Here one time, gone the next: Fluctuations in support received and provided predict changes in relationship satisfaction across the transition to parenthood.
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Extant research has demonstrated that higher mean (average) levels of social support often produce robust relational benefits. However, partners may not maintain the same level of support across time, resulting in potential fluctuations (i.e., within-person variations across time) in support. Despite the theorizing and initial research on fluctuations in relationship-relevant thoughts, feelings, and behaviors, little is known about (a) who is most likely to fluctuate in support and (b) the degree to which fluctuations, in combination with and beyond mean levels, impact relationships across time. The current preregistered research examined two dyadic longitudinal samples of first-time parents undergoing the transition to parenthood, a chronically stressful time that often entails the provision and receipt of support involving one's partner. Across both studies, we found that individuals who reported greater mental health problems, more situational stress, and more destructive dispositional attributes tended to report lower mean levels and higher fluctuations in provided and received support at subsequent assessments. Moreover, we found that greater fluctuations in perceptions and observations of support predicted decreases in relationship satisfaction over time, above and beyond the effect of mean levels. Implications for theory and studying nonlinear effects in relationships are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".