We followed a series of steps that were aligned to tenets of the behavior change wheel [9], namely, identifying behaviors that needed to change, identifying the potential drivers of and barriers to the behavior, selecting an intervention strategy and discreet behavior change techniques, and specifying an intervention (Figure 2).

A narrative review of the literature was carried out to understand problems associated with treatment management in growth hormone deficiency and to select and specify the target behavior. Literature searches were conducted using CINAHL, Medline, PsychINFO (via EBSCOHost), and the Cochrane Register for Controlled Trials and Systematic Reviews. The following keywords were used: “growth hormone,” “human growth hormone” (MeSH), “child” (MeSH), “adolescent” (MeSH), “patient compliance” (MeSH). Literature was limited to papers written in English and no date restrictions were applied. The reference lists and citations of publications that were identified were also searched for additional papers on the topic.

Underlying barriers and drivers were defined using insights from a 2018 systematic review [18] looking at the range of potentially modifiable factors that have been found to influence levels of adherence to growth hormone treatment; these factors were grouped according to the COM-B framework. The findings from this review provided direction for selecting the types of interventions that would be needed to effectively target these factors in digital interventions.

Intervention options were identified using the behavior change wheel, which proposes nine intervention functions: education, persuasion, incentivization, coercion, training, restriction, environmental restructuring, modeling, and enablement. We used APEASE criteria (acceptability, practicability, effectiveness or cost-effectiveness, affordability, safety or side effects, and equity) [19] to guide our selection of the most relevant intervention functions. We also engaged a team of specialists in health psychology with expertise in behavior change.

Based on the factors identified by Graham et al [18] and the intervention functions that were selected, a list of relevant behavior change techniques was defined to address each COM-B factor.

The full intervention was mapped out, which involved selecting delivery channels (SMS text messages, nurse-led calls, Growlink app), applying the appropriate behavior change techniques to develop content, and designing a personalization questionnaire to tailor the patient experience. In addition, a measurement strategy was designed to evaluate the effectiveness of the intervention.

A narrative review of the literature on growth hormone deficiency treatments found that despite the potential of r-hGH treatment to optimize growth potential, optimal outcomes were not always achieved; it was proposed that poor adherence was a key contributor to this [2,20,21]. The levels of nonadherence that were reported varied, particularly since definitions and assessment methods differed between studies, but with the proportion of nonadherent patients ranging from 5% to 82% across several indications for which growth hormone therapy is used [2] and with 7% to 71% of patients with growth hormone deficiency found to be nonadherent to treatment [18], it was clear that there was room to improve adherence in this population [2]. Adherence to somatropin injections was selected as a target behavior and outcome for the design of the patient support program. Table 1 further describes the target behaviors.

In work relevant to this study, Graham et al [18] conducted a systematic review of pediatric nonadherence to r-hGH treatment using the COM-B framework to identify potentially modifiable factors. Key factors were identified in the review: within the scope of capability—knowledge and understanding of the condition, a lack of understanding of the consequences of missed r-hGH doses, forgetting to administer the medication, or poor administration technique; within the scope of opportunity—inadequate contact with health care providers and the quality of the health care provider–patient relationship, as well as the discomfort and pain associated with daily injections; and within the scope of motivation—the long duration of treatment and dissatisfaction with growth response results.

These findings were largely reflective of the insights gained from our narrative review of growth hormone and adherence literature; they suggested a need to address a range of factors related to patients receiving growth hormone therapy, their caregivers, and growth hormone deficiency and its treatment to ensure optimal adherence.

While all nine of the interventions listed in the behavior change wheel were found to be relevant to nonadherence to treatment in growth hormone deficiency, we selected the five intervention functions that we felt were the most relevant and the most appropriate to address within the patient support program; these were education, persuasion, training, modeling, and enablement. This decision was based on a combination of practical considerations such as affordability and cost-effectiveness as well as on behavior change expertise from a team of specialists in health psychology. Table 2 shows the relationship between the factors identified in the COM-B, intervention functions, and selected behavior change techniques. An expanded version of Table 2 including COM-B categories, intervention functions, and intervention content is available in Multimedia Appendix 1.

The purpose of this paper was to describe the development of a patient support program aimed at supporting patients who have been prescribed Saizen in order to maximize their growth potential. A structured approach based on the behavior change wheel and the COM-B framework was used to identify the drivers of behavior and to systematically explore how these could be addressed through a pharma-funded patient support program.

The final design of the patient support program incorporated a patient-centric digital component featuring an online app linked to the injection device and frequent SMS text message delivery. The digital platform offers a convenient method for patients, caregivers, and health care providers to interact, to share, and to review adherence data for each patient. The addition of SMS text messaging allows adherence reminder messages and intervention content that was designed to address nonadherence to be sent to individual patients. SMS text messages have been successfully used in behavior change interventions as both reminders for appointments or for treatments [22], as well as to deliver interventions to change patient beliefs and to improve adherence [2]. A 2011 meta-analysis [23] of the efficacy of SMS text message reminders showed that they were effective across all age groups; there were also no differences in effect based on the timing of the messages or the rate that the messages were sent [23]. Messaging interventions have been shown to improve adherence to medications across a wide variety of clinical applications including asthma, antiretroviral treatments, and schizophrenia, in both adult and pediatric populations [22,24,25]. The effect of personalized messaging on behavior has also been shown to be more effective than that of nontailored messaging [17]. In line with the recommendations of Yardley et al [16], tailored content may also help increase engagement with digital interventions. In this patient support program, tailored content was achieved through a personalization screening questionnaire designed to determine the content and sequence of SMS text messages and nurse-led phone calls for delivery of the intervention; the online app was also designed to provide personalized adherence feedback.

Personalized telephone calls with a specialist nurse add a human element to the patient support program which may help to support continued engagement. Evidence has shown that nurses can successfully be trained to use behavior change techniques and to implement motivational interviewing techniques by a simple, brief course [26,27]. Nurse-led calls that implement motivational interviewing principles and that teach behavior change techniques have been shown to result in meaningful behavior change [28,29]. In addition, telephone-based support has been shown to be an effective delivery channel for promoting behavior change across different health conditions such as smoking cessation, increasing physical activity, and improving diet [30], as well as demonstrating a positive impact on treatment adherence [31,32]. Research has also shown that, in general, multicomponent interventions are more successful in having an impact on behavior than single-component interventions are [33]. Thus, the nurse-led coaching phone calls are likely to enhance and complement the support provided through the digital components.

Another important consideration for any patient support program is the level of health literacy. Yardley et al [16] argued that digital behavior change interventions should be accessible and engaging for people with low levels of health literacy and should also be acceptable and usable for those with higher levels of health literacy. All content that was developed for the patient support program was reviewed by an experienced health psychologist and writer, and by a creative team to ensure the pitch, tone, and level was appropriate for the range of health literacy levels in the patient group.

Our patient support program will be piloted with the aim of establishing its perceived acceptability and usefulness. The evaluation of the pilot patient support program will be conducted using an observational (real-world evidence) within-subjects design. Three categories of data will be captured: operational data, user experience data, and impact data. The primary outcome will be patient perception of the helpfulness of the patient support program. Secondary outcomes will include change in adherence and change in quality of life over the course of the patient support program, and multiple regression modeled predictors of these outcomes. Finally, data will be captured to identify ways in which various components of the patient support program could be improved, in line with the principles of continuous development in patient support program design, behavior change technique, and digital interventions proposed by Michie et al [34]. These data will be captured during routine operation via the patient support program (such as number and length of sessions), supplementary behavior-changing customer relationship management, and follow-up evaluation surveys.

The patient support program was developed using a systematic and structured approach, by drawing on relevant literature, and using appropriate evidence-based behavior change theories and frameworks. To the best of our knowledge, this represents a novel approach to the development of patient support programs in growth hormone deficiency; however, despite this, the use of the behavior change wheel inevitably required that the intervention development team make subjective and practical decisions regarding the most appropriate strategies and delivery channels. Since there was limited data on the most appropriate intervention channels and implementation of behavior change techniques for this patient population; the team drew from their own experience working in this patient population to guide some of these decisions.

The first part of the design process involved a narrative review of relevant literature. While this review captured a large volume of relevant literature, the methods were not exhaustive. Key search terms were provided, but to ensure that all relevant papers had been captured in an entirely reproducible format, a full systematic review was required. To be efficient, this paper focused, where possible, on meta-analyses and systematic reviews such as [18] which partially summarized large quantities of the literature.

Using the approach outlined by the behavior change wheel, a multicomponent patient support program for patients with growth hormone deficiency (and their caregivers) to achieve their growth potential through adherence using the Easypod connect platform was developed. By incorporating personalization screening questionnaires into the patient support program, personalized intervention messages and nurse-led phone support can be offered to patients. Work is underway to implement and validate the patient support program, to establish whether it can improve adherence in a real-world setting.