Why Do People Act Like the Proverbial Ostrich? Investigating the Reasons That People Provide for Not Monitoring Their Goal Progress

A pilot randomized controlled trial of an online intervention for Hodgkin lymphoma survivors to increase knowledge about late effects and recommended screening

BACKGROUND

Hodgkin lymphoma (HL) survivors who received chest radiotherapy are at risk for breast cancer and cardiovascular disease, but screening adherence is low. We assessed the acceptability/feasibility of a web-based educational intervention and its impact on knowledge of health risks and screening.

METHODS

HL survivors were randomized to either an interactive online educational intervention or handouts only. Surveys were completed at baseline and 3 months post-intervention. We described the acceptability/feasibility of the intervention and compared knowledge between groups.

RESULTS

Fifty-two HL survivors participated; 27 in the intervention group and 25 in the control group. Eighteen (66%) intervention participants completed the intervention and reported high acceptability (89-100%). At baseline, adherence to breast cancer screening was low across all participants. Post-intervention, those in the intervention group more often than controls correctly identified breast cancer and echocardiogram screening guidelines (35% vs. 28%, P = 0.02 and 82% vs. 52%, P = 0.04) and reported knowing how to address potential complications from cancer treatments (87% vs. 64%, P = 0.03). We detected no increase in screening behavior post-intervention.

CONCLUSION

Online education modules for high-risk HL survivors are an acceptable method to improve knowledge of health risks and screening guidelines. Future interventions should focus on improving screening uptake in this population.

IMPLICATIONS FOR CANCER SURVIVORS

Web-based learning can be useful in increasing cancer survivor knowledge of their unique risks and screening recommendations but does not necessarily change patient behavior. Involvement in a cancer survivorship program can help assess individual barriers and monitor uptake of screening.

Design of a randomized controlled trial of digital health and community health worker support for diabetes management among low-income patients

BACKGROUND

Insulin-dependent diabetes is a challenging disease to manage and involves complex behaviors, such as self-monitoring of blood glucose. This can be especially challenging in the face of socioeconomic barriers and in the wake of the COVID-19 pandemic. Digital health self-monitoring interventions and community health worker support are promising and complementary best practices for improving diabetes-related health behaviors and outcomes. Yet, these strategies have not been tested in combination. This protocol paper describes the rationale and design of a trial that measures the combined effect of digital health and community health worker support on glucose self-monitoring and glycosylated hemoglobin.

METHODS

The study population was uninsured or publicly insured; lived in high-poverty, urban neighborhoods; and had poorly controlled diabetes mellitus with insulin dependence. The study consisted of three arms: usual diabetes care; digital health self-monitoring; or combined digital health and community health worker support. The primary outcome was adherence to blood glucose self-monitoring. The exploratory outcome was change in glycosylated hemoglobin.

CONCLUSION

The design of this trial was grounded in social justice and community engagement. The study protocols were designed in collaboration with frontline community health workers, the study aim was explicit about furthering knowledge useful for advancing health equity, and the population was focused on low-income people. This trial will advance knowledge of whether combining digital health and community health worker interventions can improve glucose self-monitoring and diabetes-related outcomes in a high-risk population.

Weight-Related Information Avoidance Prospectively Predicts Poorer Self-Monitoring and Engagement in a Behavioral Weight Loss Intervention

BACKGROUND

Self-monitoring is a key component of behavioral weight loss (BWL) interventions. Past research suggests that individuals may avoid self-monitoring in certain contexts (e.g., skipping self-weighing after higher-than-usual calorie intake). However, no studies have attempted to quantify individuals' inclination to avoid information about their weight control ("weight-related information avoidance"; WIA) or prospectively examined its implications for treatment engagement and outcomes in BWL programs.

PURPOSE

Characterize WIA using a validated questionnaire among adults enrolled in BWL treatment and examine whether WIA prospectively predicts self-monitoring adherence, session attendance, treatment discontinuation, or weight loss.

METHODS

Participants (N = 87; MBMI = 34.9 kg/m2, 83% female) completed a measure of WIA prior to starting a 12 week, group-based BWL intervention. Participants were given digital self-monitoring tools and instructed to self-monitor their food intake daily, physical activity daily, and body weight weekly (Weeks 1-10) and then daily (Weeks 11-12). Session attendance and treatment discontinuation were recorded. Weight was measured in-clinic pretreatment and posttreatment.

RESULTS

While mean WIA was low (M = 2.23, standard deviation [SD] = 0.95; potential scale range: 1-7), greater WIA predicted poorer attendance (r = -.23; p = .03) and poorer self-monitoring of physical activity (r = -.28; p = .009) and body weight (r = -.32; p = .003). WIA did not predict food monitoring (p = .08), treatment discontinuation (p = .09), or 12 week weight loss (p = .91).

CONCLUSIONS

Greater WIA, as assessed via a brief questionnaire, may place individuals at risk for poorer self-monitoring and treatment engagement during BWL. Further research on the implications of WIA in the context of weight management is warranted, including evaluation of correlates, moderators, and mechanisms of action of WIA.

CLINICAL TRIAL REGISTRATION

NCT03337139.

Effectiveness of a self-regulation intervention for weight loss: A randomized controlled trial

OBJECTIVES

To evaluate effectiveness and acceptability of a novel intervention, based on self-regulation theory, for weight loss.

DESIGN

A two-arm parallel group design was employed.

METHODS

Adult participants with a BMI ≥ 30 kg/m² and the aim to lose weight were recruited and randomized to either a control or intervention group. Both groups were asked to weigh themselves daily for eight weeks. The intervention group was encouraged to use a weight tracking app, and complete daily and weekly questionnaires to prompt action planning, reflection, and evaluation of actions. Participants chose daily actions from a menu of 53 behaviours. The primary outcome was weight change after 8 weeks, assessed using linear mixed effects models. At follow-up, 20 intervention group participants were interviewed regarding their experiences in the trial.

RESULTS

100 participants were recruited, and 98% were followed up at 8 weeks. Mean weight loss was -4.18 kg (SD = 3.84) in the intervention compared to -1.01 kg (SD = 2.67) in the control group; the adjusted difference was -3.20 kg (95% CI -4.49, -1.92). Participants rated the intervention's usefulness as 8.25 (SD = 2.04) on a scale from 1 to 10. Adherence was a significant independent predictor of weight loss success (-1.54 kg per one SD, 95% CI -2.16, -0.93), but not a mediator of the intervention effect. Participants reported that the intervention enabled them to experiment with and identify effective weight loss actions.

CONCLUSIONS

Guiding participants through the self-regulation process was feasible, acceptable to participants, and led to significantly greater short-term weight loss than unguided self-weighing.

Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis

Background

Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time.

Objective

This study aimed to investigate whether it is a decline in weight loss or a drop in motivation to lose weight (using physical activity tracking as a proxy) that may be prompting a stop in weight monitoring.

Methods

We analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set a weight loss goal and stopped tracking their weight for at least six weeks after a minimum of 16 weeks of continuous tracking. Mixed effects models compared weight change, average daily steps, and physical activity tracking frequency between a 4-week period of continuous tracking and a 4-week period preceding the stop in weight tracking. Additional mixed effects models investigated subsequent changes in physical activity data during 4 weeks of the 6-week long stop in weight tracking.

Results

People lost weight during continuous tracking (mean −0.47 kg, SD 1.73) but gained weight preceding the stop in weight tracking (mean 0.25 kg, SD 1.62; difference 0.71 kg; 95% CI 0.60 to 0.81). Average daily steps (beta=−220 daily steps per time period; 95% CI −320 to −120) and physical activity tracking frequency (beta=−3.4 days per time period; 95% CI −3.8 to −3.1) significantly declined from the continuous tracking to the pre-stop period. From pre-stop to post-stop, physical activity tracking frequency further decreased (beta=−6.6 days per time period; 95% CI −7.12 to −6.16), whereas daily step count on the day’s activity was measured increased (beta=110 daily steps per time period; 95% CI 50 to 170).

Conclusions

In the weeks before people stop tracking their weight, their physical activity and physical activity monitoring frequency decline. At the same time, weight increases, suggesting that declining motivation for weight control and difficulties with making use of negative weight feedback might explain why people stop tracking their weight. The increase in daily steps but decrease in physical activity tracking frequency post-stop might result from selective measurement of more active days.

Goal-setting to Promote a Healthier Lifestyle in Later Life: Qualitative Evaluation of the AgeWell Trial

OBJECTIVE

We report a mixed method evaluation of the feasibility and implementation of the AgeWell goal-setting intervention to promote healthy ageing later life.

METHOD

Researcher field notes, goal-setting interview content, and semi-structured interviews with participants were content analysed to review trial implementation and participants' perspective on the goal-setting and mentoring intervention.

RESULTS

75 people were recruited: 21 in the goal-setting and 22 in the goal-setting with mentoring arms of the intervention. Goal-setting was feasible in the main domains of interest. Adherence to the protocol was good and the mentoring schedule was adhered to. Participants reported satisfaction with their goal attainment, but barriers for non-achievement were also identified. Recommendations for small changes to the intervention included reducing the number of goals.

CONCLUSIONS

Participants understood the goal-setting process, and were able to set realistic and achievable lifestyle goals. The intervention and the procedures were acceptable but changes in how goal-setting is both introduced and monitored are needed for wider implementation.

CLINICAL IMPLICATIONS

Goal-setting can be a useful process to help people alter their lifestyle to allow them to age more successfully and reduce risk factors associated with dementia.