Methodological approach for an integrated female-specific study of anxiety and smoking comorbidity
Farris et al.
The finding, in our words
An intensive protocol combining daily at-home saliva collection for ovarian hormones with smartphone-based ecological momentary assessment achieved 85% compliance in 50 female smokers, revealing substantial within- and between-subject heterogeneity in hormone levels, anxiety and nicotine craving. This demonstrates feasibility of decentralised, patient-centric data collection for studying complex comorbidities.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
AI analysis of salivary crystallisation patterns from self-collected saliva predicted delivery dates with high accuracy in a small cohort, offering a virtually painless home monitoring option for pregnant women that could support decentralised antenatal care.
Among 32,595 women trying to conceive using a connected home ovulation test, only 12.4% actually had a 28-day cycle despite 25.3% perceiving they did, and over half had cycles varying by 5 days or more. The findings demonstrate that connected home testing reveals substantial individual variation in cycle length and ovulation timing, which could help women better time intercourse for conception.
Self-collected salivary progesterone and the ratio of estradiol to progesterone showed strong agreement with serum levels, supporting the use of saliva as a noninvasive matrix for monitoring the menstrual cycle.
In a study of 46 perinatal nicotine users, dried blood spots and saliva were used weekly to measure reproductive hormones, finding that lower postpartum estradiol and greater peripartum declines in oxytocin were associated with increased nicotine craving and use. This demonstrates the feasibility of decentralised microsampling and remote surveys for longitudinal hormone tracking in vulnerable populations.
Menstrual blood offers a noninvasive, patient-centric matrix for detecting endometriosis, cervical cancer, and hormonal disorders through self-collected samples. Wearable in-pad biosensors enabling real-time monitoring and long-term tracking could transform fertility evaluation and early disease detection, though standardisation and large-scale validation remain critical gaps.