The role of the human-canine bond in recovery from substance use disorder: A scoping review and narrative synthesis
Bibliographic record
Abstract
Abstract Recovery from substance use disorder (SUD) is a personal journey that includes connection with self and others, including animals – known as the human-animal bond (HAB). Research shows that canines are the most common type of animal integrated into animal-assisted interventions to support people with SUD. Yet, to our knowledge, there has been no review of the evidence on the role of canines in SUD recovery. The scoping review’s objective was to examine the literature on the human-canine bond’s role in recovery from SUD among adolescents and adults, including how the bond may help or hinder recovery. The review considered records that described the human-canine bond with respect to recovery in any recovery- or therapy-related setting globally. Eleven databases were searched, and 32 sources met inclusion criteria that involved companion dogs, therapy dogs, service/assistance, dogs and others. The thematic analysis across records identified three key benefits of the human-canine bond in SUD recovery: (1) a source of social connection and a conduit for human-to-human social connection, (2) a calming and comforting effect on individuals with SUD that can reduce stress and anxiety, and (3) the human-canine bond as a motivating factor for positive change. Through these themes, the bond may help divert substance use-related thoughts and reduce cravings, bolster engagement in treatment and recovery, and help to decrease and prevent substance use. However, a few articles found no role or a limited role of the human-canine bond in recovery, and challenges and considerations were reported, particularly for marginalized populations (e.g., related to obtaining and maintaining housing, employment, and SUD treatment). Most of the records discussed canine welfare in some capacity. Calls were also made for improved policy, public awareness, and animal welfare.
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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 | 0.016 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".