Exploring the Relationship between Partner Communication and Depressive Symptoms: A Longitudinal Study of Acceptance and Rejection
Bibliographic record
Abstract
This dissertation draws upon the interactional theory of depression (Coyne, 1976) and interpersonal acceptance-rejection theory (Rohner, 2016) to explore the relationship between partner communication and depressive symptoms. A non-clinical sample of 280 partnered adults living in the United States and Canada completed self-report surveys at two time points separated by approximately eight weeks. The online surveys measured participant’s perceptions of accepting and rejecting communication they received from their romantic partners. Accepting and rejecting communication consisted of communication of warmth, indifference, and neglect. Participants also self-reported depressive symptomatology, excessive reassurance seeking, relationship satisfaction, and demographic variables. Based on a longitudinal hierarchical multiple regression analysis, results indicated that the communication variables (warmth, indifference, and neglect) did not predict depression symptoms, but prior depression symptoms did strongly predict subsequent symptoms. Excessive reassurance seeking was also a significant (albeit weak) predictor of depression symptoms. Implications for therapeutic practice and future research are discussed.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".