Purpose: Nutrition and exercise interventions during pregnancy can improve maternal and fetal health outcomes. To increase the number of women who benefit from a nutrition and exercise intervention, effective strategies to improve program adherence need to be evaluated. Based on the theory of self-control and self-regulation, the purpose of the current study was to test and compare the effect of introducing nutrition and exercise sequentially versus simultaneously on program adherence among pregnant women. Methods: Women were recruited at 12-18 weeks gestation and participated until 36 weeks gestation. Women were randomized into one of three interventions: nutrition and exercise introduced simultaneously (N+E), nutrition introduced first followed by exercise (N-First), exercise introduced first followed by nutrition (E-First). For the two sequential groups, the second intervention was added at 25 weeks gestation. Adherence was measured by scoring participants on a weekly basis for meeting the intervention goals (3 goals for nutrition, 3 goals for exercise). All adherence scores were converted to a percentage. An average percent-adherence score was calculated at the end of the intervention. Additionally, adherence was measured as dropout rate. An ANOVA analysis  compared adherence scores and a Chi-Square analysis compared differences in dropout rate. Significance was accepted as p<0.05. Results: Eighty-eight women were randomized, and sixty completed the intervention and were included in the adherence analysis (N+E=17; N-First=20; E-First=23). Average adherence in the E-First group (80.2±14.7%) was significantly higher (p=0.001, ηp²=0.21, observed power=0.93) than adherence in both N+E (60.9±17.9%, p=0.001) and N-First (66.8±16.7%; p=0.028). Although trending towards favouring E-First, there was no significant difference in dropout rate (N+E=41%, N-First=33%, E-First=21%; c² (2, N=88) = 2.91, p=0.23, Cramer’s V=0.18). Conclusion: Sequential introduction of health interventions, including introducing exercise first followed by nutrition, can improve adherence to multiple behaviour change programs during pregnancy.  

Purpose: Increasing people’s motivation to be active is a cornerstone of physical activity behaviour change. In world of limited resources, prevailing dogma is that ‘it is always better to do something than nothing’ in physical activity promotion. Our objective was to examine this assumption using econometric analyses of existing New Zealand physical activity data and to explore the implications that this has for physical activity and wellbeing promotion.

Methods: Using subjective wellbeing valuation, we derived wellbeing values from nationally representative Active NZ survey data (n=52,183). Subjective wellbeing valuation calculates the change in wellbeing associated with achieving a certain outcome and calculates the equivalent amount of income required to produce the same effect. A measure for weekly activity was used in combination with the level of agreement with the statement “I want to take part in physical activities” to derive the wellbeing value. Using adjusted analyses, we explored the relative wellbeing of people who are motivated to be physically active, but are inactive.

Results: Our results indicate that those who are motivated to be active but are inactive, have lower subjective wellbeing than those who are not motivated and inactive ($-11,219).

Conclusion: Interventions that solely aim to motivate people to be active, in the absence of opportunities to be active in the way they want to be, could have a negative or negligible impact on subjective wellbeing. Indeed, these results challenge the view that in physical activity promotion it is always better to do something than nothing; call into question the notion that standalone improvements in motivation to be physically active constitute ‘intervention success’; and re-enforce the need to take an integrated approach to promoting physical activity, particularly if the objective is to improve population wellbeing. 

Purpose: Adolescence is often characterised by unhealthy behaviours such as a high intake of energy-dense, nutrient-poor food and low physical activity levels. During this time, adolescents’ capacity to make their own decisions is increasing, however, parents remain influential in shaping many of their behaviours. This study aimed to explore parents’ views of adolescent health behaviours and identify ways in which parental involvement can be successfully incorporated into interventions to support health behaviour changes in their adolescents.

Methods: Twenty-four parents of adolescents participated in semi-structured qualitative interviews to understand their perspectives on adolescent health behaviours. Data were analysed using inductive thematic analysis.

Results: Six themes were identified which described parents perspectives on their adolescents’ health behaviours: (1)‘My role in maintaining my adolescent’s heath’ describes the way parents run their households and  control their adolescent; (2)‘What I think about health’ describes parents' past experiences and motivations for improving their own and their family’s health; (3)‘My adolescent wants…’ describes parental perceptions of what their adolescent asks them for as well as factors that will make them more likely to engage in healthier behaviours; (4)‘Things outside my control that affect my adolescent’s health’ describes changing exposure to external factors that are having increasing influence on adolescents' health behaviours as they age; (5)‘Negotiating control’ describes the changing dynamics between parents and their adolescents. (6)‘What parents think could help support adolescent health’ describes parents' suggestions for health interventions that target adolescents and ways they think parents may want to be involved.

Conclusions: Qualitative approaches provide a deeper understanding of parental perceptions of family life and their adolescents’ values and priorities. Parents are aware that they are role models to their adolescents and feel responsible for guiding them towards healthy behaviours. However, parents recognise that with their adolescents’ growing independence other factors are becoming influential in their lives and often push against engaging with healthy behaviours. Finding ways to incorporate parental support into health behaviour change interventions targeting adolescents, in a manner that is acceptable to adolescents, has the potential to improve the engagement levels with and effectiveness of such interventions.

Purpose: Sugar-sweetened beverage (SSB) consumption contributes to childhood obesity. Therefore, various intervention studies have been executed worldwide to promote water consumption of younger populations to prevent obesity. However, the Caribbean region, which has the highest average daily rates of SSB consumption, has received little research attention. Therefore, this study’s objective was to test a culturally tailored intervention for children of the Caribbean island Aruba, based on a Western-European school-based social network intervention. We hypothesized that children who are exposed to the intervention will consume more water and less SSB, and have a higher intention to consume more water and less SSB compared to the control group. The study contributes to scientific knowledge in an understudied geographic area and contributes to the field of social network-based behavioral health interventions. 

Methods: A school-based cluster randomized controlled trial design was deployed among 338 children (age M=11; girls 54%). Participating schools were randomly assigned to a treatment group (n=144) and control group (n=194). The tailored intervention lasted eight weeks and consisted of exposing children to peer influencers who were trained to promote water consumption. At pre-intervention, these influencers were selected through sociometric questions. At pre- and post-intervention, children self-reported their water and SSB consumption. 

Results: Preliminary repeated-measures MANCOVA analyses show a significant multivariate interaction effect between time and treatment (V=.047, F(4, 300)=3.714, p=.006, pη²=.047). The univariate outcomes show significant interaction effects between condition and time for water consumption (F(1, 303)=5.334, p=.022, pη²=.017) and for SSB consumption intention (F(1, 303)=8.261, p=.004, pη²=.027) but not for SSB consumption and water consumption intention. However, the observed patterns did not hold in an additional regression analysis conducted to control for differences in consumption at pre-intervention measurement.

Conclusions: Findings indicate that after the culturally tailored social network-based health intervention children consumed more water and have a higher intent to consume less SSB. The patterns of the study are in line with previous research showing that with the power of social peer influence, healthy behaviors can be promoted successfully despite the heavily promoted SSB-brands. Further research is needed to explore the role of initial level of water and SSB consumption.

Purpose: Office working adults represent an at-risk population for high levels of sedentary behaviour (SB), which has been associated with an increased risk for numerous chronic diseases. This study sought to determine the effectiveness of a Health Action Process Approach (HAPA) volitional intervention augmented with tailored text messages to reduce workplace sitting time (primary outcome) and increase specific non-SBs (i.e., standing time, walking time, stretching time, break frequency, break duration). A secondary purpose was to examine relationships among HAPA volitional constructs (i.e., action and coping planning, action control) and sedentary and non-SBs. 

Methods: In this prospective, two-arm, repeated measure, randomized controlled trial, office workers (M_age= 45.18 ±11.33 years) were randomly assigned into either a HAPA intervention (n = 29) or control (n = 31) condition. The intervention group received a single behavioural counselling (planning) session, as well as daily sedentary-related text messages over a 6-week period. Workplace sitting time, time spent in specific non-SBs, and HAPA volitional constructs were assessed at baseline, week 2, week 4, week 6 (post-intervention), and week 8 (follow-up).

Results: Significant group by time interaction effects, that favoured the intervention group, were found for workplace sitting time (p= .003, ɳ_p²= .07), standing time (p= .019, ɳ_p²= .05), and stretching time (p= .001, ɳ_p²= .08) as well as for action planning (p< .001, ɳ_p²= .20), coping planning (p< .001, ɳ_p²= .18), and action control (p< .001, ɳ_p²= .15). Significant relations, in the expected direction, were also found between the HAPA volitional constructs and sitting time, standing time, walking time, and break frequency at all time points (p values< .05). 

Conclusions: Augmenting a HAPA-based planning intervention with text messages can reduce workplace sitting time and increase time spent standing and stretching in office workers.

Purpose: The CHAnGE trial is evaluating the impact on physical activity (PA) and falls of an innovative intervention combining health coaching and activity monitors with a fall risk assessment among people aged 60+. The purpose of the current study was to better understand participants’ experiences of the intervention.

Methods: CHAnGE trial participants received a home visit and fortnightly telephone-based health coaching from a physiotherapist, involving flexible goal-setting, and provision of an activity monitor. Participants for this qualitative study were purposively recruited from the CHAnGE trial for maximum variation in pre-trial PA levels and intervention engagement, and took part in semi-structured telephone interviews. Data were managed in NVivo 12 and analysed by two researchers: (a) inductively to identify key themes using the interpretive description approach, and (b) deductively to determine how the intervention components were functioning in relation to the underlying program theory. The coding frame was co-developed iteratively, and early analyses were workshopped with co-researchers to develop shared understandings of the data and increase interpretive rigour.

Results: We included 32 participants: 22 female (69%), age range 60-82. Most participants (29, 91%) found it highly motivating to receive direct feedback from an activity monitor which quantified progress towards tailored PA goals. The majority (28, 88%) felt that coaches increased their commitment to PA by providing accountability within the context of a mutually esteemed relationship. Qualities deemed most important in the coaches were: empathy and respect, gentle encouragement, professional expertise, friendliness, active listening, and reliability. Key structural characteristics included the regularity and duration of phone contact with a dedicated coach, and an early home visit. Together, these supported relationship-building between participants and coaches. Some participants internalised their coach’s voice and described how the intervention had helped them “lock in” daily goals/activities.

Conclusion: Participants valued the synergistic interaction of flexible program plans/self-directed goals, self-monitoring of progress and regular accountability, guidance and encouragement from experienced, socially-skilled coaches. The data strongly support the concept of ‘therapeutic alliance’ as a crucial mechanism in health coaching.

Purpose:       Participation in physical activity is sub-optimal in women in their middle and older age. This trial aims to establish the acceptability and feasibility of Active Women over 50, a program comprising online information, telephone health coaching and email or SMS support to promote physical activity behaviour change among women aged 50 years and over.

Methods:      Participants were community-dwelling women aged 50+, randomised to: 1) receive the Active Women over 50 program; or 2) wait-list control. Active Women over 50 is a 3-month physical activity behaviour change program informed by the COM-B model of behaviour change and consisting of access to a website, one telephone health coaching session and 8 email or 24 SMS messages. Outcomes were feasibility measures (study methods, intervention uptake), intervention efficacy (number of daily steps), and acceptability (proportion of participants who would recommend participation in the study to another person like themselves post 3 months).

Results:        Sixty-two eligible participants (mean age 59.3, SD7.1; 47(76%) working; 44(71%) had participated in regular structured physical activity when younger) completed baseline measures and were randomised (intervention n=28, control n=34) between May and September, 2019. Recruitment was predominantly by email (n=27,48%), word of mouth (n=10,18%) and social media (n=10,18%). Mean baseline physical activity was 7459(SD=2424) daily steps. One participant did not access the intervention, 27(96%) participants accessed telephone health coaching, 15(54%) opted to receive email messages and 12(43%) SMS messages.

Google Analytics recorded 128 sessions of Active Women over 50 website usage and 640 pages viewed over 3 months. Users accessed the website via desktop computers, mobile devices and tablets, spending on average 5:48mins/session, and viewing 5 webpages/session. The most frequently viewed pages were the home page (22%), “how to be active” page (14%) and “getting started” page (12%).

Conclusions: Women aged 50+ are motivated to participate in a program offering online information, regular messaging and tailored health coaching to increase their physical activity. The high recruitment rate, uptake of health coaching, and engagement with the website suggest the program could be tested in a fully powered RCT, with the potential to be directly scalable and implemented at a population level.