The MIPAM trial – motivational interviewing and physical activity monitoring to enhance the daily level of physical activity among older adults – a randomized controlled trial

Abstract Background One in four older adults in Denmark and almost half of the very old above 75 do not meet the World Health Organization’s recommendations for a minimum of physical activity (PA). A cost-efficient and effective way to increase focus on and motivation for daily walking might be to use Physical Activity Monitors (PAMs) in combination with behavioural change intervention. Thus, the objective of this randomized controlled study was to investigate the effect of Motivational Interviewing (MI) as an add-on intervention to a PAM-based intervention measured in community-dwelling older adults. Methods This two-arm parallel group randomized controlled effectiveness trial compared a 12-weeks PAM-based intervention with additional MI (PAM+MI group) with a PAM-based intervention alone (PAM group). The primary outcome, average daily step count, was analysed with a linear regression model, adjusted for sex and baseline daily step count. Following the intention-to-treat principle, multiple imputation based on baseline step count, sex and age was performed. Results In total, 38 participants were randomized to the PAM intervention and 32 to the PAM+MI intervention arm. During the intervention period, PAM+MI participants walked on average 909 more steps per day than PAM participants, however insignificant (95%CI: − 71; 1889) and reported 2.3 points less on the UCLA Loneliness Scale (95%CI: − 4.5; − 1.24). Conclusion The use of MI, in addition to a PAM-based intervention among older adults in PA promoting interventions hold a potential clinically relevant effect on physical activity and should thus be investigated further with adequately powered RCTs. Trial registration This study was pre-registered in the clinicaltrials.gov database with identifier: NCT03906162.

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The MIPAM trial: a 12-week intervention with motivational interviewing and physical activity monitoring to enhance the daily amount of physical activity in community-dwelling older adults – a study protocol for a randomized controlled trial

BMC Geriatrics ◽

10.1186/s12877-020-01815-1 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Rasmus Tolstrup Larsen ◽

Christoffer Bruun Korfitsen ◽

Carsten Bogh Juhl ◽

Henning Boje Andersen ◽

Jan Christensen ◽

...

Keyword(s):

Public Health ◽

Physical Activity ◽

Older Adults ◽

Motivational Interviewing ◽

Self Efficacy ◽

Community Dwelling ◽

World Health ◽

Secondary Outcome ◽

Randomized Controlled ◽

Physical Activity Monitoring

Abstract Background Physical Activity Monitors (PAMs) have been shown to effectively enhance level of physical activity (PA) in older adults. Motivational interviewing is a person-centred model where participants are guided using self-reflection and counselling, and addresses the behavioural and psychological aspects of why people initiate health behaviour change by prompting increases in motivation and self-efficacy. The addition of motivational interviewing to PA interventions may increase the effectiveness of PAMs for older adults. Methods This motivational interviewing and PA monitoring trial is designed as an investigator-blinded, two arm parallel group, randomized controlled superiority trial with primary endpoint after 12 weeks of intervention. The intervention group will receive a PAM-based intervention and motivational interviewing and the control group will only receive the PAM-based intervention. The primary outcome is PA, objectively measured as the average daily number of steps throughout the intervention period. Secondary outcome measures include self-reported PA health-related quality of life, loneliness, self-efficacy for exercise, outcome expectancy for exercise, and social relations. The outcomes will be analysed with a linear regression model investigating between-group differences, adjusted for baseline scores. Following the intention to treat principle, multiple imputation will be performed to handle missing values. Discussion A moderate effect of daily PA measured using PAMs is expected in this superiority RCT investigating the effect of adding motivational interviewing to a PAM intervention. According to the World Health Organization, walking and cycling are key activities in regular PA and should be promoted. To increase the general public health and lower the burden of inactivity in older adults, cost-beneficial solutions should be investigated further. If this RCT shows that motivational interviewing can enhance the effect of PAM-based interventions, it might be included as an add-on intervention when appropriate. No matter what the results of this study will be, the conclusions will be relevant for clinicians as the dependence on technology is increasing, especially in relation to public health promotion. Trial registration NCT03906162, April 1, 2019.

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A 12-week Intervention With Motivational Interviewing and Physical Activity Monitoring, to Enhance the Daily Amount of Physical Activity in Community Dwelling Older Adults - a Randomized Controlled Trial

Case Medical Research ◽

10.31525/ct1-nct03906162 ◽

2019 ◽

Author(s):

Keyword(s):

Physical Activity ◽

Older Adults ◽

Randomized Controlled Trial ◽

Motivational Interviewing ◽

Controlled Trial ◽

Community Dwelling ◽

Daily Amount ◽

Randomized Controlled ◽

Physical Activity Monitoring ◽

Community Dwelling Older Adults

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Daily step count and incident diabetes in community-dwelling 70-year-olds: a prospective cohort study

BMC Public Health ◽

10.1186/s12889-020-09929-2 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Marcel Ballin ◽

Peter Nordström ◽

Johan Niklasson ◽

Antti Alamäki ◽

Joan Condell ◽

...

Keyword(s):

Older Adults ◽

Cohort Study ◽

Dose Response ◽

Prospective Cohort ◽

Lower Risk ◽

Community Dwelling ◽

Step Count ◽

Incident Diabetes ◽

Daily Step ◽

Daily Step Count

Abstract Background Older adults with diabetes take fewer steps per day than those without diabetes. The purpose of the present study was to investigate the association of daily step count with incident diabetes in community-dwelling 70-year-olds. Methods This prospective cohort study included N = 3055 community-dwelling 70-year-olds (52% women) who participated in a health examination in Umeå, Sweden during 2012–2017, and who were free from diabetes at baseline. Daily step count was measured for 1 week using Actigraph GT3X+ accelerometers. Cases of diabetes were collected from the Swedish National Patient Register. The dose-response association was evaluated graphically using a flexible parametric model, and hazard ratios (HR) with 95% confidence intervals (CI) were calculated using Cox regressions. Results During a mean follow-up of 2.6 years, diabetes was diagnosed in 81 participants. There was an inverse nonlinear dose-response association between daily step count and incident diabetes, with a steep decline in risk of diabetes from a higher daily step count until around 6000 steps/day. From there, the risk decreased at a slower rate until it leveled off at around 8000 steps/day. A threshold of 4500 steps/day was found to best distinguish participants with the lowest risk of diabetes, where those taking ≥ 4500 steps/day, had 59% lower risk of diabetes, compared to those taking fewer steps (HR, 0.41, 95% CI, 0.25–0.66). Adjusting for visceral adipose tissue (VAT) attenuated the association (HR, 0.64, 95% CI, 0.38–1.06), which was marginally altered after further adjusting for sedentary time, education and other cardiometabolic risk factors and diseases (HR, 0.58, 95% CI, 0.32–1.05). Conclusions A higher daily step count is associated with lower risk of incident diabetes in community-dwelling 70-year-olds. The greatest benefits occur at the lower end of the activity range, and much earlier than 10,000 steps/day. With the limitation of being an observational study, these findings suggest that promoting even a modest increase in daily step count may help to reduce the risk of diabetes in older adults. Because VAT appears to partly mediate the association, lifestyle interventions targeting diabetes should apart from promoting physical activity also aim to prevent and reduce central obesity.

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Relationship Between the Change in Daily Step Count and Brachial-Ankle Wave Velocity During a Pedometer-Based Physical Activity Program for Older Adults

ANTI-AGING MEDICINE ◽

10.3793/jaam.8.35 ◽

2011 ◽

Vol 8 (4) ◽

pp. 35-40 ◽

Cited By ~ 2

Author(s):

Ryo Miyazaki ◽

Yoshikazu Yonei ◽

Yoriko Azuma ◽

Hitoshi Chiba ◽

Koichiro Hayashi ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Wave Velocity ◽

Step Count ◽

Physical Activity Program ◽

Daily Step ◽

Activity Program ◽

Daily Step Count

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Effectiveness of Community-Delivered Functional Power Training Program for Frail and Pre-frail Community-Dwelling Older Adults: a Randomized Controlled Study

Prevention Science ◽

10.1007/s11121-021-01221-y ◽

2021 ◽

Author(s):

Nien Xiang Tou ◽

Shiou-Liang Wee ◽

Wei Ting Seah ◽

Daniella Hui Min Ng ◽

Benedict Wei Jun Pang ◽

...

Keyword(s):

Older Adults ◽

Muscle Strength ◽

Controlled Trial ◽

Community Dwelling ◽

Controlled Study ◽

Power Training ◽

Frail Older Adults ◽

Frailty Status ◽

Randomized Controlled ◽

Community Dwelling Older Adults

AbstractTranslation of community-based functional training for older adults to reduce frailty is still lacking. We evaluated the effectiveness and implementation of a community-delivered group-based functional power training (FPT) program for frail older adults within their neighborhoods. A two-arm, multicenter assessor-blind stratified randomized controlled trial was conducted at four local senior activity centers in Singapore. Sixty-one community-dwelling older adults with low handgrip strength were randomized to intervention (IG) or control (CG) group. The IG underwent the FPT program (power and balance exercises using simple equipment) delivered by a community service provider. The 12-week program comprised 2 × 60 min sessions/week. CG continued usual activities at the centers. Functional performance, muscle strength, and frailty status were assessed at baseline and 3 months. Program implementation was evaluated using RE-AIM framework. The program was halted due to Coronavirus Disease 2019-related suspension of senior center activities. Results are reported from four centers, which completed the program. IG showed significantly greater improvement in the Short Physical Performance Battery test as compared to CG (p = 0.047). No effects were found for timed up and go test performance, muscle strength, and frailty status. The community program exhibited good reach, effectiveness, adoption, and implementation. Our study demonstrated that FPT was associated with greater improvement in physical function in pre-frail/frail participants as compared to exercise activities offered at local senior activity centers. It is a feasible intervention that can be successfully implemented for frail older adults in their neighborhoods. Trial registration ClinicalTrials.gov, NCT04438876. Registered 19 June 2020–retrospectively registered.

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The translation of preschoolers’ physical activity guidelines into a daily step count target

Journal of Sports Sciences ◽

10.1080/02640414.2014.981850 ◽

2014 ◽

Vol 33 (10) ◽

pp. 1051-1057 ◽

Cited By ~ 24

Author(s):

Marieke De Craemer ◽

Ellen De Decker ◽

Ilse De Bourdeaudhuij ◽

Maïté Verloigne ◽

Yannis Manios ◽

...

Keyword(s):

Physical Activity ◽

Step Count ◽

Daily Step ◽

Physical Activity Guidelines ◽

Daily Step Count

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Abstract 11: mActive: A Blinded, Randomized mHealth Trial Supporting Digital Tracking and Smart Texting for Promotion of Physical Activity

Circulation ◽

10.1161/circ.131.suppl_1.11 ◽

2015 ◽

Vol 131 (suppl_1) ◽

Author(s):

Seth S Martin ◽

David I Feldman ◽

Roger S Blumenthal ◽

Steven R Jones ◽

Wendy S Post ◽

...

Keyword(s):

Physical Activity ◽

Phase I ◽

Real Time ◽

Phase Ii ◽

The United States ◽

Step Count ◽

Daily Step ◽

Baseline Activity ◽

Daily Step Count ◽

Digital Tracking

Introduction: The recent advent of smartphone-linked wearable pedometers offers a novel opportunity to promote physical activity using mobile health (mHealth) technology. Hypothesis: We hypothesized that digital activity tracking and smart (automated, real-time, personalized) texting would increase physical activity. Methods: mActive (NCT01917812) was a 5-week, blinded, sequentially-randomized, parallel group trial that enrolled patients at an academic preventive cardiovascular center in Baltimore, MD, USA from January 17 th to May 20 th , 2014. Eligible patients were 18-69 year old smartphone users who reported low leisure-time physical activity by a standardized survey. After establishing baseline activity during a 1-week blinded run-in, we randomized 2:1 to unblinded or blinded tracking in phase I (2 weeks), then randomized unblinded participants 1:1 to receive or not receive smart texts in phase II (2 weeks). Smart texts provided automated, personalized, real-time coaching 3 times/day towards a daily goal of 10,000 steps. The primary outcome was change in daily step count. Results: Forty-eight patients (22 women, 26 men) enrolled with a mean (SD) age of 58 (8) years, body mass index of 31 (6), and baseline daily step count of 9670 (4350). The phase I change in activity was non-significantly higher in unblinded participants versus blinded controls by 1024 steps/day (95% CI -580-2628, p=0.21). In phase II, smart text receiving participants increased their daily steps over those not receiving texts by 2534 (1318-3750, p<0.001) and over blinded controls by 3376 (1951-4801, p<0.001). The unblinded-texts group had the highest proportion attaining the 10,000 steps/day goal (p=0.02) (Figure). Conclusions: In present-day adult smartphone users receiving preventive cardiovascular care in the United States, a technologically-integrated mHealth strategy combining digital tracking with automated, personalized, real-time text message coaching resulted in a large short-term increase in physical activity.

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Exploring the Benefits of Mindfulness Training in Healthy Community-Dwelling Older Adults: a Randomized Controlled Study Using a Mixed Methods Approach

Mindfulness ◽

10.1007/s12671-018-1041-x ◽

2018 ◽

Vol 10 (4) ◽

pp. 737-748 ◽

Cited By ~ 1

Author(s):

Alexandra J. Fiocco ◽

Sasha Mallya ◽

Mitra Farzaneh ◽

Diana Koszycki

Keyword(s):

Older Adults ◽

Mixed Methods ◽

Community Dwelling ◽

Mindfulness Training ◽

Randomized Controlled Study ◽

Controlled Study ◽

Mixed Methods Approach ◽

Randomized Controlled ◽

Healthy Community ◽

Community Dwelling Older Adults

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Neural Network–Based Algorithm for Adjusting Activity Targets to Sustain Exercise Engagement Among People Using Activity Trackers: Retrospective Observation and Algorithm Development Study

JMIR mhealth and uhealth ◽

10.2196/18142 ◽

2020 ◽

Vol 8 (9) ◽

pp. e18142

Author(s):

Ramin Mohammadi ◽

Mursal Atif ◽

Amanda Jayne Centi ◽

Stephen Agboola ◽

Kamal Jethwani ◽

...

Keyword(s):

Neural Network ◽

Physical Activity ◽

Machine Learning ◽

Learning Model ◽

Step Count ◽

Daily Step ◽

Activity Tracker ◽

Activity Trackers ◽

Machine Learning Model ◽

Daily Step Count

Background It is well established that lack of physical activity is detrimental to the overall health of an individual. Modern-day activity trackers enable individuals to monitor their daily activities to meet and maintain targets. This is expected to promote activity encouraging behavior, but the benefits of activity trackers attenuate over time due to waning adherence. One of the key approaches to improving adherence to goals is to motivate individuals to improve on their historic performance metrics. Objective The aim of this work was to build a machine learning model to predict an achievable weekly activity target by considering (1) patterns in the user’s activity tracker data in the previous week and (2) behavior and environment characteristics. By setting realistic goals, ones that are neither too easy nor too difficult to achieve, activity tracker users can be encouraged to continue to meet these goals, and at the same time, to find utility in their activity tracker. Methods We built a neural network model that prescribes a weekly activity target for an individual that can be realistically achieved. The inputs to the model were user-specific personal, social, and environmental factors, daily step count from the previous 7 days, and an entropy measure that characterized the pattern of daily step count. Data for training and evaluating the machine learning model were collected over a duration of 9 weeks. Results Of 30 individuals who were enrolled, data from 20 participants were used. The model predicted target daily count with a mean absolute error of 1545 (95% CI 1383-1706) steps for an 8-week period. Conclusions Artificial intelligence applied to physical activity data combined with behavioral data can be used to set personalized goals in accordance with the individual’s level of activity and thereby improve adherence to a fitness tracker; this could be used to increase engagement with activity trackers. A follow-up prospective study is ongoing to determine the performance of the engagement algorithm.

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