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Record W4407738187 · doi:10.3233/978-1-61499-304-9-551

Item Development for the Psychosocial Impact of Assistive Devices Scale for Continence (C-PIADS)

2013· book-chapter· en· W4407738187 on OpenAlexaboutno aff
Jr. Castleman A.W., Sarah Fowler, K. Southall, van den Heuvel E., Adèle Long

Bibliographic record

VenueIOS Press eBooks · 2013
Typebook-chapter
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialScale (ratio)Physical medicine and rehabilitationPsychologyMedicineGeographyPsychotherapistCartography

Abstract

fetched live from OpenAlex

Urinary incontinence (UI) poses problems for millions of people of varying ages worldwide. Continence symptoms can be ameliorated with pelvic floor rehabilitation, drugs, or operational intervention. In addition there is a great variety of assistive technology devices (ATDs) used to aid continence management. Because continence difficulties (CD) can profoundly affect an individual's participation in society and, thereby, their health-related quality of life, it is important to have valid, responsive and sensitive measure of the impact of these devices on psychosocial experiences. One such tool, a 26-item self-report questionnaire the Psychosocial Impact of Assistive Devices Scale (PIADS) has been shown to reliably predict the adoption and use of ATDs. Our study was to investigate if and how this instrument could be modified to be sensitive to the use of continence management devices. The study used interpretive methods in which qualitative information from semi-structured interviews was combined with the findings from cognitive interviews for questionnaire pre-testing to inform the development of a new questionnaire. A total of 40 participants from Canada and UK were recruited. All interviewees self-reported CD – bladder and/or bowel - and use of ATDs to manage continence symptoms. Semi-structured interviews, lasting between 10 and 30 minutes, were conducted with all participants. The objective was to provide opportunities for interviewees to spontaneously (i.e. without reference to PIADS) identify important concerns and issues that should be considered for developing a version of the PIADS for continence technologies. Twenty-nine participants were also asked to complete the paper version of the PIADS questionnaire while considering their currently used continence device or product. They were asked to comment on the suitability and appropriateness of PIADS for assessing quality of life outcomes resulting from UI intervention and how well the questionnaire captured the impact of continence management products and devices. Finally, they were encouraged to suggest supplemental items, (i.e. issues not represented in the PIADS) perceived to impact upon quality of life outcomes following UI intervention. Results of the in-depth semi-structured questionnaires so far, reflect the findings from similar studies carried out on Foley catheter users with frequent references to the inconvenience, embarrassment and resignation to their condition. Generally, participants appeared to be able to complete the PIADS without difficulty and indicated that the tool reflected their primary psychosocial concerns with continence devices. Some indications for additional items, such as those related to stigma, are emerging. A version for continence, the C-PIADS, will require some modifications to the PIADS, and is likely to contain the addition of some new items. Following our full analysis a draft C-PIADS will be produced and this will be tested and validated as part of a European ERA-net grant in 2014.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.044
GPT teacher head0.319
Teacher spread0.275 · 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 designBench or experimental
Domainnot available
GenreMethods

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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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