Exercise as it relates to Disease/Adaptive physical activity intervention for overweight adults

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This article is a critical analysis of the paper: "An Adaptive Physical Activity Intervention for Overweight Adults: A Randomized Controlled Trial" (Mark A. Adams Et al.2013)[1]

What is the background to this research?[edit]

Overweight and obesity are defined by the accumulation of excessive body fat that presents additional health risks to an individual[2]. At the time of publication, the prevalence of overweight adults in America was 71.6%, 55% of which were obese[3]. Physical activity (PA) interventions seek to improve the lives of these vulnerable populations by changing their relationships with exercise. Methods for prescribing individuals with exercise that motivate and elicit long-term behavioural change are criteria for a successful intervention[4]. Marc A. Adams Et al. observed that PA interventions typically comprise elements that remain static, meaning exercise dosage remains the same for the legnth of a given trial. As such these types of studies are not always successful [1]. Given advancements in emerging technology, utilising an adaptive PA interventions approach is more feasible. Adams predicted that goal setting and feedback unique to each participant would produce greater adherence to a program and higher PA levels when compared to a more traditional static intervention (SI)[1].

Where is the research from?[edit]

Authors Adams, Sallis, Norman, Hovel and Hekler work in the health departments of University institutes across California and Arizona. Although this paper was among his earlier research, primary author Assoc. Prof. Marc Adams is very well-published. Adams has co-authored 197 articles and is often cited on platforms such as The Lancet and the Journal of the American Dietetic Association.

Funding for the research was obtained through grants provided by the National Heart, Lung and Blood Institute (NIH). The NIH took no role in the design, data collection and analysis of the study.

The paper was published to the Plos ONE Journal. Maintained by the Public Library of Science, PLoS ONE held a SJR (SCImago journal rank) of 1.8 at the time[5]. All Authors declared no competing interests.

What kind of research was this?[edit]

The research is classed as a comparative study, by means of parallel intervention. The aim was to determine the effectiveness of an adaptive intervention (AI) against that of a traditional SI:

  1. An adaptive shaping intervention (AI) based on behavioural economics and operant principles. Dynamic, daily activity goals to suit each participant.
  2. A static intervention (SI). Where activity goals remain the same throughout a trial.

What did the research involve?[edit]

Trial timeline.png

Men and women aged between 18 - 65 were recruited for the study. Participants had to be overweight and partake in minimal physical activity. A 10-day run-in phase was used to familiarise individuals with the pedometers used (Omron HJ-720ITC) and acquire baseline activity levels. After which, participants were randomly assigned to the SI or AI PA group. The trial period ran for a total of 6 months where participants were tasked with reaching a number of steps each day. The aim of the study to get everyone reaching 10,000 steps/day. Only 20 participants made it through to the trial phase of the study.

  1. SI were set the static goal of 10,000 steps per day.
  2. AI participants were provided with a goal that changed daily. Each day the goal was generated by an algorithm developed by the research team. The algorithm calculated parameters including: Baseline performance (10-day run-in) and a rolling window of their previous 9 days of step count submissions. This resulted in a step count that was challenging for the individual whilst being attainable. The step count would increase each consecutive day as a participant reaches their goal. Inversely, the step count would decrease each day they did not submit or reach their goal.

Both SI and AI groups received message prompts every 9 days to encourage physical activity and provide monetary incentives in the form of gift cards to various stores. The AI group would further receive daily encouragement by way of text or email if their submission met the daily step goal for example, "Well done! You're steps closer to good health".

What were the basic results?[edit]

Journal.pone.0082901.g004.png

After the 6-month parallel intervention concluded the following results indicated the AI group performed, on average, a greater number of daily steps then that of the SI group:

Baseline Trial Phase Change Improvement (%)
Static Intervention (SI) 5364 6348 984 18% Increase
Adaptive Intervention (AI) 4555 6760 2205 48% Increase

*Figures represent Steps/Day

The AI group also met more daily goals than the SI group.

Goals Met Goals Not Met
Static Intervention (SI) 22.5% 77.5%
Adaptive Intervention (AI) 58.2% 41.8%

It is also worth noting that during the intervention the AI group displayed far less day-to-day step count variability, while following an accelerated trend across the trial period (as seen in the plots pictured).

However, observations in the study exceeded results found through relating meta-analyses[1]. This could be a result of the incentive structure around the interventions. The small sample size may also inflate any findings.

What conclusions can we take from this research?[edit]

Adams Et al. sought to test the viability of an innovative adaptive PA intervention[1]. The trial showed promising results needing further exploration with a larger sample size.

The AI works well to meet the unpredictable nature of day-to-day life. Some participants had children, worked multiple jobs or fell ill during the trial and these variables all affected their ability to meet assigned step goals. The AI allowed for low activity days, and challenged participants to get active at other times in their week. The adaptive cycle of the daily goals aids in motivating participants and ultimately producing a healthier lifestyle.

Furthermore, the AI strongly supports what is fundamental to a more active lifestyle, behavioural change[4]. Behavioural adaptation occurs over a long period of time and the slow, gradual increase in physical activity promoted by the AI is very encouraging to participants[4]. The repetitive and attainable format of the AI goals provides participants the opportunity to form more stable habits that align with their unique lifestyles. Conversely, SI participants faced with the large and daunting figure of 10,000 steps/day (46% greater than average baseline) were presented with a challenging task which impacted their behaviour towards physical activity. I believe participant motivation was a key factor contributing to the high intra-group daily variability of SI goals met.

Practical advice[edit]

The final results published were analysed from data submitted by 20 final participants. The small sample size could easily skew results and therefore the same intervention method needs to be applied to a larger group.

  • The required equipment, submission platforms and feedback medium were all cost effective and easy to scale to a larger population.
  • Attainable goals set to steadily increase PA over a long period of time are effective at motivating participants.
  • Ehealth interventions are still in their infancy, however they indicate the ability to produce long-term behavioural change and form healthy habits in individuals [4].

Information/resources[edit]

For further reading on getting more physically active and relating articles, see below:

How to add more steps in a day!

Exercise and physical activity

Heart Foundation

Text Messages for weight loss

References[edit]

  1. a b c d e Adams MA, Sallis JF, Norman GJ, Hovell MF, Hekler EB, Perata E. An adaptive physical activity intervention for overweight adults: a randomized controlled trial. PloS one. 2013;8(12):e82901.
  2. WHO. Obesity [Available from: https://www.who.int/topics/obesity/en/.
  3. CDC. Obesity and Overweight 2016 [Available from: https://www.cdc.gov/nchs/fastats/obesity-overweight.htm.
  4. a b c d Michie S, Johnston M, Francis J, Hardeman W, Eccles M. From theory to intervention: mapping theoretically derived behavioural determinants to behaviour change techniques. Applied psychology. 2008;57(4):660-80.
  5. SJR. PLoS ONE Scimago Journal & Country Rank [Available from: https://www.scimagojr.com/journalsearch.php?q=10600153309&tip=sid.