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Record W3145145078 · doi:10.1111/jmft.12516

Acceptability of an online relational intimacy and sexual enhancement (iRISE) intervention after breast cancer

2021· article· en· W3145145078 on OpenAlexafffund
Kimberley Cullen, Karen Fergus

Bibliographic record

VenueJournal of Marital and Family Therapy · 2021
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreYork UniversitySTART Clinic
FundersCanadian Institutes of Health Research
KeywordsHelpfulnessIntervention (counseling)Qualitative researchPsychologyClinical psychologyBreast cancerPsychotherapistMedicineSocial psychologyCancerPsychiatry

Abstract

fetched live from OpenAlex

The purpose of this study was to develop and evaluate an online relational intimacy and sexual enhancement (iRISE) intervention for couples experiencing sexual difficulties following breast cancer (BC). The acceptability of iRISE was evaluated using a single-arm, qualitative design, with 14 couples completing satisfaction surveys and posttreatment interviews. The intervention was found to be acceptable, as demonstrated by high satisfaction ratings and qualitative feedback regarding iRISE and its online delivery. Couples spoke about the helpfulness of iRISE and how the intervention improved their sexual relationship. The use of video conferencing (eTherapy) was widely accepted by participants, who highlighted several advantages of this modality. Overall, the results support the acceptability of this online psychosexual intervention for couples affected by BC. The empirical and theoretical basis for the design of iRISE along with findings from a qualitative analysis of couples' experiences of the intervention's helpfulness to them is discussed.

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 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 score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.036
GPT teacher head0.383
Teacher spread0.347 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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