Impact of Self-Esteem Training on Individuals with Disabilities Aged 17-30
Bibliographic record
Abstract
Several studies showed that higher levels of self-esteem are correlated with lower levels of anxiety and of depression, and higher satisfactory interpersonal relationships such as security and closeness, whereas low self-esteem was found to play a pivotal role as a risk factor for anxiety, emotion regulation problems and depression. Self-esteem is a key determinant of the psychological and social well-being of individuals, particularly in people with disabilities, who often face unique challenges related to self-acceptance and social inclusion. There is a paucity of specific research on the effectiveness of psychotherapeutic interventions targeting self-esteem in people with disabilities. This experimental comparative study aims to analyse changes in self-esteem, psychological well-being, anxiety and depression in a sample of 30 individuals with mild intellectual disability, aged between 17 and 30 years, who participated in a psychotherapeutic program focused on self-esteem training and the interview technique (Semi, 1985), conducted in a public setting. The individual psychotherapeutic program was structured into 8 weekly sessions, each lasting 90 minutes, for a total duration of 8 weeks. The intervention, using an uncontrolled trial, was supported by objective measurements taken from the patients before (T0) and after the psychotherapeutic program (T1). Results analysed using SPSS 2.0 software revealed significant improvements in the participants' self-esteem and psychological well-being, as well as a reduction in anxiety and depression symptoms among the patients involved in the study.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".