A convenience sample of consumers will be recruited from participating practices. Eligible consumers will be adults aged 30 to 65 years, who can speak English and have regular access to an internet-enabled digital device, such as a smartphone, tablet, or computer. This age range was selected to maximize preventive potential, targeting individuals most likely to benefit from lifestyle changes and screening engagement before the onset of chronic conditions.

Each practice will recruit consumer participants over a 3-month recruitment period. The recruitment process will be multifaceted. Primarily, brochures or posters with QR codes will be displayed in waiting and consulting rooms, allowing individuals to access information via their mobile phones while they are waiting. This QR code links to a webpage where people can register their interest, receive study information, and complete the consent form. Additionally, study information will be disseminated via practice newsletters and/or emails if available. To minimize burden on the participating practices, clinicians are not expected to recruit consumers; however, individual clinicians can opportunistically encourage consumers to consider participation.

All general practitioners and general practice nurses from participating practices will be invited to take part in the preintervention and postintervention interviews and the postintervention survey. Clinician participation will be entirely voluntary. Study information, including a QR code link to the survey or consent form, will be emailed to potential participants by the practice. Additionally, a QR code linking to the survey or consent form will be displayed in the practice staff areas.

As a feasibility study, this trial is not powered to detect statistically significant differences in outcomes. Instead, the sample size was determined to allow for the estimation of key feasibility indicators with acceptable precision [52]. If approximately 50% of participants who consent complete the THRIVE health assessment, with a 10% margin of error at a 95% CI, a minimum sample size of 187 consumers will be required.

In line with previous general practice research [53-57], a cluster adjustment was applied to the sample calculation using an intracluster correlation coefficient of 0.05 [53-57]. With an anticipated 5 participating practices and a design effect of 1.95, allowing for an estimated 15% dropout rate, the adjusted sample size requirement will be 215 consumers. Therefore, each practice is expected to recruit at least 43 participants.

All clinicians from all participating practices will be invited to participate. The clinician sample size will be pragmatic and guided by the study objectives, given the outcomes being measured.

THRIVE was developed through an iterative design process, drawing on principles of co-design [58,59], contemporary behavior change theory, preventive care guidelines, persuasive system design, and principles from nudge theory [60]. In alignment with evidence highlighting the value of motivational communication and self-monitoring [42,43,61,62], nudge design-based principles, such as timely prompts, simplified decision pathways, concise feedback, and guideline-aligned options, are embedded.

Meaningful engagement with community members occurred throughout development. This iterative consultation shaped the platform’s functionality, content clarity, user pathways, notification timing, and overall usability. These refinements aimed to enhance engagement, reduce respondent burden, and ensure that behavioral prompts and decision pathways were intuitive and fit for users’ real-world needs. All consumer-facing content is intentionally designed to be practical and easy to follow, written at a year 7 reading level to maximize comprehension and accessibility [63]. THRIVE is currently only available in the English language. Establishing technical feasibility, core functionality, acceptability, and engagement is important before multilingual versions are developed.

The intervention’s theoretical foundation incorporates the transtheoretical model [64] and the health action process approach [65] to support goal-setting, self-efficacy, and sustained behavior change across different stages of readiness. Preventive action plans and educational content are aligned with contemporary Australian clinical guidelines, including the Royal Australian College of General Practitioners Red Book [66], Cancer Council [67], National Heart Foundation [68], and Kidney Health Australia [69] guidelines. THRIVE follows a continuous update policy, in which content is revised promptly in response to updates to national guidelines or new evidence. All changes are documented using structured version control procedures (Multimedia Appendix 1 [66,68-91]).

THRIVE generates personalized lifetime chronic condition risk estimates using a composite lifetime modeling framework. This model synthesizes demographic variables, behavioral risk factors, family history, anthropometric measures, and selected clinical data based on evidence from Australian and international epidemiological studies. Inputs and effect sizes are derived from hazard ratios, attributable risk fractions, and pooled effect estimates from meta-analyses and high-quality cohort data. Construct validation has been undertaken for risk estimates that have existing short-term (typically 5-year-risk) calculators by benchmarking THRIVE-generated risk scores against these tools, including the Australian Type 2 Diabetes Risk Assessment Tool [70], the Australian Cardiovascular Risk Score [71], and STOP-BANG for sleep apnea [92]. Validation analyses demonstrated moderate (STOP-BANG) to near-perfect (Australian Type 2 Diabetes Risk Assessment Tool) construct alignment with these established tools, and all recommendations are consistent with Australian clinical guidelines [66-69] (Multimedia Appendix 1 [66,68-91]).

Findings from this study, including quantitative engagement metrics and qualitative acceptability data, will inform subsequent model refinement to enhance usability in practice, ensure clinical appropriateness, and integrate into clinical workflows before a future large-scale trial.

THRIVE guides users through lifetime chronic condition risk assessments, facilitates goal setting, and tracks and reinforces progress through behavioral “nudges.” The intervention is largely automated and can be used independently by consumers. Once consumer participants have provided consent and completed the preintervention survey, they receive a personalized email link providing access to the THRIVE platform. The online assessment guides users through a dynamic, user-friendly series of questions tailored to individual responses. Questions incorporate 130 validated risk and protective factors, and participants receive real-time feedback to maintain motivation and minimize attrition.

After completing the assessment, participants access a personalized dashboard that presents lifetime risk estimates for 23 chronic conditions, including cardiovascular disease, metabolic conditions, osteoporosis, sleep apnea, various cancers, eye and kidney disease, and an estimated “medical age.” The medical age score reflects the impact of lifestyle choices on microlife calculations (a microlife is a statistical unit representing 30 minutes of life expectancy gained or lost due to daily habits). Color-coded indicators highlight key contributors to risk. These risk estimates and the medical age-metric personalize lifetime risk estimates. Risk estimates and the “medical age” metric are not diagnostic tools and are intended solely for promoting health education and engagement. Multimedia Appendix 1 [66,68-91] provides a summary of all variables included in THRIVE’s risk-modeling framework, as well as the guideline sources informing action-plan content.

The platform translates risk estimates into actionable guidance using rule-based logic aligned with Australian clinical guidelines [66-69]. After viewing their dashboard, participants can access an automated action plan that provides tailored lifestyle and medical screening recommendations aligned with current Australian guidelines. Recommendations are presented using nudge-informed design principles that simplify decision-making while preserving user autonomy.

Consumers can also access a clinician report that consolidates risk estimates, key health indicators, and recommendations, which they can choose to share with their general practitioner or general practice nurse to facilitate preventive-care discussions. This report also identifies Medicare Benefits Schedule items that the consumer may be eligible to receive to promote access to care. However, clinicians retain full discretion regarding consumer eligibility and the appropriateness of any care activity and associated Medicare Benefits Schedule claims.

Consumers are encouraged to set health goals and may choose to integrate data from wearable devices. They can also complete a quarterly “pulse check,” a brief reassessment that updates their health data, provides refreshed risk calculations, and tailors action plans. To support ongoing engagement, participants retain continuous access to their dashboard and can revisit it at any time to review progress or modify goals. Optional behavioral prompts and reminders are delivered to further support sustained use. Figure 1 illustrates the THRIVE dashboard and platform overview.

As a prototype, THRIVE currently operates as an externally hosted digital platform that is not integrated into electronic medical record (EMR) systems. To align with clinical workflows, patients access study information through QR codes in the waiting room, enabling them to complete the risk assessment before, during, or between appointments. Clinicians will still retain the ability to refer consumers whom they feel may benefit.

As a consumer-facing intervention, THRIVE empowers consumers to share their study involvement with clinicians through the clinician report, should they wish to prompt discussion about preventive care. Behavioral nudges are provided directly to consumers by THRIVE, without the need for clinician input. This direct link to consumers seeks to support general practitioner and general practice nurse workflows by providing health education, personalized recommendations, and ongoing encouragement.

Through the provision of tailored health information and health promotion education directly to consumers, THRIVE aims to improve the efficiency of preventive care delivery, thus supporting general practitioner and general practice nurse workflows. This feasibility phase will explore how consumers and clinicians prefer THRIVE to interface with general practice, and the findings will inform future co-design and staged EMR integration.

The recruitment period will span approximately 3 months, with follow-up data collection and analysis concluding around 9 months from the start of recruitment. Data will be collected from consumer and clinician participants across multiple time points. A mixed methods approach will be used, with qualitative insights complementing and adding depth to quantitative data (Figure 2).

Quantitative data will be collected via self-administered online surveys at baseline and 6 months post enrollment. These surveys will assess outcomes related to acceptability, engagement, and early indicators of effectiveness, including activation and self-rated health. The estimated total time commitment for consumer participants is 75 minutes over 6 months, including participation in surveys, digital assessments, and optional interviews.

Engagement data will be passively collected through the THRIVE platform, including metrics such as login frequency, dashboard views, goal setting, action plan access, and responses to health reminder prompts. Following the postintervention survey, participants will be invited to opt-in to subsequent interviews by providing their contact details. As part of this process, participants will self-report their level of intervention engagement (eg, high, medium, low, or none), to guide sampling stratification. This process ensures that codified (controlled) and identifiable (protected) data are handled separately.

Approximately 18 to 20 consumer interviews (up to 4 per clinic) will be conducted via videoconference, audio-recorded, transcribed verbatim, and complemented by researcher field notes. A qualitative descriptive approach will be used to explore perceptions of intervention acceptability, sustainability, impact, and opportunities for improvement. Final numbers will be guided by data sufficiency. The semistructured interview guide is included in Multimedia Appendix 1 [66,68-91].

Preintervention and postintervention clinicians will be invited to participate in semistructured interviews. These interviews will explore key feasibility domains such as acceptability, sustainability, perceived impact, and optimization strategies. Approximately 8 to 10 clinicians (2 per practice) will be interviewed via videoconference, with sampling guided by saturation. Interviews will be guided by qualitative descriptive methodology. Interview guides are included in Multimedia Appendix 1 [66,68-91]. The time commitment for clinicians will range from 10 to 40 minutes, depending on their level of participation across survey and interview components.

Clinicians will also complete a postintervention survey. The survey includes 15 items rated on a 7-point Likert scale and captures data on intervention acceptability, perceived usefulness, and ease of implementation, impact on workflow, barriers, and summary of use.

The primary focus of this study is feasibility, which will be assessed through consumer and clinician engagement, acceptability, and perceived sustainability (Table 1). A secondary outcome is preliminary effectiveness, evaluated through changes in consumer activation, self-rated health, and disease risk scores.

The consumer baseline survey will also capture factors that may influence engagement with the intervention, including sociodemographic characteristics, perceived disease threat, and trust in the therapeutic relationship. Perceived disease threat will be measured using 4 validated items from the UTAUT2 framework [93], rated on a 7-point Likert scale ranging from “strongly disagree” to “strongly agree” (⍺=0.817). Trust in the therapeutic relationship will be assessed using the Trust in Physician Short-Form Scale [97]. These baseline variables will form the a priori covariate set for exploratory quantitative analyses examining predictors of engagement with the THRIVE intervention and potential signals of change in secondary outcomes. They will also be used to inform question refinement for the postintervention interviews, ensuring representation of diverse experiences and perspectives across engagement levels.

Engagement will be measured using THRIVE usage logs, which automatically record participants’ interactions with the platform. Based on these behaviors over the 6-month study period, participants will be classified into 1 of 5 engagement levels (Figure 2). Individuals who consent but do not initiate or complete the risk assessment will be classified within the “no use” engagement category. This group will be included in follow-up surveys and purposive qualitative sampling to capture barriers to engagement.

Consumer acceptability will be assessed in the postintervention survey using items from 8 of the UTAUT2 domains: performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, trust, habit, and behavioral intention Multimedia Appendix 1 [66,68-91] [49,50,93,98]. The UTAUT2 has been widely applied to evaluate the adoption of consumer-facing technologies [50,93,99,100]. It has demonstrated strong internal consistency (Cronbach α range=0.637‐0.902 across domains) [93] and high reliability to evaluate acceptability (range ⍺=0.837‐0.899) [95]

Items are rated on a 7-point Likert scale, from 1 (“strongly disagree”) to 7 (“strongly agree”), with higher scores indicating greater acceptability. Six questions across 5 domains are shared between the 2 groups, with additional questions tailored to context-specific relevance depending on engagement levels. For example, in the performance expectancy domain, users respond to “I found the THRIVE program to be useful,” while nonusers respond to “I know what to do to stay healthy so I didn’t need this program.”

User participants will complete 18 items across the 8 UTAUT2 domains. Acceptability outcomes will be reported using the following 2 complementary metrics [51]: (1) the mean acceptability score across domains with scores of more than 4 considered indicative of acceptability (ie, responses in the “somewhat agree” to “strongly agree” range) and (2) the proportion of participants whose individual mean scores meet or exceed the threshold, with 70% or more representing a benchmark for acceptable uptake. Together, these metrics provide insights into both the overall perceived acceptability and the consistency of this perception across participants.

Nonuser participants will complete 12 items across 7 relevant domains (excluding “habit,” which is not applicable to those who did not engage with the intervention). The primary purpose of this analysis is to explore the domain-specific barriers to acceptability. First, item-level responses of more than 4 will be interpreted as indicating a potential concern within a specific domain. Second, we will report the proportion of nonusers whose mean domain scores are more than 4 to reflect broader patterns of perceived difficulty or lack of relevance.

These acceptability thresholds align with typical group-level acceptability criteria in other digital health evaluations [101,102] and were established a priori (Table 2).

Clinician acceptability will be assessed in the postintervention survey using 15 items drawn from 6 relevant UTAUT2 domains: performance and effort expectancy, social influence, facilitating conditions, trust, and behavioral intent Multimedia Appendix 1 [66,68-91]. These items reflect perceptions of program usefulness, its impact on care efficiency and/or remuneration, perceived barriers to consumer use, and the use of the clinician summary reports. Four survey items are negatively worded and will be reverse scored before analysis.

Acceptability outcomes will be reported using 2 complementary metrics, consistent with the approach for consumer participants. First, an overall mean acceptability score will be calculated across the 15 items. A mean score of more than 4 will be interpreted as indicating acceptability, representing a tendency toward “somewhat agree” or higher (Table 3). Second, we will report the proportion of clinicians whose individual mean score is more than 4, with 70% or more of participants meeting this threshold considered evidence of general acceptability [51]. These dual metrics allow both group-level and individual-level interpretation of findings. Additionally, domain-specific mean scores and proportions will also be calculated to explore patterns across the 6 UTAUT2 domains.

Perceptions of sustainability will be evaluated through semistructured individual interviews with consumers and clinicians. These qualitative descriptive interviews will explore user experiences, perceived barriers and enablers to continued use, and suggestions for long-term implementation and integration into clinical workflows.

The secondary outcomes are included to explore early signals of the intervention’s potential effectiveness and to inform future trial design. These outcomes include changes in consumer activation, self-rated health, and calculated disease risk scores. Consumer activation will be assessed using the 10-item Consumer Health Activation Index (CHAI), a validated measure of an individual’s knowledge, skills, and confidence in managing their health [96]. CHAI has demonstrated high internal reliability and predictive validity for health behavior change [27,96,103]. Self-rated health will be measured via a single-item rated on a 5-point Likert scale, which is widely used as a proxy for general health status [104]. Chronic condition risk scores will be calculated from data within the THRIVE platform at baseline and at 6 months postenrollment.

Consistent with contemporary guidance for feasibility studies of complex and digital health interventions, such as the UK MRC framework [48], a flexible progression framework will be used rather than a binary go or no-go decision. Feasibility outcomes (engagement and acceptability) will be interpreted alongside qualitative findings to guide iterative refinement of the intervention prior to a future effectiveness trial.

A 3-level progression approach will be applied as follows:

This approach is consistent with the study’s purpose—to inform iterative refinement and future trial design rather than to provide definitive go or no-go criteria.

To ensure analytical independence, all quantitative data extraction and cleaning will be performed exclusively by an independent research officer, who has no affiliation with In2Health Solutions. The PhD candidate will not access any study dataset until the statistical analysis plan (SAP) has been finalized, independently reviewed, and approved by the supervisors (HH, EH, and AB). The SAP will be preregistered and archived on the Open Science Framework prior to data extraction. Analyses will be conducted by the PhD candidate and independently verified by the research officer, with academic oversight provided by the supervision team. All analytical code will be version-controlled, and the SAP will contain the IBM SPSS (Statistical Package for Social Sciences) syntax for multilevel regression models, missing data procedures, and sensitivity analyses.

Descriptive statistics will be calculated for all variables, including frequencies for categorical data and means or medians for continuous variables. Engagement levels will be examined in relation to participant characteristics using nonparametric methods, including the Kruskal-Wallis H test and the Spearman rank correlation. Acceptability scores will be summarized for each domain of the UTAUT2 [49,98] and compared between user subgroups.

The proportion and patterns of missing baseline and follow-up data will be documented as part of the feasibility assessment. Given the descriptive nature of feasibility end points, no imputation will be undertaken. For baseline acceptability data, incomplete responses will be excluded from domain-level mean score calculations using listwise deletion [105]. Missing usage log data will be interpreted as nonengagement rather than missingness.

As a secondary exploratory analysis, multilevel logistic regression models will be used to examine predictors of engagement, with practice included as a random intercept to account for clustering.

Analyses of consumer activation, self-rated health, and chronic disease risk scores will be exploratory and are not intended to test hypotheses or infer causal effects. In the absence of a comparator group, these models will be used solely to identify potential signals of change and to inform outcome selection and sample size calculations for a future effectiveness trial.

To minimize analytic flexibility, covariates have been prespecified a priori and include age, gender, education, employment status, postcode (as a proxy socioeconomic indicator), baseline activation (CHAI), perceived disease threat, and trust in the therapeutic relationship. The practice site will be modeled as a random intercept to account for clustering at the practice level.

The proportion and patterns of missing data will be documented. If missingness exceeds 5%, multiple imputation using predictive mean matching will be applied to secondary outcome models [106]. Listwise deletion will be used for missing baseline covariates where required.

Consistent with feasibility study guidance, no formal adjustment for multiplicity will be undertaken. Effect estimates and 95% CIs will be reported descriptively to explore the direction and magnitude of potential change, without inferential interpretation of statistical significance. Sensitivity analyses for the exploratory multilevel models will include re-estimation under alternative intracluster correlation coefficient assumptions to assess the robustness of clustered models.