The Relationship between Adult Attachment and Mental Health Care Utilization: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Several studies have shown a relationship between individual attachment and various aspects of treatment utilization in individuals with medical problems as well as mental health disorders. This review systematically evaluates existing literature targeting the relationship between attachment and all aspects of treatment utilization, such as engagement, participation, and completion, in adults with mental health problems. METHOD: A computerized search of PsycINFO, Medline, Embase, PubMed, and Healthstar and a manual search were employed. Of 5733 titles, 105 abstracts were selected. Of these, 18 studies met full inclusion criteria. The quality of studies was evaluated and scored according to 9 characteristics. RESULTS: Most studies supported an association between attachment and treatment engagement and participation. In general, attachment anxiety was associated with higher engagement and participation in services while attachment avoidance was associated with less. Data regarding attachment dimensions and treatment completion were less conclusive. CONCLUSIONS: The review suggests a clear relationship between attachment and stages of treatment engagement and participation in a variety of psychiatric populations and treatments. The 2 attachment dimensions appear to have opposite effects, with possible risks for either treatment over- or underutilization. Clinical implications are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".