Process evaluation of the Sophia Step Study- a primary care based three-armed randomized controlled trial using self-monitoring of steps with and without counseling in prediabetes and type 2 diabetes

The Impact of Physical Activity in Patients With Type 2 Diabetes

Most patients with type 2 diabetes (T2DM) do not meet guideline-driven exercise recommendations. Physical activity (PA) is any form of bodily movement via skeletal muscle contraction. It can include walking, gardening, leisure activity, exercise, or movement for transportation or an occupation. Aerobic and resistance exercise have been well studied and are known to improve glycemic control in patients with T2DM. While data is less substantial, low-intensity PA such as walking, yoga, tai-chi, qigong, and activity for household tasks have also been shown to be effective methods of reducing hyperglycemia. Additionally, PA to break up sedentary behaviors can also have glycemic benefits. Healthcare providers should encourage patients to increase their PA as a more sustainable means of meeting guideline-directed exercise and activity recommendations. Discussing these changes with patients involves identifying motivators, setting goals, removing barriers, monitoring progress, and understanding the patient's social support and environment.

Acceptable, useful, and ineffective? Recent retirees’ experiences of a 12-month activity tracker-based physical activity intervention

Objective

Activity trackers appear cost-effective and acceptable intervention tools for promoting physical activity among older adults, particularly in the short-term. However, long-term studies focused on participants’ experiences continue to be scarce. This study evaluated participants’ experiences of a 12-month activity tracker-driven physical activity intervention.

Methods

Participants’ experiences were assessed qualitatively using open-ended questionnaire items ( n = 113) and semi-structured interviews conducted after the 12-month intervention ( n = 27). Quantitative items assessed the perceived ease-of-use and usefulness of the activity tracker during the intervention. Qualitative data was analyzed using thematic analysis and Wilcoxon signed-rank tests were used to examine changes in the perceived ease-of-use and usefulness over time.

Results

The 113 participants completing the 12-month intervention were on average 65.2 ( SD 1.0) years old and 81.4% women with 92.3% providing activity tracker data on at least 2 weeks per each intervention month. In the qualitative analysis, four main themes with 20 subthemes were identified: (a) burdens of participation, (b) affective attitudes of using the activity tracker, (c) perceived effects of using the activity tracker, and (d) no perceived behavioral effects. At 12 months, the participants found activity trackers mainly easy to use (mean 4.6, SD 0.6), reliable (mean 3.6, SD 1.2), motivating (mean 3.9, SD 1.0), and helpful in reducing sitting (mean 3.7, SD 1.0) with no changes observed during the intervention.

Conclusions

The participants’ experiences were highly varied suggesting that tailored intervention designs are likely to be required for effectively using activity trackers to promote long-term changes in daily activity among older adults.

Promoting Physical Activity in Older Adults With Type 2 Diabetes via an Anthropomorphic Conversational Agent: Development of an Evidence and Theory-Based Multi-Behavior Intervention

Introduction

Anthropomorphic conversational agents (ACA) are a promising digital tool to support self-management of type 2 diabetes (T2D), albeit little explored. There is a dearth of literature on the detailed content of these interventions, which may limit effectiveness and replication. Our aim is to describe the development of an evidence and theory-based intervention to improve physical activity in older adults with T2D, subsumed in a multi-behavior intervention via a mobile application with an ACA.

Methods

Overall decisions on the multi-behavior intervention design, such as the use of standardized behavior change techniques (BCTTv1), guided the development of the physical activity component. Firstly, recommendations on ambulatory activity were used to select the target behavior (walking). Meta-research on effective behavior change techniques (BCTs) was then identified. One meta-analysis linked effective BCTs with the three basic psychological needs of the self-determination theory (SDT). This meta-analysis, taken together with additional evidence on SDT, led to the selection of this theory to inform the design. BCTs were extracted from meta-research; we selected the most appropriate to be operationalized via the conversational agent through multidisciplinary discussions. Rules governing the dialogue flow and BCTs tailoring, taking the form "if some conditions hold then execute some action," were derived based on the Basic Psychological in Exercise Scale (competence, autonomy, and relatedness scores), in conjunction with published evidence and multidisciplinary discussions.

Results

Thirteen BCTs were implemented in the prototype via the ACA (e.g., goal setting behavior 1.1). Six if-then rules were derived and depicted in the dialogue steps through process flow diagrams, which map how the system functions. An example of a rule is "If competence score ≤ 10 then, apply BCT 1.1 with 500 steps increments as options for the daily walking goal; If competence score > 10 then, apply BCT 1.1 with 1,000 steps increments as options for the daily walking goal."

Conclusion

Evidence and SDT were translated into a mobile application prototype using an ACA to promote physical activity in older adults with T2D. This approach, which includes 13 BCTs and six if-then rules for their tailoring, may leverage the efforts of others in developing similar interventions.

Physical Activity Patterns among Individuals with Prediabetes or Type 2 Diabetes across Two Years-A Longitudinal Latent Class Analysis

BACKGROUND

This study aimed to identify distinct profiles of physical activity (PA) patterns among individuals with prediabetes or type 2 diabetes participating in a two-year PA trial and to investigate predictors of the profiles.

METHODS

Data (n = 168, collected 2013-2020) from the cohort of a randomized trial aimed at increasing PA in individuals with prediabetes and type 2 diabetes were used. PA and sedentary behaviours were assessed by waist-worn ActiGraph GT1M accelerometers at baseline and at 6, 12, 18 and 24 months. Fifteen PA and sedentary variables were entered into a latent class mixed model for multivariate longitudinal outcomes. Multinominal regression analysis modelled profile membership based on baseline activity level, age, gender, BMI, disease status and group randomisation.

RESULTS

Two profiles of PA patterns were identified: "Increased activity" (n = 37, 22%) included participants increasing time in PA and decreasing sedentary time. "No change in activity" (n = 131, 78%) included participants with no or minor changes. "Increased activity" were younger (p = 0.003) and more active at baseline (p = 0.011), compared to "No change in activity". No other predictor was associated with profile membership.

CONCLUSIONS

A majority of participants maintained PA and sedentary patterns over two years despite being part of a PA intervention. Individuals improving PA patterns were younger and more active at baseline.

Effects of a three-armed randomised controlled trial using self-monitoring of daily steps with and without counselling in prediabetes and type 2 diabetes-the Sophia Step Study

BACKGROUND

This aimed to evaluate the effects of self-monitoring of daily steps with or without counselling support on HbA1c, other cardiometabolic risk factors and objectively measured physical activity (PA) during a 2-year intervention in a population with prediabetes or type 2 diabetes.

METHODS

The Sophia Step Study was a three-armed parallel randomised controlled trial. Participants with prediabetes or type 2 diabetes were recruited in a primary care setting. Allocation (1:1:1) was made to a multi-component intervention (self-monitoring of steps with counselling support), a single-component intervention (self-monitoring of steps without counselling support) or standard care. Data were collected for primary outcome HbA1c at baseline and month 6, 12, 18 and 24. Physical activity was assessed as an intermediate outcome by accelerometer (ActiGraph GT1M) for 1 week at baseline and the 6-, 12-, 18- and 24-month follow-up visits. The intervention effects were evaluated by a robust linear mixed model.

RESULTS

In total, 188 subjects (64, 59, 65 in each group) were included. The mean (SD) age was 64 (7.7) years, BMI was 30.0 (4.4) kg/m2 and HbA1c was 50 (11) mmol/mol, 21% had prediabetes and 40% were female. The dropout rate was 11% at 24 months. Effect size (CI) for the primary outcome (HbA1c) ranged from -1.3 (-4.8 to 2.2) to 1.1 (-2.4 to 4.6) mmol/mol for the multi-component vs control group and from 0.3 (-3.3 to 3.9) to 3.1 (-0.5 to 6.7) mmol/mol for the single-component vs control group. Effect size (CI) for moderate-to-vigorous physical activity ranged from 8.0 (0.4 to 15.7) to 11.1 (3.3 to 19.0) min/day for the multi-component vs control group and from 7.6 (-0.4 to 15.6) to 9.4 (1.4 to 17.4) min/day for the single-component group vs control group.

CONCLUSION

This 2-year intervention, including self-monitoring of steps with or without counselling, prevented a decrease in PA but did not provide evidence for improved metabolic control and cardiometabolic risk factors in a population with prediabetes or type 2 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02374788 . Registered 2 March 2015-Retrospectively registered.