Research questions

The two research questions guiding this work are: (1) “How do digital stories portray cumulative exposures, critical periods, and life-course transitions?” and (2) “What insights can this analysis offer for using digital storytelling to strengthen partnerships among patients, caregivers, clinicians, and policymakers?”

Theoretical framework

We will use the Life Course Health Development (LCHD) model as a theoretical framework to guide our analysis and place the digital stories within stages of the life course: preconception, infancy, childhood, adolescence, early/ middle adulthood, and late/ older adulthood [15,16]. The LCHD model was created as a response to the limitations of traditional biomedical and biopsychosocial models, aiming to provide a more comprehensive understanding of how health develops over a lifetime [20]. It was developed by integrating research from biological, behavioral, and social sciences, and emphasizes the dynamic, interactive, and developmental nature of health across the lifespan [20]. The model is built on principles such as health development, unfolding, complexity, timing, plasticity, thriving, and harmony, which together describe health as a dynamic process shaped by interactions between biology and environment throughout life [21,15]. The model supports the design of interventions and policies that address social determinants of health and promote wellbeing across the lifespan [16,20–22].

The LCHD model recognizes that health trajectories are influenced by cumulative exposures, critical periods, and transitions at different life stages [15,23,24]. “Cumulative exposures” refers to the additive and synergistic effects of repeated or prolonged biological, psychosocial, and environmental influences across the lifespan. Examples include chronic neighborhood disadvantage, sustained caregiving stress, or long term adherence to health promoting behaviors [15]. Over time, these exposures become stacked, embedding risk or resilience into physiologic systems and shaping later function and disease vulnerability [15]. “Critical periods” in the LCHD are windows in which exposures exert disproportionately powerful effects on subsequent development. Examples include prenatal nutrition influencing metabolic setpoints or early childhood attachment shaping stress response [15]. Lastly, “transitions” denotes discrete role shifts or context changes, such as starting school, entering the workforce, receiving a chronic disease diagnosis, or moving into long term care [15]. These shifts recalibrate daily routines, social networks, and resource access. The three temporal concepts intersect with a broader set of LCHD constructs, which include: health development trajectories (the observable arc of functional capacity over time); timing and sequencing (when and in what order exposures and events occur); linked lives (the interdependence of individual trajectories within families and communities); plasticity (the capacity for adaptive change at biological and behavioral levels); agency and intentionality (how individuals and collectives act on opportunities to modify health pathways); and socio-ecological and inequity contexts (the structural conditions that stratify exposure patterns and resources).

Research team and reflexivity

Our research team comprised of master’s-prepared registered nurse researchers (SH, KS) with backgrounds in pediatrics, general medicine, geriatrics and health services research as well as one team member (ML) who is PhD-prepared and the professional DST facilitator who supported the creation of all 105 stories being reviewed for this study. ML’s involvement is primarily to provide additional context to the primary findings of the story analysis. Having been involved in the creation of all the digital stories, he will be able to speak specifically to the initial project goals for each set of stories as well as the creation process for each story, which may inform the life course theory analysis. He will not be involved in the primary coding of the stories but will be involved in the analysis and writing stage. Team members also have experience accessing health systems as patients and family caregivers, allowing us to assess digital stories with an empathetic lens. Therefore, we are well-positioned to conduct this work because of our professional and personal understandings of health systems and healthcare provision. Moreover, our research backgrounds in qualitative and mixed methods work will enhance the quality and trustworthiness of the planned study.

Data corpus

The collection of digital stories that will be analyzed comes from an initiative by Alberta Health Services (AHS) in Alberta, Canada. AHS hosts an online library of short, first person digital stories created in partnership with patients, family members, and healthcare professionals [17]. The initiative’s slogan is: “Real People. Real Experiences. Real Impact.” The publicly accessible repository currently features an array of digital stories narrated by individuals in the Early/Middle Adulthood and Late/Older Adulthood life stage with the stories encompassing every life stage, from fertility journeys (preconception) to children and adolescents navigating acute illness to older adults managing complex, chronic conditions. Contributors’ narratives span a wide spectrum of health experiences, including preventive care, emergency department encounters, long term rehabilitation, palliative care journeys, and family caregiving. Each story explores different social contexts, identities, and relational dynamics that shape health trajectories. As of May 2025, there are N = 105 digital stories published in the repository.

Currently, the repository is being maintained because it is a feasible way for managers, quality improvement professionals, and educators within AHS to embed patient stories and experiences directly into their quality improvement and educational activities. There are over 700 patient advisors with AHS. However, it is not always appropriate or feasible to have patient advisors attend specific meetings or educational opportunities. One of AHS’s main stated goals is to embed the patient voice into education and routine clinical practice context where appropriate [25]. The digital stories provide an opportunity to achieve this goal without being overly onerous on the patient advisor community. Combined, the digital stories have been viewed over 200,000 times, with the majority of those views happening within Alberta. Recently, it has become clear that the Patient Stories playlist has become a resource that has gone well beyond Alberta Health Services. Although the exact numbers of usage in specific contexts are not entirely clear, there has been significant viewership from across Canada and North America, represented in the YouTube viewership statistics. Also, there have been anecdotal reports of the stories being used in all academic nursing and medicine programs across Canada for teaching.

Originally, most of these stories were designed for health care providers to view and learn from, not for patients and families to learn from. However, it has become clear that patients and families also enjoy viewing these stories, and many patient advocacy groups or community support organizations also share the stories in different contexts. With the reorganization of Alberta Health Services recently, there has been a push to trim old programs and services and educational resources. However, there has been a very specific push to keep the patient stories repository as is because of its value to the organization and all the community partners that share these stories on a regular basis.

Setting and context

Although the data corpus of digital stories is limited to Alberta, Canada, the provincial context offers several features that make the collection a broadly informative case for life course analysis. Alberta is home to approximately 4.9 million residents who are distributed across two major metropolitan centres (Calgary and Edmonton), dozens of mid-sized towns, and vast rural and northern regions [26]. The province has one of the youngest median ages in Canada, yet it also contains rapidly growing cohorts of older adults and a sizeable Indigenous population that includes First Nations, Métis, and Inuit communities [27,28]. Almost one-quarter of Alberta residents were born outside Canada, creating a mosaic of cultural and linguistic backgrounds [26]. This population heterogeneity with varied geographic and socioeconomic contexts indicates that health experiences captured in the digital stories encompass a wide range of exposures, critical periods, and transitions that could be transferable to many other settings.

Ethical considerations

This study draws exclusively on digital stories housed in a publicly accessible AHS repository, where all storytellers provided informed consent for their narratives to be posted online. Because storytellers are intentionally identifiable by their first names within the videos, anonymity was not sought; however, their consent to be publicly identifiable was integral to their participation in the repository. As such, we have access to information that could identify individual storytellers during and after data collection, but only in the manner already made publicly available through the repository. Since this project involves secondary analysis of publicly accessible material and no interaction with storytellers or collection of new personal data, formal institutional ethics review is not required under current Canadian Tri-Council guidelines. As well, the only “new” data generated stem from our theory-based analysis using the Life Course Health Development model and do not compromise storyteller confidentiality or alter the original narratives. We received exemption from the University of Alberta’s Research Ethics Office from research ethics board review on August 19, 2025. Responsible data use will be maintained by citing the repository and presenting findings in aggregate form.

Data collection

We will watch each digital story in the repository, taking field notes using a piloted data collection form. We collaborated in-person to complete the data collection form for n = 5 digital stories to ensure that expectations were clear, and the process was standardized. The remaining n = 100 digital stories will be divided between authors to watch and record field notes independently. When recording our field notes, we will use our pre-formulated analytic reflection prompts that accompany each LCHD construct (Table 1 in S4 File) as a guide for elements to record in the data collection form. Table 2 in S4 File presents our inter-rater reliability from when we were piloting the data collection form. We understand these initial results present a relatively low agreement for several LCHD constructs; however, we have reported the results here for transparency. For LCHD constructs which had a lower agreement rating, we discussed on how or why we made our decisions. KS and SH reviewed LCHD literature together in this discussion. What resulted was the decision to create analytic reflection prompts (presented in Table 1 in S4 File) to guide data collectors more clearly in their selection of LCHD constructs.

Data collection instrument

Our unfilled data collection form is included in Supplementary File 1. The form is a fillable document in .PDF format. The form contains a space to record the digital story title, medical condition of storyteller, URL weblink of the digital story, reviewer name for follow-up if required, date of review, life course stage of both the storyteller and the persons receiving care (ranging from preconception to late/older adulthood), a checklist for LCHD constructs present in the digital story, and an open textbox to record narrative field notes.

Data processing

A Microsoft Excel spreadsheet will be created to contain a list of every digital story in the repository. The spreadsheet will contain columns for: digital story title; URL (weblink); medical condition; and life course stage. Data for these columns will be extracted from the data collection forms. Each row will be numbered so that digital stories are assigned a numerical identifier. The data collection form files will be named “DSALC Data Collection_Digital Story X” with ‘DSALC’ being the abbreviated study title (“Digital Storytelling Across the Life Course”) and ‘X’ being a placeholder for the numerical identifier in the Microsoft Excel spreadsheet. These files will then be imported into NVivo 14 [29] for subsequent data analysis.

Data analysis

We will employ a hybrid approach to coding and conduct a directed content analysis [30]. First, we will use a deductive codebook (Table 1 in S4 File) anchored to core LCHD constructs: health trajectory, sensitive/critical periods, cumulative risk and protective factors, plasticity and adaptive capacity, linked lives and intergenerational effects, and timing and environmental context [15,16]. These constructs are further described in Table 1 in S4 File under the “Digital Story Elements” column. The completed data collection forms will identify which of the deductive (‘top-down’) code groups are applicable in each digital story. We will subsequently analyze the recorded field notes from the data collection forms in NVivo 14 [29] and create inductive (‘bottom-up’) codes to capture emergent patterns, specific to Alberta and the Canadian healthcare system (e.g., encounters with universal healthcare, Indigenous Truth and Reconciliation calls, or the expansion of virtual care during the COVID-19 pandemic). The codes created inductively will be sorted under the overarching deductive codebook categories. The data analysis process will be led by KS, with assistance from three undergraduate nursing student research trainees. The undergraduate trainees will review literature on content analysis, be trained on NVivo software, and code the collected data. Team meetings will allow for check-ins with the trainees and debriefing on the coding process to mitigate potential bias. All analysis will then be reviewed and finalized by KS.

Because storytellers are identifiable in the public repository, we will take care to minimize interpretive and reputational harm in our secondary analysis. Our analysis will emphasize cross-story patterns rather than judgments about individual storytellers, and we will avoid speculative interpretations not clearly supported by the narrative content. Findings will be reported in aggregate, with identifying details used sparingly and only when necessary for analytic clarity. Ongoing team discussion during analysis will further support respectful, evidence-grounded interpretation of the stories.

Techniques to enhance trustworthiness

We will use strategies to address the four criteria outlined by Lincoln and Guba [31] to enhance trustworthiness: credibility, dependability, confirmability, and transferability. For credibility, we will meet regularly for peer debriefing sessions to explore one another’s emergent interpretations of the digital stories. For dependability, an audit trail will be maintained in NVivo 14, capturing all codebook iterations. We will ensure confirmability through regular in-person meetings. Prior to completing full data collection or analyzing all data, we will collaborate in-person to ensure our methods are standardized and consensus in our approach is achieved. Lastly, for transferability, we will offer thick description of the Alberta setting, storyteller demographics, and health system features so readers can judge the applicability of results to their own contexts. We will also explicitly interpret findings in light of the repository’s contextual specificity as a publicly curated, provincial collection within a single Canadian health system. Rather than claiming broad generalizability, we aim to support analytic transferability to settings with similar patient engagement infrastructures, storytelling initiatives, and health system contexts.

Data management

Our data management plan is guided by the Alliance Template for Qualitative Health Sciences Research [32]. All digital stories are housed in the online, open access AHS Patient & Family Storytelling repository [17]. Data collection forms, NVivo project files, reflexive journals, and audit trail materials will be stored on the University of Alberta’s encrypted research server while carrying out the study. For long term preservation, we will store the data collection forms, codebooks, and analytic memos on Open Science Framework (OSF.io) under a CC-BY 4.0 licence. Our public OSF project page where data will be made available can be accessed at https://osf.io/rcun2/. NVivo codebook files (.NVPX) will be exported to preservation-friendly.XML and.CSV formats before deposit. Original videos will not be redistributed because the copyright remains with AHS. Therefore, interested researchers will be directed to the AHS public repository for viewing.

Timeline

Data collection of field notes from the repository of digital stories is ongoing. We expect to be complete data collection activities by March 31, 2026. We expect our analysis and final report to be prepared by July 31, 2026.

Implications for practice and policy

Findings will be positioned to guide clinical practice by identifying how patient narratives can be used to initiate life course-sensitive conversations (e.g., asking adolescents about identity milestones or older adults about caregiving transitions). For health system leadership, our study will offer an evidence base for investing in DST platforms as vehicles for continuous patient-partnered learning. Among underrepresented groups, it could be recognized that patient engagement work, such as DST, could accelerate health equity goals. At a broader level, illustrating how lived experience narratives align with LCHD constructs will support the inclusion of life course perspectives in health system chronic disease strategies and patient safety frameworks.