Digital Competence of Arabic-Speaking Immigrant and Refugee Older Adults Enacting Agency and Navigating Barriers: Qualitative Descriptive Study
Bibliographic record
Abstract
BACKGROUND: Canada's immigrant and refugee older adult population is projected to grow substantially, making equitable access to information and communications technologies (ICTs) vital for enhancing quality of life in older age. Strengthening the digital competence of immigrant and refugee older adults can improve their social connectedness and access to local information. OBJECTIVE: This study explored the digital competence of Arabic-speaking immigrant and refugee older adults, focusing on how they engage with ICTs to meet their information and communication needs and the strategies they use to navigate digital barriers. METHODS: A qualitative descriptive methodology within a social constructivist paradigm was adopted, incorporating triangulated data collection and iterative co-design cycles. The qualitative approach facilitated an in-depth exploration of participants' experiences, skills, and emotions and the contextual factors influencing their digital competence. Data were collected through storytelling approaches, qualitative interviews, and focus group discussions, which were effective in capturing the experiential aspects of aging and technology use. Co-design cycles informed 6 digital learning sessions tailored to participants' immediate learning needs, fostering motivation and engagement and allowing for observation of ICT use. Digital competence was mapped across the learning domains of the Digital Competence Framework for Citizens 2.2. RESULTS: This study engaged 31 Arabic-speaking immigrant and refugee older adults residing in Canada. Most participants had limited formal education (19/31, 61%), lived with family (22/31, 70%), and reported a low income (21/31, 68%). All participants (31/31, 100%) used smartphones as their primary ICT device, whereas few (3/31, 10%) had access to a computer. In total, 3 themes were identified from the analysis, grounded in Digital Competence Framework for Citizens 2.2 competencies on information and data literacy, communication and collaboration, and safety and problem-solving. The themes focused on agency, which is enhanced or constrained using ICTs, impacting older adults' desire and ability to use these technologies to independently meet their daily needs. CONCLUSIONS: Immigrant and refugee older adults require support to navigate digital barriers and gain digital competence. Smartphones serve as a critical tool for enhancing digital agency, which can lead to greater social connectedness and improved access to local resources in older age. The findings will inform the design of future digital competence programs for older migrants, emphasizing community partnership and reciprocal learning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".