1017. Haves vs. Have-Nots in Healthcare Communication: Examining the Paradox Where PLHIV Who Need Quality Discussions with their Providers the Most, Access it the Least
Bibliographic record
Abstract
Abstract Background Quality communication between patients & HCPs is important to help to identify/address treatment gaps. Who initiates this communication may vary, but impact of good quality communication as a marker of successful care has not been fully explored in PLHIV. We investigated whether perceived comfort discussing salient issues with HCPs differed between PLHIV with vs without specific treatment challenges. Methods We analyzed self-reported data for 520 PLHIV from the 2019 Positive Perspectives study from Canada and USA. Engagement in care (low, moderate, high), was modified from the Observing Patient Involvement scale. Using Chi-squared tests, we compared communication barriers among those uncomfortable discussing with their HCP (p< .05). Results Mean age was 39.6 years. Perceived comfort discussing salient issues with HCPs was significantly lower among PLHIV with than without the specified challenges: discussing side effects (those experiencing side effects=50.4%[135/268] vs without=60.7%[153/252], p=.018); discussing privacy concerns (those hiding medications=41.3%[138/334] vs not hiding =66.7%[124/186], p< .001); discussing adherence challenges (those with suboptimal =42.4%[78/184] vs optimal adherence=57.7%[194/336], p=.001); discussing concerns about HIV illnesses (those without viral suppression=43.1%[90/209] vs virally suppressed=64.6%[201/311], p< .001); and discussing impact of HIV on their life (45.4%[100/220] vs 62.7%[188/300] among those reporting vs not reporting that HIV negatively impacts their life, respectively, p< .001). Among those uncomfortable discussing HCP/clinic-related barriers (eg, no time during visits, worried HCP might perceive them as “difficult”) and limited self-efficacy were particularly more prevalent among those with vs without specific challenges (Figure 2). Pooled analysis showed that optimal self-rated health was 33.9%[42/124]; 52.1%[112/215]; and 68.5%[124/181] among those with low, moderate, & high engagement (p< .001, Figure 3). Figure 1 Figure 2 Figure 3 Conclusion Individuals uncomfortable discussing issues with their HCP reported greater treatment challenges. Proactive HCP-driven high-quality communications with all patients is necessary to help address these concerns. Disclosures Patricia De Los Rios, MSc, GlaxoSmithKline (Shareholder)ViiV Healthcare (Employee) Benjamin Young, MD, PhD, ViiV Healthcare (Employee) Marvelous Muchenje, BSW, MSc. in Global Health, ViiV Healthcare Canada (Employee) Nicolas Van de Velde, PhD, GlaxoSmithKline (Shareholder)ViiV Healthcare (Employee) Chinyere Okoli, PharmD, MSc, DIP, ViiV Healthcare (Employee)
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".