Being there : relationships between people with cancer and their pets : what helps and what hinders
Bibliographic record
Abstract
This qualitative research examined the little studied area of human-pet relationships and their impact on persons with cancer. The goal of this study was to gather information from individuals with cancer who had a pet during their illness and explore the helpful and unhelpful aspects of that relationship as people dealt with the socio-emotional, physiological and spiritual challenges usually accompanying diagnosis and treatment. The Enhanced Critical Incident Technique method (Butterfield, Borgen, Maglio, & Amundson, 2009) was used to gather information and interpret the interviews of 13 British Columbian women with cancer about their relationships with their companion animals. From these interviews, 13 personal accounts were created to give voice to the women’s experiences. The bulk of the data focused on clear descriptions of the ways in which pets contributed to and/or detracted from the participants’ sense of wellbeing during their illness. From this 487 helping critical incidents and 109 hindering critical incidents were formed into 13 categories that represented the areas of impact. In rank order of participation rate the categories are: Companionship & Presence; Emotional & Social Support; Purpose & Role; How Pets are Different from People; Health and Pain Management; Pet Intuition & Adaptability; Being Positive & in the Moment; Pet as Protector & Caregiver; Touch; Unconditional Love & Devotion; Existential & Spiritual Factors; Family Members & Finances, and Caretaking of Sick or Dying Pet. The findings of the study are congruent with the literature from the fields of veterinary medicine, social work, nursing, and anthrozoology in that they confirm the significant and primarily positive impact of the social support, trust and bond experienced by human beings from their companion animals. The results also indicate the distress caused by the lack of resources for pets when they are ill and the suffering caused by pet illness and bereavement. Other unique findings include participants’ experience of their pets as able to intuit subtle changes post-diagnosis and instantly modify their behaviour to attend to their human companions. It is suggested that psychological theory, practice and research engage with further exploration of the relationships between people and their companion animals.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".