THE SELF-REFLECTION AND INSIGHT SCALE: A NEW MEASURE OF PRIVATE SELF-CONSCIOUSNESS
Bibliographic record
Abstract
Private self-consciousness and the subordinate constructs of self-reflection and insight are key factors in the self-regulatory process underpinning the creation of behavior change, both in clinical practice with clinical populations, and in performance enhancing coaching with nonclinical populations. This paper reports the construction and validation of the Self- Reflection and Insight Scale (SRIS) which is designed to be an advance on the Private Self-Consciousnes Scale (PrSCS; Fenigstein, Scheier, & Buss, 1975). Previous work has found the PrSCS to comprise two factors, self-reflection and internal state awareness. In a series of studies two separate factor analyses found the SRIS comprised two separate factors labeled Self-Reflection (SRIS-SR) and Insight (SRIS-IN). “Need for self-reflection” and “engagement in self-reflection” loaded on the same factor. Test-retest reliability over a 7-week period was .77 (SRIS-SR) and .78 (SRIS-IN). The PrSCS correlated positively with the SRIS-SR and negatively with the SRIS-IN. The SRIS-SR correlated positively with anxiety and stress, but not with depression and alexithymia. The SRIS-IN was negatively correlated with depression, anxiety, stress and alexithymia, and positively correlated with cognitive flexibility and self-regulation. Individuals who had kept diaries had higher SRIS-SR scores but lower SRISIN scores than did those who had not kept diaries. Implications of these findings for models of self-regulation and goal attainment 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".