https://orcid.org/0000-0002-0834-986X
Figures
Abstract
Background
Aging is the primary risk factor for sarcopenia and mobility limitations. Exercise reduces these risks, but older adults have low levels of participation in physical activity and exercise. We investigated the preliminary effectiveness of a live, online exercise program on community-dwelling older adults’ physical activity levels.
Methods
A mixed-method pilot randomized controlled trial was conducted according to CONSORT 2010 statement: extension for pilot and feasibility trials. Sedentary older adults (65–80 years) were randomly assigned to the online exercise intervention (ACTIVE) or a waitlist control (CON) group. Outcomes were measured pre-randomization and following the 8-week intervention for ACTIVE and CON and two months following the end of the intervention for the ACTIVE group. Outcomes included habitual physical activity levels, depression, anxiety, loneliness, life-space mobility, nutrition risk, and feasibility. All participants were invited to participate post-intervention in individual semi-structured qualitative interviews. Reporting of the qualitative research followed the checklist for the Consolidated Criteria for Reporting research.
Results
Seventeen older adults (71% women) were allocated to ACTIVE group, while 15 were allocated to CON group (87% women). Following the intervention, participants in the ACTIVE group reported reduced symptoms of depression (ACTIVE: pre = 4.2 ± 2.5; post = 2.2 ± 1.9; CON: pre = 3.5 ± 2.1, post = 3.5 ± 2.1; p <0.001) and improved life-space mobility (ACTIVE: pre = 62.4 ± 14.7; post = 71.8 ± 16.0; CON: pre = 65.1 ± 19.0, post = 63.6 ± 22.0; p = 0.003) compared to waitlist control participants. The ACTIVE group had good adherence (97%) and acceptability (98%). Twenty-two participants participated in qualitative interviews. Five themes were identified, including (1) Feasibility of the online exercise program; (2) Perceived health benefits and improvements; (3) Registered Kinesiologists and Physiotherapists contributed to perceived safety; (4) Social connectivity associated with synchronous/live delivery; and (5) Growing old gracefully and preventing disability.
Citation: Coletta G, Noguchi KS, Beaudoin KD, McQuarrie A, Tang A, Griffin M, et al. (2024) A live online exercise program for older adults improves depression and life-space mobility: A mixed-methods pilot randomized controlled trial. PLoS ONE 19(11): e0312992. https://doi.org/10.1371/journal.pone.0312992
Editor: Heather Macdonald, UBC: The University of British Columbia, CANADA
Received: June 23, 2024; Accepted: October 11, 2024; Published: November 11, 2024
Copyright: © 2024 Coletta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: This work was supported by the Labarge Centre for Mobility in Aging within the McMaster Institute for Research on Aging Catalyst Grant (grant number: N/A, URL: https://mira.mcmaster.ca/research-centres/labarge-centre-for-mobility-in-aging/) to SMP. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: SMP reports grants or research contracts from the US National Dairy Council, Canadian Institutes for Health Research, Dairy Farmers of Canada, Roquette Freres, Ontario Centre of Innovation, Nestle Health Sciences, Myos, National Science and Engineering Research Council and the US NIH during the conduct of the study; personal fees from Nestle Health Sciences, non-financial support from Enhanced Recovery, outside the submitted work. SMP has patents licensed to Exerkine but reports no financial gains from patents or related work. This does not alter our adherence to PLOS ONE policies on sharing data and materials
Introduction
Age is a primary risk factor for developing chronic diseases and disability, including sarcopenia, frailty, and mobility limitations. Age-related diseases increase the risk of falls and hospitalization and diminish the quality of life for older adults [1,2]. Short periods of inactivity and increased time at home alone, imposed by surgery, illness, or public health mandates during viral pandemics, exacerbate the rate at which these age-related conditions progress [3,4]. Subsequently, there is an increased risk of developing secondary health conditions, including declines in mental health [5,6], physical health, and mobility [7–9], and increased risk of social isolation [3,5,7].
Physical activity (PA) plays an important role in offsetting or delaying age-related declines in functional capacity, quality of life, disability, and mortality [10–13]. Exercise and PA are effective in alleviating declines in strength and mobility [11,14,15], reducing anxiety [13] and depression [16], and preventing cognitive decline [10,11]. Critically, exercise-based intervention trials have been shown to reduce feelings of social isolation and loneliness [17,18], providing encouraging results, particularly given the strong association between lower levels of exercise and PA and the incidence of social isolation and loneliness [19]. However, older adults have described numerous barriers to participating in PA and exercise, including lack of access to places to exercise, feeling too anxious to be physically active, and requiring a large time commitment to travel to and from the exercise facility [20–22]. Implementing interventions utilizing online resources delivered by qualified exercise-trained professionals may be a viable service-delivery option versus traditional in-person exercise interventions [3]. Importantly, older adults do not prefer tools such as pre-recorded videos, which do not create a sense of social connectivity [7]. Thus, we proposed that employing a free access online meeting application (Zoom) to deliver live exercise classes led by qualified instructors and tailored to the needs of older persons would address physical inactivity in older persons [23].
The primary objective of this pilot randomized controlled trial (RCT) was to determine the preliminary effectiveness of a live online exercise program from qualified instructors on older adults’ levels of PA compared to a waitlist control group. The secondary objectives were to examine the preliminary effectiveness of the online exercise program on older adults’ mental health, mobility, and nutrition and the program’s feasibility, as well as determine if effects were maintained during the 2-month follow-up. We hypothesized that PA levels in individuals participating in the online exercise program would improve. We also hypothesized that the online exercise program may improve symptoms of mental health, life-space mobility, and nutrition from pre-to-post intervention and be maintained during the 2-month follow-up. We hypothesized that our live online exercise program would have good acceptability and adherence.
Materials and methods
Study design
This pilot convergent parallel mixed-methods RCT was guided by the CONSORT 2010 statement: extension for pilot and feasibility trials [24,25] (S1 File). The RCT compared community-dwelling older adults participating in a live online exercise program (ACTIVE) delivered on Zoom to a waitlist control group (CON). The intervention was carried out in three waves by Registered Kinesiologists and Physiotherapists from the Physical Activity Centre of Excellence at McMaster University in Ontario, Canada. Participants in the ACTIVE and CON groups underwent data collection (accelerometry and questionnaires) pre- and post-intervention. The three waves of the live online exercise intervention were delivered for the ACTIVE group between February 2021 and January 2022. Wave 1 classes occurred between February 2021 to April 2021 (n = 8), Wave 2 classes occurred between April 2021 to June 2021 (n = 4), and Wave 3 classes occurred between November 2021 and January 2022 (n = 5). During the 8 weeks that the ACTIVE group performed our online exercise intervention, the CON group were instructed to carry out their regular daily activity. Immediately following completion of the CON condition, participants in this group were offered the opportunity to partake in our live online exercise program for their respective waves (Wave 1, n = 8; Wave 2, n = 3; Wave 3, n = 5). The ACTIVE group completed follow-up data collection 2-months after completing the intervention. The 2-month follow-up was selected as evidence suggests that changes in steps can be seen ≤4 months following the completion of a study [26]. Feasibility measures (adherence and acceptability) were collected at each Zoom class using the poll feature. One month after completing the online exercise program, participants were invited to participate in the qualitative interviews. The duration of the study was from November 2020 to May 2022 and included the global COVID-19 pandemic (https://www.cihi.ca/en/canadian-covid-19-intervention-timeline), which had periods during which Public Health advised limiting close in-person interactions (stay home/lockdown) potentially affecting older persons mobility. The study was registered at clinicaltrials.gov (NCT04627493) and approved by the Hamilton Integrated Research Ethics Board (protocol #11429).
Participants
Older community-dwelling women and men between the ages of 65 and 80 were recruited from Hamilton, Ontario, and the surrounding area. The upper age limit of 80 was chosen as mobility tends to decline far more quickly [27]; from a safety perspective, we wanted to limit the risks of our pilot program. Participants were recruited through newsletters, social media, and the local newspaper (Coffee News) between November 10th, 2020, and November 30th, 2021, which was the period during the global COVID-19 pandemic in which much of Hamilton, Ontario, was either completely closed or highly restricted. Potential participants were screened over videoconference (Zoom Video Communications Inc., 2016) to ensure they met the eligibility criteria, had access to the internet at home via a personal smartphone, tablet, or computer, and could safely participate based on the Canadian Society for Exercise Physiology Get Active Questionnaire (https://csep.ca/2021/01/20/pre-screening-for-physical-activity/). Exclusion criteria included using a walker, cane, or assistive walking device; a history of neuromuscular conditions or muscle wasting diseases; and baseline participation in ≥150 minutes of moderate-to-vigorous PA per week. To be eligible for the qualitative portion of the study, participants needed to complete our online exercise program. Before providing a written informed consent form, all potential participants were informed of the study purpose, experimental procedures, and possible risks and provided the opportunity to ask questions.
Intervention
Participants underwent an 8-week intervention consisting of thrice-weekly 60-minute online exercise classes (totalling 24 exercise classes) delivered online via Zoom. The blended group-based classes with 4–8 participants began with a 5-minute warm-up, 50 minutes of progressive strength, aerobic, and balance training focusing on functional movements, and a 5-minute cool-down. Strength exercises focused on lower (squats, hip abduction, hip extension, hamstring curls, front lunge, calf raises) and upper (biceps and triceps, shoulder press, front raise, side raise, alternating front and back fly) body exercises. Body weight was used for the first week, and household objects (e.g., water bottles, soup cans, pasta sauce) were introduced in subsequent weeks to increase the load. Participants were instructed to complete two sets of 8 repetitions, progressing to 12 repetitions per strength exercise. Aerobic exercises (marching, side steps, butt kicks, clock stepping, modified jumping jacks) were completed for 30 seconds for 2–3 sets. Participants progressed to 12 minutes of aerobic exercises by week 8. Balance exercises (side-by-side, semi-tandem, tandem, and single leg) were held for 15 seconds, and progressions included weight shifting, eyes closed, and dynamic balance. All exercises could be modified to be performed at two difficulty levels: basic and intermediate. The physiotherapist (n = 1) and registered kinesiologists (n = 3) trained to work with older adults supervised the classes and adjusted exercise intensity weekly to meet the participants’ abilities. A research team member moderated each class to ensure participant safety and assist with any technological difficulties. All training sessions were completed in the participants’ location of choice (e.g., participants’ homes) and offered through the Physical Activity Centre of Excellence, a community gym for older adults at McMaster University.
Outcome measures
All data were collected virtually. Demographic information, including gender, age, height, weight, race, highest level of education, marital status, living arrangement, and physical activity participation prior to the COVID pandemic, was collected at baseline. A scale and measuring tape were delivered to participants’ homes to collect anthropometric measures (height, weight). Accelerometers were dropped off at participants’ homes to wear for seven consecutive days and retrieved following this period. Questionnaires were administered online using LimeSurvey (LimeSurvey: An Open Source survey tool/LimeSurvey GmbH, Hamburg, Germany. URL http://www.limesurvey.org) pre-and-post-intervention for both the ACTIVE and CON and at a 2-month follow-up for the ACTIVE group. The individual qualitative post-intervention interviews were conducted via Zoom by the study lead (G.C.).
Quantitative data collection
Physical activity.
Habitual PA levels were the primary outcomes and were assessed using the armband BodyMedia Sensewear Pro II accelerometer (BodyMedia, Pittsburgh, PA, USA). Participants were instructed to wear the armband at all times, including while sleeping, and remove it only for brief periods for bathing or water activities. The armband was worn over the left tricep muscle, and data were sampled in 60-second epochs from a heat flux sensor, a galvanic skin response sensor, a skin temperature sensor, a near-body temperature sensor, and a bi-axial accelerometer. Participant characteristics, including sex, age, height, weight, smoking status, and dominant hand, were used with accelerometer data to estimate daily steps and activity energy expenditure. The Sensewear armband accelerometer has been validated in free-living older adults [28]. The data was collected for seven consecutive days pre-and-post intervention for both the ACTIVE and CON and at a 2-month follow-up for the ACTIVE group.
Mental health.
Depression, anxiety, and loneliness were included as secondary outcomes. The Geriatric Depression Scale Short Form (GDS-SF) assesses depressive symptoms using 15 questions regarding how participants felt over the past week (yes/no) [29]. Scores of >5 suggest depressive symptoms; >10 indicate moderate to severe depressive symptoms. The GDS-SF is a validated instrument for older adults [30]. The Geriatric Anxiety Inventory-Short Form (GAI-SF) measured anxiety symptoms using 5 items (e.g., “I often feel nervous” and “I worry a lot of the time”) (yes/no). Scores between 0–8 reflect an absence of clinically significant anxiety; ≥9 reflects the presence of clinically significant anxiety [31]. The GAI-SF has good internal consistency and convergent and divergent validity for older (60–88 years) community-dwelling adults and is highly correlated with the original Geriatric Anxiety Inventory [32]. The 11-item Revised University of California Los Angeles loneliness scale (R-UCLA) measured loneliness using feeling isolated and available social connections [33]. The 11-item R-UCLA has good factorability and internal reliability in adults ≥65 years of age [33]. Scores range from 11 to 33, with higher scores indicating greater loneliness [33].
Life-space mobility.
The University of Alabama Life Space Assessment, UA-LSA, was used to assess participants’ life-space mobility during the month preceding the assessment [34] and has been validated in community-dwelling older adults [35,36]. The scores range from 0 (totally bed-bound) to 120 (travelled out of town daily without assistance).
Nutrition risk.
The Seniors in the Community Risk Evaluation for Eating and Nutrition (SCREENII) is a valid and reliable tool to identify the risk for impaired nutritional states in community-living older adults [37]. The scoring of this tool ranges from 0 to 64; a score less than 50 is considered high nutrition risk.
Feasibility.
Adherence was measured using the percentage of classes attended, and good adherence was defined a priori as >75% attendance (i.e., ≥19/24 sessions). Acceptability was measured using participant satisfaction using a 6-point Likert rating scale including: 1) very dissatisfied, 2) dissatisfied, 3) somewhat dissatisfied, 4) somewhat satisfied, 5) satisfied, and 6) very satisfied. Satisfaction was defined a priori as >60% of all ratings were satisfactory using a Zoom poll at the end of each call.
Qualitative data collection
All participants (ACTIVE and waitlist CON) who completed our 8-week live online exercise program were invited via email to participate in an optional one-on-one 30-minute qualitative interview, regardless of group allocation. Semi-structured, open-ended 1:1 interviews were conducted and audio recorded via Zoom by the trained study lead (G.C., female) for a sub-sample of participants [38]. A qualitative interview guide (S1 Table) was developed with a qualitative methodology expert (M.G.). Questions were not provided or piloted with participants prior to the interview. The interviewer had a Bachelor of Science and was a Ph.D. student at the time of the interviews. There were no established relationships before the study commencement, and participants were aware that this research topic was of interest to the interviewer and part of the interviewer’s Ph.D. dissertation. Participants were probed about their experiences and perceptions of exercise and our online exercise program [38]. Transcripts were not returned to participants. Reporting of the qualitative research followed the checklist for the Consolidated Criteria for Reporting research (COREQ) [39].
Sample size
A convenience sample size of 32 participants is aligned with previous online exercise pilot studies with sample sizes ranging from 10–44 [40,41]. For the qualitative interviews, we aimed to conduct between 20–24 interviews with a purposeful subsample of interested participants from the pilot RCT [42].
Randomization, allocation concealment, and blinding
Eligible participants were randomized (block sizes from 4–8) to either the intervention group (ACTIVE) or the waitlist control group (CON). An investigator (S.M.P) generated the random allocation sequence using Research Randomizer (https://www.randomizer.org/). Participant group allocation was only provided to the study lead once baseline data collection was completed and immediately before the online exercise program started. Allocation concealment was attained in this study by ensuring a password-protected randomization schedule was accessed only by the investigator responsible for randomization and only at the time of randomization for each participant. G.C. was responsible for enrolling participants and advising them on group allocation. Given the nature of the study, it was impossible to blind the participants or investigators to the intervention.
Analysis
Quantitative.
Descriptive statistics were calculated for demographic information and expressed as means ± standard deviation (SD) for continuous variables and counts (percent) for categorical variables. Pre-to-post-intervention changes in quantitative outcome measures were analyzed using a two-way repeated measures ANOVA once all data collection had been completed. The normality of the dependent variables and residuals was first assessed by visual inspection, followed by the Shapiro-Wilk test. If the assumptions of the ANOVAs were violated, data was log 10 transformed. A time comparison using a two-tailed paired t-test was used to analyze changes in quantitative outcome measures post-intervention to follow-up for the ACTIVE group. Missing data were deemed missing completely at random and addressed by multiple imputations [43]. The final intention-to-treat analysis included all randomized participants who met inclusion/exclusion criteria. A p-value <0.05 was considered statistically significant. Analyses were performed using IBM SPSS Statistics for Mac, version 28.0.
Qualitative.
Semi-structured interviews were thematically analyzed using the computer software Dedoose Version 9.0.17 (Los Angeles, CA, United States) [44]. The first two transcripts were coded independently by two coders (G.C. and K.S.N.), and initial patterns and themes were discussed to inform the preliminary coding book [24]. The coding book was shared and refined with input from a qualitative expert. The coders reviewed the subsequent transcripts using the coding book and iteratively revised them to reflect new concepts, meeting regularly to ensure consistency between interpretations. Themes and subthemes were inductively developed and refined with the research team. A third researcher was available if consensus could not be reached, but it was not required. Participants did not provide feedback on the findings.
Results
Participants’ characteristics
Thirty-three older women and men participated in this study. Participant characteristics are presented in Table 1. There were no differences between groups for any variable. One participant in the ACTIVE group withdrew from the intervention due to an injury not attributed to the intervention. One participant in the CON group exceeded the 150 moderate-to-vigorous PA per week at baseline and, therefore, did not meet the eligibility criteria and was removed from the analysis. Missing data was deemed missing completely at random. Linear regression was used to impute missing data; thus, analyses for the ACTIVE and CON groups are n = 17 and n = 15, respectively (Fig 1).
ITT = Intention to treat.
Habitual physical activity levels
There were no differences between groups for daily steps and daily active energy expenditure measured by the accelerometer following the intervention compared to the CON (Table 2). However, a main effect of time was observed from pre-to-post intervention for daily steps and active energy expenditure (p < 0.05). The data were not normally distributed for daily active energy expenditure, and were transformed. The log 10 transformation did not change the interpretation; therefore, the original data is presented in Table 2. All ACTIVE and CON group participants complied with the full 7-day protocol pre-intervention, and 28 participants complied post-intervention. At the two-month follow-up, the ACTIVE group showed no significant differences from post-intervention (p > 0.05; Table 3). 14 participants complied with the full 7-day protocol in the ACTIVE group and wore the accelerometer for 85.8 ± 0.2% of the time.
Mental health
We observed an interaction (p = 0.012) for the Geriatric Depression Scale where the ACTIVE group decreased from pre-to-post intervention (Table 4). There were no significant between or within-group differences for symptoms of anxiety and loneliness (Table 4). The data were not normally distributed for GAI-SF, and were transformed. The log 10 transformation did not change the interpretation; therefore, the original data is presented in Table 4. Most participants in the ACTIVE and CON groups had scores less than 5 (absence of clinically significant anxiety) on the GAI-SF. At the two-month follow-up, the ACTIVE group showed no significant differences from post-intervention in depressive symptoms, anxiety symptoms, and loneliness (p > 0.05; Table 3).
Life-space mobility
We observed an interaction (p = 0.014) for life-space mobility where the ACTIVE group increased from pre-to-post intervention (Table 4). At the two-month follow-up, the ACTIVE group maintained the difference from post-intervention on the life-space assessment (p > 0.05; Table 3).
Nutrition risk
There were no between-group differences in nutrition risk (Table 4); scores lower than 50 indicated greater risk. However, a main effect of time was observed from pre-to-post intervention (p = 0.014). Pre-intervention, participants in both the ACTIVE (n = 14; 82%) and CON (n = 12; 80%) groups had scores below 50 at baseline, indicating that our participants were at high nutrition risk at study entry. At the two-month follow-up, the ACTIVE group showed no significant differences in the SCREENII (p > 0.05; Table 3).
Feasibility
Attendance rates were 97% in the ACTIVE group, ranging from 22/24 to 24/24 classes. The two most common reasons for non-attendance were illness (n = 1 missed session in 4 participants) and health appointments (n = 1 missed session in 3 participants). No adverse health events were reported throughout the study. Overall, participants reported being either satisfied or very satisfied with the intervention 98% of the time. Four participants reported being ‘somewhat satisfied’ between 1–4 times. Both adherence and acceptability were feasible based on the a priori definitions.
Qualitative
A sub-sample of participants who completed our online exercise program (N = 22; ACTIVE, n = 12; and CON, n = 10) participated in 30-minute interviews. Five overarching themes and eight sub-themes were identified related to perceptions, experiences, and feasibility of the program. These themes included the feasibility of the online exercise program, perceived health benefits and improvements, Registered Kinesiologists and Physiotherapists contributed to perceived safety, social connectivity associated with synchronous/live delivery, and growing old gracefully and preventing disability. Illustrative quotes for themes and sub-themes are presented in Table 5.
Feasibility of the online exercise program.
Qualitative data reinforced our quantitative findings, conveying that the program had good acceptability and feasibility. Sub-themes were identified: 1) Acceptability of instructors, 2) Acceptability of exercises, and 3) Acceptability of time/location. Participants highlighted their satisfaction with the instructors and their age-appropriate exercise modifications.
Perceived health benefits and improvements.
Participants described perceived health benefits and improvements after completing the online exercise program. Sub-themes included: 1) Improved function, 2) Improved chronic disease management, and 3) Improved energy and overall health. The qualitative data contradicted our quantitative findings; participants described walking more, feeling better physically and mentally, and perceived benefits in chronic disease management.
Registered Kinesiologists and Physiotherapists contributed to the perceived safety of the intervention.
Participants perceived the program as safe, attributing it to the Registered Kinesiologists and Physiotherapists who delivered it. A few participants expressed the importance of personalized training to ensure proper form and reduce the possibility of injury. The qualitative findings reinforce program feasibility as the instructors contribute to the program’s acceptability.
Social connectivity associated with synchronous/live delivery.
Participants described social connectivity associated with synchronous/live delivery was identified as a theme with positive and negative aspects. The sub-themes include: 1) Group-based exercise program fosters connections, and 2) Socializing is not an important aspect when exercising. Most participants found that group-based exercise fostered connection, whereas a few described socializing as “not an important aspect of exercise.”
Growing old gracefully and preventing disability.
Many participants described the desire to grow old gracefully ‐ maintain mobility and health while participating in meaningful activities ‐ and prevent disability. The potential loss of independence and fear of disability with aging motivates participation in the program. Community-dwelling older adults who participated were motivated before the start of the program and actively sought out the program.
Discussion
We investigated the preliminary effectiveness and feasibility of an online exercise program for community-dwelling older adults. The program did not affect participants’ habitual PA levels but reduced depressive symptoms, improved life-space mobility, and had excellent adherence and acceptability.
Habitual PA did not change pre- to post-intervention or at the 2-month follow-up for the ACTIVE group. Daily steps and daily active energy expenditure may not have changed due to the decreased level of PA in older adults during the quarantine period of COVID-19, which was in place while the study was implemented [45]. However, participants perceived improved function (e.g., walking, strength, gardening), chronic disease management (e.g., reduced blood pressure, vertigo), and improved energy and overall health. Participants stated they “felt better” and “had more energy”.
The between-group changes in the GDS-SF showed the preliminary mental health benefits of the program. Participants in the ACTIVE group had reduced symptoms of depression compared to the CON group post-intervention, which were maintained at follow-up. Pre-intervention, 58% of our participants scored below five on the GDS-SF, suggesting no depressive symptoms. Strong evidence suggests the benefits of aerobic and resistance exercise on mental health, particularly depression [16]. Evidence also suggests the benefits of exercise in improving anxiety and loneliness [19,46]; however, there were no between-group differences in these outcomes. Most participants scored below five on the GAI-SF at pre-intervention, indicating the absence of clinically significant anxiety, which may have resulted in a floor effect. Similarly, most participants scored low on the R-UCLA loneliness scale pre-intervention. Interestingly, participants qualitatively described the importance of social connectivity and their desire to connect with other participants in the group. For example, two participants desired continued connection with the group following the end of the program (i.e., exchanging email or phone numbers). In contrast, a few participants preferred to refrain from engaging in socialization, as they did not view this as an important aspect of exercise and felt their social needs were already met.
Our results from a life space perspective are consistent with pre-post exercise intervention (stretching, muscle strength, balance, and walking) for older women [47], in which these authors reported improved life-space mobility scores post-intervention. Our data showed that the intervention improved life-space mobility in the ACTIVE group. The online exercise program may have emboldened participants to navigate spaces outside their homes, neighbourhoods, or towns. Higher scores on life-space mobility are associated with higher quality of life, improved social participation, reduced cognitive impairment, improved physical health, and decreased nutritional risk [48,49]. However, participants’ SCREENII scores were categorized as high nutrition risk. This score is associated with poor health outcomes for older adults (e.g., increased risk of hospitalization and mortality) [50]. Future research should focus on multi-component interventions.
Our program was feasible, with 97% of classes attended and 98% of participants were either satisfied or very satisfied with each class. Online exercise programs are novel and emerging modalities for engaging community-dwelling older adults in exercise. There is evidence from different patient populations using online exercise to improve important outcomes, including falls, balance, and health conditions. However, many programs focus on exergaming [51] or virtual gyms [52] and do not include live, real-time instructors to support individualized adaptations. Participants described enjoying the social connectivity associated with synchronous/live delivery. Overall, the live instructors, the routine of the group-based online program, and accountability facilitated engagement and high satisfaction, resulting in high program adherence. Online exercise programs are viable service-delivery options, particularly when in-person programming is unavailable due to physical distance, space limitations, and/or public health measures encouraging reduced mobility to slow viral spread. Future work should focus on synchronous online resources to engage older adults in exercise programs.
The qualitative interviews highlighted participants’ desire to grow old gracefully and prevent disability. Some participants described the fear of disability from aging as a motivator to exercise. Others described their desire to continue to play with grandchildren, maintain their activities of daily living, and become healthier as motivators. These findings are consistent with previous studies investigating older adults’ influences, motivations, and barriers to PA engagement [53,54].
There are several limitations with our study; however, primarily, we acknowledge the small sample size. The study was a pilot and, therefore, underpowered to determine if there was an interaction for our primary outcome. However, we noted that participants reported perceived health benefits and improved physical function post-intervention. Another limitation of the study includes a lack of blinding for our assessors and participants to group allocation. Our study only included English-speaking individuals with internet access at home with a tablet, computer, or phone. Future studies should attempt to include marginalized populations to improve generalizability with different language options, including subtitles.
Conclusions
Our online exercise program reduced symptoms of depression, improved life-space mobility, and demonstrated good feasibility and perceived health benefits. We did not see an effect of the intervention in the ACTIVE group on accelerometry-derived outcomes. Nonetheless, following participation in the online exercise program, participants perceived physical and mental health benefits. Given the feasibility of the methods and perceived benefits of the intervention, our online exercise program has the potential to support synchronous exercise programs at home. The findings will inform a larger RCT utilizing synchronous online exercise programming delivered by healthcare professionals with modifications to the protocol regarding progressions, longer training periods, and a larger sample size. Future work will focus on the effectiveness of group-based synchronous exercise programs on functional assessments.
Supporting information
S1 Table. Semi-structured interview questions.
https://doi.org/10.1371/journal.pone.0312992.s001
(DOCX)
S1 File. CONSORT pilot or feasibility trial checklist.
https://doi.org/10.1371/journal.pone.0312992.s002
(PDF)
Acknowledgments
We want to acknowledge and thank the Physical Activity Centre of Excellence (PACE) Registered Kinesiologists and Physiotherapists for their assistance in designing and delivering our online exercise program.
References
- 1. Gilmour H, Ramage-Morin PL. Association of frailty and pre-frailty with increased risk of mortality among older Canadians. Health Rep. 2021;32(4):15–26. pmid:33881275
- 2. Yeung SSY, Reijnierse EM, Pham VK, Trappenburg MC, Lim WK, Meskers CGM, et al. Sarcopenia and its association with falls and fractures in older adults: A systematic review and meta-analysis. J Cachexia Sarcopenia Muscle. 2019;10(3):485–500. pmid:30993881
- 3. Berg-Weger M, Morley JE. Editorial: Loneliness and Social Isolation in Older Adults during the COVID-19 Pandemic: Implications for Gerontological Social Work. J Nutr Health Aging. 2020;24(5):456–8. pmid:32346678
- 4. Coletta G, Phillips SM. An elusive consensus definition of sarcopenia impedes research and clinical treatment: A narrative review. Ageing Res Rev. 2023;86:101883. pmid:36792012
- 5. Patel SS, Clark-Ginsberg A. Incorporating Issues of Elderly Loneliness into the Coronavirus Disease-2019 Public Health Response. Disaster Med Public Health Prep. 2020:1–2. pmid:32379016
- 6. Losada-Baltar A, Jimenez-Gonzalo L, Gallego-Alberto L, Pedroso-Chaparro MDS, Fernandes-Pires J, Marquez-Gonzalez M. "We Are Staying at Home." Association of Self-perceptions of Aging, Personal and Family Resources, and Loneliness With Psychological Distress During the Lock-Down Period of COVID-19. J Gerontol B Psychol Sci Soc Sci. 2021;76(2):e10–e6. pmid:32282920
- 7. Goethals L, Barth N, Guyot J, Hupin D, Celarier T, Bongue B. Impact of Home Quarantine on Physical Activity Among Older Adults Living at Home During the COVID-19 Pandemic: Qualitative Interview Study. JMIR Aging. 2020;3(1):e19007. pmid:32356777
- 8. McGlory C, von Allmen MT, Stokes T, Morton RW, Hector AJ, Lago BA, et al. Failed Recovery of Glycemic Control and Myofibrillar Protein Synthesis With 2 wk of Physical Inactivity in Overweight, Prediabetic Older Adults. J Gerontol A Biol Sci Med Sci. 2018;73(8):1070–7. pmid:29095970
- 9. Oikawa SY, Callahan DM, McGlory C, Toth MJ, Phillips SM. Maintenance of skeletal muscle function following reduced daily physical activity in healthy older adults: a pilot trial. Appl Physiol Nutr Metab. 2019;44(10):1052–6. pmid:30794431
- 10. Daskalopoulou C, Stubbs B, Kralj C, Koukounari A, Prince M, Prina AM. Physical activity and healthy ageing: A systematic review and meta-analysis of longitudinal cohort studies. Ageing Res Rev. 2017;38:6–17. pmid:28648951
- 11. Falck RS, Davis JC, Best JR, Crockett RA, Liu-Ambrose T. Impact of exercise training on physical and cognitive function among older adults: a systematic review and meta-analysis. Neurobiol Aging. 2019;79:119–30. pmid:31051329
- 12. Steffl M, Bohannon RW, Sontakova L, Tufano JJ, Shiells K, Holmerova I. Relationship between sarcopenia and physical activity in older people: a systematic review and meta-analysis. Clin Interv Aging. 2017;12:835–45. pmid:28553092
- 13. Stubbs B, Vancampfort D, Rosenbaum S, Firth J, Cosco T, Veronese N, et al. An examination of the anxiolytic effects of exercise for people with anxiety and stress-related disorders: A meta-analysis. Psychiatry Res. 2017;249:102–8. pmid:28088704
- 14. Hill KD, Hunter SW, Batchelor FA, Cavalheri V, Burton E. Individualized home-based exercise programs for older people to reduce falls and improve physical performance: A systematic review and meta-analysis. Maturitas. 2015;82(1):72–84. pmid:25989701
- 15. Gine-Garriga M, Roque-Figuls M, Coll-Planas L, Sitja-Rabert M, Salva A. Physical exercise interventions for improving performance-based measures of physical function in community-dwelling, frail older adults: a systematic review and meta-analysis. Arch Phys Med Rehabil. 2014;95(4):753–69. pmid:24291597
- 16. Miller KJ, Goncalves-Bradley DC, Areerob P, Hennessy D, Mesagno C, Grace F. Comparative effectiveness of three exercise types to treat clinical depression in older adults: A systematic review and network meta-analysis of randomised controlled trials. Ageing Res Rev. 2020;58:100999. pmid:31837462
- 17. Hwang J, Wang L, Siever J, Medico TD, Jones CA. Loneliness and social isolation among older adults in a community exercise program: a qualitative study. Aging Ment Health. 2019;23(6):736–42. pmid:29543517
- 18. Lindsay-Smith G, O’Sullivan G, Eime R, Harvey J, van Uffelen JGZ. A mixed methods case study exploring the impact of membership of a multi-activity, multicentre community group on social wellbeing of older adults. BMC Geriatr. 2018;18(1):226.
- 19. Schrempft S, Jackowska M, Hamer M, Steptoe A. Associations between social isolation, loneliness, and objective physical activity in older men and women. BMC Public Health. 2019;19(1):74. pmid:30651092
- 20. Miller W, Brown PR. Motivators, Facilitators, and Barriers to Physical Activity in Older Adults: A Qualitative Study. Holistic Nursing Practice. 2017;31(4):216–24. pmid:28609406
- 21. Gray PM, Murphy MH, Gallagher AM, Simpson EE. Motives and Barriers to Physical Activity Among Older Adults of Different Socioeconomic Status. J Aging Phys Act. 2016;24(3):419–29. pmid:26671896
- 22. Wingood M, Peters DM, Gell NM, Brach JS, Bean JF. Physical Activity and Physical Activity Participation Barriers Among Adults 50 Years and Older During the COVID-19 Pandemic. American journal of physical medicine & rehabilitation. 2022;101(9):809–15. pmid:35473919
- 23. de Lima JGR, Abud GF, de Freitas EC, Júnior CRB. Effects of the COVID-19 pandemic on the global health of women aged 50 to 70 years. Experimental Gerontology. 2021:111349.
- 24.
Creswell JW, Clark VLP. Designing and conducting mixed methods research. Thousand Oaks, CA: Sage Publications, Inc; 2017.
- 25. Eldridge SM, Chan CL, Campbell MJ, Bond CM, Hopewell S, Thabane L, et al. CONSORT 2010 statement: extension to randomised pilot and feasibility trials. BMJ. 2016;355:i5239. pmid:27777223
- 26. Chaudhry UAR, Wahlich C, Fortescue R, Cook DG, Knightly R, Harris T. The effects of step-count monitoring interventions on physical activity: systematic review and meta-analysis of community-based randomised controlled trials in adults. Int J Behav Nutr Phys Act. 2020;17(1):129. pmid:33036635
- 27. Rantakokko M, Manty M, Rantanen T. Mobility decline in old age. Exerc Sport Sci Rev. 2013;41(1):19–25. pmid:23038241
- 28. Mackey DC, Manini TM, Schoeller DA, Koster A, Glynn NW, Goodpaster BH, et al. Validation of an armband to measure daily energy expenditure in older adults. J Gerontol A Biol Sci Med Sci. 2011;66(10):1108–13. pmid:21734231
- 29. Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res. 1982;17(1):37–49. pmid:7183759
- 30. Dennis M, Kadri A, Coffey J. Depression in older people in the general hospital: a systematic review of screening instruments. Age Ageing. 2012;41(2):148–54. pmid:22236655
- 31. Byrne GJ, Pachana NA. Development and validation of a short form of the Geriatric Anxiety Inventory—the GAI-SF. Int Psychogeriatr. 2011;23(1):125–31. pmid:20561386
- 32. Johnco C, Knight A, Tadic D, Wuthrich VM. Psychometric properties of the Geriatric Anxiety Inventory (GAI) and its short-form (GAI-SF) in a clinical and non-clinical sample of older adults. Int Psychogeriatr. 2015;27(7):1089–97. pmid:25111285
- 33. Lee J, Cagle JG. Validating the 11-Item Revised University of California Los Angeles Scale to Assess Loneliness Among Older Adults: An Evaluation of Factor Structure and Other Measurement Properties. Am J Geriatr Psychiatry. 2017;25(11):1173–83. pmid:28864097
- 34. Peel C, Baker PS, Roth DL, Brown CJ, Bodner EV, Allman RM. Assessing Mobility in Older Adults: The UAB Study of Aging Life-Space Assessment. Physical Therapy. 2005;85(10):1008–19. pmid:16180950
- 35. Taylor JK, Buchan IE, van der Veer SN. Assessing life-space mobility for a more holistic view on wellbeing in geriatric research and clinical practice. Aging Clin Exp Res. 2019;31(4):439–45. pmid:30078096
- 36. Baker PS, Bodner EV, Allman RM. Measuring life-space mobility in community-dwelling older adults. J Am Geriatr Soc. 2003;51(11):1610–4. pmid:14687391
- 37. Keller HH, Goy R, Kane SL. Validity and reliability of SCREEN II (Seniors in the community: risk evaluation for eating and nutrition, Version II). Eur J Clin Nutr. 2005;59(10):1149–57. pmid:16015256
- 38. Adams WC. Conducting Semi-Structured Interviews. Handbook of Practical Program Evaluation2015. p. 492–505.
- 39. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–57. pmid:17872937
- 40. Nikitina S, Didino D, Baez M, Casati F. Feasibility of Virtual Tablet-Based Group Exercise Among Older Adults in Siberia: Findings From Two Pilot Trials. JMIR Mhealth Uhealth. 2018;6(2):e40. pmid:29487045
- 41. Sinclair Elder JA, Scott SW, Kluge M, Elder LC. CyberEx Internet-Based Group Exercise for Rural Older Adults: A Pilot Study. Activities, Adaptation & Aging. 2016;40(2):107–24.
- 42. Martinez-Mesa J, Gonzalez-Chica DA, Duquia RP, Bonamigo RR, Bastos JL. Sampling: how to select participants in my research study? An Bras Dermatol. 2016;91(3):326–30. pmid:27438200
- 43. Jakobsen JC, Gluud C, Wetterslev J, Winkel P. When and how should multiple imputation be used for handling missing data in randomised clinical trials ‐ a practical guide with flowcharts. BMC medical research methodology. 2017;17(1):162. pmid:29207961
- 44. Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology. 2006;3(2):77–101.
- 45. Oliveira MR, Sudati IP, Konzen VM, de Campos AC, Wibelinger LM, Correa C, et al. Covid-19 and the impact on the physical activity level of elderly people: A systematic review. Exp Gerontol. 2022;159:111675. pmid:34954282
- 46. Gordon BR, McDowell CP, Lyons M, Herring MP. The Effects of Resistance Exercise Training on Anxiety: A Meta-Analysis and Meta-Regression Analysis of Randomized Controlled Trials. Sports Med. 2017;47(12):2521–32. pmid:28819746
- 47. Matsuda K, Ikeda S, Nakahara M, Ikeda T, Okamoto R, Kurosawa K, et al. Factors affecting the coefficient of variation of stride time of the elderly without falling history: a prospective study. J Phys Ther Sci. 2015;27(4):1087–90. pmid:25995563
- 48. Seinsche J, Jansen CP, Roth S, Zijlstra W, Hinrichs T, Giannouli E. Multidimensional interventions to increase life-space mobility in older adults ranging from nursing home residents to community-dwelling: a systematic scoping review. BMC Geriatr. 2023;23(1):412. pmid:37415132
- 49. Kuspinar A, Verschoor CP, Beauchamp MK, Dushoff J, Ma J, Amster E, et al. Modifiable factors related to life-space mobility in community-dwelling older adults: results from the Canadian Longitudinal Study on Aging. BMC Geriatr. 2020;20(1):35. pmid:32005107
- 50. Keller HH, Ostbye T. Nutritional risk and time to death; predictive validity of SCREEN (Seniors in the Community Risk Evaluation for Eating and Nutrition). J Nutr Health Aging. 2003;7(4):274–9. pmid:12917754
- 51. Leutwyler H, Hubbard E, Cooper B. A Group Videogame-Based Physical Activity Program Improves Walking Speed in Older Adults Living With a Serious Mental Illness. Innov Aging. 2022;6(6):igac049. pmid:36452052
- 52. Baez M, Khaghani Far I, Ibarra F, Ferron M, Didino D, Casati F. Effects of online group exercises for older adults on physical, psychological and social wellbeing: a randomized pilot trial. PeerJ. 2017;5:e3150. pmid:28392983
- 53. Hardy S, Grogan S. Preventing Disability through Exercise: Investigating Older Adults’ Influences and Motivations to Engage in Physical Activity. Journal of Health Psychology. 2009;14(7):1036–46. pmid:19786530
- 54. Schutzer KA, Graves BS. Barriers and motivations to exercise in older adults. Preventive medicine. 2004;39(5):1056–61. pmid:15475041