Predictors of shared decision-making among treatment-seeking emerging adults in primary care and community addiction and mental health settings: A cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Shared decision-making (SDM) is a process in which healthcare providers (HCPs) and patients make health-related decisions collaboratively, guided by the best available evidence. Previous research suggests that emerging adults (aged 18-29) with mental health concerns might prefer SDM over traditional approaches; however, it remains unclear whether prevalent symptoms of anxiety, depression, or health-related quality of life (HRQL) are associated with the level of SDM that occurs during a clinical encounter. OBJECTIVE: This study explored whether prevalent symptoms of anxiety, depression or HRQL among emerging adults were associated with the perceived level of SDM involvement during a single clinic visit at a primary care or community addiction and mental health (AMH) setting. METHODS: A cross-sectional survey was conducted using a subset of data (emerging adults and their HCPs) obtained from an overarching study on SDM in adults (18-64 years) in Alberta, Canada. Sociodemographic data were collected and reported descriptively. SDM was the primary outcome variable and was measured dyadically (i.e., the mean score between HCPs and patients) using the Alberta Shared Decision-Making Instrument (ASK-MI). Symptoms of patient anxiety/depression and HRQL were measured using the Hospital Anxiety and Depression Scale (HADS) and the EQ-5D-5L. Pearson R correlation matrices were conducted to explore relationships between SDM, anxiety/depression, HRQL, and demographic variables. RESULTS: Forty-two emerging adult patients and 31 HCP dyads were recruited from six community AMH settings and eight primary care settings. The mean SDM dyad rating was 8.69 (SD, ± 2.01), indicating an "excellent" level of SDM. Symptoms of anxiety, depression, and HRQL were not significantly correlated with SDM dyad ratings during the clinic visit. Post hoc analyses showed that patient age was inversely related to SDM dyad ratings; R = -0.34, p = 0.03. DISCUSSION: In this study, emerging adults reported high levels of perceived engagement in SDM, regardless of their HRQL or symptoms of anxiety and depression. However, several limitations, such as the risk of performance bias, should be considered when interpreting these findings. To strengthen the evidence base, future research should aim to address these limitations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".