A Web-Based Study of Dog Ownership and Depression Among People Living With HIV
Bibliographic record
Abstract
BACKGROUND: People living with human immunodeficiency virus (PLHIV) are approximately twice as likely to be depressed compared with HIV-negative individuals. Depression is consistently associated with low antiretroviral therapy (ART) adherence, an important step within the HIV care continuum related to HIV disease progression and overall health. One factor that may have positive psychosocial benefits and promote ART adherence is dog ownership. Research indicates that dog ownership is associated with lower depression, and initial evidence suggests its positive impact on psychosocial outcomes for PLHIV. OBJECTIVE: The aim of our study was to expand the existing research by examining the relationship between current dog ownership and depression for a sample of PLHIV while controlling for demographic characteristics and other potential confounders. METHODS: Participants aged 18 years or older and who self-reported an HIV diagnosis were recruited via social media into When Dogs Heal, a cross-sectional Web-based survey to collect data among adult PLHIV. The research visit was conducted via a Web-based survey, and there was no in-person interaction with the participant. Primary outcome measures included demographic questions (age, race, ethnicity, gender, and sexual orientation), pet ownership (type of pet owned and current dog ownership), depression (Center for Epidemiologic Studies Depression Scale, 10 items), and resilience (Resilience Research Centre Adult Resilience Measure, 28 items). RESULTS: A total of 252 participants were enrolled into the study in January 2016, with a final analytic sample of 199 participants. Mean age was 49 years, 86.4% (172/199) of participants were male, and 80.4% (160/199) were white. Current dog ownership was prevalent among the sample (68.3%, 136/199). Bivariate analysis indicated that there was no significant relationship between depression and demographic characteristics (age, race, ethnicity, gender, and sexual orientation), with P>.05. The multivariate logistic regression, including age, race, ethnicity, gender, resilience, and current dog ownership, was significant, with P<.001. Of the 6 predictor variables, only 2 were statistically significant: dog ownership and resilience. Noncurrent dog owners had 3 times higher odds of depression in comparison with current dog owners: odds ratio 3.01; 95% CI 1.54-6.21. CONCLUSIONS: Growing evidence suggests that dog ownership reduces the likelihood of depression and, therefore, may confer long-term health benefits on PLHIV. Future studies should explore whether dog-specific interventions are a feasible and efficacious intervention to improve outcomes among PLHIV.
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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 | 0.000 | 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".