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Record W2408987488 · doi:10.1007/s00059-007-2824-3

[Management of sexual dysfunctions in the rehabilitation of cardiovascular diseases. Results of a staff survey].

2007· article· en· W2408987488 on OpenAlexaboutno aff
Cindy Günzler, Anja Harms, Levente Kriston

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineErectile dysfunctionSexual dysfunctionRehabilitationQuarter (Canadian coin)Family medicineContinuing medical educationPsychiatryContinuing educationPhysical therapyMedical education

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Many studies demonstrate a high prevalence of erectile dysfunction (ED) in cardiovascular patients. Findings show that patients often do not talk about their sexual problems. Many patients believe that their physician would not take their problem seriously. However, they wish to be asked by their physician and want to get information. The medical staff also avoids to broach the issue of sexual problems even when they assume an ED. Reasons for an insufficient inquiry are often lack of time or knowledge as well as emotional inhibitions. METHODS: 51 members of the medical staff of five hospitals for rehabilitation of cardiovascular diseases filled in a standardized, anonymous five-page questionnaire. It consisted of questions regarding sociodemography, estimated prevalence of sexual dysfunction, knowledge, responsibility, impediments for adequate diagnosis and therapy, as well as need for continuing medical education. Likely predictors (age, sex, profession, knowledge, and responsibility) for an active attitude were examined using relative risks. RESULTS: Of the 51 employees, 54% were men, more than half were physicians. The mean age was 44.3 years. The estimated prevalence of sexual dysfunction was 45.4 +/- 20.3%. Less than half of the medical professionals rated their knowledge concerning therapy motivation (47.9%) and general consultation of cardiovascular patients (38.8%) as at least good (see Figure 1). While more than two thirds felt responsible for motivation to subsequent treatment of sexual dysfunction, less than one quarter motivated the patients actively. Over 50% felt responsible for consultation and information, but only 27% did it actively (see Figure 2). The main impediment for an adequate management of sexual problems was the lack of time (38.3%). However, every fourth also believed that the patient would not accept the diagnosis (29.2%) or a therapy (22.9%). One third of the employees agreed that the own lack of knowledge makes care of sexual problems difficult. On the question what would be helpful to improve the management with sexual concerns, most employees said that education and training (85.7%) would be the most effective method (see Figure 3). The highest need for training can be seen in diagnostics (64.4%; see Figure 4). Almost all professionals believed that a screener would be reasonable. A higher knowledge state was the only significant predictor for an active management of sexual problems (see Table 1). CONCLUSION: The reported prevalence of sexual dysfunction in cardiac rehabilitation is very high. This requires skills concerning diagnosis and treatment of sexual dysfunction, which are only scarcely present. Furthermore, there are many impediments that are mainly positioned in the health-care system. The skills should be improved by an effort in continuing medical education. Patients with ED often have depression and a reduced quality of life. To improve the quality of life of patients in the cardiovascular rehabilitation, the treatment of ED is a necessary condition. Trials show that a widespread rehabilitation program which includes a sexual education leads to a better sexual activity. The patients' quality of life can only be improved, if the medical staff includes relevant concomitant disorders to cardiovascular disease, like ED, in the treatment program of patients.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.272
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2007
Admission routes1
Has abstractyes

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