Can patients be ‘attached’ to healthcare providers? An observational study to measure attachment phenomena in patient–provider relationships
Bibliographic record
Abstract
OBJECTIVES: To develop and assess the validity of measures of patients' attachment-related perceptions of experiences with healthcare providers (HCPs). SETTING: Online survey. PARTICIPANTS: 181 people provided consent and 119 completed the survey (66%). Most participants were women (80%). PRIMARY AND SECONDARY OUTCOME MEASURES: Questions were developed to assess possible attachment functions served by an HCP and patients' attachment-related attitudes towards an HCP. Scales were constructed based on exploratory factor analysis. Measures of adult attachment, therapeutic alliance, perceived HCP characteristics and health utilisation were used to validate scales. RESULTS: Possible safe haven and secure base functions served by HCPs were strongly endorsed. A model with good fit (root mean square error of approximation=0.056) yielded 3 factors: 'HCP experienced as supportive and safe' (SUPPORT, α=0.94), 'HCP experienced as aversive' (AVERSE, α=0.86) and 'more and closer contact wanted with HCP' (WANT, α=0.85). SUPPORT was correlated with positive HCP characteristics and not with attachment insecurity. AVERSE was inversely correlated with positive HCP attributes and correlated with attachment insecurity. WANT was unrelated to positive HCP attributes, but correlated with attachment insecurity. Frequency of HCP contact was related to WANT (Kruskal-Wallis=21.9, p<0.001) and SUPPORT (Kruskal-Wallis=13.2, p=0.02), but not to AVERSE (Kruskal-Wallis=1.7, p=0.89). CONCLUSIONS: Patients attribute attachment functions of secure base and safe haven to HCPs. SUPPORT is related to positive appraisal of HCP characteristics; AVERSE is associated with discomfort in the HCP relationship that is related with perceived HCP characteristics and patients' insecure attachment; WANT is associated with unmet needs for connection with an HCP related to insecure attachment, but not to perceived HCP characteristics. These scales may be useful in studying the application of attachment theory to the HCP-patient relationship.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".