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Record W1570521467 · doi:10.5539/gjhs.v8n4p142

The Effectiveness of Mindfulness-Based Stress Reduction on Perceived Pain Intensity and Quality of Life in Patients With Chronic Headache

2015· article· en· W1570521467 on OpenAlexvenueno aff
Nour‐Mohammad Bakhshani, Ahmadreza Amirani, Hamed Amirifard, Mahnaz Shahrakipoor

Bibliographic record

VenueGlobal Journal of Health Science · 2015
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
FundersZahedan University of Medical Sciences
KeywordsMedicineMindfulness-based stress reductionMindfulnessQuality of life (healthcare)Physical therapyMeditationIntervention (counseling)Chronic painMigraineAuraTension headacheInternal medicineClinical psychologyPsychiatryNursing

Abstract

fetched live from OpenAlex

The aim of this study was to determine the effectiveness of Mindfulness-Based Stress reduction (MBSR) on perceived pain intensity and quality of life in patients with chronic headache. Thus, forty patients based on the diagnosis of a neurologist and diagnostic criteria of the International Headache Society (IHS) for migraine and chronic tension-type headache were selected and randomly assigned to the intervention group and control group, respectively. The participants completed the Pain and quality of life (SF-36) questionnaire. The intervention group enrolled in an eight-week MBSR program that incorporated meditation and daily home practice, per week, session of 90-minutes. Results of covariance analysis with the elimination of the pre-test showed significantly improvement of pain and quality of life in the intervention group compared with the control group. The findings from this study revealed that MBSR can be used non-pharmacological intervention for improvement the quality of life and development of strategies to cope with pain in patients with chronic headache. And can be used in combination with other therapies such as pharmacotherapy.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.048
GPT teacher head0.376
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations102
Published2015
Admission routes1
Has abstractyes

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