The Predictive Power of Psychological Needs and Self-efficacy for the Level of Marital Happiness
Bibliographic record
Abstract
This study aimed at identifying the most common psychological needs among wives, identifying the degree of self-efficacy and the level of martial happiness among the study sample individuals as well as identifying the extent to which these psychological needs contribute to predicting the level of marital happiness. The study consisted of (150) married female lawyers. To succeed the study objectives, the scale of psychological needs was developed; it consisted of (20) items that measure four basic dimensions: psychological security, the need to achievement, the need to affiliation, and need to respect. The scale of self-efficacy (Schwarzer & Jerusalem, 1995) was used, and the scale of marital happiness was developed; it consisted of (40) items that measure five main dimensions: emotional adjustment, intellectual adjustment, family adjustment, social adjustment, and economic adjustment. The study results directed that the most common psychological need among wives is the need to achievement. The results revealed that the level of self-efficacy among the study sample individuals was medium. The results showed that the level of marital happiness among the married Jordanian female lawyers was medium for the total degree and each of the following dimensions (emotional adjustment, economic adjustment, intellectual adjustment, social adjustment), while the dimension of family cohesion was of a high degree. The results revealed that there is a predictive power for the psychological needs and self-efficacy concerning the level of marital happiness. In the light of the results, the study recommended the necessity of conducting further experimental researches in the domain of self-efficacy and marital happiness by developing counseling programs to improve these variables among spouses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".