The contribution of interactive health communication (IHC) and constructed meaning to psychosocial adjustment among women newly diagnosed with breast cancer /
Bibliographic record
Abstract
L'auteur a accordé une licence non exclusive permettant à la Bibliothèque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par télécommunication ou par l'Internet, prêter, distribuer et vendre des thèses partout dans le monde, à des fins commerciales ou autres, sur support microforme, papier, électronique et/ou autres formats.L'auteur conserve la propriété du droit d'auteur et des droits moraux qui protège cette thèse.Ni la thèse ni des extraits substantiels de celle-ci ne doivent être imprimés ou autrement reproduits sans son autorisation.Conformément à la loi canadienne sur la protection de la vie privée, quelques formulaires secondaires ont été enlevés de cette thèse.Bien que ces formulaires aient inclus dans la pagination, il n'y aura aucun contenu manquant.the women who participated in this study and whose bravery in the face of extreme adversity was inspirational.Special thanks to Mariene, Judith, and Renée for their profound insights into the breast cancer experience. 1 was extremely fortunate to work with Dr. David Fleiszer who provided an example of the highest level ofintegrity 1 could -hope to attain. 1 am in awe ofhis devotion and steadfast dedication to help women stricken with breast cancer.Dr. Fleiszer and 1 began collaborating in 2001 to implement patient education programs using the OIES software for breast cancer patients in the Cedars Breast Clinic.Dr. Fleiszer provided me with access to numerous resources to collect data for my dissertation including a modern room fully equipped with a computer, internet, and the latest in technology where 1 could privately interview and train patients.These resources-are scarce in today's overburdened clinics. 1 was also provided access to a photocopier, fax machine, and printer, which made my work infinitely easier, particularly considering the 15 months 1 worked on site. 1 am also grateful to Dr. Fleiszer and the Cedars Breast Clinic for the wonderful collaborative support oftheir receptionists and nurses.My co-supervisor, Dr. Bruce M. Shore, provided me with support and treated me with respect and kindness.While wearing many hats, hewas always accessible and has my sincere appreciation for providing the fastest tum around time known to man allowing me to create and produce the dissertation in final form within three months following completion of my statistical analysis.Dr. Carmen Loiselle, my co-advisor, education.1 was successful in this competition and was awarded an FRSQ-FCAR Santé doctoral bursary.The "Programme de bourses de formation de 2e cycle (doctorat) en recherche en santé" (86150), provided me with a $26,666 award (see Appendix F) for which 1 am most appreciative.1 am indebted to Dr. Veronika Huta for her statistical expertise, constant encouragement and friendship.Without Veronika's guidance 1 could never have entered my burgeoning data set into SPSS format, coded, scored, analyzed and written up within two months.Dr. Brenda McGibbon-Taylor, herselfa breast cancer survivor, helped with the final phase of the statistical analysis.Brenda also introduced
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".