Group Model Building on causes and interventions for falls in Singapore: insights from a systems thinking approach.

BACKGROUND: Falls in older adults are the result of a complex web of interacting causes, that further results in other physical, emotional, and psychological sequelae. A conceptual framework that represents the reciprocal dynamics of these causal factors can enable clinicians, researchers, and policymakers to clarify goals in falls intervention in older adults. METHODS: A Group Model Building (GMB) exercise was conducted with researchers and clinicians from academic units and public healthcare institutes in Singapore. The aim of the exercise was to produce a shared visual representation of the causal structure for falls and engage in discussions on how current and future falls intervention programmes can address falls in the older adults, especially in the Asian context. It was conducted in four steps: 1) Outlining and prioritising desirable patient outcomes, 2) Conceptual model building, 3) Identifying key intervention elements of effective falls intervention programmes, 4) Mapping of interventions to outcomes. This causal loop diagram (CLD) was then used to generate insights into the current understanding of falls causal relationships, current efforts in falls intervention in Singapore, and used to identify gaps in falls research that could be further advanced in future intervention studies. RESULTS: Four patient outcomes were identified by the group as key in falls intervention: 1) Falls, 2) Injurious falls, 3) Fear of falling, and 4) Restricted mobility and life space. A CLD of the reciprocal relationships between risk factors and these outcomes are represented in four sub-models: 1) Fear of falling, 2) Injuries associated with falls, 3) Caregiver overprotectiveness, 4) Post-traumatic stress disorder and psychological resilience. Through this GMB exercise, the group gained the following insights: (1) Psychological sequelae of falls is an important falls intervention outcome. (2) The effects of family overprotectiveness, psychological resilience, and PTSD in exacerbating the consequences of falls are not well understood. (3) There is a need to develop multi-component falls interventions to address the multitude of falls and falls related sequelae. CONCLUSION: This work illustrates the potential of GMB to promote shared understanding of complex healthcare problems and to provide a roadmap for the development of more effective preventive actions.

Care Needs Profiles and Their Association with Caregiver Strain among Community-Dwelling Older Adults with Cognitive Impairment.

INTRODUCTION: This study examined distinct profiles of met and unmet care needs among community-dwelling older adults with cognitive impairment and their association with caregiver strain. METHODS: Latent class analysis and multivariable regression were applied to data from 266 caregivers of older Singaporeans, aged 60 years and above, with cognitive impairment. Care needs were evaluated by caregivers using the Camberwell Assessment of Need for the Elderly. Caregiver strain was measured by the Zarit Burden Interview. RESULTS: Four need profiles were identified: (1) no need (38% of caregivers), (2) met social and memory needs (29%), (3) no social and met memory needs (17%), and (4) unmet social and memory needs (16%). The unmet social and memory needs profile was associated with a higher level of caregiver strain, compared to the no need profile. DISCUSSION: A person-centered approach captured heterogeneity in the care needs of community-dwelling older adults with cognitive impairment. Policymakers should develop tailored interventions based on need profiles that may help reduce caregiver strain.

Transitions in Social Network Types over Time among Older Adults.

OBJECTIVE: Network typology studies have identified heterogeneous types of older adults' social networks. However, little is known about stability and change in social network types over time. We investigate transitions in social network types among older adults, aged 60 years and older, and factors associated with such transitions. METHODS: We used data on 1,305 older adults, participating in 2 waves of a national, longitudinal survey, conducted in 2016-2017 and 2019, in Singapore. Latent transition analysis identified the distinct types of social networks and their transition patterns between the waves. Multinomial logistic regression examined the association of baseline and change in physical, functional, and mental health and baseline sociodemographic characteristics with network transitions into more diverse or less diverse types. RESULTS: We found 5 social network types at both waves, representing the most to the least diverse types - diverse, unmarried and diverse, extended family, immediate family, and restricted. Between waves, about 57% of respondents retained their social network type, whereas 24% transitioned into more diverse types and 19% into less diverse types. Those who were older and less educated and those with worsening functional and mental health were more likely to transition into less diverse types versus remaining in the same type. DISCUSSION: The findings capture the dynamics in social network composition among older adults in the contemporary aging society. We highlight sociodemographic and health disparities contributing to later life social network diversity.

Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community.

BACKGROUND: A rapidly ageing population with increasing prevalence of chronic disease presents policymakers the urgent task of tailoring healthcare services to optimally meet changing needs. While healthcare needs-based segmentation is a promising approach to efficiently assessing and responding to healthcare needs at the population level, it is not clear how available schemes perform in the context of community-based surveys administered by non-medically trained personnel. The aim of this prospective cohort, community setting study is to evaluate 4 segmentation schemes in terms of practicality and predictive validity for future health outcomes and service utilization. METHODS: A cohort was identified from a cross-sectional health and social characteristics survey of Singapore public rental housing residents aged 60 years and above. Baseline survey data was used to assign individuals into segments as defined by 4 predefined population segmentation schemes developed in Singapore, Delaware, Lombardy and North-West London. From electronic data records, mortality, hospital admissions, emergency department visits, and specialist outpatient clinic visits were assessed for 180 days after baseline segment assignment and compared to segment membership for each segmentation scheme. RESULTS: Of 1324 residents contacted, 928 agreed to participate in the survey (70% response). All subjects could be assigned an exclusive segment for each segmentation scheme. Individuals in more severe segments tended to have lower quality of life as assessed by the EQ-5D Index for health utility. All population segmentation schemes were observed to exhibit an ability to differentiate different levels of mortality and healthcare utilization. CONCLUSIONS: It is practical to assign individuals to healthcare needs-based population segments through community surveys by non-medically trained personnel. The resulting segments for all 4 schemes evaluated in this way have an ability to predict health outcomes and utilization over the medium term (180 days), with significant overlap for some segments. Healthcare needs-based segmentation schemes which are designed to guide action hold particular promise for promoting efficient allocation of services to meet the needs of salient population groups. Further evaluation is needed to determine if these schemes also predict responsiveness to interventions to meet needs implied by segment membership.

Reducing Falls Among Community-Dwelling Older Adults From Clinicians' Perspectives: A Systems Modeling Approach.

Background and Objectives: Falls among older adults are a significant health problem globally. Studies of multicomponent fall prevention programs in randomized controlled trials demonstrate effectiveness in reducing falls; however, the translation of research into the community remains challenging. Although there is an increasing interest to understand the factors contributing to implementation barriers, the dynamic relationships between factors are less well examined. Furthermore, evidence on implementation barriers from Asia is lacking as most of these studies originate from the West. As such, this study aims to engage stakeholders in uncovering the factors that facilitate or inhibit implementing community-based fall prevention programs in Singapore, with a focus on the interrelationship between those factors. Research Design and Methods: Health care professionals familiar with fall prevention programs were invited to discuss the enablers and challenges to the implementation. This effort was facilitated using a systems modeling methodology of Group Model Building (GMB) to share ideas and create a common conceptual model of the challenges. The GMB employs various engagement techniques to draw on the experiences and perceptions of all stakeholders involved. Results: This process led to the development of a Causal Loop Diagram (CLD), a qualitative conceptual model of the dynamic relationships between the barriers and facilitators of implementing fall prevention programs. Results from the CLD show that implementation is influenced by two main drivers: health care provider factors that influenced referrals, and patient factors that influenced referral acceptance and long-term adherence. Key leverage points for potential interventions were identified as well. Discussion and Implications: The overall recommendation emphasized closer coordination and collaboration across providers to ensure sustainable and effective community-based fall prevention programs. This has to be supported by a national effort, involving a multidisciplinary stakeholder advisory group. These findings generated would be promising to guide future approaches to fall prevention.

Systems modelling as an approach for eliciting the mechanisms for hip fracture recovery among older adults in a participatory stakeholder engagement setting.

Introduction: Due to an aging population, the rising prevalence and incidence of hip fractures and the associated health and economic burden present a challenge to healthcare systems worldwide. Studies have shown that a complex interplay of physiological, psychological, and social factors often affects the recovery trajectories of older adults with hip fractures, often complicating the recovery process. Methods: This research aims to actively engage stakeholders (including doctors, physiotherapists, hip fracture patients, and caregivers) using the systems modeling methodology of Group Model Building (GMB) to elicit the factors that promote or inhibit hip fracture recovery, incorporating a feedback perspective to inform system-wide interventions. Hip fracture stakeholder engagement was facilitated through the Group Model Building approach in a two-half-day workshop of 25 stakeholders. This approach combined different techniques to develop a comprehensive qualitative whole-system view model of the factors that promote or inhibit hip fracture recovery. Results: A conceptual, qualitative model of the dynamics of hip fracture recovery was developed that draws on stakeholders' personal experiences through a moderated interaction. Stakeholders identified four domains (i.e., expectation formation, rehabilitation, affordability/availability, and resilience building) that play a significant role in the hip fracture recovery journey.. Discussion: The insight that recovery of loss of function due to hip fracture is attributed to (a) the recognition of a gap between pre-fracture physical function and current physical function; and (b) the marshaling of psychological resilience to respond promptly to a physical functional loss via uptake of rehabilitation services is supported by findings and has several policy implications.

Association between housing type and accelerated biological aging in different sexes: moderating effects of health behaviors.

INTRODUCTION: Despite associated with multiple geriatric disorders, whether housing type, an indicator of socioeconomic status (SES) and environmental factors, is associated with accelerated biological aging is unknown. Furthermore, although individuals with low-SES have higher body mass index (BMI) and are more likely to smoke, whether BMI and smoking status moderate the association between SES and biological aging is unclear. We examined these questions in urbanized low-SES older community-dwelling adults. METHODS: First, we analyzed complete blood count data using the cox proportional hazards model and derived measures for biological age (BA) and biological age acceleration (BAA, the higher the more accelerated aging) (N = 376). Subsequently, BAA was regressed on housing type, controlling for covariates, including four other SES indicators. Interaction terms between housing type and BMI/smoking status were separately added to examine their moderating effects. Total sample and sex-stratified analyses were performed. RESULTS: There were significant differences between men and women in housing type and BAA. Compared to residents in ≥3 room public or private housing, older adults resided in 1-2 room public housing had a higher BAA. Furthermore, BMI attenuated the association between housing type and BAA. In sex-stratified analyses, the main and interaction effects were only significant in women. In men, smoking status instead aggravated the association between housing type and BAA. CONCLUSION: Controlling for other SES indicators, housing type is an independent socio-environmental determinant of BA and BAA in a low-SES urbanized population. There were also sex differences in the moderating effects of health behaviors on biological aging.

Classification trees for identifying non-use of community-based long-term care services among older adults.

Home- and center-based long-term care (LTC) services allow older adults to remain in the community while simultaneously helping caregivers cope with the stresses associated with providing care. Despite these benefits, the uptake of community-based LTC services among older adults remains low. We analyzed data from a longitudinal study in Singapore to identify the characteristics of individuals with referrals to home-based LTC services or day rehabilitation services at the time of hospital discharge. Classification and regression tree analysis was employed to identify combinations of clinical and sociodemographic characteristics of patients and their caregivers for individuals who did not take up their referred services. Patients' level of limitation in activities of daily living (ADL) and caregivers' ethnicity and educational level were the most distinguishing characteristics for identifying older adults who failed to take up their referred home-based services. For day rehabilitation services, patients' level of ADL limitation, home size, age, and possession of a national medical savings account, as well as caregivers' education level, and gender were significant factors influencing service uptake. Identifying subgroups of patients with high rates of non-use can help clinicians target individuals who are need of community-based LTC services but unlikely to engage in formal treatment.