT resources to enable the installation of appropriate AT to meet identified needs ( 4 ). Limitations Limitations of this study include the low number of participants with moderate to severe dementia, high safety risk or high wandering risk. This restricts the transferability or generalisability of results, and further research is required to validate results for these populations ( 56 ). Safety risk and wandering risk and AT were categorised according to non-validated criteria. The reliability and validity of these instruments is therefore uncertain and restricts comparisons of these results with further research ( 57 ). Limited sample numbers also meant it was not possible to further validate the cluster analysis solutions on additional data ( 58 ). Summary This study has explored the impact of multiple factors upon AT installed for people with dementia living at home and provides validation of the use of partitioning around medoids cluster analysis as a method within this field. Results indicate that installation of AT for people with dementia living at home is influenced not only by their level of safety or wandering risk, but also by the level of caregiver support they receive and their living situation. There are a number of changes required to facilitate dementia friendly person-centred care. Policies should support assessment which considers the needs of the person with dementia, their caregivers and other members of their social network before installing AT. In order to improve effectiveness of AT interventions for people with dementia living at home there is a requirement for educators and professional bodies to advance assessment practice through mentorship and training. Assessors require to develop validated comprehensive assessment tools which account for different circumstances and impairments often experienced within this population, and which consider a wide range of care needs including psychological and social needs. There is also a requirement for assessment tools to direct assessors towards appropriate interventions ( 59 ), through evaluation of a wide range of needs experienced both by the person with dementia and members of their support network. There is a requirement for a wider range of AT to be available for installation in order to meet the individual needs of people with dementia and their caregivers. Declarations Ethics approval and consent to participate : This secondary data study received ethical approval from Queen Margaret University Ethics committee. Consent for publication : Not applicable Availability of data and materials : The dataset analysed during the current study are not publicly available prior to publication of the main report but will then be available from [email protected] on request. Competing interests : The authors declare that they have no competing interests Funding : Not applicable Authors contributions : EC, RR and KF made substantial contributions to the conception of the study. EC, SG, RR and KF contributed to the design of the work. EC, RR and KF were responsible for the acquisition, analysis and interpretation of data, EC and SG drafted the manuscript, all authors were involved in critical revision of the manuscript. All authors read and approved the manuscript submitted. All authors agree both to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated, resolved and the resolution documented in the literature. Acknowledgements : The authors wish to acknowledge the Attila RCT management group for granting permission to access the dataset on which this study was based. Authors’ information: References (1) World Health Organization. Global action plan on the public health response to dementia 2017-2025. 2017. (2) Kenigsberg PA, Aquino JP, Bremond F, Charras K, Dening T, Droes RM, et al. Assistive technologies to address capabilities of people with dementia: from research to practice. Dementia 2017;18(4):1568-1595. (3) Farmer C, Fenu E, O'Flynn N, Guthrie B. Clinical assessment and management of multimorbidity: summary of NICE guidelines. BMJ 2016 21 September 2016;354:i4843. (4) Hansen A, Hauge S, Helleso R, Bergland A. 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Alzheimer's & Dementia: Translational Research and Clinical Interventions 2019;5:420-430. (27) Everitt BS, Landau S, Leese M. Cluster Analysis. London: Arnold; 2001. (28) Gao X, Yang M. Understanding and enhancement of internal clustering validation indexes for categorical data. Algorithms 2018;11(177). (29) Hofstetter H, Dusseldorp E, van Empelen P, Paulussen TWGM. A primer on the use of cluster analysis or factor analysis to assess co-occurrence of risk behaviors. Preventative Medicine 2014;67:141-146. (30) Clatworthy J, Buick D, Hankins M, Weinman J, Horne R. The user and reporting of cluster analysis in health psychology: A review. British Journal of Health Psychology 2005;10:329-358. (31) Kaufman L, Rousseeuw PJ. Finding Groups in Data: An Introduction in Cluster Analysis. New York.: John Wiley & Sons; 1990. (32) Martin DP. Clustering mixed data types in R. 2016; Available at: www.r-bloggers.com/clustering-mixed-data-types-in-r/; (33) Filaire T. 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British Journal of Occupational Therapy 2010 April;73(4):152-159. (40) Gagnon-Roy M, Bourget A, Stocco S, Courchesne AL, Kuhne N, Provencher V. Assistive technology addressing safety issues in dementia: A scoping review. The American Journal Of Occupational Therapy: Official Publication Of The American Occupational Therapy Association 2017;71(5):1-10. (41) Spring HJ, Rowe MA, Kelly A. Improving Caregivers' Well-being by using Technology to Manage Nighttime Activity in Persons with Dementia. Research in Gerontological Nursing 2009;2(1):39-48. (42) Wood E, Ward G, Woolham J. The development of safer walking technology: a review. Journal of Assistive Technologies 2015;9(2):100-115. (43) O'Keeffe J. The use of assistive technology to reduce caregiver burden. Issue Brief. Research Summit on Dementia Care: Building Evidence for Service and Supports. 2017. (44) Gibson G, Dickinson C, Brittain K, Robinson L. Personalisation, customisation and bricolage: how people with dementia and their families make assistive technology work for them. Ageing and Society 2018:1-18. (45) Dunk B, Longman B, Newton L. GPS technologies in managing the risks associated with safer walking in people with dementia - a practical perspective. Journal of Assistive Technologies 2010;4(3):4-8. (46) Dickins M, Goeman D, O'Keefe F, Iliffe S, Pond D. Understanding the conceptualisation of risk in the context of community dementia care. Social Science and Medicine 2018;208:72-79. (47) Lehmann SW, Black BS, Shore A, Kasper J, Rabins PV. Living alone with dementia: lack of awareness adds to functional and cognitive vulnerabilities. International Psychogeriatrics 2010;22(5):778-784. (48) van Ooteghem K, Musselman KE, Mansfield A, Gold D, Marcil ME, Keren R, et al. Key factors for the assessment of mobility in advanced dementia: A consensus approach. Alzheimer's & Dementia: Translational Research and Clinical Interventions 2019;5:409-419. (49) Miranda-Castillo C, Woods B, Orrell M. The needs of people with dementia living at home from user, caregiver and professional perspectives: a cross-sectional survey. BMC Health Serv Res 2013 02/04;13:43-43. (50) Raiha I, Isoaho R, Ojanlatva A, Viramo P, Sulkava R, Kivela S. Poor performance in the Mini-Mental State Examination due to causes other than dementia. Scandinavian Journal of Primary Health Care 2001;19:34-38. (51) Tierney MC, Charles J, Naglie G, Jaglal S, Kiss A, Fisher RH. Risk factors for harm in cognitively impaired seniors who live alone: A prospective study. Journal of the American Geriatrics Society 2004 September;52(9):1435-1441. (52) Tudor Car L, El-Khatib M, Perneczky R, Papachristou N, Atun R, Rudan I, et al. Prioritizing problems in and solutions to homecare safety of people with dementia: supporting carers, streamlining care. BMC Geriatrics 2017;17(26):1-8. (53) Neubauer NA, Lapierre N, Rios-Rincon A, Miguel-Cruz A, Rousseau J, Liu L. What do we know about technologies for dementia-related wandering? A scoping review, Canadian Journal of Occupational Therapy 2018;85(3):196-208. (54) Sugarhood P, Wherton J, Procter R, Hinder S, Greenhalgh T. Technology as system innovation: A key informant interview study of the application of the diffusion of innovation model to telecare. Disability and Rehabilitation: Assistive Technology 2014;9(1):79-87. (55) Handley M, Bunn F, Goodman C. Dementia friendly interventions to improve the care of people living with dementia admitted to hospitals: a realist review. BMJ OPen 2017;7:e015257 (56) Lipworth W, Mason PH, Kerridge I, Ioannidis JPA. Ethics and epistemology in big data research. Bioethical Inquiry 2017;14:489-500. (57) Clark-Carter D. Quantitative Psychological Research: The Complete Student's Companion. 4th ed. Oxon: Routledge; 2019. (58) Brock G, Pihur V, Datta S, Datta S. clValid, an R package for cluster validation. 2011 October 17, 2011:1-32. (59) Schmid R, Eschen A, Rüegger-Frey B, Martin M. Instruments for comprehensive needs assessment in individuals with cognitive complaints, mild cognitive impairment or dementia: a systematic review. Int J Geriatr Psychiatry 2012 April;27(4):329-341. 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EH21 6UU.","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Eleanor","middleName":"","lastName":"Curnow","suffix":""},{"id":3865243,"identity":"034d34d0-2809-46eb-aaf8-83b769371284","order_by":1,"name":"Robert Rush","email":"","orcid":"","institution":"Queen Margaret University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Rush","suffix":""},{"id":3865244,"identity":"957ffe81-1b5e-40e1-9cc7-77b485690833","order_by":2,"name":"Sylwia Gorska","email":"","orcid":"","institution":"Queen Margaret University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sylwia","middleName":"","lastName":"Gorska","suffix":""},{"id":3865245,"identity":"7ac35197-e3a5-4944-b564-7da6e0ace21b","order_by":3,"name":"Kirsty Forsyth","email":"","orcid":"","institution":"Queen Margaret University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kirsty","middleName":"","lastName":"Forsyth","suffix":""}],"badges":[],"createdAt":"2020-10-20 23:42:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-95753/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-95753/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-021-02546-7","type":"published","date":"2021-10-30T15:06:23+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":3241882,"identity":"bcd77c0a-8052-4964-903d-f8df903b7818","added_by":"auto","created_at":"2020-10-28 13:48:17","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51936,"visible":true,"origin":"","legend":"Participants with documented Needs and installed Assistive Technology","description":"","filename":"Fig1.JPG","url":"https://assets-eu.researchsquare.com/files/rs-95753/v1/d147985dfda4cfb040c131a5.JPG"},{"id":3241883,"identity":"1ff2916f-6173-4f79-90c3-05baa2ff2383","added_by":"auto","created_at":"2020-10-28 13:48:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49780,"visible":true,"origin":"","legend":"Silhouette Plot for Wandering Cluster Solution","description":"","filename":"Fig2.JPG","url":"https://assets-eu.researchsquare.com/files/rs-95753/v1/8ba23065485f6241804da618.JPG"},{"id":3241884,"identity":"33331e6f-82e6-4402-86c1-c2002409296a","added_by":"auto","created_at":"2020-10-28 13:48:18","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":58492,"visible":true,"origin":"","legend":"Silhouette Plot for Safety Cluster Solution","description":"","filename":"Fig3.JPG","url":"https://assets-eu.researchsquare.com/files/rs-95753/v1/8d789c7cfcf8def6ed269995.JPG"},{"id":17059312,"identity":"769b219c-f87e-417f-aef8-ea65f6fc77b1","added_by":"auto","created_at":"2022-01-06 15:06:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":524984,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-95753/v1/e3f1abd4-f097-4cde-a4e7-aa09937bbefc.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eDifferences in Assistive Technology Installed for People With Dementia Living at Home Who Have Wandering and Safety Risks\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eAssistive technology (AT) has been proposed as an intervention which can reduce the risk of adverse outcomes related to safety and wandering, by meeting the needs of people with dementia. However, there is an acknowledged gap between required care and the AT services provided for people with dementia (1), and evidence for their effectiveness remains inconsistent (2). The reasons for this are unclear but perhaps include incomplete awareness of differences in the requirements of people with dementia in the real world (3), insufficient assessment of their circumstances (4,5), and limited availability of AT interventions (6,7).\u003c/p\u003e\n\u003cp\u003eVariations of the model of healthcare utilisation indicate that many characteristics have an impact upon health service use (8-10). However, the relative importance of each characteristic, their impact, together with the heterogeneity of user requirements and other person characteristics restricts understanding of their relationship to AT interventions (11-14). Research into the effects of multiple variables on the provision of AT is scarce (11). Need factors have traditionally been viewed as the most immediate cause of health service use (15). However, predisposing characteristics including the relationship between the person with dementia and their caregiver are important predictors of health care utilisation (10). Additionally, enabling resources such as caregiver support can facilitate or inhibit the use of healthcare services (16).\u003c/p\u003e\n\u003cp\u003eUnmet needs and risks are strongly associated with adverse outcomes (17,18) , and wandering and safety risks have been identified as primary concerns for caregivers of people with dementia (19,20). As there is evidence that these risks can be modified, this study will focus upon AT installed to reduce risks in these areas (18).\u003c/p\u003e\n\u003cp\u003eIn order to provide people with dementia with effective, client centred AT interventions service providers must understand patterns of need for people with dementia and how these relate to specific AT interventions (11,21,22). Hence, there is a need to explore the relationship between multiple variables and AT use.\u003c/p\u003e\n\u003cp\u003eThis research aims to investigate patterns in person characteristics of people with dementia living at home, specifically: wandering and safety risks; Mini Mental State Examination scores (MMSE) (23); living situation; caregiver support; and how these relate to installed AT.\u003c/p\u003e"},{"header":"Methods","content":" \u003cp\u003eThis study used secondary analysis of data collected from the ATTILA RCT investigating the impact of AT on institutionalisation for people with dementia living at home in 11 Council with Adult Social Service Responsibilities (CASSR) areas across England (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePopulation Characteristics\u003c/p\u003e \u003cp\u003eThree categories of population characteristics have been shown to have an impact upon healthcare utilisation namely predisposing, enabling and need categories (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These data included participant risk of wandering and safety categorised for the primary study according to the number of incidents previously experienced by the person with dementia. A low rating indicates no or very few relevant incidents, occasional incidents would be classified as moderate, and a high-risk rating indicates very frequent or very serious incidents. Level of caregiver support was categorised according to the amount of times the caregiver was present; (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) live-in caregiver, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) caregiver visits at least once / day, or (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) caregiver visits less than once/ day. Living situation was categorised as (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) living with spouse/ partner, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) living alone or (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Other. All participants categorised as \u0026ldquo;other\u0026rdquo; were living with another person who was not their spouse or partner, generally another relative. MMSE was scored on a scale which ranged from 0 to 30, where 30 indicates no dementia; scores of 26\u0026ndash;29 indicate questionable dementia; 21\u0026ndash;25 indicates mild dementia; 11\u0026ndash;20 suggests moderate dementia and a score of 0\u0026ndash;10 indicates severe dementia (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Assessment of need was conducted in line with normal CASSR practice to determine level of need and required AT services. AT considered in this study was installed within six months of recruitment. The list of installed AT categories is provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The installation of AT reflects normal CASSR practice and was not funded, assessed or installed by the RCT (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCategories of Assistive Technology\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"1\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic AT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePendant alarm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-monitored smoke detector\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-monitored carbon monoxide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKey safe\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivity monitors assessment only\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther devices\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReminder or prompting devices\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDate and time reminders\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem locator devices\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication reminders/dispensers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVoice recorders and memo minders\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther reminder/prompting devices\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDevices to promote safety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivity monitors - on-going monitoring\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFall detectors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContinence management devices\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlarm and pager units\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlood detectors and water temperature monitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGas detectors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonitored carbon monoxide detectors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonitored smoke detectors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonitored extreme temperature sensors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLighting devices\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther safety and security devices\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSafer walking technologies\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTo locate the user\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTo alert the responder to movement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunication devices\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTelephones\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication aids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther communication devices\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDevices that support meaningful use of leisure time\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComputer aids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDementia friendly TV/radio/music players\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectronic photo albums/electronic reminiscence aids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectronic games\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther devices -support meaningful use of leisure time\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMethodology\u003c/p\u003e \u003cp\u003eTo identify groups of people with dementia who have similar AT needs this study employed cluster analysis. This technique is essentially concerned with discovering intrinsic discrete groups within data (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Reduction of a heterogeneous sample into a number of more homogeneous groups provides a means to organise large quantities of information and facilitates consideration of multiple characteristics (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). A Partitioning Around Medoids (PAM) algorithm for clustering data was employed due to its toleration of Gower distance to measure dissimilarity (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Gower distance assesses partial dissimilarities and can accommodate mixed data types (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). The number of clusters was determined through examination of the silhouette coefficient (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Observations with large silhouette width (almost 1) can be considered well clustered. Silhouette width was used as a means to evaluate the clustering solution relative to other possible clustering solutions and facilitated the selection of the most robust solution.\u003c/p\u003e \u003cp\u003eUtility of the clustering solutions was tested through exploration of their relationship with installed AT. Installed AT data was stratified according to each of the clustering solutions in turn. The wandering cluster solution included data describing caregiver support, living situation, MMSE and level of risk of wandering of the participants. Similarly, the safety cluster solution included data describing caregiver support, living situation, MMSE and level of safety risk of the participants. Installed AT data was also stratified according to wandering risk, and safety risk for comparison purposes. Where data was available the strength of these associations between installed AT and level of wandering, safety risk and clustering solutions were tested using Chi square analyses (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese analyses were conducted using R Studio Software (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), and the Cluster package (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEthics\u003c/p\u003e \u003cp\u003eApproval for this secondary data analysis study was obtained from Queen Margaret University Ethics Committee.\u003c/p\u003e \u003cp\u003eFIGURE 1 NEAR HERE\u003c/p\u003e "},{"header":"Results","content":" \u003cp\u003eThe dataset contained anonymised information on 451 participants with dementia or suspected dementia living at home in England who had a documented needs assessment available for analysis (Fig.\u0026nbsp;1). Fifty-six participants did not have documented MMSE scores for unspecified reasons (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and were excluded from the analysis. These excluded participants were more likely to have high risk of wandering and high safety risk when compared with the remaining population. The relationship between MMSE and wandering or safety risk were not significant although participants with low risk of wandering had higher MMSE scores (M\u0026thinsp;=\u0026thinsp;19.05 (SD\u0026thinsp;=\u0026thinsp;6.1)) than participants with high risk of wandering (M\u0026thinsp;=\u0026thinsp;14.35 (SD\u0026thinsp;=\u0026thinsp;7.1)). Similarly, participants with low safety risk had higher MMSE score (M\u0026thinsp;=\u0026thinsp;18.35 (SD\u0026thinsp;=\u0026thinsp;6.66)) than participants with high safety risk (M\u0026thinsp;=\u0026thinsp;16.15 (SD\u0026thinsp;=\u0026thinsp;8.35)). This indicates that participants with increased cognitive impairment experience higher levels of wandering and safety risks.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePopulation with and without Mini Mental State Examination Score\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithout MMSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith MMSE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56(12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e395(87.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u0026thinsp;=\u0026thinsp;Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e229 (57.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving Situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e182 (46.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse/partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e160 (40.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53 (13.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiver Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiver visits at least once per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95 (24.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiver visits less than once per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e107 (27.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLive-in caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193 (48.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk of Wandering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e293 (74.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76 (19.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 ( 6.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSafety Risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e211 (53.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158 (40.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 ( 6.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eNote\u003c/em\u003e. \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;451, MMSE\u0026thinsp;=\u0026thinsp;Mini Mental State Examination (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Mean, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Standard Deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOverall, 1335 AT devices were installed during the 6-month period after baseline. Participants with MMSE scores (n\u0026thinsp;=\u0026thinsp;395) included within this analysis, had 1217 AT devices installed during this period (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eClustering solutions including both safety and wandering risk data together with caregiver support, living situation and MMSE score had an average silhouette width below 0.5 indicating that these structures were not robust. Therefore, two separate clustering solutions were developed based on the following data variables: Risk of Wandering or Safety Risk, Caregiver Support, Living Situation and MMSE score. These will now be described in turn.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides a summary of the characteristics of the participants included in each of the three clusters based upon caregiver support, MMSE, living situation and risk of wandering data. Clusters were named to reflect dominant characteristics of participants within that cluster (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e): (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \u0026ldquo;Living with Spouse/ Partner\u0026rdquo;, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \u0026ldquo;Living with Other\u0026rdquo; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) \u0026ldquo;Living alone\u0026rdquo;.\u003c/p\u003e \u003cp\u003eFIGURE \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e NEAR HERE\u003c/p\u003e \u003cp\u003eSix participants included in this third cluster exhibited negative silhouette width (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These participants were unusual within this dataset as they lived with spouse or partner or other yet did not have a live-in caregiver. Due to their small number it was not possible to draw conclusions regarding the Assistive Technology installations for these participants. This clustering solution had an average silhouette width of 0.63 indicating that a reasonable structure has been found (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Medoids or exemplars are also presented for each cluster.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePartitioning Around Medoids (PAM) Summary for Wandering Cluster\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaregiver Support \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving Situation \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRisk of Wandering \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Living with Spouse/ Partner (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;156)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in caregiver: 147(94.2)\u003c/p\u003e \u003cp\u003eCaregiver visits at least once per day: 8(5.1)\u003c/p\u003e \u003cp\u003eCaregiver visits less than once per day: 1(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin: 0.0\u003c/p\u003e \u003cp\u003e1st Qu.: 13.0\u003c/p\u003e \u003cp\u003eMedian:19.0\u003c/p\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e: 17.6\u003c/p\u003e \u003cp\u003e3rd Qu.: 24.0\u003c/p\u003e \u003cp\u003eMax: 28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving alone: 0(0)\u003c/p\u003e \u003cp\u003eLiving with Spouse/ Partner: 156(100.0)\u003c/p\u003e \u003cp\u003eOther: 0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow:112(71.8)\u003c/p\u003e \u003cp\u003eMod: 34(21.8)\u003c/p\u003e \u003cp\u003eHigh: 10(6.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Living with Other (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in caregiver: 46(90.2)\u003c/p\u003e \u003cp\u003eCaregiver visits at least once per day: 4(7.84)\u003c/p\u003e \u003cp\u003eCaregiver visits less than once per day: 1(1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin: 0.0\u003c/p\u003e \u003cp\u003e1st Qu.: 14.5\u003c/p\u003e \u003cp\u003eMedian: 18.0\u003c/p\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e: 17.6\u003c/p\u003e \u003cp\u003e3rd Qu.: 24.0\u003c/p\u003e \u003cp\u003eMax: 29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving alone: 0(0)\u003c/p\u003e \u003cp\u003eLiving with Spouse/ Partner: 0(0)\u003c/p\u003e \u003cp\u003eOther: 51(100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow: 36(70.6)\u003c/p\u003e \u003cp\u003eMod: 10(19.6)\u003c/p\u003e \u003cp\u003eHigh: 5(9.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Living Alone (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in caregiver: 0(0)\u003c/p\u003e \u003cp\u003eCaregiver visits at least once per day: 83(44.2)\u003c/p\u003e \u003cp\u003eCaregiver visits less than once per day: 105(55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin: 0.0\u003c/p\u003e \u003cp\u003e1st Qu.: 15.0\u003c/p\u003e \u003cp\u003eMedian:20.0\u003c/p\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e: 18.8\u003c/p\u003e \u003cp\u003e3rd Qu.: 23.0\u003c/p\u003e \u003cp\u003eMax: 28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving alone: 182(96.8)\u003c/p\u003e \u003cp\u003eLiving with Spouse/ Partner: 4(2.1)\u003c/p\u003e \u003cp\u003eOther: 2(1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow:145(77.1)\u003c/p\u003e \u003cp\u003eMod: 32(17.0)\u003c/p\u003e \u003cp\u003eHigh: 11(9.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMedoids for Wandering Clusters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Living with Spouse/ Partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving with spouse/partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Living with Other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Living Alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaregiver visits less than once per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote\u003c/em\u003e. \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;395, PAM\u0026thinsp;=\u0026thinsp;Partitioning Around Medoids, MMSE\u0026thinsp;=\u0026thinsp;Mini Mental State Examination (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), Min\u0026thinsp;=\u0026thinsp;Minimum, Qu\u0026thinsp;=\u0026thinsp;Quarter, \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Mean, Max\u0026thinsp;=\u0026thinsp;Maximum.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provides a summary of the characteristics of the participants based upon caregiver support, MMSE, living situation and safety risk data. Clusters were named (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \u0026ldquo;Live with Someone\u0026rdquo;, and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \u0026ldquo;Live-out Caregiver\u0026rdquo; to reflect characteristics of their participants (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFIGURE \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e NEAR HERE\u003c/p\u003e \u003cp\u003eAll participants had positive silhouette widths in this solution (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This average silhouette width of 0.59 indicates that a reasonable structure has been identified (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Again, medoids are presented for each cluster.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePartitioning Around Medoids (PAM) Summary for Safety Cluster\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaregiver Support \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving Situation \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSafety Risk \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Live with Someone (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;208)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in Caregiver:\u003c/p\u003e \u003cp\u003e193(92.79)\u003c/p\u003e \u003cp\u003eCaregiver visits at least once per day: 12(5.77)\u003c/p\u003e \u003cp\u003eCaregiver visits less than once per day: 3(1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin.:0.00\u003c/p\u003e \u003cp\u003e1st Qu.:14.00\u003c/p\u003e \u003cp\u003eMedian:18.00\u003c/p\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e: 17.66\u003c/p\u003e \u003cp\u003e3rd Qu.:24.00\u003c/p\u003e \u003cp\u003eMax.:29.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving alone: 0(0.0)\u003c/p\u003e \u003cp\u003eLiving with spouse/ partner: 158(75.96)\u003c/p\u003e \u003cp\u003eOther: 50(24.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow: 121(58.17)\u003c/p\u003e \u003cp\u003eModerate:70(33.65)\u003c/p\u003e \u003cp\u003eHigh: 17 (8.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Live out Caregiver (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;187)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in Caregiver: 0(0.0)\u003c/p\u003e \u003cp\u003eCaregiver visits at least once per day: 83(44.38)\u003c/p\u003e \u003cp\u003eCaregiver visits less than once per day: 104(55.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin. 0.00\u003c/p\u003e \u003cp\u003e1st Qu.:15.00\u003c/p\u003e \u003cp\u003eMedian:20.00\u003c/p\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e: 18.72\u003c/p\u003e \u003cp\u003e3rd Qu.:23.00\u003c/p\u003e \u003cp\u003eMax.:28.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving alone:182(97.33)\u003c/p\u003e \u003cp\u003eLiving with spouse/ partner: 2(1.07)\u003c/p\u003e \u003cp\u003eOther: 3(1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow: 90(48.13)\u003c/p\u003e \u003cp\u003eModerate:88(47.06)\u003c/p\u003e \u003cp\u003eHigh: 9(4.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMedoids for Safety Clusters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Live with Someone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive-in Caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving with spouse/ partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Live out Caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaregiver visits less than once per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote\u003c/em\u003e. \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;395, PAM\u0026thinsp;=\u0026thinsp;Partitioning Around Medoids, MMSE\u0026thinsp;=\u0026thinsp;Mini Mental State Examination (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), Min\u0026thinsp;=\u0026thinsp;Minimum, Qu\u0026thinsp;=\u0026thinsp;Quarter, \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Mean, Max\u0026thinsp;=\u0026thinsp;Maximum.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAssociations between the clusters and categories of installed AT are presented in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, together with associations identified between installed AT and risk of wandering or safety risk.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations with Installed Assistive Technology\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWandering (N\u0026thinsp;=\u0026thinsp;451)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedication Reminders and Dispensers (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 13.18, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001)\u003c/p\u003e \u003cp\u003ePendant Alarms (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 7.79, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eActivity Monitors for Ongoing Monitoring (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 15.78, ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.0003)\u003c/p\u003e \u003cp\u003eSafer Walking Technologies to Locate the User (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 39.04, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.00001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntercoms (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 27.90, ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.00001)\u003c/p\u003e \u003cp\u003eSafer Walking Technologies to alert a Responder of Movement (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 40.40, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.00001)\u003c/p\u003e \u003cp\u003eTelephones (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 13.51, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSafety (N\u0026thinsp;=\u0026thinsp;451)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSafer Walking Technologies to Locate the User (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 13.41, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFall Detectors (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 68.62, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.00001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWandering Cluster (N\u0026thinsp;=\u0026thinsp;395)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLiving with Spouse/ partner\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLiving with Other\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLiving Alone\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFall Detectors (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 6.94, * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.03)\u003c/p\u003e \u003cp\u003eSafer Walking Technologies to alert a responder of movement (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 7.33, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedication Reminders and Dispensers (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 15.91, ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.0003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSafety Cluster (N\u0026thinsp;=\u0026thinsp;395)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLive with Someone\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLive Out Caregiver\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSafer Walking Technologies to alert a Responder of Movement (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 19.67, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.000009)\u003c/p\u003e \u003cp\u003eSafer Walking Technologies to Locate the User (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 21.96, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.000003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMonitored Smoke Detectors (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 7.58, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.006)\u003c/p\u003e \u003cp\u003ePendant Alarms (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e = 10.42, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eNote\u003c/em\u003e. AT\u0026thinsp;=\u0026thinsp;Assistive Technology, NA\u0026thinsp;=\u0026thinsp;Not available, * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, associations are presented under group which most frequently received this category of AT.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRisk of wandering was associated with installation of safer walking technologies to alert a responder of movement \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;40.40, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;.00001), safer walking technologies to locate the user \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;39.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.00001, medication reminders and dispensers \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;13.18, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001, telephones \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;13.51, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001, intercoms \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;27.90, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.00001, pendant alarms \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;7.79, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.02 and activity monitors for ongoing monitoring χ\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;15.78, p\u0026thinsp;=\u0026thinsp;.0003) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Pendant alarms and medication reminders and dispensers were most frequently installed for participants with low risk of wandering. Activity Monitors for Ongoing Monitoring and Safer walking technologies to locate the user were most frequently installed for participants with moderate risk of wandering. Intercoms, Telephones and Safer Walking Technologies to alert a Responder of Movement were most frequently installed for participants with high risk of wandering.\u003c/p\u003e \u003cp\u003eSafety risk was associated with installation of safer walking technologies to locate the user \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;13.41, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001 most frequently installed for people with low safety risk; and fall detectors \u003cem\u003eχ\u0026sup2;\u003c/em\u003e (2, N\u0026thinsp;=\u0026thinsp;451)\u0026thinsp;=\u0026thinsp;68.62, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.00001 which were most frequently installed for people with high safety risk.\u003c/p\u003e \u003cp\u003eThe wandering cluster solution was associated with installation of fall detectors \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;395)\u0026thinsp;=\u0026thinsp;6.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.03, safer walking technologies to alert a responder of movement \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;395)\u0026thinsp;=\u0026thinsp;7.33, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.02 and medication reminders and dispensers \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (2, N\u0026thinsp;=\u0026thinsp;395)\u0026thinsp;=\u0026thinsp;15.91, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.0003.\u003c/p\u003e \u003cp\u003eThe safety cluster solution was associated with safer walking technologies to alert a responder of movement χ\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;395)\u0026thinsp;=\u0026thinsp;19.67, p\u0026thinsp;=\u0026thinsp;.000009 and safer walking technologies to locate the user \u003cem\u003eχ\u003c/em\u003e\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;395)\u0026thinsp;=\u0026thinsp;21.96, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.000003. Both types of safer walking technologies were most frequently installed for participants \u0026ldquo;living with someone\u0026rdquo;. Monitored smoke detectors χ\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;395)\u0026thinsp;=\u0026thinsp;7.58, p\u0026thinsp;=\u0026thinsp;.006 and pendant alarms χ\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;395)\u0026thinsp;=\u0026thinsp;10.42, p\u0026thinsp;=\u0026thinsp;.001) were also associated with the safety cluster solution and were most frequently installed for participants in the \u0026ldquo;live out caregiver\u0026rdquo; cluster.\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eThis study has developed understanding of the interaction of heterogeneous person characteristics including predisposing characteristics, needs and enabling resources, and their impact upon installed AT interventions in current practice. Results demonstrate that robust clusters created from data describing the characteristics of people with dementia can provide a basis for the exploration of the impact of multiple factors upon AT installations for this population. Subsequently this study validated these cluster solutions through demonstration of their applicability to data describing AT installed for people with dementia living at home.\u003c/p\u003e \u003cp\u003eCluster analyses appear to have grouped people with dementia according to their caregiver support and living situation, although MMSE and risk of wandering or safety risk were also considered. Subsequent analysis of the relationship between the cluster solutions and installed AT illustrated differences in patterns of AT installation in regard to safety and wandering risk indicating that these are associated with contrasting areas of concern. AT provided to mitigate safety risk suggests consideration of mobility issues, including falls. Whereas, installed AT associated with level of wandering risk is more varied perhaps because of a wider area of interest. Associations between installed AT and clustering solutions in this study indicate that the relationship between the person with dementia and their caregiver or support network may also influence AT provision in a number of ways. These include that; (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) AT is provided to meet the needs of the caregiver; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) input from the caregiver is required to obtain, maintain or monitor AT; and/ or (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) the caregiver provides a different view of the needs of the person with dementia resulting in a change in AT provision. These will now be discussed in turn.\u003c/p\u003e \u003cp\u003eInstallation of safer walking technologies to alert a responder of movement were associated with the \u0026ldquo;living with spouse/ partner\u0026rdquo;, or the \u0026ldquo;live with someone\u0026rdquo; clusters. Additionally, installation of safer walking technologies to locate the user was associated with the \u0026ldquo;live with someone\u0026rdquo; cluster. This type of AT may be used by caregivers to track people with dementia who are perceived to have lower risk of becoming lost and as a back up to caregiver support (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). However, as GPS technologies are generally used to back-up other forms of support and rarely facilitate independent walking for the person with dementia (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), results indicate that AT provision may be influenced by the needs of caregivers, such as fear of losing the person with dementia, to improve quality of life, and reduce stress (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). This confirms previous studies indicating a reduction in caregiver anxiety following the installation of AT (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Safety is a known concern for caregivers even when the person with dementia is unable to leave the home (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), and often leads to restrictions being placed upon the independent activity of the participant. Caregivers prioritise the safety of the person with dementia even above their autonomy or privacy (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). If safer walking technologies are primarily installed to alleviate caregiver anxiety, this explains why this type of AT was less likely to be provided for people with dementia living alone. Caregiver anxiety is associated with the institutionalisation of the person with dementia; hence caregiver stress reduction has direct benefit for them and may be the reason for their acceptance of AT which restricts their autonomy (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This may not be the case for people with dementia living alone. AT providers are therefore required to balance the needs and rights of people with dementia, whilst also considering the needs of the caregiver (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eParticipants living with others were more likely to receive installations of fall detectors, safer walking technologies to alert a responder of movement and safer walking technologies to locate the user. Whereas, participants living alone received more basic AT items such as monitored smoke detectors, and carbon monoxide detectors. Reasons for these differences are unclear but in addition to the absence of caregivers\u0026rsquo; concerns, may include there being no-one to adapt, monitor or respond to AT on their behalf (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Caregivers who live with the person with dementia are likely to be able to respond more quickly to alerts than monitoring centres. As, wandering incidents may occur frequently, they can require high levels of response which are unavailable from formal response teams. Familiar caregivers will also have more understanding of the particular requirements of the person with dementia (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurther, caregivers and co-residents may influence the assessment process, and therefore the AT installed for people living with others. Decisions to use tracking technologies have been shown to be informed by the caregivers\u0026rsquo; personal assessment of the safety of the participant (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Additionally, caregivers report higher levels of need than people with dementia report themselves (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Results indicate a focus on the priorities of caregivers rather than people with dementia. People with dementia identify daily activities and socialising as their priority (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Focussing on activities which increase participation can increase wellbeing, and reduce anxiety related behaviour such as wandering (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn such incidences, people with dementia living with others are more likely to have a caregiver who is able to provide an overview of their needs and abilities on their behalf (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResults of this study indicate that there are factors other than safety or wandering risk, which can affect installation of AT. Factors which may not be considered during the AT needs assessment include the impact of caregiver needs, the caregiver\u0026rsquo;s view of the person with dementia\u0026rsquo;s needs or the support received from informal caregivers. This may reflect limitations in the skills and knowledge of staff conducting the assessment of need (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). People living alone are less likely to be diagnosed with dementia, and clinicians often struggle to identify their needs (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Additionally, people with more severe impairment often have less documented assessment than people with milder cognitive impairment (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). People with moderate to severe dementia may have difficulty understanding questions in assessment tools (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Poor vision and hearing, deficient schooling and consequences of stroke or tremor may also make the completion of assessments difficult (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Overall, this suggests that needs which are perhaps considered difficult to assess or cannot be directly observed such as psychological needs often remain unassessed (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). People with dementia living with others may be more likely to have a caregiver who can provide an overview of their needs and abilities. Whereas, the reduced level of understanding of the needs of particular groups such as people with dementia living alone, results in them being less likely to receive services, despite being identified as a high-risk group (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). In order to account for the AT needs of people at all stages of dementia there is a requirement for the development of skilled assessors, validated assessment tools and alternative methods of assessment. Further, these groups are also less likely to be included in research which would advance understanding of their intervention requirements (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs caregivers have been identified as key actors in ensuring the safety of people with dementia (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), it is important to consider their views during the assessment of the person with dementia. Caregivers often monitor and maintain AT on behalf of the person with dementia. Additionally, AT is often provided for the reassurance and support of caregivers (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). It is therefore, difficult to distinguish between the needs of people with dementia and their caregivers as these are interwoven in a complex manner due to multiple interdependencies between these groups (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Consideration of the views, needs and capabilities of the person with dementia and their caregiver or people they live with, during the assessment process will provide a target for the tailoring of interventions and increase the ability to meet needs.\u003c/p\u003e \u003cp\u003eThis study indicates limitations in the needs assessment of people with dementia. Staff appear to lack confidence in assessment of people with moderate or severe dementia, or dementia and other impairments which may restrict communication. There is a requirement to develop validated assessment tools which consider the needs of people with dementia and communication difficulties. Additional training in the assessment of people with dementia should be available to clinicians working in this field to facilitate the development of expertise. Results also indicate assessors have limited understanding of the relationship between personal characteristics and AT (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), which may be due to organisational policy, or limitations of time, support, training, knowledge and resources (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Additionally, a supply led allocation process or preoccupation with risk generated interventions restricts choice and may increase distress (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Policies, staff training and resources should be reviewed to ensure that they support person centred care. Assessment should focus on the individuality of the person with dementia and their circumstances, thereby increasing the acceptability of person centred rather than supply led AT interventions (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Stakeholders will need to ensure access to sufficient AT resources to enable the installation of appropriate AT to meet identified needs (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e "},{"header":"Limitations","content":"\u003cp\u003eLimitations of this study include the low number of participants with moderate to severe dementia, high safety risk or high wandering risk. This restricts the transferability or generalisability of results, and further research is required to validate results for these populations (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Safety risk and wandering risk and AT were categorised according to non-validated criteria. The reliability and validity of these instruments is therefore uncertain and restricts comparisons of these results with further research (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Limited sample numbers also meant it was not possible to further validate the cluster analysis solutions on additional data (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e).\u003c/p\u003e \n\u003ch2\u003eSummary\u003c/h2\u003e\n \u003cp\u003eThis study has explored the impact of multiple factors upon AT installed for people with dementia living at home and provides validation of the use of partitioning around medoids cluster analysis as a method within this field. Results indicate that installation of AT for people with dementia living at home is influenced not only by their level of safety or wandering risk, but also by the level of caregiver support they receive and their living situation. There are a number of changes required to facilitate dementia friendly person-centred care. Policies should support assessment which considers the needs of the person with dementia, their caregivers and other members of their social network before installing AT. In order to improve effectiveness of AT interventions for people with dementia living at home there is a requirement for educators and professional bodies to advance assessment practice through mentorship and training. Assessors require to develop validated comprehensive assessment tools which account for different circumstances and impairments often experienced within this population, and which consider a wide range of care needs including psychological and social needs. There is also a requirement for assessment tools to direct assessors towards appropriate interventions (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), through evaluation of a wide range of needs experienced both by the person with dementia and members of their support network. There is a requirement for a wider range of AT to be available for installation in order to meet the individual needs of people with dementia and their caregivers.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: This secondary data study received ethical approval from Queen Margaret University Ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: The dataset analysed during the current study are not publicly available prior to publication of the main report but will then be available from \u003ca href=\"mailto:[email protected]\"\[email protected]\u003c/a\u003e on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eEC, RR and KF made substantial contributions to the conception of the study. EC, SG, RR and KF contributed to the design of the work. EC, RR and KF were responsible for the acquisition, analysis and interpretation of data, EC and SG drafted the manuscript, all authors were involved in critical revision of the manuscript. All authors read and approved the manuscript submitted. All authors agree both to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated, resolved and the resolution documented in the literature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: The authors wish to acknowledge the Attila RCT management group for granting permission to access the dataset on which this study was based.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; information:\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e(1) World Health Organization. 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Preventative Medicine 2014;67:141-146.\u003c/p\u003e\n\u003cp\u003e(30) Clatworthy J, Buick D, Hankins M, Weinman J, Horne R. The user and reporting of cluster analysis in health psychology: A review. British Journal of Health Psychology 2005;10:329-358.\u003c/p\u003e\n\u003cp\u003e(31) Kaufman L, Rousseeuw PJ. Finding Groups in Data: An Introduction in Cluster Analysis. New York.: John Wiley \u0026amp; Sons; 1990.\u003c/p\u003e\n\u003cp\u003e(32) Martin DP. Clustering mixed data types in R. 2016; Available at:\u0026nbsp;\u003ca href=\"http://www.r-bloggers.com/clustering-mixed-data-types-in-r/;\"\u003ewww.r-bloggers.com/clustering-mixed-data-types-in-r/;\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003e(33) Filaire T. Clustering on mixed data type. 2018; Available at: ttps://towardsdatascience.com/clustering-on-mixed-type-data-8bbd0a2569c3?gi=cad2f6350c29;, 30/04/2019.\u003c/p\u003e\n\u003cp\u003e(34) Richardson JTE. The analysis of 2 x 2 contingency tables - Yet again. Statistics in Medicine 2011;30:890.\u003c/p\u003e\n\u003cp\u003e(35) Viechtbauer W. Conducting Meta-analyses in R with the Metafor Package. Journal of Statistical Software ;36(3):1-48.\u003c/p\u003e\n\u003cp\u003e(36) R Core Team. R: A language and environment for statistical computing. 2017; Available at:\u0026nbsp;\u003ca href=\"https://www.r-project.org/\"\u003ehttps://www.R-project.org/\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003e(37) Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K, Studer M, et al. Package 'Cluster': Methods for Cluster Analysis. 2019.\u003c/p\u003e\n\u003cp\u003e(38) Department of Statistics University of California Berkeley. Cluster Analysis. 2011; Available at: h//\u003ca href=\"http://www.stat.berkeley.edu/~s133/Cluster2a.html\"\u003ewww.stat.berkeley.edu/~s133/Cluster2a.html\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003e(39) Bantry White E, Montgomery P, McShane R. Electronic tracking for people with dementia who get lost outside the home: a study of the experience of familial carers. British Journal of Occupational Therapy 2010 April;73(4):152-159.\u003c/p\u003e\n\u003cp\u003e(40) Gagnon-Roy M, Bourget A, Stocco S, Courchesne AL, Kuhne N, Provencher V. Assistive technology addressing safety issues in dementia: A scoping review. The American Journal Of Occupational Therapy: Official Publication Of The American Occupational Therapy Association 2017;71(5):1-10.\u003c/p\u003e\n\u003cp\u003e(41) Spring HJ, Rowe MA, Kelly A. Improving Caregivers' Well-being by using Technology to Manage Nighttime Activity in Persons with Dementia. Research in Gerontological Nursing 2009;2(1):39-48.\u003c/p\u003e\n\u003cp\u003e(42) Wood E, Ward G, Woolham J. The development of safer walking technology: a review. Journal of Assistive Technologies 2015;9(2):100-115.\u003c/p\u003e\n\u003cp\u003e(43) O'Keeffe J. The use of assistive technology to reduce caregiver burden. Issue Brief. Research Summit on Dementia Care: Building Evidence for Service and Supports. 2017.\u003c/p\u003e\n\u003cp\u003e(44) Gibson G, Dickinson C, Brittain K, Robinson L. Personalisation, customisation and bricolage: how people with dementia and their families make assistive technology work for them. Ageing and Society 2018:1-18.\u003c/p\u003e\n\u003cp\u003e(45) Dunk B, Longman B, Newton L. GPS technologies in managing the risks associated with safer walking in people with dementia - a practical perspective. Journal of Assistive Technologies 2010;4(3):4-8.\u003c/p\u003e\n\u003cp\u003e(46) Dickins M, Goeman D, O'Keefe F, Iliffe S, Pond D. Understanding the conceptualisation of risk in the context of community dementia care. Social Science and Medicine 2018;208:72-79.\u003c/p\u003e\n\u003cp\u003e(47) Lehmann SW, Black BS, Shore A, Kasper J, Rabins PV. Living alone with dementia: lack of awareness adds to functional and cognitive vulnerabilities. International Psychogeriatrics 2010;22(5):778-784.\u003c/p\u003e\n\u003cp\u003e(48) van Ooteghem K, Musselman KE, Mansfield A, Gold D, Marcil ME, Keren R, et al. Key factors for the assessment of mobility in advanced dementia: A consensus approach. Alzheimer's \u0026amp; Dementia: Translational Research and Clinical Interventions 2019;5:409-419.\u003c/p\u003e\n\u003cp\u003e(49) Miranda-Castillo C, Woods B, Orrell M. The needs of people with dementia living at home from user, caregiver and professional perspectives: a cross-sectional survey. BMC Health Serv Res 2013 02/04;13:43-43.\u003c/p\u003e\n\u003cp\u003e(50) Raiha I, Isoaho R, Ojanlatva A, Viramo P, Sulkava R, Kivela S. Poor performance in the Mini-Mental State Examination due to causes other than dementia. Scandinavian Journal of Primary Health Care 2001;19:34-38.\u003c/p\u003e\n\u003cp\u003e(51) Tierney MC, Charles J, Naglie G, Jaglal S, Kiss A, Fisher RH. Risk factors for harm in cognitively impaired seniors who live alone: A prospective study. Journal of the American Geriatrics Society 2004 September;52(9):1435-1441.\u003c/p\u003e\n\u003cp\u003e(52) Tudor Car L, El-Khatib M, Perneczky R, Papachristou N, Atun R, Rudan I, et al. Prioritizing problems in and solutions to homecare safety of people with dementia: supporting carers, streamlining care. BMC Geriatrics 2017;17(26):1-8.\u003c/p\u003e\n\u003cp\u003e(53) Neubauer NA, Lapierre N, Rios-Rincon A, Miguel-Cruz A, Rousseau J, Liu L. What do we know about technologies for dementia-related wandering? A scoping review, Canadian Journal of Occupational Therapy 2018;85(3):196-208.\u003c/p\u003e\n\u003cp\u003e(54) Sugarhood P, Wherton J, Procter R, Hinder S, Greenhalgh T. Technology as system innovation: A key informant interview study of the application of the diffusion of innovation model to telecare. Disability and Rehabilitation: Assistive Technology 2014;9(1):79-87.\u003c/p\u003e\n\u003cp\u003e(55) Handley M, Bunn F, Goodman C. Dementia friendly interventions to improve the care of people living with dementia admitted to hospitals: a realist review. BMJ OPen 2017;7:e015257\u003c/p\u003e\n\u003cp\u003e(56) Lipworth W, Mason PH, Kerridge I, Ioannidis JPA. Ethics and epistemology in big data research. Bioethical Inquiry 2017;14:489-500.\u003c/p\u003e\n\u003cp\u003e(57) Clark-Carter D. Quantitative Psychological Research: The Complete Student's Companion. 4th ed. Oxon: Routledge; 2019.\u003c/p\u003e\n\u003cp\u003e(58) Brock G, Pihur V, Datta S, Datta S. clValid, an R package for cluster validation. 2011 October 17, 2011:1-32.\u003c/p\u003e\n\u003cp\u003e(59) Schmid R, Eschen A, R\u0026uuml;egger-Frey B, Martin M. Instruments for comprehensive needs assessment in individuals with cognitive complaints, mild cognitive impairment or dementia: a systematic review. Int J Geriatr Psychiatry 2012 April;27(4):329-341.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"living situation, caregiver support, secondary data analysis, living alone","lastPublishedDoi":"10.21203/rs.3.rs-95753/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-95753/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: 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. 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.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: 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.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: 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.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: 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.\u003c/p\u003e","manuscriptTitle":"Differences in Assistive Technology Installed for People With Dementia Living at Home Who Have Wandering and Safety Risks","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-10-28 13:42:46","doi":"10.21203/rs.3.rs-95753/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-03-18T00:00:00+00:00","index":2,"fulltext":"Recommendation: Accept after discretionary revisions\nForm responses:\n---\n\nComments to Author:\n---\nline 112 - I did not understand how the risk of adverse incidents was assessed in detail. Please clarify this step again.\nline 121 - Who administered the MMSE? It is important to clarify this aspect. I believe that the exclusive administration of the MMSE cannot determine the level of severity of dementia. Useful to mention this aspect in the research Bias.\nTable 3 - 4 - 5 - The graphic appearance of the tables should be improved. For example, to make it easier to read, one could divide N , % and p value (when present). Useful reprogramming.\nline 222 - 231 - There are two yellow marks (highlighter). to be removed* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons after the final decision on the manuscript has been made. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Declaration of competing interests: **'I declare that I have no competing interests'**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **No**\n"},{"type":"decision","content":"Minor revision","date":"2021-03-18T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-02-04T00:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-12-07T00:00:00+00:00","index":1,"fulltext":"Recommendation: Accept after minor essential revisions\nForm responses:\n---\n\nComments to Author:\n---\nThe instruments used to categorized the safety risk and wandering risk and AT are not sufficiently explained and categorised according to non-validated criteria. The reliability and validity of these instruments, as satetd in the limitations, is therefore uncertain and restricts comparisons of these results with further research. Limited sample numbers also meant it was not possible to further validate the cluster analysis solutions on additional data. The use of specific scales in the measurement of need assessment and matching AT and the user are recommended (i.e.: MPT: matching person and technology, FEAT: Functional Evaluation for Assistive Technology; UEQ: user experience questionnaire or similia)* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons after the final decision on the manuscript has been made. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **No**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"reviewerAgreed","content":"","date":"2020-11-16T00:00:00+00:00","index":1,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-11-14T00:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-10-21T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-10-20T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-10-20T12:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2020-10-09T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e8a28881-f4d8-44aa-a3f7-d60ef142b1b3","owner":[],"postedDate":"October 28th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":883712,"name":"Geriatrics \u0026 Gerontology"}],"tags":[],"updatedAt":"2022-01-06T15:06:23+00:00","versionOfRecord":{"articleIdentity":"rs-95753","link":"https://doi.org/10.1186/s12877-021-02546-7","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2021-10-30 15:06:23","publishedOnDateReadable":"October 30th, 2021"},"versionCreatedAt":"2020-10-28 13:42:46","video":"","vorDoi":"10.1186/s12877-021-02546-7","vorDoiUrl":"https://doi.org/10.1186/s12877-021-02546-7","workflowStages":[]},"version":"v1","identity":"rs-95753","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-95753","identity":"rs-95753","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}