Behavior change is not one size fits all: psychosocial phenotypes of childhood obesity prevention intervention participants

"Simply complicated": Uncovering the processes of lifestyle behavior change among college and university students with access to a digital multiple lifestyle intervention

Background

One approach to promoting healthy lifestyle behaviors is to target students with digital interventions. One of these is the digital intervention Buddy. This study aimed to understand why college and university students' chose to participate in a digital multiple lifestyle behavior intervention trial (Buddy), and their subsequent experiences of the behavior-change process.

Methods

College and university students taking part in a trial of the Buddy intervention were individually interviewed after completing the 4-month intervention. Participants were guided to narrate their experiences and actions that followed signing up. Altogether, 50 interviews were conducted via telephone. The verbatim transcribed texts were analyzed qualitatively.

Results

The analysis generated seven personas, which illustrated the students' different levels of engagement with the intervention and the behavior-change process. These were: the Occupied, the Kickstarter, the Aimless, the Reflective, the Goal-oriented, the Compliant, and the Personally developed. Buddy worked best for students who had clear ideas about what they wanted to change and why, and who were aware of their needs, and those who could translate information and reflection into action and had the mental and physical energy needed to make changes.

Conclusions

The progress of behavior change depends on the interaction between the digital mode of delivery, the intervention materials of Buddy, the individual's expectations, needs, and skills, and their current life situation. This suggests that designing lifestyle interventions could benefit from more often considering the various personas' different intentions, knowledge, and contexts. By doing so, interventions are likely to emerge that can better match different needs in the target population.

Exploring the Effect of the Dynamics of Behavioral Phenotypes on Health Outcomes in an mHealth Intervention for Childhood Obesity: Longitudinal Observational Study

BACKGROUND

Advancements in mobile health technologies and machine learning approaches have expanded the framework of behavioral phenotypes in obesity treatment to explore the dynamics of temporal changes.

OBJECTIVE

This study aimed to investigate the dynamics of behavioral changes during obesity intervention and identify behavioral phenotypes associated with weight change using a hybrid machine learning approach.

METHODS

In total, 88 children and adolescents (ages 8-16 years; 62/88, 71% male) with age- and sex-specific BMI ≥85th percentile participated in the study. Behavioral phenotypes were identified using a hybrid 2-stage procedure based on the temporal dynamics of adherence to the 5 behavioral goals during the intervention. Functional principal component analysis was used to determine behavioral phenotypes by extracting principal component factors from the functional data of each participant. Elastic net regression was used to investigate the association between behavioral phenotypes and weight change.

RESULTS

Functional principal component analysis identified 2 distinctive behavioral phenotypes, which were named the high or low adherence level and late or early behavior change. The first phenotype explained 47% to 69% of each factor, whereas the second phenotype explained 11% to 17% of the total behavioral dynamics. High or low adherence level was associated with weight change for adherence to screen time (β=-.0766, 95% CI -.1245 to -.0312), fruit and vegetable intake (β=.1770, 95% CI .0642-.2561), exercise (β=-.0711, 95% CI -.0892 to -.0363), drinking water (β=-.0203, 95% CI -.0218 to -.0123), and sleep duration. Late or early behavioral changes were significantly associated with weight loss for changes in screen time (β=.0440, 95% CI .0186-.0550), fruit and vegetable intake (β=-.1177, 95% CI -.1441 to -.0680), and sleep duration (β=-.0991, 95% CI -.1254 to -.0597).

CONCLUSIONS

Overall level of adherence, or the high or low adherence level, and a gradual improvement or deterioration in health-related behaviors, or the late or early behavior change, were differently associated with weight loss for distinctive obesity-related lifestyle behaviors. A large proportion of health-related behaviors remained stable throughout the intervention, which indicates that health care professionals should closely monitor changes made during the early stages of the intervention.

TRIAL REGISTRATION

Clinical Research Information Science KCT0004137; https://tinyurl.com/ytxr83ay.

Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity

OBJECTIVES

To examine the feasibility of promoting engagement with data-driven self-management of health among individuals from minoritized medically underserved communities by tailoring the design of self-management interventions to individuals' type of motivation and regulation in accordance with the Self-Determination Theory.

METHODS

Fifty-three individuals with type 2 diabetes from an impoverished minority community were randomly assigned to four different versions of an mHealth app for data-driven self-management with the focus on nutrition, Platano; each version was tailored to a specific type of motivation and regulation within the SDT self-determination continuum. These versions included financial rewards (external regulation), feedback from expert registered dietitians (RDF, introjected regulation), self-assessment of attainment of one's nutritional goals (SA, identified regulation), and personalized meal-time nutrition decision support with post-meal blood glucose forecasts (FORC, integrated regulation). We used qualitative interviews to examine interaction between participants' experiences with the app and their motivation type (internal-external).

RESULTS

As hypothesized, we found a clear interaction between the type of motivation and Platano features that users responded to and benefited from. For example, those with more internal motivation reported more positive experience with SA and FORC than those with more external motivation. However, we also found that Platano features that aimed to specifically address the needs of individuals with external regulation did not create the desired experience. We attribute this to a mismatch in emphasis on informational versus emotional support, particularly evident in RDF. In addition, we found that for participants recruited from an economically disadvantaged community, internal factors, such as motivation and regulation, interacted with external factors, most notably with limited health literacy and limited access to resources.

CONCLUSIONS

The study suggests feasibility of using SDT to tailor design of mHealth interventions for promoting data-driven self-management to individuals' motivation and regulation. However, further research is needed to better align design solutions with different levels of self-determination continuum, to incorporate stronger emphasis on emotional support for individuals with external regulation, and to address unique needs and challenges of underserved communities, with particular attention to limited health literacy and access to resources.

Psychosocial-Behavioral Phenotyping: A Novel Precision Health Approach to Modeling Behavioral, Psychological, and Social Determinants of Health Using Machine Learning

BACKGROUND

The context in which a behavioral intervention is delivered is an important source of variability and systematic approaches are needed to identify and quantify contextual factors that may influence intervention efficacy. Machine learning-based phenotyping methods can contribute to a new precision health paradigm by informing personalized behavior interventions. Two primary goals of precision health, identifying population subgroups and highlighting behavioral intervention targets, can be addressed with psychosocial-behavioral phenotypes. We propose a method for psychosocial-behavioral phenotyping that models social determinants of health in addition to individual-level psychological and behavioral factors.

PURPOSE

To demonstrate a novel application of machine learning for psychosocial-behavioral phenotyping, the identification of subgroups with similar combinations of psychosocial characteristics.

METHODS

In this secondary analysis of psychosocial and behavioral data from a community cohort (n = 5,883), we optimized a multichannel mixed membership model (MC3M) using Bayesian inference to identify psychosocial-behavioral phenotypes and used logistic regression to determine which phenotypes were associated with elevated weight status (BMI ≥ 25kg/m2).

RESULTS

We identified 20 psychosocial-behavioral phenotypes. Phenotypes were conceptually consistent as well as discriminative; most participants had only one active phenotype. Two phenotypes were significantly positively associated with elevated weight status; four phenotypes were significantly negatively associated. Each phenotype suggested different contextual considerations for intervention design.

CONCLUSIONS

By depicting the complexity of psychological and social determinants of health while also providing actionable insight about similarities and differences among members of the same community, psychosocial-behavioral phenotypes can identify potential intervention targets in context.

Q-Methodology and Psychological Phenotyping to Design Patient-Centered Diabetes Education for Persons With Type 2 Diabetes on Insulin Therapy

PURPOSE

The purpose of this study was to identify the psychological phenotypes of persons with type 2 diabetes (T2D) on insulin therapy to better inform personalized diabetes education strategies to improve self-management behaviors.

METHODS

Q-methodology, a research approach combining the quantitative rigor of statistical analysis with qualitative data on perception of diabetes self-management by persons with T2D on insulin therapy, was used. The Summary of Diabetes Self-Care Activity measure and A1C in the past 6 months were used to further describe self-management behaviors of each P-sample, Q-sorter. Of 160 statements, 33 Q-sample statements were selected as Q-set. Then, 37 P-samples (24 men; 13 women) were recruited from a university-affiliated diabetes clinic in South Korea. Data obtained from each P-sample with a Q-set and a Q-sorting table, a forced-choice normal distribution table, were analyzed using varimax rotation.

RESULTS

Forty-one percent of the variance was explained with 5 factors represented by 27 Q-sorters, explaining variance ranging from 5% to 17% for each factor: Factor A (n = 6): those showing self-management education need but possessing inadequate health literacy; Factor B (n = 4): those valuing lifestyle modification to control diabetes; Factor C (n = 5): those valuing antidiabetic medication to control diabetes; Factor D (n = 6): carpe diem, accepting diabetes as destiny; and Factor E (n = 6): those overestimating their competencies to control diabetes. Ten Q-sorters fell into either confounded or nonsignificant.

CONCLUSIONS

Tailoring messages and educational approaches based on patients' psychological phenotypes are necessary to promote optimal self-management behaviors.

Obesity researches in youth: A scientometrics study in Middle East countries

BACKGROUND

The alarming trends of obesity/overweight in youth have been interested policy makers and other stakeholders to exact follow and analysis of related scientific evidence. The present paper quantify the trends of outputs of youth obesity/overweight researches in Middle East countries.

MATERIALS AND METHODS

The Scopus database systematically searched as the most comprehensive multidisciplinary database, for all related obesity/overweight that focused on youth age groups concerns, from 2000 to 2017. These scientometrics analysis included the trends of scientific products, citations, and other scientometric index in Middle East countries.

RESULTS

During 2000-2017, in the field of youth obesity, 2350 papers published (0.40% of total 591,105 indexed paper of this region) by Middle East countries. In this regard, Iran with 574 publication (24.43%) had the first rank. After that Turkey and Saudi Arabia, respectively, with 489 (20.81%) and 313 (13.32%) papers, had the next ranks. Over 18-year period, based on the findings all of Eastern Mediterranean countries follow the progressive plans for topics related to youth obesity. Between them, Iran and Turkey have significant growth rates (0.77% and 0.40%, respectively). Scientometric indicators such as "number of published papers," "number of citations" confirmed that during the 2000-2017 the P-trends of total number of related published papers and the correspond citations, in region countries, were significant (2168 papers and 34,132 citations, P < 0.001).

CONCLUSION

Most of countries at global and regional levels follow ascending trends in publications and citations in obesity/overweight fields. Iran's position has grown significantly among them. Maintaining and promoting this position requires careful planning and special attention. The findings also could be used for better health policy and complementary researches.

Psychosocial phenotyping as a personalization strategy for chronic disease self-management interventions

BACKGROUND

As the U.S. population grows older and more diverse, self-management needs are increasingly complicated. In order to deliver effective personalized interventions to those suffer from chronic conditions social determinants of health must be considered. Therefore, psychosocial phenotyping holds strong promise as a tool for tailoring interventions based on precision health principles.

PURPOSE

To define psychosocial phenotyping and develop a research agenda that promotes its integration into chronic disease management as a tool for precision self-management interventions.

METHODS

Since psychosocial phenotyping is not yet used in interventions for self-management support, we conducted a literature review to identify potential phenotypes for chronic disease self-management. We also reviewed policy intervention case reports from the Centers for Medicare and Medicaid Services to examine factors related to social determinants of health in people with chronic illnesses. Finally, we reviewed methodological approaches for identifying patient profiles or phenotypes.

RESULTS

The literature review revealed areas within which to collect data for psychosocial phenotyping that can inform personalized interventions. The findings of our exemplar cases revealed that several environmental or key SDOH such as factors realted with economic stability and neighborhood environment have been closely linked with the success of chronic disease management interventions. We elucidated theory, definitions, and pragmatic conceptual boundaries related to psychosocial phenotyping for precision health.

CONCLUSIONS

Our literature review with case example analysis demonstrates the potential usefulness of psychosocial phenotyping as a tool to enhance personalized self-management interventions for people with chronic diseases, with implications for future research.

Pediatric Adapted Liking Survey (PALS) with Tailored Nutrition Education Messages: Application to a Middle School Setting

We tested the feasibility of a school-based, liking-based behavioral screener (Pediatric Adapted Liking Survey (PALS)) and message program to motivate healthy diet and activity behaviors. Students, recruited from middle- (n = 195) or low-income (n = 310) schools, online-reported: likes/dislikes of foods/beverages and physical/sedentary activities, scored into healthy behavior indexes (HBI); perceived food insecurity; and sleep indicators. Students received tailored motivating or reinforcing messages (aligned with behavior change theories) and indicated their willingness to improve target behaviors as well as program feasibility (acceptability; usefulness). Although HBIs averaged lower in the lower versus middle-income school, frequencies of food insecurity were similar (39-44% of students). Students in both schools reported sleep concerns (middle-income school-43% reported insufficient hours of sleep/night; low-income school-55% reported excessive daytime sleepiness). Students across both schools confirmed the PALS acceptability (>85% agreement to answering questions quickly and completion without help) and usefulness (≥73% agreed PALS got them thinking about their behaviors) as well as the tailored message acceptability (≥73% reported the messages as helpful; learning new information; wanting to receive more messages) and usefulness (73% reported "liking" to try one behavioral improvement). Neither message type nor response varied significantly by food insecurity or sleep measures. Thus, this program feasibly delivered students acceptable and useful messages to motivate healthier behaviors and identified areas for school-wide health promotion.

Codevelopment of Healthy and Unhealthy Dietary Behaviors: A Dyadic Examination of Parenting Practices and Adolescent Characteristics

OBJECTIVE

To identify the pathways through which external, parental, and adolescent factors influence adolescents' motivation to adopt healthy dietary behaviors.

METHODS

A total of 28 ethnically and socioeconomically diverse (25% White) families were interviewed in which adolescents (mean age = 12.7 years; 50% girls) and parents (mean age = 43.3 years; 68% mothers) were interviewed separately. Data were first analyzed thematically, and family summaries, supplemented with diagrams, were then used to identify the processes through which factors influenced adolescents' dietary behaviors.

RESULTS

The analyses identified 3 main motivational pathways (intrinsic motivation, extrinsic motivation, and amotivation), wherein variability and inconsistencies were observed across and within pathways. The unique combination of external factors, parenting profiles, as well as adolescents' willingness to be socialized by family members, differentiated these pathways from each other.

CONCLUSIONS AND IMPLICATIONS

Health interventions need to target the overall approaches that parents use to socialize their adolescent to make healthy food choices instead of targeting specific parenting practices.

The obesity epidemic in the face of homeostatic body weight regulation: What went wrong and how can it be fixed?

Ever since the pioneering discoveries in the mid nineteen hundreds, the hypothalamus was recognized as a crucial component of the neural system controlling appetite and energy balance. The new wave of neuron-specific research tools has confirmed this key role of the hypothalamus and has delineated many other brain areas to be part of an expanded neural system sub serving these crucial functions. However, despite significant progress in defining this complex neural circuitry, many questions remain. One of the key questions is why the sophisticated body weight regulatory system is unable to prevent the rampant obesity epidemic we are experiencing. Why are pathologically obese body weight levels defended, and what can we do about it? Here we try to find answers to these questions by 1) reminding the reader that the neural controls of ingestive behavior have evolved in a demanding, restrictive environment and encompass much of the brain's major functions, far beyond the hypothalamus and brainstem, 2) hypothesizing that the current obesogenic environment impinges mainly on a critical pathway linking hypothalamic areas with the motivational and reward systems to produce uncompensated hyperphagia, and 3) proposing adequate strategies for prevention and treatment.

Competency-Based Approaches to Community Health: A Randomized Controlled Trial to Reduce Childhood Obesity among Latino Preschool-Aged Children

Background: Health behavior change interventions that target childhood obesity in minority populations have led to inconsistent and short-lived results. The purpose of this study was to test a novel intervention that was personalized and family-based in a Latino population to reduce childhood obesity. Methods: Competency-Based Approaches to Community Health (COACH) was a randomized controlled trial. Latino parent-child pairs were recruited from community settings in Nashville, TN. Child eligibility criteria included age 3-5 years and a BMI ≥50th percentile. The intervention included 15 weekly, 90-minute sessions followed by 3 months of twice-monthly health coaching calls. The control group was a twice-monthly school readiness curriculum for 3 months. Sessions were conducted by a health coach in local community centers, with groups of 8-11 parent-child pairs. The primary outcome was child BMI trajectory across 12 months, measured at four times. The intervention's effect was assessed by using a longitudinal, linear mixed-effects growth model, adjusting for child gender, baseline child and parent age, and baseline parent BMI and education. Results: Of the 305 parent-child pairs assessed for eligibility, 117 were randomized (59 intervention, 58 control). Child BMI was available for 91.5% at 1-year follow-up. Mean baseline child age was 4.2 [standard deviation (SD) = 0.8] years, and 53.8% of children were female. Mean baseline child BMI was 18.1 (SD = 2.6) kg/m². After adjusting for covariates, the intervention's effect on linear child BMI growth was -0.41 kg/m² per year (95% confidence interval -0.82 to 0.01; p = 0.05). Conclusions: Over 1-year follow-up, the intervention resulted in slower linear BMI growth for Latino preschool-aged children from poverty.

Food, Health, & Choices: Curriculum and Wellness Interventions to Decrease Childhood Obesity in Fifth-Graders

OBJECTIVE

To evaluate Food, Health, & Choices, two 10-month interventions.

DESIGN

Cluster-randomized, controlled study with 4 groups: curriculum, wellness, curriculum plus wellness, and control.

SETTING

Twenty elementary schools (5/group) in New York City.

PARTICIPANTS

Fifth-grade students (n = 1,159). At baseline, 44.6% were at the ≥85th body mass index (BMI) percentile for age and 86% qualified for free or reduced-price lunch.

INTERVENTION

Curriculum was 23 science lessons based on social cognitive and self-determination theories, replacing 2 mandated units. Wellness was classroom food policy and physical activity bouts of Dance Breaks.

MAIN OUTCOME MEASURES

For obesity, age- and sex-specific BMI percentiles were used (anthropometric measures). The researchers also employed 6 energy balance-related behaviors and 8 theory-based determinants of behavior change (by questionnaire).

ANALYSIS

Pairwise adjusted odds in hierarchical logistic regression models were determined for >85th BMI percentile. Behaviors and theory-based determinants were examined in a 2-level hierarchical linear model with a 2 × 2 design for intervention effects and interactions.

RESULTS

Obesity showed no change. For behaviors, there was a negative curriculum intervention change in physical activity (P = .04). The wellness intervention resulted in positive changes for sweetened beverages frequency (P = .05) and size (P = .006); processed packaged snacks size (P = .01); candy frequency (P = .04); baked good frequency (P = .05); and fast food frequency (P = .003), size (P = .01), and combo meals (P = .002). Theory-based determinants demonstrated no change.

CONCLUSIONS AND IMPLICATIONS

The findings of the lack of a decrease in obesity, behavior changes only for the wellness intervention, and no changes in theory-based determinants warrant further research.

Multi-etiological Perspective on Child Obesity Prevention

PURPOSE OF REVIEW

The simple energy balance model of obesity is inconsistent with the available findings on obesity etiology, prevention, and treatment. Yet, the most commonly stated causes of pediatric obesity are predicated on this model. A more comprehensive biological model is needed upon which to base behavioral interventions aimed at obesity prevention. In this light, alternative etiologies are little investigated and thereby poorly understood.

RECENT FINDINGS

Three candidate alternate etiologies are briefly presented: infectobesity, the gut microbiome, and circadian rhythms. Behavioral child obesity preventive investigators need to collaborate with biological colleagues to more intensively analyze the behavioral aspects of these etiologies and to generate innovative procedures for preventing a multi-etiological problem, e.g., group risk analysis, triaging for likely causes of obesity.