Population aging worldwide1 intersects with older adults’ low levels of physical activity (PA)2,3 and increased prevalence of chronic diseases4 to create a “perfect storm.” Thus, active aging is a public health priority.5 Although many interventions effectively increased older adults’ PA,6 most focused on short-term behavior change (ie, immediately postintervention). To achieve longer-term health benefits, positive health behaviors must be maintained—defined as behaviors that persist for a minimum of 6 months after the initial behavior change.7 Maintenance is particularly important for older adults, who otherwise experience age-related declines in PA8,9 and mobility.10 A recent systematic review6 noted that, of 14 older-adult PA interventions, only 3 had a follow-up period of 1 year or longer.11,12 This prompted a call from authors of a systematic review of reviews13 for more PA intervention studies with longer follow-up periods.
To enhance population health, effective interventions must be scaled up to reach greater numbers of individuals.14 Over 400 studies of PA interventions in older adults were published since 1990, yet only 6 of them11,15–19 were scaled up and evaluated.20 Of these, only 2 studies assessed whether PA behavior change was maintained.11 In the PACE-up and PACE-lift trials, adults aged 45–75 years participated in a 12-week pedometer-based walking intervention. Those in the walking group maintained higher levels of moderate to vigorous PA (by accelerometry) compared with adults in the control group 3 to 4 years after the intervention ended. Among the many reasons that few effective interventions are scaled up and sustained are the resources required to do so, shifting priorities among funding partners, public interest, and lack of political will.21,22
Choose to Move (CTM) is a scalable, 6-month PA intervention targeting low physically active (<150 min/wk) older adults.23–26 CTM is being scaled up in a phased approach across British Columbia, Canada. The 6-month CTM intervention enhanced PA, mobility, and social connectedness (ie, decreased feelings of loneliness and social isolation) among older adult participants aged 60 years and older.23 In this study, we followed up these participants 12 months after the intervention ceased (18 mo after participants began the intervention). Our primary objective was to assess whether participant-level outcomes were maintained in the year following CTM (from 6 to 18 mo). We define maintenance of the intervention benefit as no statistically significant difference between the measures taken at 6 and 18 months. We hypothesized that the intervention-related benefits in PA, social connectedness (loneliness and social isolation), mobility, and muscle strength would not be maintained 12 months after completing CTM. Our secondary objective was to report whether the participant-level outcomes at 18 months differed from baseline (preintervention) values. We hypothesized that the outcomes would return to baseline such that values at 18 months would be similar to baseline values. As in a previous analysis,23 we planned (a priori) to split the cohort by age (60–74 and ≥75 y) to assess change by age group.
Methods
Choose to Move
Choose to Move is not prescriptive, but was designed, based on evidence,16 as an adaptable model whereby participants choose what they enjoy and are able to do. At the organization level, CTM builds community capacity to support awareness of, and access to, local health-promoting opportunities. At the individual (participant) level, CTM activity coaches provided personalized support to create PA action plans customized to each individual’s activity preferences, resources, and mobility capacity. CTM also addressed barriers to PA, and provided opportunities for social support and for older adults to share and learn with fellow participants. During the 6-month intervention, trained activity coaches from 2 community-based delivery partner organizations (Young Men’s Christian Association [YMCA]; British Columbia Parks and Recreation Association [BCRPA]) provided participants with (1) a 60-minute one-on-one consultation, (2) 4 motivational group meetings (up to 12 participants/group), and (3) 10 telephone check-ins. Activity coaches provided more support during the first 3 months (1 one-on-one meeting, 7 telephone calls, and 4 group meetings) compared with the last 3 months (3 telephone calls) (Figure 1).
—The timing of program components and data collection for the present study. The Choose to Move program consisted of 4 motivational group meetings, 1 one-on-one session with an activity coach, and 10 check-ins (phone, e-mail, or in person).
Citation: Journal of Physical Activity and Health 18, 10; 10.1123/jpah.2020-0850
Study Design and Participants
Conceptual frameworks for implementation and evaluation, guiding principles, the intervention, and evaluation methods are described in detail elsewhere.23–25 Briefly, we used a type 2 hybrid effectiveness implementation study design27 to evaluate CTM. We previously reported outcomes measured at 0 (baseline), 3 (mid-intervention), and 6 (postintervention) months.23 The current study presents our findings 1 year after the intervention ceased (18 mo from baseline). The University of British Columbia and Simon Fraser University Clinical Research Ethics Boards (H15-02522 [UBC] and 22015s0614 [SFU]) approved all study procedures.
Together, delivery partners reached small (n = 8), medium (n = 7), and large (n = 11) urban communities across British Columbia. Delivery partner organizations recruited participants using a variety of strategies (eg, local promotions, such as program guides, posters, and information sessions; media advertisements; and word of mouth). Eligible participants were community-dwelling men and women aged ≥60 years, English speaking, and physically inactive (self-reported <150 min/wk of PA), with no contraindications to PA participation (Physical Activity Readiness-Questionnaire+28 or physician clearance). We trained delivery partners to describe the evaluation to registered participants and invite them to participate. Of 534 participants across 56 programs delivered between January 2016 and May 2017, 458 (86%) older adults consented to participate in the evaluation (province-wide assessment). Of these participants, 209 older adults enrolled in the 23 programs in proximity to Greater Vancouver also consented to a more comprehensive assessment (comprehensive subset).
Following cessation of the 6-month intervention, we invited 406 (89%) participants to complete a follow-up assessment between June 2017 and May 2018—approximately 12 months after completing their 6-month assessment (Figure 2). We did not invite those participants who had dropped out of CTM (n = 50) or withdrawn from the evaluation (n = 2). We obtained consent from 238 (52%) participants from the baseline cohort (60–74 y, n = 168; ≥75 y, n = 70).
—Participant flow through the study. Participants in the comprehensive subset completed more detailed assessments (physical activity, mobility, and muscle strength) in addition to the paper-based surveys completed by the provincial cohort.
Citation: Journal of Physical Activity and Health 18, 10; 10.1123/jpah.2020-0850
Measurements
At 18 months, we replicated previous measurement protocols.23 We used data from 0, 6, and 18 months in this analysis. We provide a brief description of our measurement protocols below, as they are described in greater detail elsewhere.23
Province-Wide Assessment
At each time point, we collected survey-based data. Participants completed their surveys at group meetings (baseline) or at home (6 and 18 mo) via mailed surveys; participants who required extra assistance (3%) at 6 and 18 months completed the surveys over the phone with a trained research assistant. All participants completed a baseline demographic survey; the items included age category, sex, self-reported height and weight, educational attainment, ethnicity, number of chronic conditions, and self-rated health (single question29,30). Participants self-reported PA (number of days per week ≥30 min) using a valid and reliable single-item questionnaire31,32 and capacity for mobility as no/any difficulty walking 400 m and/or climbing one flight of stairs.33 We assessed loneliness using a 3-item questionnaire (loneliness score; range 3–9, where higher scores indicate greater loneliness) that shows good internal consistency, discriminant validity, and convergent validity,34 and social isolation using a 3-item questionnaire35 adapted from 2 questions on social contact frequency36 (social isolation score; range 0–15, where higher scores indicate less social isolation).
Comprehensive Subset Assessment
In addition to the measures described above, we assessed PA, mobility, and muscle strength on a subset of participants at each time point using methods described in detail elsewhere.23 Participants in the comprehensive subset completed their assessments at group meetings (baseline), dedicated measurement sessions (6 and 18 mo), or via mailed surveys (if they missed a group meeting or measurement session). We administered the CHAMPS questionnaire to assess PA (energy expenditure and frequency of moderate and all activities).37 Trained research assistants assessed mobility using the Short Physical Performance Battery (SPPB)38 (summary score, range 0–12) and the participants’ muscle strength (grip strength, to the nearest 0.1 kg) using a handheld dynamometer (Jamar Plus; Performance Health Canada, Mississauga, ON).
Statistical Analysis
We performed all analyses using Stata (version 13.1; StataCorp, College Station, TX). We first assessed whether participants with 18-month data differed from those who completed the intervention but did not return for follow-up. We used chi-squared or Fisher exact test for categorical variables (sex, age category, ethnicity, education, chronic conditions, mobility limitations, and subset participation) and unpaired t tests for continuous variables (body mass index).
To address our objectives, we fit linear mixed effects models for each continuous variable (province-wide assessment: PA [single-item], social isolation, loneliness, mobility [self-reported]; comprehensive subset: PA [CHAMPS], mobility [SPPB], muscle strength) with time (0, 6, and 18 mo) as a categorical predictor. We first fit an empty means random intercept model and tested whether random slopes improved model fit using likelihood ratio tests. In model 1, we included the sex and age category as fixed effects. Model 2 included additional covariates: delivery partner, baseline mobility limitation (yes/no), number of chronic conditions (0, 1, ≥2), education, and body mass index. In both models, we added fixed effects sequentially and tested interactions with time after the addition of each fixed effect. With the exception of an age × time interaction, the interactions were retained in the model only if the likelihood ratio test was significant (P < .05). We assessed model fit graphically using residual plots. Adjusted values were calculated at each time point using the margins command in Stata with a Bonferroni adjustment to account for multiple comparisons between and within age groups. In the provincial cohort, we also used chi-squared tests to assess differences in the proportion of participants with mobility limitations over time (6–18 and 0–18 mo) within each age group. We used a Bonferroni adjustment to account for multiple comparisons (significance at: .05/2 = .025).
Results
Participants
Of the 238 participants who consented to the follow-up evaluation, 3 participants withdrew or did not complete the evaluation. For analysis, we included all available data across 3 time points; the number of participants with data at 3, 2, and 1 time points was 235 (51%), 172 (38%), and 51 (11%), respectively. For those who returned for follow-up, baseline demographic characteristics, number of chronic conditions, mobility limitations, and body mass index were similar to those who did not return (Table 1). However, more participants who returned for follow-up rated their health as good or excellent for their age as compared with those who did not return (59% vs 45%, P = .04).
Baseline Participant Sociodemographic, General Health, and Mobility Characteristics for Participants Who Completed the 18-Month Follow-Up Measurement (POST, 12-mo After Choose to Move Ended) and Participants Who Completed the Intervention but Did Not Return for the 18-Month Follow-Up (No POST)
| Outcome | Completed POST (n = 235) | No POST (but finished intervention) (n = 171) | P value |
|---|---|---|---|
| Participants, n (men/women) | 54/181 | 41/130 | .815 |
| % (men) | 23% | 24% | |
| Completed 6-mo measurement | 223 (95%) | ||
| Comprehensive subset participants, n (%) | |||
| Yes | 117 (50%) | 78 (46%) | |
| No | 118 (50%) | 93 (54%) | .406 |
| Age group, n (%) | |||
| 60–74 y | 166 (71%) | 122 (71%) | |
| ≥75 y | 69 (29%) | 49 (29%) | .877 |
| BMI, kg/m2 | |||
| Men | 28.8 (4.4) | 29.3 (4.8) | .566 |
| Women | 29.5 (7.5) | 29.8 (7.1) | .735 |
| Ethnicity, n (%) | |||
| White | 203 (86%) | 148 (87%) | |
| Asian | 17 (7%) | 14 (8%) | |
| Other | 15 (6%) | 9 (5%) | .849 |
| Educational attainment, n (%) | |||
| Secondary or less | 50 (21%) | 39 (23%) | |
| Some trade, technical school, or college | 77 (33%) | 55 (32%) | |
| Some university | 108 (46%) | 77 (45%) | .934 |
| Chronic conditions, n (%) | |||
| 0 | 31 (13%) | 21 (12%) | |
| 1 | 87 (37%) | 71 (42%) | |
| >2 | 117 (50%) | 79 (46%) | .656 |
| Mobility limitations (walk or stairs), n (%)a | |||
| Yes | 95 (41%) | 83 (49%) | |
| No | 136 (59%) | 87 (51%) | .125 |
| Self-rated health at baseline, n (%)b | |||
| Very poor, poor, or fair for age | 95 (41%) | 93 (54%) | |
| Good or excellent for age | 137 (59%) | 77 (45%) | .040 |
Abbreviation: BMI, body mass index. Note: Values are presented as n (%) or mean (SD).
an = 231 POST and 170 no-POST, bn = 232 POST and 170 no-POST.
Province-Wide Assessment
We present outcomes for the whole sample (province-wide assessment) in Table 2. As the results were similar for models 1 and 2, we focus on the fully adjusted models (model 2) below.
Adjusted Means (95% CIs) for Outcome Measures by Time Point and Age Group in the Province-Wide Choose to Move Assessment Cohort
| Adjusted means (95% CI) | ||||||
|---|---|---|---|---|---|---|
| Outcome | Month | 60–74 y | ≥75 y | Comparison, mo | P value (60–74 y) | P value (≥75 y) |
| PA (number of days per week >30 min) | 0 (n = 444) | 2.1 (1.9 to 2.3) | 2.7 (2.4 to 3.0) | |||
| 6 (n = 362) | 3.5 (3.3 to 3.7) | 3.1 (2.7 to 3.5) | 6 vs 18 | .007 | >.99 | |
| 18 (n = 228) | 3.0 (2.8 to 3.3) | 2.9 (2.4 to 3.3) | 0 vs 18 | <.001 | >.99 | |
| Social isolation (score, 0–15) | 0 (n = 445) | 11.2 (10.8 to 11.5) | 12.8 (12.3 to 13.3) | |||
| 6 (n = 362) | 11.6 (11.2 to 11.9) | 12.6 (12.1 to 13.1) | 6 vs 18 | .684 | .158 | |
| 18 (n = 227) | 11.8 (11.4 to 12.2) | 12.0 (11.4 to 12.7) | 0 vs 18 | .001 | .033 | |
| Loneliness (score, 3–9) | 0 (n = 441) | 4.7 (4.5 to 4.9) | 4.2 (3.9 to 4.5) | |||
| 6 (n = 358) | 4.4 (4.2 to 4.6) | 3.9 (3.6 to 4.2) | 6 vs 18 | .247 | .161 | |
| 18 (n = 226) | 4.5 (4.3 to 4.7) | 4.2 (3.8 to 4.5) | 0 vs 18 | .263 | >.99 | |
Abbreviations: BMI, body mass index; CI, confidence interval; PA, physical activity. Note: Results are presented for the linear mixed model adjusted for age, sex, delivery organization, baseline mobility, number of chronic conditions, education, and BMI.
Physical Activity
Objective 1 (6–18 mo)
In the younger participants, PA decreased between 6 and 18 months (−0.5 d/wk; 95% CI, −0.8 to −0.1; P = .007). In the older participants, PA did not differ between 6 and 18 months.
Objective 2 (0–18 mo)
In the younger participants, PA at 18 months was higher than at baseline (+0.9 d/wk; 95% CI, 0.5 to 1.3; P < .001). In the older participants, PA did not differ between 0 and 18 months.
Mobility
Objective 1 (6–18 mo)
Among both age groups, the prevalence of mobility limitations did not differ between 6 and 18 months (60–74 y: 31% vs 34%, P = .458; ≥75 y: 43% vs 54%, P = .155).
Objective 2 (0–18 mo)
Among both age groups, the prevalence of mobility limitations did not differ between 0 and 18 months (60–74 y: 41% vs 34%, P = .149; ≥75 y: 50% vs 54%, P = .625).
Social Isolation
Objective 1 (6–18 mo)
In both the younger and older participants, social isolation did not differ between 6 and 18 months.
Objective 2 (0–18 mo)
Among the younger participants, the social isolation score was higher (indicating lower social isolation) at 18 months compared with baseline (+0.7; 95% CI, 0.2 to 1.1; P = .001). Among the older participants, the social isolation score at 18 months was significantly lower (indicating greater social isolation) as compared with baseline (−0.7; 95% CI, −1.4 to −0.05; P = .033).
Loneliness
Objective 1 (6–18 mo)
Among younger and older participants, loneliness scores at 18 months did not differ compared with 6 months.
Objective 2 (0–18 mo)
The loneliness scores at 18 months were not significantly different from the baseline values in either the younger or older participants.
Comprehensive Subset Assessment
We present the outcomes for the comprehensive subset assessment in Table 3.
Adjusted Means (95% CIs) for Outcome Measures by Time Point and Age Group in the Comprehensive Choose to Move Assessment Subset
| Adjusted means (95% CI) | ||||||
|---|---|---|---|---|---|---|
| Outcome | Month | 60–74 y | ≥75 y | Comparison, mo | P value (60–74 y) | P value (≥75 y) |
| PA, all exercise, kcal/wk | 0 (n = 191) | 2469 (2132 to 2806) | 3001 (2423 to 3578) | |||
| 6 (n = 168) | 3145 (2775 to 3515) | 3105 (2482 to 3728) | 6 vs 18 | .225 | .639 | |
| 18 (n = 103) | 2686 (2193 to 3179) | 2619 (1865 to 3374) | 0 vs 18 | >.99 | >.99 | |
| PA, moderate exercise, kcal/wk | 0 (n = 191) | 1096 (856 to 1337) | 1427 (1016 to 1838) | |||
| 6 (n = 168) | 1522 (1265 to 1779) | 1701 (1270 to 2131) | 6 vs 18 | .738 | .285 | |
| 18 (n = 103) | 1301 (969 to 1632) | 1214 (714 to 1714) | 0 vs 18 | .832 | >.99 | |
| PA, all exercise, freq/wk | 0 (n = 191) | 14.1 (12.5 to 15.8) | 19.0 (16.1 to 21.8) | |||
| 6 (n = 168) | 19.1 (17.4 to 20.9) | 19.5 (16.6 to 22.5) | 6 vs 18 | .001 | .711 | |
| 18 (n = 102) | 15.1 (13.0 to 17.3) | 17.5 (14.2 to 20.9) | 0 vs 18 | >.99 | >.99 | |
| PA, moderate exercise, freq/wk | 0 (n = 191) | 4.5 (3.6 to 5.4) | 6.3 (4.7 to 7.8) | |||
| 6 (n = 168) | 6.9 (5.9 to 7.8) | 7.1 (5.5 to 8.7) | 6 vs 18 | .028 | .761 | |
| 18 (n = 102) | 5.3 (4.1 to 6.4) | 6.0 (4.2 to 7.9) | 0 vs 18 | .544 | >.99 | |
| Mobility (SPPB score, 1–12) | 0 (n = 192) | 10.2 (9.8 to 10.5) | 9.5 (8.9 to 10.1) | |||
| 6 (n = 157) | 10.6 (10.2 to 11.0) | 10.1 (9.5 to 10.7) | 6 vs 18 | >.99 | >.99 | |
| 18 (n = 81) | 10.7 (10.3 to 11.2) | 10.1 (9.4 to 10.8) | 0 vs 18 | .005 | .06 | |
| Muscle strength, grip strength, kg | 0 (n = 189) | 51.2 (49.2 to 53.2) | 43.2 (39.7 to 46.6) | |||
| 6 (n = 154) | 53.6 (51.6 to 55.7) | 46.3 (42.9 to 49.7) | 6 vs 18 | .744 | .188 | |
| 18 (n = 75) | 52.5 (50.1 to 55.0) | 43.9 (40.1 to 47.6) | 0 vs 18 | .547 | >.99 | |
Abbreviations: BMI, body mass index; CI, confidence interval; freq, frequency; PA, physical activity; SPPB, Short Physical Performance Battery. Note: Results are presented for the linear mixed model adjusted for age, sex, delivery organization, baseline mobility, number of chronic conditions, education, and BMI.
Physical Activity (CHAMPS)
Objective 1 (6–18 mo)
In younger participants, energy expenditure did not differ between 6 and 18 months. PA frequency (all activities and moderate activities) decreased significantly from 6 to 18 months in the younger participants (−4.0; 95% CI, −6.6 to −1.4; P = .001). In the older participants, neither energy expenditure nor activity frequency differed between 6 and 18 months.
Objective 2 (0–18 mo)
In both the younger and older participants, neither energy expenditure nor PA frequency (all activities and moderate activities) differed between 0 and 18 months.
Mobility (SPPB)
Objective 1 (6–18 mo)
For both age groups, the SPPB scores did not differ between 6 and 18 months.
Objective 2 (0–18 mo)
Among younger participants, mobility at 18 months was significantly higher than at baseline (+0.5; 95% CI, 0.1 to 1.0; P = .003). Among the older participants, mobility did not differ significantly between 0 and 18 months.
Muscle Strength
Objective 1 (6–18 mo)
For both age groups, muscle strength did not differ between 6 and 18 months.
Objective 2 (0–18 mo)
For both age groups, muscle strength did not differ between 0 and 18 months.
Discussion
The literature related to the scale-up of older adult PA interventions is sparse, particularly as it relates to the maintenance of behavior change. We extend this literature by (1) evaluating change in participant-level outcomes in the year following CTM—an effective 6-month scaled-up PA intervention23 and (2) assessing maintenance of these same outcomes from baseline to 18 months (secondary objective). Twelve months after participating, those aged 60–74 years demonstrated lower PA compared with PA levels at the end of the CTM intervention. However, they were more physically active at that final 18-month assessment than at the start of the intervention. Intervention-related benefits in social isolation, loneliness, mobility, and muscle strength were maintained in this age group over time. In the older participants (≥75 y), intervention-related benefits in loneliness and mobility were maintained in the 12 months following the intervention. When compared with baseline values, PA levels in older participants were similar at 18 months, whereas feelings of social isolation were slightly escalated. We discuss the implications of these findings below.
While actively participating in the 6-month intervention, PA among younger participants increased at 3 months and remained stable through a 3-month taper phase (fewer contacts with their activity coach).23 Our findings 12 months after CTM ended are meaningful, given that all participants self-reported as low-active (<150 min/wk of PA) when they started CTM. Increasing PA, especially from low levels, has public health benefits.39 Maintaining even a light level of PA is associated with a reduced risk of all-cause and cardiovascular mortality.40 Increased PA (relative to baseline) in CTM participants aged 60–75 years counters the known age-related decline in PA and health.8,9 Among participants aged 75 years and older, PA returned to baseline levels during the 3-month taper phase,23 but PA did not decline further in the 12 months following CTM. In CTM participants, maintenance may indicate that older adults retained and applied learning and skills from CTM (eg, goal setting, action planning).
The 6-month CTM intervention enhanced mobility (defined as any limitations with walking or stair climbing) in the younger participants and muscle strength in the younger and older participants.23 These benefits were maintained during the 12-month follow-up period, as was the intervention-related increase in mobility (by SPPB) in all participants. This finding highlights the importance of continuous engagement in PA over time, to maintain functional capacity and reduce frailty.9,41 Importantly, low SPPB scores predict long-term disability and/or institutionalization.42 Given the close relationship between PA and mobility,9,41 PA may have effectively countered common age-related declines in mobility.10 However, we interpret the results in the older age group with caution, given the small sample size due to attrition at follow-up.
The intervention benefits related to social outcomes were maintained 1-year postintervention in both age groups, with the exception of social isolation, which increased slightly in the older participants when compared with baseline. Loneliness is associated with deteriorating health, including accelerated loss of physical functioning with age.43 Similarly, the caring and respect that occurs with social connections and an associated sense of well-being can protect against health problems.44 Conversely, social isolation exacerbates negative health effects in older adults; these include increased risk for all-cause mortality45 and dementia.46 The participants’ positive relationship with their activity coach and interactions with other participants influenced feelings of social connectedness during CTM.47,48 Sharing information and experiences, learning from their peers, and engaging with others who share familiar experiences also contributed to feelings of social connection.35 It seems imperative to maintain social and mental health benefits; to do so, programs that support these outcomes must be ongoing. However, the amount or quality of interaction afforded through participation in CTM may have been insufficient to counter feelings of social isolation in our oldest participants.
Previous PA programs for older adults showed benefits at 12 (but not 24) months, based on a meta-analysis of mostly small-scale trials.49 Therefore, our study provides a novel contribution to scale-up science and adds important evidence with a study where an intervention was implemented and evaluated at scale.11,15–19 To improve population health, effective PA interventions for older adults must be scalable50 and scaled up.14
Strengths and Limitations
To date, most PA programs for older adults have targeted clinical populations and were not translated from clinical trials into “real world” settings or scaled up. Our novel study assessed whether functional improvements that older adults accrued during a 6-month scaled-up intervention were maintained 1 year after the intervention ceased.
We acknowledge that our study had a number of limitations. First, although we retained a reasonable proportion of participants, those with poorer self-rated health were less likely to complete the follow-up assessment; this is similar to previous studies.51 Second, the pragmatic measures we used were reliable and valid, but were limited mostly to self-report. Third, our sample included a relatively small number of adults ≥75 years, which could limit our ability to convincingly detect maintenance or decline in health outcomes in this group. As older adults are at risk for increased social isolation52 and diminished mobility,10,53 it seems important to target this population.
Implications of This Work and Future Directions
The results we observed at follow-up raise at least 2 questions. First, what is the minimum dose of an intervention required to maintain short- and long-term impact? Second, can booster contacts effectively maintain PA behaviors and health benefits54? In addition, we call for more detailed studies that describe the implementation process to identify best fit in (for example) different geographic, cultural, and even clinical settings; how best to engage delivery partners in planning, scaling-up, and sustaining an intervention; and how to adapt the intervention and implementation strategies to optimize cost effectiveness while retaining health benefits.
Global health initiatives achieved scale-up success using a phased approach and integrating programs into functioning systems and services.55 We opine that investing in long-term program success and utilizing health-promoting opportunities that exist in local environments may maintain healthy behaviors and associated outcomes. An integrated approach to scale-up acknowledges levels of influence on behavior change across a socioecological continuum that spans individual to systems-level influences.13 It is time for a paradigm shift toward implementing studies that target scale-up of effective health-promoting interventions for older adults—and even more so—to determine how to sustain programs that promote and maintain positive behaviors in the future.
Acknowledgments
We thank our delivery partner organizations, facility managers and coordinators, activity coaches, and all the older adults who participated in Choose to Move. Thanks also to staff and trainees from AART (Centre for Hip Health and Mobility, University of British Columbia, Vancouver, Canada) for data collection. Study data were collected and managed using REDCap electronic data capture tools hosted at the University of British Columbia. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources.56
References
- 1.↑
Statistics Canada. Canadian Demographics at a Glance. Catalogue No. 91-003-X. 2016. Retrieved from https://www150.statcan.gc.ca/n1/en/catalogue/91-003-X. Accessed May 15, 2021.
- 2.↑
Clarke J, Colley R, Janssen I, Tremblay MS. Accelerometer-measured moderate-to-vigorous physical activity of Canadian adults, 2007 to 2017. Health Rep. 2019;30(8):3–10. PubMed ID: 31454407 doi:10.25318/82-003-x201900800001-eng
- 3.↑
Hallal PC, Andersen LB, Bull FC, et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012;380(9838):247–257. PubMed ID: 22818937 doi:10.1016/S0140-6736(12)60646-1
- 4.↑
Hung WW, Ross JS, Boockvar KS, Siu AL. Recent trends in chronic disease, impairment and disability among older adults in the United States. BMC Geriatr. 2011;11:47. PubMed ID: 21851629 doi:10.1186/1471-2318-11-47
- 5.↑
Healthy Aging and Wellness Working Group. Healthy aging in Canada: A new vision, a vital investment from evidence to action. 2006. https://www.health.gov.bc.ca/library/publications/year/2006/Healthy_Aging_A_Vital_latest_copy_October_2006.pdf. Accessed April 27, 2021.
- 6.↑
Grande GD, Oliveira CB, Morelhao PK, et al. Interventions promoting physical activity among older adults: a systematic review and meta-analysis. Gerontologist. 2020;60(8):583–599. PubMed ID: 31868213 doi:10.1093/geront/gnz167
- 7.↑
Prochaska JO, Crimi P, Lapsanski D, Martel L, Reid P. Self-change processes, self-efficacy and self-concept in relapse and maintenance of cessation of smoking. Psychol Rep. 1982;51(3, pt 1):983–990. PubMed ID: 7163454 doi:10.2466/pr0.1982.51.3.983
- 8.↑
Sun F, Norman IJ, While AE. Physical activity in older people: a systematic review. BMC Public Health. 2013;13:449. PubMed ID: 23648225 doi:10.1186/1471-2458-13-449
- 9.↑
Bauman A, Merom D, Bull FC, Buchner DM, Fiatarone Singh MA. Updating the evidence for physical activity: summative reviews of the epidemiological evidence, prevalence, and interventions to promote “active aging.” Gerontologist. 2016;56(suppl 2):S268–S280. PubMed ID: 26994266 doi:10.1093/geront/gnw031
- 10.↑
Ferrucci L, Cooper R, Shardell M, Simonsick EM, Schrack JA, Kuh D. Age-related change in mobility: perspectives from life course epidemiology and geroscience. J Gerontol A Biol Sci Med Sci. 2016;71(9):1184–1194. PubMed ID: 26975983 doi:10.1093/gerona/glw043
- 11.↑
Harris T, Kerry SM, Limb ES, et al. Physical activity levels in adults and older adults 3-4 years after pedometer-based walking interventions: long-term follow-up of participants from two randomised controlled trials in UK primary care. PLoS Med. 2018;15(3):e1002526. PubMed ID: 29522529 doi:10.1371/journal.pmed.1002526
- 12.↑
Oliveira JS, Sherrington C, Paul SS, et al. A combined physical activity and fall prevention intervention improved mobility-related goal attainment but not physical activity in older adults: a randomised trial. J Physiother. 2019;65(1):16–22. PubMed ID: 30581138 doi:10.1016/j.jphys.2018.11.005
- 13.↑
Zubala A, MacGillivray S, Frost H, et al. Promotion of physical activity interventions for community dwelling older adults: a systematic review of reviews. PLoS One. 2017;12(7):e0180902. PubMed ID: 28700754 doi:10.1371/journal.pone.0180902
- 14.↑
Milat AJ, Newson R, King L, et al. A guide to scaling up population health interventions. Public Health Res Pract. 2016;26(1):e2611604. PubMed ID: 26863167 doi:10.17061/phrp2611604
- 15.↑
Wilcox S, Dowda M, Leviton LC, et al. Active for life: final results from the translation of two physical activity programs. Am J Prev Med. 2008;35(4):340–351. PubMed ID: 18779028 doi:10.1016/j.amepre.2008.07.001
- 16.↑
Stewart AL, Mills KM, Sepsis PG, et al. Evaluation of CHAMPS, a physical activity promotion program for older adults. Ann Behav Med. 1997;19(4):353–361. PubMed ID: 9706362 doi:10.1007/BF02895154
- 17.
Phelan EA, Williams B, Snyder SJ, Fitts SS, LoGerfo JP. A five state dissemination of a community-based disability prevention program for older adults. Clin Interv Aging. 2006;1(3):267–274. PubMed ID: 18046880 doi:10.2147/ciia.2006.1.3.267
- 18.
Seguin RA, Economos CD, Hyatt R, Palombo R, Reed PN, Nelson ME. Design and national dissemination of the StrongWomen Community Strength Training Program. Prev Chronic Dis. 2008;5(1):A25. PubMed ID: 18082014
- 19.↑
Petrescu-Prahova MG, Eagen TJ, Fishleder SL, Belza B. Enhance®Fitness dissemination and implementation,: 2010-2015: a scoping review. Am J Prev Med. 2017;52(3)(suppl 3):S295–S299. PubMed ID: 28215384 doi:10.1016/j.amepre.2016.08.015
- 20.↑
Gray SM, McKay HA, Nettlefold L, et al. Physical activity is good for older adults-but is programme implementation being overlooked? A systematic review of intervention studies that reported frameworks or measures of implementation. Br J Sports Med. 2020. PubMed ID: 33028586 doi:10.1136/bjsports-2020-102465
- 21.↑
Brownson RC, Allen P, Jacob RR, et al. Understanding mis-implementation in public health practice. Am J Prev Med. 2015;48(5):543–551. PubMed ID: 25891053 doi:10.1016/j.amepre.2014.11.015
- 22.↑
Hailemariam M, Bustos T, Montgomery B, Barajas R, Evans LB, Drahota A. Evidence-based intervention sustainability strategies: a systematic review. Implement Sci. 2019;14(1):57. PubMed ID: 31171004 doi:10.1186/s13012-019-0910-6
- 23.↑
McKay H, Nettlefold L, Bauman A, et al. Implementation of a co-designed physical activity program for older adults: positive impact when delivered at scale. BMC Public Health. 2018;18(1):1289. PubMed ID: 30470209 doi:10.1186/s12889-018-6210-2
- 24.
McKay HA, Sims-Gould J, Nettlefold L, Hoy CL, Bauman AE. Implementing and evaluating an older adult physical activity model at scale: framework for action. TJACSM. 2017;2(2):10–19. doi:10.1249/TJX.0000000000000026
- 25.↑
McKay HA, Mackey DC, Gray SM, et al. Translational formative evaluation before scale-up of a physical activity intervention for older men. TJACSM. 2019;4(14):106–113. doi:10.1249/TJX.0000000000000090
- 26.↑
Sims-Gould J, McKay HA, Hoy CL, et al. Factors that influence implementation at scale of a community-based health promotion intervention for older adults. BMC Public Health. 2019;19(1):1619. PubMed ID: 31795995 doi:10.1186/s12889-019-7984-6
- 27.↑
Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50(3):217–226. PubMed ID: 22310560 doi:10.1097/MLR.0b013e3182408812
- 28.↑
Canadian Society for Exercise Physiology. The physical activity readiness questionnaire for everyone. 2012. https://store.csep.ca/pages/getactivequestionnaire. Accessed April 18, 2021.
- 29.↑
Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–483. PubMed ID: 1593914
- 30.↑
Eriksson I, Unden AL, Elofsson S. Self-rated health. Comparisons between three different measures. Results from a population study. Int J Epidemiol. 2001;30(2):326–333. PubMed ID: 11369738 doi:10.1093/ije/30.2.326
- 31.↑
Milton K, Bull FC, Bauman A. Reliability and validity testing of a single-item physical activity measure. Br J Sports Med. 2011;45(3):203–208. PubMed ID: 20484314 doi:10.1136/bjsm.2009.068395
- 32.↑
Milton K, Clemes S, Bull F. Can a single question provide an accurate measure of physical activity? Br J Sports Med. 2013;47(1):44–48. PubMed ID: 22522584 doi:10.1136/bjsports-2011-090899
- 33.↑
Simonsick EM, Newman AB, Visser M, et al. Mobility limitation in self-described well-functioning older adults: importance of endurance walk testing. J Gerontol A Biol Sci Med Sci. 2008;63(8):841–847. PubMed ID: 18772472 doi:10.1093/gerona/63.8.841
- 34.↑
Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A short scale for measuring loneliness in large surveys: results from two population-based studies. Res Aging. 2004;26(6):655–672. PubMed ID: 18504506 doi:10.1177/0164027504268574
- 35.↑
Franke T, Sims-Gould J, Nettlefold L, Ottoni C, McKay HA. Choose to move: a health promoting physical activity intervention can also enhance social connectedness. BMC Public Health. 2021;21:312. PubMed ID: 33549090 doi:10.1186/s12889-021-10363-1
- 36.↑
Vernoff J, Kulka RA, Douvan EAM. Mental Health in America: Patterns of Help-Seeking From 1957 to 1976. New York, NY: Basic Books; 1981.
- 37.↑
Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc. 2001;33(7):1126–1141. PubMed ID: 11445760 doi:10.1097/00005768-200107000-00010
- 38.↑
Guralnik JM, Ferrucci L, Pieper CF, et al. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci. 2000;55(4):M221–M231. PubMed ID: 10811152 doi:10.1093/gerona/55.4.m221
- 39.↑
Powell KE, Paluch AE, Blair SN. Physical activity for health: what kind? How much? How intense? On top of what? Annu Rev Public Health. 2011;32:349–365. PubMed ID: 21128761 doi:10.1146/annurev-publhealth-031210-101151
- 40.↑
Aggio D, Papachristou E, Papacosta O, et al. Trajectories of physical activity from midlife to old age and associations with subsequent cardiovascular disease and all-cause mortality. J Epidemiol Community Health. 2020;74(2):130–136. PubMed ID: 31704805 doi:10.1136/jech-2019-212706
- 41.↑
Chase JD, Phillips LJ, Brown M. Physical activity intervention effects on physical function among community-dwelling older adults: a systematic review and meta-analysis. J Aging Phys Act. 2017;25(1):149–170. PubMed ID: 27620705 doi:10.1123/japa.2016-0040
- 42.↑
Gawel J, Vengrow D, Collins J, Brown S, Buchanan A, Cook C. The short physical performance battery as a predictor for long term disability or institutionalization in the community dwelling population aged 65 years old or older. Phys Ther Rev. 2013;17(1):37–44. PubMed ID doi:10.1179/1743288x11y.0000000050
- 43.↑
Perissinotto CM, Stijacic Cenzer I, Covinsky KE. Loneliness in older persons: a predictor of functional decline and death. Arch Intern Med. 2012;172(14):1078–1083. PubMed ID: 22710744 doi:10.1001/archinternmed.2012.1993
- 44.↑
Feeney BC, Collins NL. A new look at social support: a theoretical perspective on thriving through relationships. Pers Soc Psychol Rev. 2015;19(2):113–147. PubMed ID: 25125368 doi:10.1177/1088868314544222
- 45.↑
Eng PM, Rimm EB, Fitzmaurice G, Kawachi I. Social ties and change in social ties in relation to subsequent total and cause-specific mortality and coronary heart disease incidence in men. Am J Epidemiol. 2002;155(8):700–709. PubMed ID: 11943687 doi:10.1093/aje/155.8.700
- 46.↑
Fratiglioni L, Paillard-Borg S, Winblad B. An active and socially integrated lifestyle in late life might protect against dementia. Lancet Neurol. 2004;3(6):343–353. PubMed ID: 15157849 doi:10.1016/S1474-4422(04)00767-7
- 47.↑
Sims-Gould J, Franke T, Lusina-Furst S, McKay HA. Community health promotion programs for older adults: what helps and hinders implementation. Health Sci Rep. 2020;3(1):e144. PubMed ID: 32166190 doi:10.1002/hsr2.144
- 48.↑
Gray SM, McKay HA, Hoy CL, et al. Getting ready for scale-up of an effective older adult physical activity program: characterizing the adaptation process. Prev Sci. 2020;21(3):355–365. PubMed ID: 31916183 doi:10.1007/s11121-019-01085-3
- 49.↑
Hobbs N, Godfrey A, Lara J, et al. Are behavioral interventions effective in increasing physical activity at 12 to 36 months in adults aged 55 to 70 years? A systematic review and meta-analysis. BMC Med. 2013;11:75. PubMed ID: 23506544 doi:10.1186/1741-7015-11-75
- 50.↑
Milat AJ, King L, Bauman AE, Redman S. The concept of scalability: increasing the scale and potential adoption of health promotion interventions into policy and practice. Health Promot Int. 2013;28(3):285–298. PubMed ID: 22241853 doi:10.1093/heapro/dar097
- 51.↑
Henderson RM, Miller ME, Fielding RA, et al. Maintenance of physical function 1 year after exercise intervention in at-risk older adults: follow-up from the LIFE study. J Gerontol A Biol Sci Med Sci. 2018;73(5):688–694. PubMed ID: 29490012 doi:10.1093/gerona/glx231
- 52.↑
Cudjoe TKM, Roth DL, Szanton SL, Wolff JL, Boyd CM, Thorpe RJ. The epidemiology of social isolation: national health and aging trends study. J Gerontol B Psychol Sci Soc Sci. 2020;75(1):107–113. PubMed ID: 29590462 doi:10.1093/geronb/gby037
- 53.↑
Milanovic Z, Pantelic S, Trajkovic N, Sporis G, Kostic R, James N. Age-related decrease in physical activity and functional fitness among elderly men and women. Clin Interv Aging. 2013;8:549–556. PubMed ID: 23723694 doi:10.2147/CIA.S44112
- 54.↑
Muller-Riemenschneider F, Reinhold T, Nocon M, Willich SN. Long-term effectiveness of interventions promoting physical activity: a systematic review. Prev Med. 2008;47(4):354–368. PubMed ID: 18675845 doi:10.1016/j.ypmed.2008.07.006
- 55.↑
Yamey G. Scaling up global health interventions: a proposed framework for success. PLoS Med. 2011;8(6):e1001049. PubMed ID: 21738450 doi:10.1371/journal.pmed.1001049
- 56.↑
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2008;42(2):377–381. PubMed ID: PMC2700030 doi:10.1016/j.jbi.2008.08.010
