Table 6.
Summary of 52 targeted papers
| Cluster | Source | Method | Findings | Limitations |
|---|---|---|---|---|
| Challenges | [46] | Seven persons with dementia (PwD) and eight people with normal cognition (CTLs) over the age of 65 were tracked for four weeks using a GPS device. This was done when they went out of their houses during a period of four weeks | When compared to cognitively intact CTLs, PwDs engaged in more medically related and less sport-related activities, while neurotypical CTLs walked more and spent more time outside at nighttime | Limited generalization because of a small sample size |
| [47] | Measures of planning (HOTAP test), spatial working memory (Grid-Span test), and visuospatial attention were used to test cognitive abilities (Attention Window test). An instrumented version of the Timed Up-and-Go test was used to measure the ability to move around (iTUG). Smartphones with accelerometers and GPS were used to measure mobility over a one-week period. | The assessments of mobility were whittled down to four orthogonal components: the factors indicating “real-life mobility”, “sit-to-stand transition”, and “turn” connected with fewer cognitive measures, while the factor indicating straight gait linked with just one cognitive indicator | Only limited number of factors were analysed | |
| [48] | Tests: gait speed, Five Times Sit to Stand, Four Square Step Test (FSST), and Dynamic Gait Index (DGI) | There were significant connections reported between increased regional grey matter volume (GMV) in many areas, most notably the parietal and temporal lobes, and better performance in gait speed, distance gained in the digit span test (DGI), and forced swimming speed test (FSST) | Limitations are not described | |
| [45] | Regression models | Cognition, logic, and response time were all shown to have a substantial impact on a person’s life space, and reasoning ability was found to be the most predictive. In addition to the standard cognitive tests, assessments of everyday function showed strong relationships with living space | The findings indicated the necessity of doing more research over a longer time span | |
| [36] | Global positioning systems and location kits were used to track the participants for 28 consecutive days (GPS) | The outside-of-home time spent by seniors with cognitive impairments has a severely constrained spatial range | ||
| [49] | There were 260 neighbourhood men and women aged 75–80 who responded to a mail survey evaluating physical mobility (utilising the Life Space Questionnaire) and mental wellbeing (using the SF36 Health Related Quality of Life Profile) | It has been shown that elderly women are more prone to face a lack of mobility and confined life space, which makes them more sensitive to social isolation | ||
| [50] | For up to seven days, 393 participants between the ages of 18 and 65 were tested using the Patient Health Questionnaire (PHQ-9) and cellphones equipped with global positioning systems (GPS). A number of different linear regressions have been performed | The 50-m buffer used in the fully adjusted residential and mobility-based models revealed a negative correlation between depression symptoms and proximity to green space | Work on the environment and psychological health necessitate further investigation of dynamic sensitivity assessment methods | |
| [51] | More than 100 older adults were observed in their homes for a cross-sectional research. Multiple logistic regression was used to discover characteristics that could distinguish three degrees of frailty | Gait speed (area under the curve, AUC = 0.802), hip sway (AUC = 0.734), and steps/day (AUC = 0.736) were the most sensitive parameters for the identification of prefrailty | ||
| [52] | Cross-sectional research that took account of 118 multimorbid older adults that presented with cognitive issues |
Low and high life-space mobility (LSM) can be distinguished by a crucial value on the receiver-operating characteristic curve (ROC) People with cognitive impairment can benefit from tailoring therapy to their specific LSA-CI scores and tracking their progress over time |
Further investigation must focus on GPS as the subsequent best feasible practical method for determining LSM, which is a drawback of this work | |
| [53] | For this study, researchers drew on the medical records of 13,400 people in Quebec who were diagnosed with schizophrenia during 2001–2002 | The resulting model shows that at the individual basis, men, wonder patients, and physiological comorbidity enhance the risk of early home movement, while older adult patients are less prone to relocate sooner | Diagnostic codes stored in administrative systems can have an impact on estimating accuracy | |
| Conditions | [54] | Customized mobility measures for Montreal Island, based on location and individual data on travel patterns that have been geocoded | Seniors and non-seniors, as well as those who own or do not own a car, have vastly different levels of access to transportation. The focus of this study was on the possible accessibility of the information | Follow-up studies might use the findings from this study to choose case studies of real access and utilisation of health care services and associated health outcomes |
| [55] | Six community-dwelling older individuals completed a 14-day self-reported activity journal to collect data. The examination of the data includes 1453 occurrences | To better educate themselves and their patients, doctors and researchers may use workflows to define the everyday activities of older adults and develop education and preventive plans that are specific to each person’s level of activity | Data is from a sample which is small and spans only over two weeks | |
| [56] | Non-dementia community-dwelling seniors were researched in 571 cases. A total of 303 individuals reported incidents of life-space constrictions over an overall follow-up period of 4.3 years | A higher chance of life space recovery was seen in people who had a valid driver’s licence. Older adults with a valid driver’s licence were less likely to report life-space restriction and more likely to recuperate from living restriction if such an event happened. | Even though there was a link between driving status and reports of life space being too small, the authors could not determine whether it was because of the group of people who had never had a valid driver’s licence or the group of people who had a valid licence at some point but did not renew it at least 12 months before our baseline interview. | |
| [57] | Data from the Hamilton CMA in Canada and multi-level models are used in this study to analyse the variables that influence travel distance, with a particular focus on demographic ageing issues | Whereas this age impact is apparent in all modes of analysis (driving a car, riding in a car, and using IRIS), driving a car has a far more pronounced effect. When it comes to a vehicle driver’s distance travelled, a neighborhood’s mix of business and residential properties had a negative correlation with distance travelled exclusively in the case of the car driver | The evaluated variables were restricted to a small number. According to this study, it would be interesting to find out if older adults have similar domestic constraints (such as taking on the responsibility of caring for grandchildren) to women (for example, health limitations) or other factors (such as the loss of a licence, for example), that put them at the same degree of limit to move much further | |
| [58] | Analysis of data from the Life-Space Mobility in Old Age cohort study at the beginning of the research period. Participants’ houses for structured interviews. Participants were older adult individuals (N = 848) who live in a community. Mobility was measured in one’s environment (Impact on Participation and Autonomy questionnaire subscale, Life-Space Assessment; University of Alabama, Birmingham Study of Aging), as well as short physical performance battery |
The average life-space mobility score was 64.0 out of 100 For those who had poor physical performance and had a more limited feeling of autonomy, their life-space mobility was restricted by around one-third of the variance. Outside, a person’s feeling of self-determination was influenced by their physical performance in turn |
The research of the participants’ level of variability may have been raised by administering a more taxing physical function test or a discriminative assessment of their sense of self-determination | |
| [59] | Statistical analysis, regression, correlation | Larger living quarters were linked to higher self-reported impairment levels. According to generalised logit models adjusting for demographics and season, a wider living space was related with reduced vision disability, greater levels of lower extremity motor function, global awareness and social participation as well as with personality and a sense of life’s meaning. As a health indicator in old age, older individuals’ range of environmental mobility may be a valuable supplement to measurements of handicap | It was only possible to evaluate the correlations of life space since the studies were cross-sectional. As a result, volunteering participants from the set of community-dwelling individuals may have had bigger living spaces than the overall population | |
| [60] | Data come from the 5-year follow-up of the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) Study (N = 2,765; mean age = 73.6; 75.8% women; 73.7% White). Life-space constriction was defined as not traveling beyond one’s town. A series of logistic regression and Cox proportional hazard models were used to estimate risk for incident life-space constriction by race and gender. | At the outset, life-space restriction was more common among people of colour and women. At follow-up, women were more likely than men to have experienced incident life-space compression. Compared to Whites, Blacks had a decreased chance of life-space restriction over time | Towns were defined in a small sample size and may have differed from respondent to respondent as well as geographically (e.g., rural vs. urban areas) | |
| [61] | For a 2-year period, 848 persons aged 75 to 90 were questioned in their homes and evaluated using generalised estimation equation models (GEEs) | The findings emphasise the necessity of ensuring that older adults have access to out-of-home mobility options to preserve their quality of life | Self-evaluation of quality of life (QOL) might fluctuate. As a result, we cannot say with certainty when the shifts in QOL occurred. Because certain baseline factors may have changed over time, as different chronic illnesses, for example, we cannot discount the potential that these alterations reflect the connection between mobility change and quality of life | |
| [41] | Home-based interviews at the start of the research, followed by phone interviews after 2 years. The two were a part of the Life-space mobility in old age cohort study’s long-term analysis. A total of 755 residents of Central Finland aged 75–90 years were included in the study. Results: ADL disability status and LSA score (range 0–120) | Restrictions and declines in mobility in old age may be early indicators of increased vulnerability to impairment, as per the findings of this work | Those older adults who were more frail were underrepresented in the sample, and those who were included had a slightly increased likelihood of dropping out during the follow-up, which is a condition that is frequent in studies on ageing | |
| [62] | We used multivariable logistic regression analysis on the binary outcome transportation walking (vs. motorised transportation) to evaluate the association with perceived mobility facilitators in the neighbourhood. The results showed that walking was more likely to be used than motorised transportation. | According to the findings of this study, older people’s transportation preferences appear to be influenced by their perceptions of the environmental qualities of the surrounding neighbourhood. It may be feasible to boost the number of older adults who walk for transportation on a population level by taking environmental measures or by providing information to older adults about the alternatives available to them in the surrounding area | The cross-sectional study design does not permit inferences of causality, and the results may be influenced by residential self-selection, limited sample size, and variables with small subgroups. In addition, the study relied on self-reporting, and some of the measures, including physical activity and the outcome variable, were rather crude. | |
| [35] | Central Finland’s Jyvaskyla and Muurame municipalities provided the participants for this likely cohort research with a follow-up period of two years. The subjects were 75–90 years of age and lived in community settings. The research was conducted in the context of the Life-Space Mobility in Old Age study (LISPE), which was carried out during the years of 2012 and 2014 | Even after accounting for several measures of health and functioning, the results maintained their statistical significance. According to the findings of this study, providing assistance to senior citizens in the pursuit of personally meaningful objectives throughout their lives may add to a bigger life space while also, as a result, to a higher quality of life in old age | There is a possibility that the participants had other objectives in mind, but they did not state those in the interview. Since we do not have any data on the participants’ objectives at the follow-up, we are unable to determine whether or not they have evolved | |
| [63] | A FitBit Surge was used in three days to monitor thirty subjects | A substantial correlation was found between the number of hours spent using GPS and levels of cognition. The results of this study point to the possibility that GPS watches might be used to continually monitor changes in functional health in order to provide information for preventative efforts | Sample size is too small, alongside the time period of the test | |
| [34] | The participants in the research ranged in age from 75 to 90 years of age, and their step counts and total activity were monitored using an accelerometer (a Hookie AM20 Activity Meter) over 7 days | The Life-Space Assessment (LSA) questionnaire was utilised to do an analysis of life-space mobility. Overall, sixteen percent of people who moved around independently had a life-space region that was limited to the neighbourhood. Participants whose life spaces were more limited were less physically active, and around seventy percent of them had unusually low values in daily step counts (615 steps) and moderate exercise time (6.8 min). A favourable correlation was found between higher step counts and total activity time and life-space mobility. | There is a need for prospective research to shed light on the chronological sequence of low levels of physical activity and restrictions in the ability to move freely in one’s life space. The sensitivity of an accelerometer in older persons walking with assistance devices is yet unknown. Because of this, it is probable that the physical activity measurements utilised in this study overestimated the amount of activity engaged in by those who routinely use assistive devices such as walkers. The life-space mobility score takes into consideration whether the individual relies on human assistance or assistive equipment in order to reach a particular level of life-space | |
| [64] | In addition to an investigation of the mean journey characteristics, a sequence alignment approach is utilised in this process | Walking was the form of transport that was most common for persons of senior age, regardless of the type of trip purpose. The vast majority of activities are carried out in the immediate vicinity; trips further afield are often reserved for medical needs and trips to see relatives. Second, variables such as older age, living alone, a high degree of physical handicap, a poor level of education, large distances from home to the nearest public transit, having paid job, and an inability to drive are all things that prevent senior people from travelling. | The following are some of the limitations of the study as well as opportunities for more research: a) In order to achieve more valuable policy implications, a more strict statistical causation is necessary between the structural motif information and the sociodemographic data; b) An in-depth study of the policy implications should be performed. | |
| [65] | Cross-sectional postal survey was carried out, logistic and linear regression models were used. | The only factor that was linked with the total quantity of walking in minutes per week was residential density. There were shown to be moderating effects of gender, age, and the utilisation of walking aids. It would suggest that making improvements to the physical environment might be a viable chance to incentivize and allow older persons to walk for transportation | There is a source of uncertainty in the fact that older adults have a tendency to exaggerate their level of physical activity when answering the questionnaire. Additionally, it is possible that the respondents did not adequately differentiate between walking for transportation and other types of walking activities. | |
| [66] | We used data from the RECORD Cohort Study collected in 2011–2012 in the Paris metropolitan area, France. A sample of 2062 individuals was investigated, Multilevel linear regression was used. | The factor analysis produced five dimensions of spatial behaviour, which are as follows: the significance of the residential neighbourhood when it comes to spaces for activity; the number of activities available; the size, eccentricity, and specialisation of the activity space; and finally, the importance of the residential neighbourhood in the activity space | The primary weakness of the study is that the data on frequent mobility were self-reported, and the researchers did not take environmental factors into account | |
| [67] | In the metropolitan region of Helsinki, Finland, there are two distinct age groups of adults: younger and older | The findings indicate that there is a large divide between the two groups with regard to the frequency as well as the associated factors of a variety of multi-local travel habits | We were able to examine the impacts of many factors with support from statistical tools in this study, but without longitudinal data, causality of relationships cannot be clearly verified. A frequent disadvantage of all data acquired using map-based surveys is that there may have been some biases added to the study due to variances in the amount of participation in mapping among participants and disparities in their level of mapping abilities. They were obtained separately and not meant for comparison, even though they were collected using the same approach and through a comparable survey | |
| [68] | It is hoped that this study will shed light on how seniors cope with their socio-spatial environment by including both quantitative and qualitative approaches, as well as spatial analytic techniques, into a single study | By adjusting their lifestyle on a regular basis, senior suburbanites implicitly opt to remain in their homes as they get older. Because of their strong sense of self-sufficiency and loyalty to the “suburban way of life”, these people have high housing expectations | ||
| [69] | A multi-level linear model of geriatric walkability, built environment, and subjective perception is developed in this work in order to illustrate the type and degree of interaction between variables at all levels | The findings reveal that older people’s walking efficiency is influenced by their perceptions of safety and mobility. Either consistency or variation can be shown in the effect on senior walking distance efficiency of built environment variables | ||
| [70] | Seven hundred twenty-eight Mexican American men and women aged 75 and older were surveyed as part of this cross-sectional research project. Multiple regressions were used | The lives of older Mexican Americans in the United States were severely constrained, with nearly 80% of them confined to their homes or immediate neighbourhoods. There was a correlation between having less life space and older age, female sex, stroke, high levels of depressive symptoms, BMI of 35 or above, and ADL difficulty. | It will be necessary for future research to investigate the correlation between life space and health outcomes, as well as to characterise the development of life space over the course of time in this group. | |
| [71] | Using data from the 2011 Hong Kong Travel Characteristics Survey (TCS), we identified three distinct categories of out-of-town travel: required, maintenance, and discretionary. There were two models employed: Poisson and linear regression | During particular times of the day, certain older adults with specific socioeconomic and geographic characteristics confront possible geographical hurdles to meeting their mobility demands | Were not described | |
| Opportunities | [72] | Real-life GPS data from 95 older persons were used to develop a collection of mobility indicators that reflects various elements of everyday movement | There are several studies that do not adequately reflect the time, distribution, and stop-move segmentation of motions. To provide a complete picture of an older person’s everyday movement, factor analysis uncovers the following six dimensions: living space, the number of activities performed outside of the house, the amount of time spent using active transportation modes, the stability and extension of living space, and the timing of mobility | Poor data quality due to low participant compliance or particular movement patterns (staying a lot indoors) that are linked to low socioeconomic level. For healthy ageing outcomes, it is not necessary to identify which aspects of mobility are most significant (e.g., active living, independence, social participation) |
| [73] | Patterns and motifs are used to help us. Various daily movement patterns were associated with socio-economic and built-environment variables | About 82% and 86% of all senior replies on workdays and non-workdays, respectively, may be summed up in 15 different themes. When it comes to non-workdays, seniors are more likely to display basic motifs with three or fewer unique places, but during workdays, they tend to display more complex patterns |
No strong generalizability can be derived from research on senior daily mobility patterns and the relationship between these various patterns of daily mobility and socio-demographic indicators as well as built environment components This study exclusively examines the travel habits of those above the age of 60. Our results are compared to other studies, however a direct comparison between persons over 60 and those under 60 is not possible. To get a fuller picture of how people engage inside their own households, a more in-depth look at how they interact with each other within their own households is required |
|
| [74] | Drawing from the findings acquired from time–space diaries and surveys filled by older adults in three Czech cities, the model of socio-spatial isolation was established | That social exclusion is a multifaceted (comprising of passiveness, isolation, and loneliness) issue that is both geographically specific and gendered is suggested by the research. A person’s level of passivity is closely linked to their income and their participation in recreational sports. Age, gender, and educational attainment, as well as the regularity with which a person works and engages in certain leisure activities, all of which are limited by health issues, financial resources, and physical mobility, all contribute to a sense of isolation | Sample size is small, and there are fewer variables in the model as a result (e.g., interaction terms are limited to the socio-demographic) | |
| [52] | Elicitation of important knowledge using a systematic approach. The scenario model is implemented and validated using the OBO Edit tool | Using a scenario model, the first step in providing help to people with disabilities who are able to move around outside is being taken. Building an ATD capable of providing situational awareness aid and perhaps improving the quality of life for folks presenting with disabilities is based on this approach | Despite the study’s limitations, the use of GPS as the next best available practical approach was adequate as a reference standard to determine LSM. | |
| [52] | The LSA-CI was used in a cross-sectional study of 118 multimorbid older adults with cognitive impairment to document their life-space mobility (LSM). The study’s findings were supported by GPS-based distance measurements to the researcher’s house. | Clinical treatments can be tailored to the LSA-CI cut-off score and monitored over time | Limited analysed factors | |
| [75] | The study was conducted using a longitudinal cohort design (n = 33) with older persons who resided in the community. At baseline and one year later, GPS data and activity records were obtained | When paired with qualitative data, GPS technology is a powerful and valuable tool for acquiring new information. The use of GPS recorders in assessment and intervention design is an option | GPS and movement logs were only gathered for two periods of time. As the sample comprised mostly Caucasian females with access to personal automobiles, the categories described by these individuals cannot be generalised to other populations. Elders who indicated high levels of self-perceived well-being were included in the study | |
| [33] | Data gathered by employing GPS receivers in conjunction with questionnaires and time diaries | A new interpretation of the Ecological Press Model of Aging was created using the findings, which incorporated family structure as a moderator of the effects of environmental stress. In the long-standing interaction between the environment and the health of older persons, social constructions play a critical role. | This study had a limited sample size of 30 people, thus the findings should be used as a starting point for further research in the field of ageing. | |
| [76] | This is modelled by differences in demand intensity and mobility | Seniors have a greater demand severity and are less mobile than their non-elderly counterparts. More healthcare funds should be provided and better public transit to institutions, particularly in rural regions, is needed to increase the availability of healthcare for the older adults | An older person’s healthcare use behaviour is modelled using only two variables (will be solved in future research). Second and third-tier hospitals are handled equally in this study (next research will examine if a hierarchical pattern exists among these institutions). The older population’s demand is assumed to be the same throughout the research region | |
| [77] | A mixed-method approach was used in the research, which included both qualitative and quantitative components. A total of nine German cities with various spatial structural features took part in the study (140 qualitative interviews and 5500 surveys) | The results show a strong affinity to the area in which they live and the people who live there. There is a good chance that future older persons will be able to stay in their homes for a long time because of the large percentage of people who own their own homes. The few people who plan on moving within the region or using their second homes more regularly are likely to live in various locations in the future | There are not many outcomes. Geographically, a more in-depth worldwide comparison of persistence would be a worthwhile study project in the future | |
| [40] | In Beijing, China, a survey of 139 participants (i.e., older individuals aged 60 and above with varying degrees of disability) was conducted in three separate areas | (1) In order to effectively assist disabled older people to age in place, we characterised unmet needs for older adults care (ADL and IADL assistance) among community-dwelling disabled older adults; (2) discovered disabled older adults had much more unfulfilled necessities for both ADL and IADL aid due to a lack in connections to care resources; and (3) characterised the linkages to care assets for stronger support disabled older adults to live independently. | There is a problem with the sample size. Self-reporting or surrogate reporting was used to obtain all data. As a result, the variables may be overestimated or underestimated | |
| [78] | There were 844 participants in the study who were 55 years or older and lived in the Helsinki Metropolitan Area in Finland. They completed a map of their daily errands and indicated which mode of transportation they used and how often. Participants’ walking excursions were culled from the data, and the impacts of personal, psychological, and environmental factors on older individuals’ ability to walk were studied both directly and indirectly | There was a strong correlation between the number of older adults who walked to work and where they lived, as well as the number of crosswalks, transit stops, and recreational sports venues in the area. Walking by older individuals was shown to be most affected by the number of transit stops within walking distance. Individuals’ demographic and psychological characteristics had little bearing on whether or not the built environment affected their ability to walk as they aged. Walking was positively influenced by a person’s level of education and fitness aspirations, but wealth had a negative impact. Physical activity objectives were an indirect indicator of how gender and self-perceived health affected walking | It is possible that the PPGIS approach as a whole limits the investigated population group since people who have inadequate computer literacy or no internet access are not included in the study measurement. Detailed information on destination density would have been useful, however this was not attainable due to a lack of data | |
| [79] | Observational and questionnaire surveys, 687 seniors aged sixty-five and older | A person’s biology is not the most essential component. Instead, even the oldest-old group of eighty-five and older can be more active if they maintain a healthy weight range and utilise a walking assistance properly | Because of the lack of local resident registrations, the samples were not selected by random sampling | |
| [80] | Accumulative behavioural scenario variants, Albatross system as the simulator | The older adults of the future will have to work longer hours, adjust their activity pattern to include more social and leisure activities, escape the morning rush hour by changing their schedules, and maybe add more spatial variety into their living arrangements | not described | |
| [81] | A community-based survey (Philadelphia, 2010) assessed mobility (Life-Space Assessment [LSA]; range = 0–104) of older adults (n = 675, census tracts = 256). Social capital was assessed for all adults interviewed from 2002–2010 | Mobility may not be as influenced by social capital as other local variables. Research on mobility should take into account the interplay between neighbourhood and individual factors | There may have been a reduction in the measure’s capacity to identify variations in movement between groups as a result of replies being standardised | |
| [82] | Forty-four participants who took part in a reality cave exercise and a sub-group of 10 people who visited an unfamiliar area as pedestrians describe their experience of walking a predetermined route. | In unfamiliar situations, there are a variety of issues that older people face, such as bad signage and confusing places as well as poor pavement and “sensory overload”, which refers to the noise and complexity of the surroundings. Participants relied more on landmarks and unique structures to help them find their way through new locations | Low sample size | |
| [83] | 92 global positioning system (GPS)-recorded mobility tracks from 47 participants (24 women, 23 men) from the Cardiovascular Health effects of Air pollution in Telangana, India (CHAI) project (mean: 4.1 days/person). The mean age was 44 (standard deviation: 14) years | Using a principal component analysis, it was discovered that 86% of the variance in women’s and 61% of the variance in men’s mobility can be attributed to the size of the activity area, the mobility of the dwelling and the mobility within the hamlet. All three characteristics were linked to a person’s age, socioeconomic position, and level of urbanisation | As a result, it is difficult to examine how unique person traits affect the correlation between predictors and mobility indicators. However, our automated system was unable to discriminate between time spent indoors and outside. data gathering may not be reflective of a person’s mobility patterns if it takes place in a short period of time | |
| [84] | Using data gathered through in-depth interviews, follow-along interviews, and mapping activities, three individuals’ perspectives on ageing at home in Dublin are explored. Participants’ place-based functionings are shown through the use of annotated maps | There are many diverse ways in which people value and negotiate their place-based functioning, relying on their requirements, preferences, and health or mobility issues. Additionally, the results show the significance of helpful settings and social assistance in facilitating older adult individuals to accomplish their greatest valued functioning’s over time, such as being able to get outside, start engaging and communicate with everyone, complete daily duties and odd jobs assertively, and continue to stay self-sufficient | It is possible that subsequent study may examine the ageing experience of people from varied socioeconomic and ethnic origins, including those who are homebound, in a broader range of circumstances. Additionally, these strategies might be developed over time | |
| [85] | Participants in focus groups | According to the resultant walkability typology, most urban street blocks offer only modest protection for the older adults. Older adults who dwell in seniors’ apartments may be compelled to engage in indoor activities rather than participate in urban life, resulting in a sort of spatial isolation | Limited sample size | |
| [86] | 49 older adults from the Tel-Aviv Metropolitan area (Israel). Participants were tracked for an average of 28 consecutive days using a location kit that combined GPS with RFID technology | Demographics, sex, and ease of access to a private vehicle all play a crucial role in determining how far senior persons with cognitive impairment can travel outside the home. These patterns show that out-of-home mobility is generally declining | External elements have to be pared down. Additional factors, such as the weather and the length of the day, can be incorporated into the study to determine whether seasonal trends can be discerned | |
| COVID aspects | [87] | GPS-based mobility data for a wider time frame of six months (March 20–August 20) divided into four tiers and analysis for all the US counties (N = 3142) | All three mobility matrices (trip rate, out-of-county travel rate, and miles/person travelled) fell until the first wave reached its apex, after which they began to climb. Within- and outside-county travel were found to be inversely associated with infection rates in spatial models. Areas with high concentrations of COVID-infected persons had a higher proportion of those who worked from home, lower percentages of the older adults and educated, as well as a higher proportion of the poor | Because of the nationwide trend of COVID cases, the research duration was partitioned into four tiers, which was not possible to accommodate individually for states with various infection rates and varying timetables for stay-at-home orders and reopening. It is impossible to conclude that each tier of states had a uniform pattern of mobility. It was fair to reduce the amount of granularity in exchange for the study’s relatively long time period, which was divided into four equal halves. Because the study relies on GPS-enabled smartphone data, it excludes persons who do not own a smartphone from the findings |
| [88] | Participant responses were mapped out using a map-based questionnaire, and 75–85-year-olds indicated locations for physical activity, places that made it easier to get around outside, and destinations for other activities | During COVID-19, there was a noticeable decrease in activity destinations recorded, with most of those being for physical activity, and they were all located closer to home | In COVID-19, individuals dropped participation due to adverse selection (improved health and functioning and more competency with digital devices), which reduced the sample size. So the results of this study should be considered with caution and could only be applicable to those over the age of 75 who are well-functioning and technologically proficient. To improve the likelihood of completing the self-completed MQ successfully, sufficient test and training are required. Because all of the variables in the research were self-reported, there is a risk of bias in the data |