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Disability in women suffering from interstitial cystitis/bladder pain syndrome

2012· article· en· W1746079838 on OpenAlexaffabout
Laura Katz, Dean A. Tripp, J. Curtis Nickel, Robert Mayer, Maria Reimann, Arndt van Ophoven

Bibliographic record

VenueBritish Journal of Urology · 2012
Typearticle
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsInterstitial cystitisBiopsychosocial modelPain catastrophizingPsychosocialAnxietyMoodMedicineClinical psychologyAffect (linguistics)Depression (economics)Psychological interventionPsychiatryPhysical therapyChronic painPsychologyInternal medicine

Abstract

fetched live from OpenAlex

What's known on the subject? and What does the study add? Interstitial cystitis/bladder pain syndrome ( IC / BPS ) is a disease that is associated with significant disability in the areas of self‐care, sexual functioning, occupation, family and home responsibilities, and social functions. Compared to age‐ and cohort‐matched controls, patients with IC / BPS reported poorer mental and physical quality of life ( QoL ), as well as greater pain, depression, anxiety, catastrophizing, sexual dysfunction and less social support. In particular, catastrophizing and depression are suggested to be important for understanding the factors promoting a poorer QoL in IC / BPS . The findings of the present study suggest that psychosocial factors are significant in mediating the relationship between impairments and patient disability, with negative affect (i.e. depression, anxiety) and pain catastrophizing acting as significant mediators. These findings argue that catastrophizing and negative affect may be the mechanisms by which pain and symptoms elevate reports of patient disability. Understanding how pain and pain‐associated symptoms may become disabling through cognitive mechanisms represents an importance advance for IC / BPS management. Clinical interventions in women suffering from IC / BPS should target catastrophizing and mood for reduction using cognitive behavioural strategies aiming to decrease pain‐related disability. Objectives To examine a biopsychosocial framework of patient disability in patients suffering from interstitial cystitis/bladder pain syndrome ( IC / BPS ). To evaluate the impact of psychosocial factors on the relationship between pain and disability within women with IC / BPS . Patients and Methods Women with IC / BPS completed questionnaires including demographics, symptoms and problems ( IC Symptom and Problem Indices), pain (McGill Pain Questionnaire), quality of life (Medical Outcomes Study – Short Form 12), disability (Pain Disability Index) and psychosocial variables (Center for Epidemiological Studies – Depression Scale; State Trait Anxiety Inventory; Pain Catastrophizing Scale; Multidimensional Scale of Perceived Social Support). Exploratory and confirmatory factor analyses were employed to determine the factor structure and composition of the measured variables. Structural equation modelling was used to examine model fit and the mediation effect of the psychosocial factors (negative affect, catastrophizing and social support) on impairments and functional disability. Results Questionnaires completed by 196 women with IC / BPS provided data for the present study. The measurement model showed good fit to the data. Negative affect ( P < 0.001) and catastrophizing ( P < 0.001) were significant in explaining the relationship between impairments and functional disability, whereas social support did not. Conclusions Disability in patients suffering from IC / BPS is partially explained by the impact of negative affect and catastrophizing. As a result of the refractory nature of IC / BPS , patient management within a biopsychosocial framework represents an essential area of investigation. Decreases in negative affect and catastrophizing will probably lead to improvements in pain‐related disability.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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.

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

Citations22
Published2012
Admission routes2
Has abstractyes

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