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Record W4411656871 · doi:10.51847/kklpzlvgsy

10.51847/kKlpZlvGSy

2000· article· en· W4411656871 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsResilience (materials science)Irrational numberPsychologyReduction (mathematics)Developmental psychologyTraining (meteorology)MathematicsGeography

Abstract

fetched live from OpenAlex

The researches of recent 20 years show that resilience is a multidimensional structure and affected by environmental texture, time, age, gender, cultural origin and life conditions.Due to this, studying the effective factors on resilience in recent years has been increased.The statistical population of this research included all mothers of children with mild and severe mental retardation in exceptional primary schools in academic years of 2015-2016 in Tehran city.The research is a quasi-experimental design with pre-test, posttest and control group.Sampling was accomplished by simple random method and finally, 60 persons were selected and they were placed in 2 groups of training and witness.The intervention of test group included resilience training during eight sessions.The main tools of this research included initial incompatible schema questionnaire with short form (SQ-SF) and irrational thoughts (IBT) and Conner-Davidson resilience.The collected data were analyzed by using of SPSS software.In this study, descriptive statistic was used and in order to study the relation between variables, inferential statistic including covariance analysis and Means comparison were utilized.Generally, we can express that the amounts of irrational thoughts, also initial incompatible schema of mothers that have been trained in terms of resilience in some sub-variables are less than the mothers that haven't been trained.Key words: resilience, irrational thoughts, retardation 1. Introduction The parents of children with mental retardation tolerate more stress than other parents (Singer & et al, 2007, Macci & et al, 2008).This stress may be resulted from the following cases: Concerns about this issue that how children cope with future problems, behavioral problems and inability level of child, change in family relations, heavy economic expenses, windswept dreams, compassionate behaviors of others, negative attitude of society, lack of information, limited access to services, facilitations and contradictions related to have another child which finally lead to appear irrational thoughts in these parents (Vitter, 20143; Blue & et al, 2006).Mental retardation of children always confronts the families and especially mothers with mental challenges.Resilience training to the mothers can help to increase the mental ability and better compatibility of them with special conditions of their child.The compatibility rate depends on two factors: 1-personal characteristics like attitudes, skills.2-The nature of situations that the person faces with it like familial problems, sudden and natural accidents, resilience of peoples , ability in effective compatibility with environment despite exposure to risky factors (Gomez & Mclaren, 2006).Louleh & Hastings (2009) in a research found out that creating resilience through creating psychological acceptance causes to reduce the stress, adjust the initial incompatible schema and increase the mental health of parents, employees and teachers who were interacting with the retarded persons.In a research which has been accomplished by Wang & et al (2009) about the effect of planning for increasing the resilience to promote the schools , health in Hong Kong, the results have indicated that these considerations have been effective on increasing the resilience and promoting the health; and promotion of

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.070
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9300.922

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 head0.023
GPT teacher head0.287
Teacher spread0.264 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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