Increasing Effectiveness of a Physical Activity Smartphone Intervention With Positive Suggestions: Randomized Controlled Trial. (Preprint)

BACKGROUND Electronic Health (eHealth) interventions have a potential to increase physical activity of their users. However, their effectiveness varies and they often have only short-lasting effects. One possible way to enhance their effectiveness, is increasing positive outcome expectations of the users by giving them positive suggestions regarding the effectiveness of the intervention. It has been shown that when individuals have positive expectations regarding various types of interventions, they tend to benefit from these interventions more. OBJECTIVE The main objective of this web-based study was to investigate whether positive suggestions can change the expectations of the participants regarding the effectiveness of a smartphone physical activity intervention and subsequently enhance the number of steps participants take during the intervention. Additionally, we studied if suggestions affect perceived app effectiveness, engagement with the app, self-reported vitality and fatigue of the participants. METHODS A 21-day physical fully automated activity intervention aimed at helping participants to walk more steps. The intervention was delivered via a smartphone-based application (app), that deliver specific tasks to participants (e.g., setting activity goals or looking for social support) and recorded daily step count of the participants. Participants were randomized to either a positive suggestions group (n = 69) or a control group (n = 64). Positive suggestions emphasizing the effectiveness of the intervention were implemented in an online flyer sent to the participants before the intervention. Suggestions were repeated on day 8 and 15 of the intervention via the app. RESULTS Participants significantly increased their daily step count from baseline compared to 21 days of the intervention (t (107) = -8.62, p < .001) regardless of the suggestions. Participants in the positive suggestions group had more positive expectations regarding the app (B= -1.61, SE= 0.47, p < 0.001) and higher expected engagement with the app (B= 3.80, SE= 0.63, p < .001) compared to the participants in the control group. No effect of suggestions on the step count (B = -22.05, SE = 334.90, p = .95), perceived effectiveness of the app (B= 0.78, SE= 0.69, p= 0.26), engagement with the app (B= 0.78, SE= 0.75, p= 0.29), and vitality (B= 0.01, SE= 0.11, p= 0.95) were found. Positive suggestions decreased the fatigue of participants during the three weeks of the intervention (B= 0.11, SE= 0.02, p< 0.001). CONCLUSIONS Even though the suggestions did not affect the number of daily steps, they increased the positive expectations of the participants and decreased their fatigue. These results indicate that adding positive suggestions to eHealth physical activity interventions might be a promising way to influence subjective, but not objective, outcomes of interventions. Future research should focus on finding ways to strengthen the suggestions as they have a potential to boost effectiveness of eHealth interventions. CLINICALTRIAL osf.io/cwjes

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The Adverse Impact of Glaucoma on Psychological Function and Daily Physical Activity

Journal of Ophthalmology ◽

10.1155/2020/9606420 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8

Author(s):

Wenbin Huang ◽

Kai Gao ◽

Yaoming Liu ◽

Mengyin Liang ◽

Xiulan Zhang

Keyword(s):

Mental Health ◽

Physical Activity ◽

Social Function ◽

Step Count ◽

Control Group ◽

Advanced Stage ◽

Daily Step ◽

Daily Step Count ◽

Glaucoma Group

Purpose. To evaluate the impact of glaucoma on vision-related quality of life and physical activity. Methods. This study included 50 glaucoma patients and 50 healthy control subjects. Sociodemographic and clinical data were collected from all subjects. A Chinese version of the NEI VFQ-25 was used to evaluate the quality of life. Objective physical activity was assessed by wearing an accelerometer for 7 consecutive days. Results. No significant difference was found in sociodemographic data between the two groups (all p<0.05). Visual acuity and visual field scores were worse in the glaucoma group than in the control group (all p<0.001). The VFQ-25 scores indicated significantly lower scores for ocular pain, social function, mental health, role difficulties, and color vision in the glaucoma group than in the normal group (all p<0.05). The average daily step count was lower in the glaucoma group than in the normal group. High, moderate, and low average daily step counts in the glaucoma group were associated with early-, moderate-, and advanced-stage glaucoma, respectively, while the step count was significantly lower in the advanced-stage glaucoma group than in the control group p=0.037. A positive relationship was found between the average daily step count and social function and mental health (both p<0.05). Conclusions. We demonstrated an adverse impact of glaucoma on psychological function and daily physical activity. Social function and mental health showed declines in glaucoma patients, and physical activity was limited in patients with advanced-stage glaucoma.

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Does Patient Preference for Mode of Intervention Delivery Impact Intervention Efficacy and Attrition?

American Journal of Health Promotion ◽

10.1177/0890117119871002 ◽

2019 ◽

Vol 34 (1) ◽

pp. 63-66

Author(s):

Ronald C. Plotnikoff ◽

Fiona G. Stacey ◽

Anna K. Jansson ◽

Benjamin Ewald ◽

Natalie A. Johnson ◽

...

Keyword(s):

Controlled Trial ◽

Intervention Group ◽

Step Count ◽

Future Research ◽

Study Group ◽

Daily Step ◽

Study Participation ◽

Face To Face ◽

Exercise Specialist ◽

Daily Step Count

Purpose: To explore whether there was a difference in objectively measured physical activity and study participation between people who received their preferred study group allocation (matched) and those who did not receive their preferred study group (mismatched). Design: Secondary data from the NewCOACH randomized controlled trial. Setting: Insufficiently active patients in the primary care settings in Sydney and Newcastle, Australia. Participants: One hundred seventy-two adults aged 20 to 81 years. Intervention: Participants indicated their intervention preference at baseline for (1) five face-to-face visits with an exercise specialist, (2) one face-to-face visit and 4 telephone follow-ups with an exercise specialist, (3) written material, or (4) slight-to-no preference. Participants were then allocated to an intervention group and categorized as either “matched” or “mismatched” based on their indications. Participants who reported a slight-to-no preference was categorized as “matched.” Measures: Daily step count as measured by pedometers and study participation. Analysis: Mean differences between groups in daily step count at 3 and 12 months (multiple linear regression models) and study participation at baseline, 3 months, and 12 months (χ2 tests). Results: Preference for an intervention group prior to randomization did not significantly (all P’s > .05 using 95% confidence interval) impact step counts (differences of <600 steps/day between groups) or study participation. Conclusion: Future research should continue to address whether the strength of preferences influence study outcome and participation and whether the study preferences change over time.

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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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Salud paso por paso : a culturally-tailored physical activity intervention with hispanic adults with type 2 diabetes mellitus

10.32469/10355/88130 ◽

2021 ◽

Author(s):

◽

Julio Cesar Loya

Keyword(s):

Physical Activity ◽

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Physical Activity Intervention ◽

Controlled Trial ◽

Control Group ◽

Culturally Tailored ◽

Hispanic Adults

Limited information is available regarding culturally-tailored physical activity (PA) interventions for Hispanic adults with type 2 diabetes mellitus (T2DM). A community-partnered approach was used to examine a novel culturally-tailored PA intervention using a pre-post, no control group design. The intervention consisted of six weekly 45-minute sessions for participants to engage in PA led by the researcher. A total of 21 individuals participated in the study. The typical participant was a 53-year-old female (90 percent) Hispanic adult living with T2DM with low acculturation. On average, before the intervention, the participants walked 10,285 (sd 14,779) steps per week with 43.4 (sd 68.1) minutes of PA per week. Despite implementation during the COVID-19 pandemic, the intervention was feasible and acceptable, and 19 (90.5 percent) participants attended all intervention sessions. There were significant increases in steps per week (p=0.007; d=1.03) and minutes of PA per week (p=0.000; d=1.62). Findings suggest that Salud Paso por Paso has promise as a strategy to enhance PA behaviors in the priority population. A randomized, controlled trial with a larger study sample is warranted to examine efficacy and impact on the diabetes health outcomes of Hispanic adults with T2DM.

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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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Feedback From Activity Trackers Improves Daily Step Count After Knee and Hip Arthroplasty: A Randomized Controlled Trial

The Journal of Arthroplasty ◽

10.1016/j.arth.2018.06.024 ◽

2018 ◽

Vol 33 (11) ◽

pp. 3422-3428 ◽

Cited By ~ 13

Author(s):

Neill Van der Walt ◽

Lucy J. Salmon ◽

Benjamin Gooden ◽

Matthew C. Lyons ◽

Michael O'Sullivan ◽

...

Keyword(s):

Randomized Controlled Trial ◽

Hip Arthroplasty ◽

Controlled Trial ◽

Step Count ◽

Daily Step ◽

Randomized Controlled ◽

Activity Trackers ◽

Daily Step Count ◽

Knee And Hip Arthroplasty

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Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: a 24-week matched case control study

International Journal of Behavioral Nutrition and Physical Activity ◽

10.1186/s12966-020-01043-1 ◽

2020 ◽

Vol 17 (1) ◽

Author(s):

Emma Pearson ◽

Harry Prapavessis ◽

Christopher Higgins ◽

Robert Petrella ◽

Lauren White ◽

...

Keyword(s):

Physical Activity ◽

Financial Incentives ◽

Step Count ◽

Daily Step ◽

Individual Level ◽

Significant Difference ◽

Daily Step Count ◽

Steps Per Day ◽

The Impact ◽

Experimental Group

Abstract Background Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements. Methods A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1–12; intervention: weeks 13–24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week). Results The main analysis included 61,170 users (mean age = 32 yrs.; % female = 64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p < 0.0001; ηp2 = 0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R2 = 0.699) with each new STC corresponding to approximately 200 more steps per day. Conclusion Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

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A Pilot Study Comparing Pedometer Counts with Reported Physical Activity in Elementary Schoolchildren

Pediatric Exercise Science ◽

10.1123/pes.16.4.355 ◽

2004 ◽

Vol 16 (4) ◽

pp. 355-367 ◽

Cited By ~ 18

Author(s):

Greet Cardon ◽

Ilse De Bourdeaudhuij

Keyword(s):

Physical Activity ◽

Pilot Study ◽

Vigorous Physical Activity ◽

Step Count ◽

Regression Equations ◽

Moderate Correlation ◽

Daily Step ◽

Step Counts ◽

Daily Step Count

In this study pedometer counts were recorded for 6 consecutive days for 92 children (mean age = 9.6 years; range 6.5–12.7) and were compared with the number of minutes per day in which the participants engaged in moderate-to-vigorous physical activity (MVPA). Diaries filled out with the assistance of one of the children’s parents were used to determine minutes of MVPA. The average daily step count was significantly higher in boys than in girls, although the average daily MVPA engagement in minutes did not vary significantly between genders. Based on the regression equations, 60 min of MVPA was equivalent to 15,340 step counts in boys, 11,317 step counts in girls, and 13,130 step counts when results for both genders were combined. A moderate correlation (r = .39, p < .001) was found between pedometer step counts and reported minutes of MVPA. According to the present study findings, however, predictions and promotion of daily MVPA engagement in children based on pedometer counts per day should be made with caution.

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