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Record W4377240979 · doi:10.1093/jsxmed/qdad060.020

(020) Implementing a Virtual Mindfulness-based Group Therapy to Improve Male Sexual Dysfunction

2023· article· en· W4377240979 on OpenAlexaff
Jeffrey Campbell, M Pignanelli, D Deroches, J Macdonald

Bibliographic record

VenueThe Journal of Sexual Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMindfulnessErectile dysfunctionClinical psychologyQuality of life (healthcare)Sexual functionPhysical therapyMedicineFemale sexual dysfunctionHypnosisSexual dysfunctionPsychologyPsychotherapistPsychiatryAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Erectile dysfunction (ED) is almost always multi-factorial. Simultaneous performance anxiety and psychogenic inhibition can impair erectile function even when underlying organic aetiologies are present. Sex therapy should be considered first-line treatment for ED. Mindfulness is a technique to focus on being aware of what you're sensing and feeling in the moment, without interpretation or judgment. Mindfulness-based therapy programs have been successful at improving female sexual dysfunction and prostate cancer survivors quality of life (QOL). Objective To design and evaluate the feasibility of a virtual, mindfulness-based group therapy (vMBGT) program for patients experiencing mild-to-moderate ED. We secondarily assess relationship satisfaction, QOL, and changes in erectile function after intervention. Methods A mixed-methods approach was taken for this feasibility pilot study. A total of 18 participants (mean age: 42; range 22-69 years) with ED were recruited to participate in a 4-week virtual mindfulness-based group therapy program. Three groups were led by trained facilitators on a weekly basis via Webex platform and ran 1.5-2 hours in length, followed by daily home-practice and sex education between sessions. Participants completed questionnaires (International Index of Erectile Functioning, Erection hardness scale, Relationship Assessment Scale, Five Facets of Mindfulness Questionnaire) as a baseline and 3 months after treatment. Qualitative exit interviews and program feedback was requested from all participants. Results The dropout rate for this study was 11%. Two of the eighteen men missed 2 of the 4 sessions; one participant dropped out and one had unanticipated work commitments. There was a statistically significant improvement in the mean IIEF scores from baseline 41 to 49 after vMBGT intervention (p < 0.05). There was a clinically significant improvement in SHIM score by 4 points. There was an improvement in EHS at 3 months compared to baseline (p=0.08) Overall, feedback was positive, and all participants responded that they would recommend this program to others. Some participants felt that the material could be lengthened to 6 weeks and/or that an in-person setting would have been more interactive, whereas others appreciate the convenience and comfort of the virtual platform. Conclusions This is the first published vMGBT program for patients experiencing mild to moderate ED. This program is feasible, the content was well received, and patients had improvement in their erectile function and QOL. Our pilot study has provoked a change to the treatments we can offer patients with ED and we have modified the program based on feedback. Further studies are needed to compare this to medical management and other psychotherapy interventions. Disclosure No

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)0.000
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.050
GPT teacher head0.330
Teacher spread0.280 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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