Impact of Health Information-Seeking Behavior and Personal Factors on Preferred Role in Treatment Decision Making in Men With Newly Diagnosed Prostate Cancer
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (PC) patients continue to have unmet information needs at the time of diagnosis and are often unable to communicate their preferences to physicians at the time of the treatment consultation. OBJECTIVE: The objective of the study was to determine the impact of health information-seeking behavior (HISB) and personal factors on patients' preferred role in treatment decision making (TDM). METHODS: Participants consisted of 150 men with newly diagnosed PC seen at 2 urology clinics in western Canada. A survey questionnaire was used to gather information on HISB, personal factors influencing treatment choice, and decision control. RESULTS: More than 90% of the participants reported a preference to play either an active or collaborative role in TDM and having either an "intense" or "complementary" HISB. No significant association was found between HISB and preferred role in TDM. Impact of treatment on survival and urinary function and the urologist's recommendation were identified as the 3 main factors influencing the treatment decision. CONCLUSIONS: At the time of diagnosis, the majority of men want to be involved in TDM and have access to information. Our findings suggest that the type and amount of information men want to access are dependent on HISB. Assessing factors having an impact on TDM may prove useful to guide patient-clinician treatment discussions. IMPLICATIONS FOR PRACTICE: This survey provides clinicians with a method to assess information and decision preferences of men with newly diagnosed PC and factors having an influence on treatment choice.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".