(110) Characterizing Sexuality and Assessing Predictors of Sexual Satisfaction in Patients with Multiple Myeloma
Bibliographic record
Abstract
Abstract Introduction There is a paucity of literature documenting cancer-related sexual concerns among patients with multiple myeloma (MM). Despite profound sexual changes being reported in other types of hematological cancer (i.e., lymphoma, leukemia), all types of hematological cancer patients tend to be grouped together, potentially overlooking the unique concerns of patients with MM. Objective This study is the first to characterize sexuality uniquely in the MM population, and to examine predictors of sexual satisfaction for MM, comparatively with participants with other hematological cancer types. Methods We performed a mixed modality self-report survey of patients with hematological cancer, recruiting both in-person and online. Men and women with MM (N=89) and other hematological cancers (N=84) participated in our survey. The survey included demographics and health information, as well as several quantitative sexuality measures including sexual distress, sexual function, sexual flexibility, sexual interest, sexual communication, and sexual satisfaction. Results MM survivors exhibited poor sexual function but low sexual distress, and endorsed mid-high scores on measures of sexual interest, sexual flexibility, sexual communication, and sexual satisfaction. Results indicate that for MM and other hematological cancer survivors, lower sexual distress and higher sexual communication were associated with higher sexual satisfaction (b = .428, p < .001; b = -.299, p = .001) while sexual flexibility, sexual interest, and sexual function did not explain significant variance in sexual satisfaction. Thematic analysis on open-ended questions indicates that potentially unique to MM, consequences of bone disease (i.e., bone pain, bone fracture, and spinal cord compression) affected sexual expression and resulted in reduced mobility impacting sexual activity, as well as painful sexual experiences, or anxiety relating to sex. Conclusions This study supported the need for sexual health interventions for those diagnosed with MM. Further, it demonstrated that sexual interventions that are used for other hematological cancer patients may be similarly effective for those with MM. Special consideration regarding the impact of bone disease on sexual expression in MM patients should be taken. Disclosure No
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".