Patient Profiling: Determining the Effects of Patient Factors on Vocal Fatigue.
Julianna C Comstock Smeltzer, Sy Han Chiou, Adrianna C Shembel
PMID 37419718WHAT IT FOUND
How much a voice disorder impacts a patient's life predicts their vocal fatigue severity.
However, knowing a patient's age, gender, diagnosis type, singing background, or body awareness does not help predict how fatigued their voice will feel.
Key findings
01There is a significant positive association between voice handicap scores (VHI-10) and vocal fatigue scores (VFI-Part1), where a one-unit increase in handicap predicts a 0.91 unit increase in fatigue.
02Voice disorder type (functional, structural, neurological), patient age, and gender showed no significant relationship with self-perceived vocal fatigue severity.
03Self-identifying as a singer and interoceptive awareness scores did not significantly predict vocal fatigue responses.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
Read the rest of this summary
You get three full summaries a month, free, and we do not ask for a card. Search, the TL;DRs and your library stay unlimited either way.
What it does not show
The Vocal Fatigue Index (VFI) is a snapshot of current experience and lacks a specific time reference, so patients may interpret 'frequency' of symptoms differently (e.g., today vs. last month). Responses may be influenced by transient factors like current mood, time of day, or recent vocal demands prior to the appointment. The study is cross-sectional, so it identifies associations but cannot prove that psychosocial impact causes vocal fatigue or vice versa.
Declared interests
The authors report no conflict of interest.
The easy way to misread this
Do not interpret the lack of demographic effects as evidence that these factors are irrelevant to voice health. The study only shows they do not predict self-reported vocal fatigue severity in this specific cross-sectional sample. It does not rule out that age or gender influences the underlying pathophysiology or treatment response.
Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →