Introduction: The review explores the potential benefits of cognitive retraining interventions in improving healthy behaviours, and its possible use as an alternative or complementary approach to traditional weight loss interventions.

Method: Studies were selected using different electronic databases (PubMed, Scopus, Embase), to identify RCTs published in the last 23 years on cognitive retraining interventions for weight loss. A total of 12 studies were finalized for systematic review and six for meta-analysis based on the inclusion criteria. The risk of bias was assessed by the two reviewers independently using the criteria outlined in the Joanna Briggs Institute Critical Appraisal Tool for RCTs. The R software was used to perform meta-analysis.

Result: The overall effect estimates slightly favoured the intervention group, with a standardised mean difference (SMD) of -0.26 [95% CI (-0.58- 0.06) P<0.05; I2= 0.00%]. This suggests that although the effect was not statistically significant, cognitive retraining interventions may have a small effect on weight loss. The findings of the systematic review revealed that cognitive retraining interventions may be effective in modifying lifestyle behaviours and these changes may contribute to achieving and maintaining weight loss in the long run.

Conclusion: Interventions exhibited a positive effect on weight loss. These interventions demonstrated promise in modifying lifestyle behaviours, suggesting a potential role in achieving and sustaining long-term weight loss. Further research is warranted to refine and validate these findings.

Purpose: This research aimed to understand women’s eating motivation by identifying motivational profiles grounded in self-determination theory (SDT) that consider the specific eating regulation styles as well as the degree of self-determination. The derived profiles were compared on intuitive eating, maladaptive eating, and self-reported health.

Methods: Using sponsored ads on Facebook, 472 New Zealand women aged 40-50 years were recruited to complete an online survey. Participants (n = 472) reported motivation for eating using the Regulation of Eating Behaviour Scale (REBS), eating behaviour using the Intuitive Eating Scale-2 (IES-2) and the Dutch Eating Behaviour Questionnaire (DEBQ), and perceived health using the five-item World Health Organisation Wellbeing Index (WHO-5) and the EQ-5D Visual Analogue Scale (EQ-VAS). Novel bifactor S-1 exploratory structural equation modelling was used to analyse the REBS and disaggregate the global self-determination factor from the specific factors representing each of the unique regulation styles. Latent profile analysis was used to identify motivational profiles and chi-square analysis compared the derived profiles on the outcome variables.

Results/findings: Five distinct profiles characterised by differing levels of the global and specific forms of motivation were identified: (a) self-determined, (b) internalised, (c) externally motivated, (d) amotivated, and (e) uninterested. Women in the self-determined (57% of women) profile had higher intuitive eating and lower maladaptive eating scores and reported better mental and physical health. Women in the internalised (11%) profile reported better mental and physical health but had mixed results related to intuitive eating and maladaptive eating. Women in the externally motivated (8%), amotivated (11%), and uninterested (13%) profiles tended to have lower intuitive eating and higher maladaptive eating scores and reported lower mental and physical health.

Conclusions: This is the first study to examine motivational profiles for eating that considers both global and specific forms of motivation, and to examine these profiles in relation to important eating behaviours and health outcomes. Motivational profiles with higher self-determined motivation towards eating regulation appears to be beneficial. Therefore, SDT informed eating behaviour interventions that enhance women’s self-determined motivation may lead to improved health and wellbeing outcomes.

Purpose:

Physical activity and eating-related behaviors are central factors in maintaining weight loss. The interplay between the motivation to engage in both behaviors long-term is an understudied, albeit fundamental, topic. A long-term weight loss trial from 2009 described a spill-over effect from exercise motivation to eating behaviors. This current randomized control trial seeks to revisit and expand upon these findings by examining the reciprocal effects between exercise and eating motivation, as well as steps taken and energy intake, over a 12-month period in a large, diverse sample.



Methods:

This is an ancillary NoHoW study, utilizing data from 669 participants from Denmark, UK, and Portugal over a period of 12 months (age 46±11y, 70% women) who had complete data for the target variables. The study collected information on exercise motivation (BREQ3 questionnaire), eating motivation (REBS), steps taken (Fitbit charge 2, 14-day average before data collection calendar day), and energy intake (Intake24, 4 consecutive 24h dietary recalls before data collection calendar day). Data were modeled with latent growth models and cross-lagged panel analysis using Mplus software.



Results/findings:

Both autonomous and controlled motivation models indicate a positive spill-over effect from exercise to eating motivation and vice versa over 12 months. That is, an increase in exercise autonomous motivation is linked to an increase in eating autonomous motivation, and an increase in exercise controlled motivation to an increase in eating controlled motivation. However, the associations were either small or non-existent when it comes to the relationship between motivation and behavior (i.e., steps taken or energy intake). The only exception was that higher initial levels of exercise controlled motivation resulted in higher energy intake after 6 months.



Conclusions:

The results are aligned with previous finding, suggesting a motivational spill-over from exercise motivation to eating motivation for both autonomous and controlled forms of motivation. For controlled, a relation is also found from eating motivation to exercise motivation. This spill-over can be found longitudinally over the 12 months of the study. We did not find spill-overs from specific motivations to behavior, except from exercise controlled motivation to energy intake.

Purpose: Physical activity and sedentary time are independent health determinants among adults. However, whether similar associations are observed in adolescents has been less explored. We aimed to examine the joint associations of moderate-vigorous physical activity (MVPA) and sedentary time (ST) with adiposity and cardiometabolic risk factors in adolescents.

Methods: The baseline data of a prospective cohort study were used. We included 309 adolescents aged 10-16 years (53% girls). Measurements were conducted between 2016 and 2018. MVPA and ST were measured using hip-worn accelerometers for at least 7 days. Adiposity (fat percent) was measured using DXA. A cardiometabolic risk score was calculated from waist circumference, blood pressure, HDL-C, triglycerides, and homeostasis assessment model of insulin resistance (HOMA-IR). MVPA and ST (min/day) were split into high and low categories using their median values, thus forming four groups: High-MVPA/Low-ST, High-MVPA/High-ST, Low-MVPA/Low-ST, and Low-MVPA/High-ST. Multivariable linear regression was used to test the association of group membership with adiposity and cardiometabolic risk adjusting for age, sex, race, and BMI.

Results: Group membership was significantly associated with adiposity and the cardiometabolic risk score (P=0.001). Compared to the High-MVPA/Low-ST group (reference), High-MVPA/High-ST showed no difference in adiposity (β=2.58% [-0.72-5.88], P=0.12) or cardiometabolic risk score (β=1.09 units [-0.04-2.22], P=0.06). In contrast, compared to High-MVPA/Low-ST, the Low-MVPA/Low-ST group showed higher adiposity (β=4.43% [1.17-7.67], P<0.01) and cardiometabolic risk score (β= 1.29 units [0.18-2.40], P=0.02). Similar and more pronounced effects were observed in the Low-MVPA/High-ST group for both adiposity (β=5.49% [2.72-8.27], P<0.01) and cardiometabolic risk score (β=1.96 units [1.01-2.90], P<0.01).

Conclusions: In adolescents, having high MVPA is associated with less adiposity and a lower cardiometabolic risk score independently of ST. Importantly, the negative association with low MVPA are worsened when accompanied by high ST. These joint associations between MVPA and ST highlight the relevance of targeting both behaviors in health interventions in this age group.

Purpose: Action control theories such as the Multi-Process Action Control (M-PAC) framework have potential for explaining maintenance of physical activity (PA) behavior during adolescence when age-related declines typically occur. However, advanced analytical approaches with the capacity to model the relationship between theoretical correlates of PA and PA behavior as a complex dynamical system have received limited attention. Unraveling the complexity of these relationships stands to advance current theorizing and inform intervention development. This study explored the auto-regressive and cross-lagged effects of variables outlined in the M-PAC framework and PA behavior using a cross-lagged panel network model.
Methods: This study used three waves of data from the Canadian ADAPT prospective cohort study. A total of 1,421 adolescents (Mean age = 15.93 ± 0.53 years; 54% female) completed yearly surveys from Grade 11 to one-year post high school graduation beginning in October 2019. Measures assessed the reflective (instrumental attitude, affective attitude, perceived opportunity, perceived capability), regulatory (behavioral regulation), and reflexive (habit, identity) processes outlined in the M-PAC framework, as well as the International Physical Activity Questionnaire-Short Form to assess moderate-to-vigorous PA. Two cross-lagged panel network analyses, adjusted for age, gender, race/ethnicity, parental education, and school, were computed to understand the temporal relationships between variables from Grade 11 to Grade 12, and Grade 12 to one-year post-graduation.
Results: Only unidirectional relationships from M-PAC variables to PA were observed. Affective attitudes (B=4.27), behavioral regulation (B=15.52), habit (B=7.92) and identity (B=4.54) in Grade 11 were significant positive predictors of PA in Grade 12. Affective attitudes (B=20.30), behavioral regulation (B=17.98), and habit (B=13.73) in Grade 12 were significant positive predictors of PA one-year post graduation, whereas an inverse association was observed for perceived opportunity (B=-23.21). Behavioral regulation and affective attitudes were the most influential variables within these models.
Conclusions: PA enjoyment and post-intentional processes appeared to have the strongest influence on PA behavior one year later during adolescence, particularly when transitioning out of high school amidst the Covid-19 pandemic. Future studies should explore these complex relationships at shorter intervals and with device-measured PA behavior to determine whether these effects replicate.