An ethno-botanical study of medicinal plants used for the management of respiratory tract disorders in northern parts of Palestine
Nuha Shawarb; Manal Badrasawi; Hassan Abu Qaoud; Fatima Hussein · 2023 · BMC Complementary Medicine and Therapies
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Abstract Background The medicinal application of natural plant remedies is well established. These medicinal plants are still in use within the Palestinian community to treat several illnesses. This research is intended to study the use of natural plants to treat different types of respiratory tract disorders. Method This ethno botanical study focused on the medicinal plants that are used to treat respiratory diseases in the northern part of Palestine; Nablus, Tulkarm, Qalqilia, and Jenin. A questionnaire was distributed to 120 respondents. The data obtained included names of the plants used,
Abstract by Nuha Shawarb; Manal Badrasawi; Hassan Abu Qaoud; Fatima Hussein, BMC Complementary Medicine and Therapies (2023) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data
Negative / Null Result ReportMeteorological Causes of the Secular Variations in Observed Extreme Precipitation Events for the Conterminous United States
Negative / Null Result ReportThe Next Generation of Sepsis Clinical Trial Designs
Negative / Null Result ReportAnalysis of DNA Methylation in Young People: Limited Evidence for an Association Between Victimization Stress and Epigenetic Variation in Blood
Negative / Null Result ReportStudy preregistration: an early example and analysis.
Negative / Null Result ReportInsights Into LSTM Fully Convolutional Networks for Time Series Classification
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: DOAJ · DOI 10.1186/s12906-023-04176-5