Page 89 - ITPS-7-4

INNOSC Theranostics and
Pharmacological Sciences Digital therapeutics for obesity management

significant challenges. Achieving a fully blinded condition, DTx. Moreover, incorporating additional factors such as
akin to placebo-controlled trials for medications, is also genetic predispositions, social and economic circumstances,
difficult. Consequently, new RCT frameworks tailored to and coexisting health conditions could further optimize the
DTx have been developed. These include the multiphase development of personalized DTx solutions.
optimization strategy, sequential multiple assignment
randomized trials, micro-randomized trials, clustered 3.3.1.4. Temporal strategies for intervention frequency
RCTs, unequal allocation RCTs, and control optimization The engagement rate in DTx is significantly influenced
trials. Each of these designs addresses different research by temporal methods for intervention frequency. In
questions, aiming to provide gold-standard evidence in general, an intervention can be applied at three different
clinical medicine. In addition, due to the digital nature of time points: daily, weekly, and monthly. Prior research
these technologies, RCTs for DTx can employ fully digital, using weekly or monthly interventions revealed high rates
innovative designs, incorporating digital enrollment, of attrition. Given that DTx engagement rates impact
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digital intervention, and digital outcome phenotyping, clinical outcomes, it is imperative to take into account
potentially eliminating the need for on-site visits. Table 3 the level of contact between physicians and users. Higher
presents a summary of multiple clinical trials. involvement may be stimulated by daily interventions that
are more intensive. However, users and coaches may find
3.3.1.3. Individual feedback tailoring in DTx a too frequent intervention taxing or tiresome. By using
Personalized PDTs have the capability to provide cutting-edge digital technologies like AI and machine
customized feedback using individualized data across learning to replace tedious tasks with automated services,
various domains, as previously discussed. It has been this can be lessened. 36
demonstrated that this personalized approach is essential
because it significantly impacts engagement with digital 3.3.1.5. Psychological theory for intervention strategies based on
interventions and the potential for sustained lifestyle empirical evidence
modifications over time. However, the majority of While digital health technologies have advanced
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interventions delivered through mobile applications employ significantly, it is essential to evaluate the integration
standardized behavioral approaches (such as reminders of evidence-based behavior change strategies and
for monitoring and appointments, and general health clinical protocols within these modalities. Evidence-
education), utilize content that is uniformly generated, based interventions refer to strategies supported by
or incorporate algorithms that are minimally customized empirical evidence demonstrating their effectiveness and
and focus narrowly on domains like diet, physical activity, accountability. Key psychological interventions, such as
and body weight. 32,33 These approaches have demonstrated cognitive-behavioral therapy, dialectical behavioral therapy,
constraints in engaging participants in the intervention acceptance and commitment therapy, and mindfulness-
and sustaining treatment effectiveness. Therefore, utilizing based cognitive therapy, are well-established in clinical
tailored feedback and adaptive interventions based on practice. Cognitive-behavioral therapy, particularly, is
baseline and/or real-time multifaceted assessments widely utilized across various mental health conditions,
(including behavior, emotions, cognition, and motivation) prompting researchers to explore its expansion through
can enhance both engagement and the overall efficacy of digital platforms. Incorporating these scientifically

Table 3. Summary of clinical trials and studies evaluating the effectiveness of prescription digital therapeutics in obesity
management 28
Study Population Intervention Delivery digital device
Spring et al. 29 Adults with obesity Technology-supported Smartphone, web portal
Nezami et al. 30 Mothers with overweight and obesity, Smart group (mobile Smartphone
children aged 3 – 5 years application-supported)
Spring et al. 31 Adults aged 18 – 65 years Temporally simultaneous intervention Smartphone
Kim et al. 32 Old adults with diabetes (mean age 60) Mobile-based glucose diary Smartphone
Fitzsimmons-Craft et al. 33 Women with eating disorders CBT-guided self-help Smartphone
Lowe et al. 34 Female and male adults with a BMI in Time-restricted eating Smartphone, wearable
the range of 27 – 43 devices
Kim et al. 21 Overweight and obese women adults Human-based digital CBT Smartphone, web portal
Abbreviations: CBT: Cognitive-behavioral therapy; BMI: Body mass index.

Volume 7 Issue 4 (2024) 6 doi: 10.36922/itps.4042