Sensory Processing Sensitivity and the Subjective Experience of Parenting: An Exploratory Study
Bibliographic record
Abstract
Objective To explore the relationship between sensory processing sensitivity (SPS) and parental subjective experience (PSE). Background SPS is a temperament trait characterized by greater sensitivity to environmental and social stimuli; no previous research has examined the relation of SPS to PSE (e.g., how much parents feel parenting is difficult or feel connected to their child). Method In the first of two online studies, mothers were unaware of the study's relation to SPS ( N = 92). In the second, mothers ( n = 802) and fathers ( n = 65) were recruited through an SPS‐related website. SPS was assessed by the short version of the Highly Sensitive Person Scale; PSE by 27 items with three components—Parenting Difficulties, Good Coparenting Relationship, and Attunement to Child. Results Controlling or not for external stressors, negative affectivity, children's age, and socioeconomic status, high‐SPS mothers in both studies scored meaningfully higher on Parenting Difficulties and Attunement to Child; high‐SPS fathers scored higher on Attunement to Child. SPS had little association with Coparenting Relationship. Conclusion Parents high in SPS report more attunement with child, although mothers found parenting more difficult. Implications This information could aid family researchers, particularly by considering the role of adult temperament. It also suggests that interventions focused on high‐SPS parents could improve their parenting experience and hence perhaps enhance child development. Thus, this research and what may follow from it could advance both theory and practice.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".