The Effectiveness of Emotional Freedom Techniques on Reducing Symptoms of Post-Traumatic Stress Disorder Among Women Affected by Marital Infidelity
Bibliographic record
Abstract
Objective: This study aimed to examine the effectiveness of Emotional Freedom Techniques in reducing symptoms of PTSD among women affected by marital infidelity. Methods and Materials: The present research was an experimental case study utilizing a multiple baseline design across subjects. The study population consisted of all women affected by marital infidelity who had sought help at the Mehravar Counseling Center in Tehran during the fall and winter of 2021 due to various clinical symptoms arising from their spouse's infidelity. A total of 5 women were selected through purposive sampling based on the results of the self-report PTSD symptom scale (Foa, Riggs, Dancu, & Rothbaum, 1993) and clinical interviews. The Emotional Freedom Technique by Church (2014) was individually administered over 6 sessions lasting 30 to 45 minutes each to the sample group. Data analysis was conducted using visual analysis (charting), the Reliable Change Index, and the percentage of improvement formula (percentage increase). Findings: Results, obtained through visual analysis (charting), the Reliable Change Index, and the percentage of improvement formula (percentage increase), showed that the Emotional Freedom Technique led to a reduction in PTSD symptoms during treatment and follow-up stages. Conclusion: According to the study's findings, it is possible to reduce PTSD symptoms in individuals affected by marital infidelity using the Emotional Freedom Technique.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".