Background
Lifestyle interventions that include a focus on dietary change, increasing physical activity, and behavioral strategies can produce clinically significant weight loss and improve quality of life [
1‐
3] and therefore are recommended in current obesity guidelines [
4]. However, nationally representative data suggest that only a small portion of adults with obesity (< 10%) use weight loss interventions [
5]. Even in settings where interventions are readily available at low or no cost, a large majority of eligible individuals do not take the first step of initiating weight loss interventions [
6‐
8]. Low initiation of evidence-based weight loss interventions limits the ability of these interventions to impact population-level weight [
9,
10].
To increase initiation of evidence-based weight loss interventions among adults with obesity, facilitators of and barriers to initiating interventions must be identified. There is substantial literature focused on attrition from weight loss interventions [
11,
12], however, this literature is of limited value for addressing intervention initiation because the factors that lead to intervention initiation may be different from those that lead to discontinuation. Indeed, several theoretical models of behavior change differentiate between factors involved in initiation and maintenance of behavior [
13,
14]. For example, Rothman suggests that initiation of a health behavior is determined primarily by favorable expectations about outcomes of behavior change, whereas maintenance of behavior is determined by satisfaction with achieved outcomes [
13]. Another body of literature focuses on the facilitators of and barriers to engaging in the weight loss behaviors of dietary change and exercise (independent of intervention use). However, this literature is limited in its ability to address reasons for initiating weight loss interventions; joining a weight loss intervention involves many elements in addition to dietary change and exercise (e.g., group meetings, prescriptions to track food) and therefore likely has distinctive barriers and benefits.
We are aware of three studies that specifically address barriers to weight loss intervention initiation [
15‐
17]. All asked participants to endorse items from a list of potential barriers to intervention use. These studies revealed some potentially important intervention barriers, such as cost, stigma, concerns about group format, and concerns about intervention effectiveness. However, because these studies used close-ended surveys, they did not provide participants the opportunity to identify barriers outside of those queried about by the researchers; thus, it is possible that important barriers are missing from this research. The use of close-ended surveys in these studies also limits the details available about the identified barriers, decreasing the usefulness of this information for developing approaches to address low treatment initiation. For example, one study identified negative feelings towards interventions as a barrier to intervention use, but did not specify the nature or source of those negative feelings [
15]. Additionally, these previous studies did not focus on the potential benefits of interventions. Obtaining information on what adults with obesity see as the benefits of interventions will be crucial to inform strategies to increase intervention initiation among this population. Thus, in the current study, we aimed to describe the range of reasons that adults with obesity provide for initiating or not initiating evidence-based behavioral weight loss interventions. To do this, we conducted focus groups with individuals who had recently chosen to try to lose weight with the assistance of evidence-based behavioral interventions (“intervention initiators”) or without the assistance of any formal intervention (“intervention non-initiators”).
Methods
Design, setting, population, and recruitment
We used a stratified purposeful sampling approach. We conducted one-time focus groups with intervention initiators who had chosen to initiate behavioral weight loss interventions in the past year and separate groups with intervention non-initiators who had not used any weight loss interventions for at least the past 5 years. Focus groups were used because the topic was initially perceived not to be sensitive in nature, and because focus groups offer greater convenience. We additionally conducted individual interviews with intervention non-initiators to allow us to go in to greater depth about topics that were raised during the focus groups and to see if other themes would emerge given the additional privacy afforded by interviews. Initiator and non-initiator focus groups were conducted separately given that the different experiences of the participants with regard to weight loss interventions necessitated that some questions differ between the two groups.
Participants were recruited from an academically-affiliated primary care clinic; a commercial weight loss intervention center (Weight Watchers); and the VA-based weight loss intervention program called MOVE!, all in Durham, NC. Intervention non-initiators were recruited from the primary care setting and intervention initiators from all three settings. Weight Watchers and the VA MOVE! program were selected as recruitment sites because they are evidence-based programs [
6,
18,
19] that represent different intervention approaches and cater to different populations. Evidence-based intervention was defined using the American College of Cardiology/American Heart Association Task Force 2013 guidelines for the management of overweight and obesity in adults [
4]. In particular, we considered an intervention to be evidence-based if it contained components focused on diet, physical activity, and behavioral strategies and was conducted by a trained interventionist and provided opportunity for repeated sessions. Among other differences between the two programs from which we recruited, participation in the VA MOVE! Weight Management Program generally required a provider referral at the time of our study, whereas Weight Watchers did not.
To identify primary care patients, electronic health records were used to extract contact information of patients who met eligibility criteria for age, BMI, and contraindications to weight loss, and who had a primary care appointment in the previous 2 months. These patients were sent an informational letter and were proactively called for further screening if they did not opt out. Participants recruited at weight loss programs were informed of the study via an announcement at the beginning of a class and were called by telephone for screening if they gave permission and contact information.
Inclusion criteria included age 18–70 and BMI ≥ 30 kg/m2 based on self-reported weight and height. Because we were interested in why individuals attempt weight loss with assistance from an evidence-based comprehensive intervention versus attempt weight loss on their own without formal assistance, we excluded people who had made no weight loss attempt in the past year (i.e., those who responded negatively to “Have you tried to lose weight in the past year by changing your diet or physical activity level?”). We focused on the past year so that participants would be more likely to recall their experience of choosing to use or not use a weight loss program. Exclusion criteria included conditions contraindicated for weight loss (e.g., pregnancy, cancer in past year) or bariatric surgery in past year. An additional inclusion criterion for intervention initiators was that they had used an evidence-based formal weight loss intervention in the past year (with evidence-based intervention defined according to clinical guidelines presented above). Individuals were eligible if they used a group or individual format interventions. Intervention non-initiators were required to have no use of evidence-based formal interventions in the past 5 years. A five-year time frame was selected to create a clear distinction between intervention initiators and non-initiators.
Procedures
Focus groups and individual interviews were conducted on the academic medical center campus. Group discussions lasted approximately 90 min, and individual interviews lasted about 30 min. Groups and individual interviews were moderated by the first author, who had no clinical relationship with participants. All focus groups and interviews were audio recorded and later transcribed. We planned a priori to conduct three focus groups for initiators and three for non-initiators, and then to evaluate if this number of groups was sufficient to achieve informational redundancy and conduct more as needed. At the end of each focus group and interview, two authors reviewed themes that emerged. No new themes were raised in the third wave of groups, indicating saturation had been reached. However, we elected to conduct individual interviews of non-intervention initiators after considering that participants might be reluctant to share in a focus group setting their concerns about group-based interventions. We determined that saturation was reached by the end of eight interviews and thus did not conduct more.
A semi-structured moderator script was used to guide discussion (see Additional file
1 for script). This script was developed based on a qualitative content analysis approach, a method for interpreting textual data through a systematic classification process [
20]. The moderator script for initiators and non-initiators differed as a consequence of the different histories these groups had with weight loss interventions. We began the non-initiator discussions by asking what led participants to try to lose weight in the past year without intervention. We then provided a definition of evidence-based intervention. We asked them to think about evidence-based interventions delivered in a group setting and to discuss what it would take for them to join such a program as well as what concerns they might have about doing so. We chose to focus on group format interventions given that they are the most common and often most cost-effective intervention approach. We also asked about telephone and internet-based treatments, but that data is not presented here.
We began the initiator groups by asking them to discuss what led them to join a weight loss intervention. When it was not spontaneously addressed, we probed about the role of learning more about diet, physical activity, social support, and motivation. We also asked the initiator groups what barriers they had to overcome before joining a program.
For initiators and non-initiators, we next queried about the following specific barriers to intervention based on past research in the areas of behavioral intervention initiation, weight management more generally, and the authors’ experiences: embarrassment discussing weight, interacting with others, time/scheduling conflicts [
16,
17], cost [
17], support from family/friends [
21], intervention asking them to do things they do not wish to do (self-monitoring, exercising more than they want to) [
22], and who would lead the intervention. The moderator guide was created by two study authors and was reviewed by other study authors. We pilot-tested the guide with a small focus group (data not analyzed) and refined the interview guide by re-wording and re-ordering questions before collecting the data reported herein.
Data analysis
A conventional content analysis approach was used to analyze the data [
20]. Focus group and individual data were analyzed with the same approach and presented together, consistent with the study goal of generating as many perspectives as possible. All transcripts were placed into qualitative data management software (Atlas.ti, Version 7.5). Two coders with backgrounds in social and clinical psychology independently coded the first transcript using open coding, allowing codes to emerge from the data, then compared and reconciled codes. They repeated this procedure for approximately 60% of the transcripts in order to develop a taxonomy of consensus codes. The coding scheme was then applied to the remaining transcripts by a single coder. After reviewing codes, both coders identified subthemes that emerged from the codes and higher-order themes emerging from the subthemes. A matrix was created to compare presence of specific codes by intervention initiation status for each subtheme. Quotes in this manuscript (provided in tables) were chosen to be illustrative of the subthemes.
Discussion
Effective interventions to help individuals lose weight are underutilized. Only a few previous studies have examined the perspectives of adults with obesity on barriers and benefits to weight loss intervention initiation [
15‐
17], and those studies queried participants about a narrow range of possible barriers to intervention use and did not address potential benefits of intervention use. In the current study, we aimed to describe the breadth of benefits and barriers to initiating evidence-based weight loss interventions as perceived by a diverse sample of adults with obesity who have recently tried to lose weight, either with or without the help of a formal weight loss intervention. Our data revealed several novel facilitators and barriers to intervention initiation and identified potential differences in perspectives between intervention initiators and non-initiators.
Reasons for intervention initiation reported by participants were aggregated in to the broad themes of practical factors, anticipated intervention effectiveness, and anticipated pleasantness of interventions. The theme
anticipated effectiveness of intervention related to participants’ sense for how well an intervention would work for them, and the factors that influenced that. This theme has some conceptual overlap with constructs from several theoretical models, including
perceived benefits of health behavior from the Health Belief Model [
23] and
outcome expectancies from Social Cognitive Theory [
24]. Anticipated effectiveness was also suggested as a determinant of intervention initiation by past research. Specifically, Tinker and Tucker found that the most highly cited barrier to intervention initiation was the belief that individuals could lose weight as well on their own as with an intervention [
15]. However, that study, and existing theory, do not provide information on what factors influence perceptions of effectiveness. In this study, we found that intervention initiation is favored when content is perceived to be individualized and addresses individuals’ perceived needs; when social aspects of an intervention that are perceived to increase intervention effectiveness are present (such as a leader to increase accountability); and when sources of evidence for an intervention’s effectiveness are trustworthy (such as a recommendation by a health care provider). There was some evidence of a potential difference between initiators and non-initiators in perceptions of intervention effectiveness. Of particular note, non-initiators were concerned that intervention would not be individualized or would not offer them any new information, whereas initiators, who predominantly enrolled in group-based interventions, did not express this concern.
Anticipated pleasantness of interventions also emerged as a theme from our data. This theme primarily focused on negative experiences that individuals anticipate with interventions. There is some conceptual overlap of this theme with The Health Belief Model construct
perceived barriers to health behavior. Negative or unpleasant experiences have also been identified as a barrier to dietary change or intervention in past empirical literature. For example, Burke et al. reported that some weight loss intervention participants found self-monitoring burdensome [
22] and numerous studies report that taste preferences can be a barrier to changing diet [
25,
26]. Additionally, Ciao et al. [
16] identified shame and stigma as barriers to weight loss intervention use in a small portion of their participants. However, the current study provides a fuller picture of the potential unpleasant experiences that concern intervention initiators and non-initiators. Unpleasant experiences of concern included discomfort with social aspects of intervention (e.g., fear of judgement), dislike of anticipated dietary recommendations, and worry about needing to disclose sensitive information in a group. Whereas past research identified that dietary tracking and eating less preferred foods could be viewed negatively [
22,
25,
26], the current study is the first to our knowledge to identify the role of dietary monitoring and taste preferences as potential barriers to initiating interventions. We also found that differences emerged between intervention initiators and non-initiators related to anticipated pleasantness. For example, non-initiators reported a desire to avoid relying on others for weight loss and to maintain their autonomy, whereas initiators reported that intervention initiation was facilitated when they recognized a need to get help in order to lose weight.
We also identified
practical factors as a theme. Practical barriers such as cost have been identified in previous studies on intervention use barriers [
16,
17] and these factors are consistent with the construct
perceived barriers of health behavior within the Health Belief Model.
These results may inform strategies for increasing initial engagement in weight loss interventions. Two distinct approaches to increasing intervention initiation can be informed by results of the current study. First,
intervention-focused approaches involve changing some aspect of an intervention to increase the chances of initiation. For example, a barrier to intervention entry described by some of our participants was intensive dietary tracking, which is common in evidence-based programs. Interventions that offer simpler tracking approaches may be more appealing to some patients. Previous research suggests that simpler self-monitoring approaches can be effective for increasing adherence and weight loss [
27,
28], suggesting that offering approaches that utilize these simpler self-monitoring methods might be valuable for increasing intervention uptake. As another example, our results suggest that some individuals are seeking a physical activity-focused approach to weight loss and are not drawn to existing interventions that primarily focus on diet. Greater intervention enrollment might result if intervention options were available that placed greater emphasis on physical activity. It is notable that some individuals’ intervention preferences, such as greater emphasis on physical activity or less dietary tracking, may make the intervention less effective. Potentially, offering interventions that are less effective than the gold-standard intervention approach (while still more effective than no intervention) could increase population weight loss if the greater uptake offsets the lower weight loss per person.
The other potential set of approaches to increasing intervention entry are individual-focused approaches, which focus on addressing individual barriers and facilitators to entering existing evidence-based interventions. For example, some non-initiators felt that they already knew everything that an intervention would tell them. Thus, when communicating to individuals interested in losing weight, it may be important to communicate that an intervention is valuable for providing motivation and support, rather than just knowledge. Efforts to increase initiation could involve providing education on the evidence for relatively greater importance of diet compared to physical activity for weight loss. Given the variability we observed in intervention preferences and barriers to interventions, offering several types of interventions, or interventions that can be customized on important dimensions, may lead to greater uptake.
There are several limitations to this study. Although we compared initiators and non-initiators, there were some differences in the prompts that were used between the two groups, due to differences in their history of intervention use. Our intervention non-initiator group included people who may have used an intervention more than 5 years ago; different results might be obtained with only individuals who have never used intervention. Because our interview script asked specifically about group-based interventions, our data may not have captured factors that would differentially affect the decision to enter a one-on-one intervention. Individuals not represented in our study, such as those who attended one-on-one programs, may have perspectives that we did not observe in this study.
Finally, although there is some evidence that intervention initiation differs by race and gender [
29‐
31], this study was not designed to examine gender and racial or ethnic differences. It is notable that a few of the factors relevant to intervention initiation identified in this study differ across races in the general US population, and thus could contribute to racial differences in intervention initiation. In particular, we identified that obtaining a referral from a trusted health care provider could facilitate intervention entry; given that African Americans on average report greater distrust of health care professionals [
32], lower trust may contribute to racial differences in intervention initiation. Similarly, we identified cost as a barrier to intervention entry; given mean differences in wealth between African Americans and white Americans, this cost barrier could also contribute to racial differences in intervention use.