Protocol for a Randomized Controlled Trial of Proactive Web-Based Versus Telephone-Based Information and Support: Can Electronic Platforms Deliver Effective Care for Lung Cancer Patients?
Bibliographic record
Abstract
BACKGROUND: Community-based services such as telephone support lines can provide valuable informational, emotional, and practical support for cancer patients via telephone- or Web-based (live chat or email) platforms. However, very little rigorous research has examined the efficacy of such services in improving patient outcomes. OBJECTIVE: This study will determine whether: proactive telephone or Web-delivered support produces outcomes superior to printed information; and Web-delivered support produces outcomes comparable to telephone support. METHODS: A consecutive sample of 501 lung cancer outpatients will be recruited from 50 Australian health services to participate in a patient-randomized controlled trial (RCT). Eligible individuals must: be 18 years or older; have received a lung cancer diagnosis (including mesothelioma) within the previous 4 months; have an approximate life expectancy of at least 6 months; and have Internet access. Participants will be randomly allocated to receive: (1) an information booklet, (2) proactive telephone support, or (3) proactive Web support, chat, and/or email. The primary patient outcomes will be measured by the General Health Questionnaire (GHQ-12) and Health Education and Impact Questionnaire (heiQ) at 3 and 6 months post recruitment. The acceptability of proactive recruitment strategies will also be assessed. RESULTS: It is hypothesized that participants receiving telephone or Web support will report reduced distress (GHQ-12 scores that are 0.3 standard deviations (SD) lower) and greater self-efficacy (heiQ scores that are 0.3 SDs higher) than participants receiving booklets. Individuals receiving Web support will report heiQ scores within 0.29 SDs of individuals receiving telephone support. CONCLUSIONS: If proven effective, electronic approaches such as live-chat and email have the potential to increase the accessibility and continuity of supportive care delivered by community-based services. This evidence may also inform the redesigning of helpline-style services to be effective and responsive to patient needs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".