Bibliographic record
Abstract
Hoarding, which includes the excessive acquisition of, and inability to discard, numerous possessions, is a debilitating mental health condition and is associated with significant family dysfunction and burden on family members. Currently, little is known about the effect that family members have on individuals‟ hoarding symptomatology and functioning, and vice versa. Thus, the present study examined the nature and frequency of family accommodation (i.e., the process by which family members participate in hoarding symptoms or modify personal and family routines in response to an individual‟s symptoms; Calvocoressi, Mazure, Stanislav, et al., 1999), in 52 individuals with self-reported hoarding problems and their close significant others (CSOs; i.e., intimate partner or family member). Participants completed the Family Accommodation Interview for Hoarding (FAI-H), which is an 11-item clinician-rated interview that was adapted from a previously validated measure for this study, and a series of self-report questionnaires. The FAI-H was found to be a valid and reliable assessment of accommodation in this hoarding sample. Most CSOs reported engaging in at least some accommodating behaviours; however, CSOs who lived with the individual with the hoarding problem engaged in accommodating behaviours more frequently than those who did not live with the individual with the hoarding problem. More than half of the CSOs endorsed hoarding participant-driven, as well as personally-driven motivations for engaging in accommodating behaviours, and believed that their accommodating behaviours were reasonable or helpful for both the individual with the hoarding problem and themselves. Family accommodation was positively associated with hoarding symptom severity, relationship conflict, CSOs‟ rejecting attitudes toward the individual with hoarding problems, relationship problems, impairment in activities of daily living, and hoarding participant-rated anger. Family accommodation partially mediated the association between hoarding symptom severity and relationship conflict, averaging across hoarding participants and CSOs, and between hoarding symptom severity and impairment in activities of daily living for individuals with hoarding problems, but not CSOs. Results of the present study further elucidate the role of accommodation in hoarding, and increase our understanding of the interpersonal processes that may play an important role in problematic hoarding.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".