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Background the Pictorial Fit-Frail Scale (PFFS) was designed as a simple and practical approach to the identification of frailty. Objectives To investigate the feasibility and reliability of this visual image-based tool, when used by patients, caregivers and healthcare professionals (HCPs) in clinical settings. Design observational study. Setting three outpatient geriatric healthcare settings. Subjects patients (n = 132), caregivers (n = 84), clinic nurses (n = 7) and physicians (n = 10). Methods the PFFS was administered to all patients. Where available, HCPs and caregivers completed the scale based on the patients’ health. In the geriatric day hospital, the PFFS was completed on admission and administered again within 7–14 days. Time and level of assistance needed to complete the scale were recorded. Intraclass correlation coefficients (ICCs) and 95% confidence intervals (CIs) were used to assess test−retest and inter-rater reliability. Results mean time to complete the scale (minutes:seconds ± SD) was 4:30 ± 1:54 for patients, 3:13 ± 1:34 for caregivers, 1:28 ± 0:57 for nurses and 1:32 ± 1:40 for physicians. Most patients were able to complete the scale unassisted (64%). Mean patient PFFS score was 11.1 ± 5.3, mean caregiver score was 13.2 ± 6.3, mean nurse score was 10.7 ± 4.5 and mean physician score was 11.1 ± 5.6; caregiver scores were significantly higher than patient (P Conclusion the PFFS is a feasible and reliable tool for use with patients, caregivers and HCPs in clinical settings. Further research on the validity and responsiveness of the tool is necessary.

Objective:To assess the feasibility, reliability, and validity of the Pictorial Fit-Frail Scale (PFFS) among patients, caregivers, nurses, and geriatricians in an outpatient memory clinic.Design:Observational study.Setting:A Canadian referral-based outpatient memory clinic.Participants:Fifty-one consecutive patients and/or their caregivers, as well as attending nurses and geriatricians.Measurements:Participants (patients, caregivers, nurses, and geriatricians) were asked to complete the PFFS based on the patient’s current level of functioning. Time-to-complete and level of assistance required was recorded. Participants also completed a demographic survey and patients’ medical history (including the Mini-Mental State Examination [MMSE], and Comprehensive Geriatric Assessment [CGA]) was obtained via chart review.Results:Patient participants had a mean age of 77.3±10.1 years, and average MMSE of 22.0±7.0, and 53% were female. Participants were able to complete the PFFS with minimal assistance, and their average times to completion were 4:38±2:09, 3:11±1:16, 1:05±0:19, and 0:57±0:30 (mins:sec) for patients, caregivers, nurses, and geriatricians, respectively. Mean PFFS scores as rated by patients, caregivers, nurses, and geriatricians were 9.0±5.7, 13.1±6.6, 11.2±4.5, 11.9±5.9, respectively. Patients with low MMSE scores (0–24) took significantly longer to complete the scale and had higher PFFS scores. Inter-rater reliability between nurses and geriatricians was 0.74, but it was lower when assessments were done for patients with low MMSE scores (0.47, pConclusions:The PFFS is feasible, even among people with some slight cognitive impairment, though it may be less useful when patients with severe dementia administer it to themselves. Further, the PFFS may help inform clinicians about areas of concern as identified by patients, enabling them to contribute more to diagnostic and treatment decisions or helping with health tracking and care planning.

Objective:Cognitive reserve (CR) capacity can be viewed as the maximum processing potential of neural systems that support adaptive cognitive performance in age-related cognitive decline. CR is a complex construct that can only be measured indirectly. Proxy measures (e.g., psychosocial/lifestyle variables) are traditionally used to reflect CR. However, strong relationships have been observed between these measures and cognitive functions (e.g., executive function [EF], processing resources [PR], fluid/crystallized abilities); therefore, the organizational structure of indicators implicated in CR remains unclear. The objective of this study was to test a hypothetical, theoretical model of CR capacity that includes both traditional CR proxy indicators and measures of cognitive function [Satz et al. (2011).Journal of Clinical and Experimental Neuropsychology,33(1), 121–130], which remain, as yet, untested.Method:Construct validity of the model was investigated in healthy older adults through exploratory and confirmatory factor analysis (EFA and CFA) using data from the Maastricht Ageing Study (MAAS). A secondary CFA was conducted to validate the model using data from the Irish Longitudinal Study on Ageing (TILDA).Results:EFA and CFA in MAAS established a two-factor model comprising EF/PR and cumulative cognitive enrichment (CCE), which was further validated in a secondary analysis in TILDA. Convergent and discriminant validity was supported in MAAS (range ofR2= .228–.635; factor correlation confidence interval (CI) = .622, .740) and TILDA (range ofR2= .172–.899; factor correlation CI = .559, .624).Conclusions:A dual model of CR elucidated the relationships between hypothesized indicators of CR capacity and revealed a two-factor structure suggesting that both control (EF/PR) and representational processes (CCE) are involved in CR capacity.

BackgroundStandardized frailty assessments are needed for early iden-tification and treatment. We aimed to develop a frailty scale using visual images, the Pictorial Fit-Frail Scale (PFFS), and to examine its feasibility and content validity.MethodsIn Phase 1, a multidisciplinary team identified domains for measurement, operationalized impairment levels, and re-viewed visual languages for the scale. In Phase 2, feedback was sought from health professionals and the general public. In Phase 3, 366 participants completed preliminary testing on the revised draft, including 162 UK paramedics, and rated the scale on feasibility and usability. In Phase 4, following translation into Malay, the final prototype was tested in 95 participants in Peninsular Malaysia and Borneo.ResultsThe final scale incorporated 14 domains, each conceptual-ized with 3–6 response levels. All domains were rated as “understood well” by most participants (range 64–94%). Percentage agreement with positive statements regarding appearance, feasibility, and usefulness ranged from 66% to 95%. Overall feedback from health-care professionals sup-ported its content validity.ConclusionsThe PFFS is comprehensive, feasible, and appears gener-alizable across countries, and has face and content validity. Investigation into the reliability and predictive validity of the scale is currently underway.

Background Older people are at increased risk of adverse health events because of reduced physical activity. There is concern that activity levels are further reduced in the context of the COVID-19 pandemic, as many older people are practicing physical and social distancing to minimize transmission. Mobile health (mHealth) and eHealth technologies may offer a means by which older people can engage in physical activity while physically distancing. Objective The objective of this study was to assess the evidence for mHealth or eHealth technology in the promotion of physical activity among older people aged 50 years or older. Methods We conducted a rapid review of reviews using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched for systematic reviews published in the English language in 3 electronic databases: MEDLINE, CINAHL Plus, and Scopus. Two reviewers used predefined inclusion criteria to select relevant reviews and extracted data on review characteristics and intervention effectiveness. Two independent raters assessed review quality using the AMSTAR-2 tool. Results Titles and abstracts (n=472) were screened, and 14 full-text reviews were assessed for eligibility. Initially, we included 5 reviews but excluded 1 from the narrative as it was judged to be of critically low quality. Three reviews concluded that mHealth or eHealth interventions were effective in increasing physical activity. One review found that the evidence was inconclusive. Conclusions There is low to moderate evidence that interventions delivered via mHealth or eHealth approaches may be effective in increasing physical activity in older adults in the short term. Components of successful interventions include self-monitoring, incorporation of theory and behavior change techniques, and social and professional support.

Background Goal Attainment Scaling (GAS) is an individualized outcome measure that allows the setting of personalized treatment goals. We compared the responsiveness of GAS when individuals set only one goal instead of the recommended three or more goals. Methods We conducted exploratory analyses on data from two randomized controlled trials: the Video-Imaging Synthesis of Treating Alzheimer’s Disease (VISTA) (n = 130); and the Mobile Geriatric Assessment Team (MGAT) (n = 265). Independent t-tests and standardized response means (SRMs) were used to assess responsiveness of one- vs. multiple-goal GAS. Results In VISTA, clinician-rated multiple-goal GAS detected higher goal attainment in the intervention group (p = 0.01; SRM = 0.48). One-goal GAS, whether rated by patients or by clinicians, did not detect differences in goal attainment between groups (patient: p = 0.56, SRM = 0.10; clinician: p = 0.10, SRM = 0.29). In MGAT, multiple-goal GAS (outcome goals: p p p p Conclusion One-goal GAS detected significant change in response to a patient-centred, multi-domain care initiative. As such, in similar contexts, one-goal GAS may be an effective means of optimizing personalization and improving GAS feasibility through reduced administration time. However, it is not yet clear if one-goal GAS is responsive in the context of a pharmacological intervention and further research is recommended.

Purpose Guidelines for the use of goal attainment scaling (GAS) recommend that the patient specify at least three goals. Even so, this may not always be feasible or align with patient preferences. Investigations into the psychometric properties of GAS using three or more goals largely support its reliability, validity, and responsiveness compared with standard measures. As evaluations of responsiveness rely on variability estimates, this metric may be impacted when GAS is based on fewer than three goals. For this reason, we investigated the responsiveness of one- and two-goal GAS. Methods Secondary analyses were conducted on data from a mixed sample of pediatric, adolescent and adult subjects with hemophilia A. The standardized response mean (SRM) and its 95% confidence intervals (CI) were used to assess responsiveness of one- and two-goal GAS at six and twelve weeks. Results Both one-goal and two-goal GAS demonstrated similar responsiveness to change at 6-week (Patient-Rated GAS: one-goal SRM [95% CI] = 0.70 [0.45–1.08], two-goal = 0.96 [0.68–1.30]; Clinician-Rated GAS: one-goal = 1.26 [0.81–1.77], two-goal = 1.01 [0.73–1.32]) and 12-week follow-up (Patient-Rated GAS: one-goal SRM [95% CI] = 1.14 [0.53–1.71], two-goal = 1.35 [0.92–1.82]; Clinician-Rated GAS: one-goal = 1.71 [1.12–2.30], two-goal = 1.48 [1.02–2.02]). Larger SRMs were observed for clinician-rated GAS, but all were within the rubric of a large effect size. Conclusions One-goal GAS is responsive to change in a clinical population. Further research is recommended in a larger sample where responsiveness of one- and multiple-goal GAS can be compared

Objectives:Misplacing objects is often reported as a clinically important symptom in dementia. Here we explored misplacing objects in relation to dementia type and stage in an online sample of individuals with dementia and their caregivers.Methods:Participants were recruited from www.dementiaguide.com, a web-based tracker for common dementia symptoms. Users provided information about symptoms that they selected as important for monitoring. We analysed cross-sectional data from respondents who tracked at least three symptoms, which allowed for staging dementia severity.Results:Of 2,775 users with three-plus symptoms, 787 (28%) identified misplacing objects for symptom tracking. Misplacing objects was monitored by users across all stages of dementia, but was more prevalent in mild and severe dementia. Three common clinical subtypes of misplacing were investigated: lost & found (forgetting the location of items), hidden away (hiding items so others would not find them), and odd places (putting items in usual spots). Of the 787, 96% targeted lost & found, the most frequent type. Odd places (targeted in 56%) significantly increased with dementia severity (p < 0.001). Misplacing objects was most strongly associated with the symptoms of interaction with strangers (OR 4.60, 95% CI: 3.20-6.62), reading (3.68: 2.86-4.73), shopping (3.55: 2.73-4.61) and travel/vacationing (3.31: 2.54-4.31).Conclusions:Misplacing objects was most often selected for tracking in mild and severe stages of dementia. As disease advances, misplacing more often reflects odd placement of objects rather than their simple loss. Misplacing objects may be a clinically important therapeutic target for improving patients’ quality of life and lessening caregiver burden.