A Systematic Review of the Symptom Distress Scale in Advanced Cancer Studies
Bibliographic record
Abstract
BACKGROUND: The 13-item Symptom Distress Scale (SDS) is a widely used symptom measurement tool, yet a systematic review summarizing the symptom knowledge generated from its use in patients with advanced cancer is nonexistent. OBJECTIVES: This was a systematic review of the research literature in which investigators utilized the SDS as the measure of symptoms in patients with advanced cancer. METHODS: We searched PubMed, CINAHL, EMBASE, and Web of Science for primary research studies published between 1978 and 2013 that utilized the SDS as the measurement tool in patients with advanced cancer. Nine hundred eighteen documents were found. Applying inclusion/exclusion criteria, 21 articles and 2 dissertations were included. RESULTS: The majority of investigators utilized descriptive, cross-sectional research designs conducted with convenience samples. Inconsistent reporting of SDS total scores, individual item scores, age ranges and means, gender distributions, cancer types, cancer stages, and psychometric properties made comparisons difficult. Available mean SDS scores ranged from 17.6 to 38.8. Reports of internal consistency ranged from 0.67 to 0.88. Weighted means indicated fatigue to be the most prevalent and distressing symptom. Appetite ranked higher than pain intensity and pain frequency. CONCLUSIONS: The SDS captures the patient's symptom experience in a manner that informs the researcher or clinician about the severity of the respondents' reported symptom distress. IMPLICATIONS FOR PRACTICE: The SDS is widely used in a variety of cancer diagnoses. The SDS is a tool clinicians can use to assess 11 symptoms experienced by patients with advanced cancer.
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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 | 0.020 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".