Introduction

Obesity: a key public health problem

Obesity is typically defined as a condition of excess or abnormal accumulation of body fat at a level that impairs health.1 Individuals with a body mass index (BMI) of ≥ 30 kg/m² are considered obese. Obesity has been highlighted as one of the top 10 risk factors for global burden of disease.2,3 In 2017, the UK prevalence of obesity was 24.9%, one of the highest rates in Europe.4 In Scotland, where this study was undertaken, the prevalence of obesity increased from approximately 15% in the mid-1990s to 29% in 2017.5 This high prevalence of obesity places a significant burden on health services, with individuals with increased BMI using greater health-care resources than those with healthy BMI.6

Obesity, alongside poor diet and physical inactivity, is a significant contributor to diseases such as diabetes, cancer, heart disease, hypertension and stroke.7 Preventative interventions that are accessible and engaging and successfully improve health behaviours are necessary to reverse current trends. Interventions to date have had limited impact and approaches that are known to work are not always adopted.8 Therefore, novel interventions that incorporate effective approaches are needed.

To inform the background to this study, a literature search was completed on the MEDLINE and PsycINFO databases from inception to 2017 using keywords including obesity, overweight, weight loss, social support, social network, digital health, ehealth, mhealth, physical activity, exercise and diet. A summary of the findings is presented in Chapter 2, Overarching approach: 6SQuID to The HelpMeDoIt! intervention content.

Previous weight loss research

Although obesity has been a major public health issue for years, there is still no consensus on the most cost-effective approach to support individuals to lose weight. The obesity system map9 highlights the complex layers of influence acting to create and maintain current levels of obesity. This links with the multiple interacting domains of the socioecological model that contribute to the problem.10 Research has demonstrated that tackling multiple health behaviours, such as diet and physical activity, can be effective. However, interventions to date have had mostly small or no effects, with longer-term maintenance remaining a key challenge.11

Previous research has shown that theory-based interventions, which specifically link elements of an intervention to outcomes, generally have greater success.12 Despite this, many interventions are not theory based and most do not attempt to take account of the complexity of influences contributing to the development and maintenance of obesity.12 Evidence indicates that intervention effectiveness generally increases with the intensity or amount of intervention delivered (total contact time or number of contacts).13,14 The challenge is how this can be achieved while keeping the intervention cost-effective, as successful interventions often employ intensive, high-cost, one-to-one approaches.13 These interventions have low reach as the intervention is deliverable to only a small proportion of the population. Given the scale of the problem of lifestyle-related illness, it is clear that alternative, cost-effective approaches need to be developed and tested.

Behaviour change: goal–setting, self-monitoring and social support

Guidance from the National Institute for Health and Care Excellence (NICE)15 highlights the importance of developing interventions that are based on theory and identify specific intervention components. A refined taxonomy of 40 behaviour change techniques for physical activity and healthy eating, by Michie et al.,16 highlighted the wide range of approaches used in studies aiming to change lifestyle behaviours. The NICE guidance identified three of these techniques as showing promise for behaviour change, including setting goals, monitoring progress and harnessing social support. Studies employing these techniques have been associated with better outcomes.11,17 Goal-setting and self-monitoring are techniques associated with intrapersonal processes, whereas engaging social support is linked with interpersonal processes. These techniques derive, in the main, from social cognitive theory18 and control theory,19 two of the key theories on which the HelpMeDoIt! intervention is based (described further in Chapter 2).

Goal-setting and self-monitoring (intrapersonal processes)

The important role of goal-setting and self-monitoring is well established in behaviour change research. In a meta-analysis of behaviour change interventions for physical activity and healthy eating, more effective interventions were shown to combine self-monitoring with at least one other technique derived from control theory (e.g. intention formation, specific goal-setting).17 Goal-setting and self-monitoring are two of the most commonly used behaviour change strategies in weight loss interventions, and are typically used in conjunction.20,21 A recent meta-analysis of behaviour change techniques in 48 weight loss interventions found that goal-setting and self-monitoring were the most effective components of the interventions.21 Other intrapersonal processes, which we planned to address within our intervention, included intrinsic motivation, self-efficacy, action-planning22 and implementation intentions23 (described further in Chapter 2).

Social support (interpersonal process)

Social support and its relation to health behaviour change is undertheorised. This is partly because social support is a broad and somewhat loosely used concept; for example, it is an element in the widely used terms of ‘social capital’ and ‘social networks’, which are used to frame ideas about social support.24,25

Social support is multifaceted: there are various types of social support (e.g. emotional, instrumental, informational)26,27 and there are different kinds of support-giving/-receiving behaviours (e.g. reinforcement, encouragement, motivation, feedback, empathy, role-modelling).28 Although it is generally used as a positive construct, social support may also have negative elements, such as bullying or co-dependency.24,29 Minimising negative support, as well as promoting positive support, should be a consideration of behaviour change interventions.29

Social support is also conceptualised in varied ways in terms of who provides the support. Family,30 friends and colleagues,31 influential people within existing social networks,32 and fellow members of groups with a shared behavioural goal (e.g. weight loss, exercise)33 have been found to be effective in supporting behaviour change in alcohol consumption, smoking prevention and cessation, physical activity, diet and sexual behaviour.

There is evidence that using a ‘buddy’ or ‘helper’ can be effective for weight loss. One trial31 found that when people came with a friend to a weight loss programme they were more likely to adhere to the programme, have greater weight loss and maintain weight loss than those who came alone. Another study34 exploring predictors of adherence to a weight loss programme found that having a buddy (family member or friend) led to an increase in programme adherence from 79.9% to 96.1%. In a study35 of 704 participants in a 15-week online weight loss programme, 54% of participants chose to use a buddy, and they lost more weight than those who did not have a buddy. The same level of effectiveness was found whether the buddies were romantic or non-romantic. A systematic review36 of 21 studies supported these findings, reporting that spousal support could be effective for weight loss. These findings identify the important role that a buddy, or helper, could have in supporting weight loss.

Individuals draw on different types of support from different people in their network. For example, they may derive emotional support from a close friend in their network but may choose to recruit a more distant friend for that person’s expertise in a particular area. Family and friends are significant social influences on health behaviour as a result of factors such as intimacy, influence and proximity to day-to-day health behaviours. They are also immediately accessible to participants because this type of support does not entail joining any kind of formal group.

Social support is important in the initiation and longer-term maintenance of behaviour change,13,31,37 and is typically employed and theorised as one of several elements of behaviour change interventions.38 In reviews13,17 it has been identified as one contributing factor to effectiveness, alongside goal-setting and self-monitoring. Common intervention elements theorised to operate in conjunction with social support are self-efficacy,39 perceived control39,40 and social norms.41 Ferranti et al.42 found that social support is positively correlated with healthy diet. Social support is also associated with increased physical activity40,43 and can improve weight loss maintenance,31 encourage health-promoting behaviours and promote well-being.44 There is also evidence that unhealthy lifestyle behaviours are correlated with less social support.15 For many of us, a significant proportion of our social contact is now via digital technologies, and therefore an intervention using this medium to facilitate social support may be useful. In one study45 of an online intervention, despite social support not being specifically promoted as part of the intervention, findings demonstrated that perceived social support from existing social networks and the use of self-regulatory behaviours were strong predictors of improved physical activity and nutrition behaviour. Similarly, Neuhauser and Kreps46 argue that communication that is interpersonal, affective (not just rational), interactive, individually tailored and set within an individual’s social context is more likely than other forms of communication to be effective in changing health behaviour, and that this should be incorporated within new technology- and internet-based interventions. This type and quality of social support would be better facilitated through contact with family and existing friends, rather than anonymous online groups. However, social support from friends and families tends not to be incorporated into the formal design of online behaviour change interventions.

Using technology to influence lifestyle

Emerging evidence in this field suggests that technology-based interventions can be effective, for example texting to promote healthy behaviours.47 A growing body of evidence on web-based interventions employing goal-setting and self-monitoring has demonstrated positive effects on programme engagement and health behaviours.12,48 Mobile apps in particular could be a convenient, potentially cost-effective and wide-reaching weight management strategy.49 There is also evidence that new technologies can be effective with both young and older people.50,51 However, interventions have often been rather simplistic and not based on the best evidence or theory of effective behaviour change.52 The effectiveness of these interventions could be enhanced by incorporating well-evidenced behaviour change techniques and promoting support from an individual’s social network to assist them to achieve health-related goals.

A key driving force behind digital health is the need to move to more cost-effective health-care delivery models. Reviews53,54 of digital health interventions have demonstrated that few evaluations have captured data that sufficiently allow for consideration of economic outcomes and the overall effectiveness and cost-effectiveness of interventions. NICE55 plans to develop a new evaluation system for digital health apps to respond to the recent growth in digital health.

The growing accessibility of internet and smartphones

Technology offers opportunities to deliver behaviour change interventions that can reach a large proportion of the population at a low cost.56 In particular, smartphone apps and web-based interventions can be effective in reaching large numbers of people.47,57,58 In 2017, internet access was available in 88% of UK households.59 Smartphones were owned by 85% of adults, of whom 55% reported checking their phone within 15 minutes of waking.60 Interventions delivered via these technologies have the potential to reach large numbers of people, including ‘Silver Swipers’ (those aged 55–75 years), who were the fastest-growing adopters of smartphones in 2017;60 and those from lower socioeconomic groups, with 73% of people living in Scotland’s 20% most deprived areas having access to the internet.61

Previous research

There are many smartphone apps (and accompanying websites) for weight loss available that incorporate some or all of the key behaviour change features of goal-setting, self-monitoring and social support [e.g. StickK (Brooklyn, NY, USA), www.stickk.com (accessed 1 June 2016);62 MyFitnessPal (Under Armour, Inc., Baltimore, MD, USA), www.myfitnesspal.com (accessed 1 June 2016)63]. However, a systematic review64 of the most popular apps for weight loss (n = 28) found that the majority were of inadequate quality, lacked evidence-based information on weight loss and lacked appropriate behaviour change techniques. Furthermore, although evidence from research-based interventions using new technologies suggested that they could be effective,47,57,58 the interventions were often simplistic and not based on the best evidence and theory of effective behaviour change.52 The effectiveness of these interventions could be enhanced by incorporating well-evidenced behaviour change techniques and promoting support through an individual’s social network (family, friends and colleagues).

There is a need to improve our understanding of how interventions involving new technologies effectively facilitate changes, for example factors such as optimal website design, how to maximise exposure to websites or what type of prompting works best are areas that still require development.65 Particular aspects of new technologies may enhance interventions, such as through higher intensity (e.g. more frequent contact with people in an individual’s social network). This may increase the success of an intervention13 but at a lower cost than traditional methods. Some applications may also allow for more personalisation or individual tailoring of an intervention to suit individual needs, which may also improve success rates.66 However, the evidence base is limited and, to date, somewhat mixed.67 Therefore, although there have been promising signs in this emerging field, such as the potential for high reach and for engaging hard-to-reach groups, there is a need to address research gaps in understanding how new technologies might support or enhance known health behaviour change mechanisms.

Currently available websites or apps for weight loss use various strategies for behaviour change, including elements such as monetary incentives or prizes, competing with others and behavioural goals. Some apps provide an element of social support, such as a chat forum.63 There is some evidence to suggest that online social networks can have a positive impact on health behaviour change.68 However, online users are typically not known to each other and the apps are not designed to harness the ‘offline world’ and the immediate support of family, friends and colleagues. Evidence indicates that support from key individuals in a person’s life is more effective than that provided by anonymous online contacts.13

The perceived value of, and demand for, social support has resulted in many health behaviour change websites having chat forums or bulletin boards, which facilitate support from other users. These provide empathy and encouragement, but may not be able to build on evidence of the importance of who provides the social support and the many mechanisms through which social support can facilitate and sustain behaviour change. None of the resources we explored focused on the combination of elements that we used in our intervention, most importantly social support from key individuals within that person’s social network. These are individuals whom they know well, and who are part of their everyday lives and available to support them when needed, in a sustainable ongoing way.

The summary above has identified goal-setting, self-monitoring and social support as promising behaviour change techniques.69 Although they have featured in a number of apps, for which there is mixed evidence, we have not identified any existing intervention that specifically aims to mobilise support from existing social networks using an application- (app) and web-based intervention. This is the unique aspect of the HelpMeDoIt! intervention, and this is the first study to our knowledge to explore the feasibility of engaging social support from existing social networks, in combination with goal-setting and self-monitoring, in a digital health intervention for weight loss. If brief engagement with an app could catalyse input from existing social connections to support longer-term change, then this could offer a sustainable approach to behaviour change.

Rationale for the current study

Policy

Improving health behaviours is a priority for government. However, current health behaviour change initiatives require improvements in their reach and effectiveness to have a significant impact on the population’s health. The House of Lords Science and Technology Select Committee report on behaviour change8 highlighted that no single approach is likely to be effective in tackling priority health behaviours and that complex interventions addressing multiple levels of behavioural determinants are likely to be needed to bring about sustained change. HelpMeDoIt! is a complex intervention addressing two of these levels: the intrapersonal and the interpersonal.

Economy

Lifestyle-related illness represents a significant cost to the NHS. One-to-one individualised lifestyle interventions are unlikely to yield substantial population-level improvements at a realistic cost to the public purse unless they are highly effective. In comparison, web- and app-based behaviour change interventions can reach substantial numbers at a lower cost. New technologies, such as smartphone apps, present opportunities to promote healthy lifestyles cost-effectively on a large scale.70 Content, covering evidence-based behaviour change components with the engagement of community-based social support resources, can be delivered in an engaging and accessible way.

Evidence base

Although the intervention elements of goal-setting, monitoring and social support are well established, and although new technologies have shown promise, the evidence base is limited and theoretically underdeveloped.50,52 Studies are often limited by small, short-term effects71 and high attrition.12,72 There are significant gaps in understanding how these elements work together, for example how social support operates through personal networks mediated by new technologies, and what impact this has on mechanisms such as monitoring and goal-setting. There is a need to (1) explore the application and mechanisms of goal-setting, monitoring and social support via web and app-based interventions; (2) explore how they interact with each other: and (3) test this type of intervention in both a feasibility and a full-scale effectiveness trial. Feasibility trials of this nature are a necessary first step in developing public health improvement interventions, particularly where mechanisms, such as social support, are not well understood and where technological innovations present new possibilities.

Future impact

The proposed intervention has the potential to have both reach and effectiveness in all socioeconomic groups including those who are traditionally hard to reach. If the intervention were proven effective in a future powered trial, it could be applied to other behaviour change areas and would be universally available through a free-to-access website and/or promoted in specific NHS and community settings across the UK.

Study aims and objectives

The principal element of the HelpMeDoIt! intervention is social support from members of an individual’s close social network. This study explored the promising role of social support in successful health behaviour change, and developed theory concerning the types of social support that participants seek within their personal networks, which individuals they choose, the types of support provided in the context of a web- and app-based environment, the interaction with known behaviour change mechanisms such as goal-setting and monitoring, and the impact that this has on health behaviour change.

The aims of the study were to develop and test the feasibility of an intervention (HelpMeDoIt!) to promote health behaviour change for adults with obesity delivered via an app and website, which (1) incorporated evidence-based behaviour change techniques (goal-setting, self-monitoring and social support) and evidence-based information on weight loss strategies; and (2) delivered this information via a platform that was both usable for and acceptable to participants.

The study was completed in two stages (Figure 1):

• In stage 1 the intervention was developed and piloted with the help of a panel of user representatives to address (1) the engagement and ease of use of the website and app and its success in promoting realistic goal-setting; (2) the acceptability of the social support content; (3) the functionality of the technology and its facilitation of social support from helpers; and (4) the views of the panel on how the intervention might attract and support helpers.
• Stage 2 was a feasibility trial, with an accompanying process and economic evaluation, which aimed to examine reach, feasibility, acceptability and trial parameters for a future effectiveness trial. Findings from stage 2 will help to assess whether or not a larger randomised controlled trial (RCT) is warranted.

FIGURE 1 The two stages of the HelpMeDoIt! study. (Figure not reproduced here; see the original article.)

Key objectives of the study

1. To develop an app- and web-based intervention that enables participants to set and monitor goals and facilitate effective social support (see Chapter 2).
2. To investigate recruitment and retention as well as feasibility and acceptability of the intervention (see Chapters 4–6).
3. To explore the potential of the intervention to reach traditionally ‘hard-to-reach’ groups (e.g. lower socioeconomic groups) (see Chapters 4 and 6).
4. To explore the barriers to and facilitators of implementing the intervention (see Chapter 5).
5. To assess the feasibility and acceptability of different outcome measures for diet and physical activity in this population (see Chapters 4 and 5).
6. To use outcome data (diet, physical activity, BMI) to help decide on a primary outcome and to estimate the potential effect size of the intervention to facilitate the calculation of an appropriate sample size for a full trial (see Chapters 4 and 7).
7. To assess data collection tools and obtain estimates of key cost drivers to inform the design of a future cost-effectiveness analysis (see Chapter 4).
8. To investigate how participants and helpers engage with goal-setting, monitoring and social support using new technologies and how these elements interact within a behaviour change intervention (see Chapters 5 and 6).
9. To develop a conceptual model of how the key mechanisms of goal-setting, monitoring by self and others, social support and behaviour change are facilitated by the intervention (see Chapter 6).
10. To test the logic model and theoretical basis of the intervention in stages 1 and 2 (see Chapter 6).
11. To explore the characteristics of participants’ social networks and the influence social networks have on participant experiences and outcomes of the intervention (note that this was not part of the original funding application and will be published at a later date).
12. To assess whether or not an effectiveness trial is warranted (see Chapter 7).