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Effectiveness of Systemic-Constructivist Couple Therapy on Alexithymia and Differentiation of Self among Women Hurt by Infidelity

2020· article· en· W3138493883 on OpenAlexaboutno aff
Saminah Porhoseanali, Azita Afkhradei

Bibliographic record

VenueWomen and Family Studies · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyClinical psychologyPopulationMann–Whitney U testStatistical populationMedicineDescriptive statisticsStatistics

Abstract

fetched live from OpenAlex

The present study aims at investigating the effectiveness of Systemic-Constructivist Couple Therapy (SCCT) on alexithymia and differentiation of self among women hurt by infidelity. The current study used quasi-experimental research method as well as pretest-posttest and control group. The statistical population included all infidelity hurt women referred to Counseling and Psychotherapy Center of Sirjan in 2018 which 30 women selected among them by goal-oriented sampling method (inclusion and exclusion criteria) and appointed into two experimental (15) and control (15) groups. Systemic-Constructivist Couple Therapy approach applied on experimental group in nine 2-hour sessions, two sessions a week; control group placed in waiting list. In order collect data Toronto Alexithymia Scale (TAS) (1994) by Bagby and others and Differentiation of Self Inventory (DSI) (1982) by Skowron and Friedlander used in two pretest and posttest stages. Data analyzed by means of multivariate covariance analysis test. The findings of the study revealed that by controlling pretest effect, there is significant difference between experimental and control group in pretest mean scores regarding alexithymia and differentiation of self variables. Accruing to the result of the present study it is concluded that Systemic-Constructivist Couple Therapy influence on alexithymia reduction and differentiation of self increase as an effective interference among women hurt by infidelity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.045
GPT teacher head0.331
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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