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Introduction: Imposter syndrome is common among health disciplinary students, leading to serious consequences. However, the impact of imposter syndrome on self-esteem and quitting intention among respiratory therapy students has not been well researched. Objective: To report on the prevalence of imposter syndrome and assess its impacts on self-esteem and quitting intention among respiratory therapy students in Saudi Arabia. Methods: A nonprobability cross-sectional questionnaire using the Clance Impostor Phenomenon Scale and the Rosenberg Self-Esteem Scale was self-administered and distributed among respiratory therapy students between October 2022 and April 2023. Data analysis was performed using Descriptive and inferential statistics. Results: Of the 1500 respiratory therapy students invited to participate in the study, 901 surveys were completed; and thus, included in the final analysis. Of whom, 92% were presented with imposter syndrome: 44% with moderate, 35% with frequent, and 13% with intense feelings. In addition, 60% of respiratory therapy students and interns experienced low self-esteem, while only 0.5% indicated high self-esteem. More than 50% of the study participants thought about quitting the respiratory therapy program, and 30% have been diagnosed with psychological disorders. Furthermore, there was a significant association between imposter syndrome and low self-esteem, p < 0.001. Factors associated with imposter syndrome and low self-esteem were family income (<0.005) and parents' education (<0.005), quitting intention (<0.005), and having been diagnosed with psychological disorders (<0.005). Genders, academic levels, and grade point average were not associated with either imposter syndrome or self-esteem (>0.005). Conclusion: Imposter syndrome and low self-esteem are prevalent among respiratory therapy students, both of which are associated with considering leaving the respiratory therapy program. Effective interventions should be implemented to ameliorate the symptoms imposter syndrome and low self-esteem; thus, improving the academic experience of respiratory therapy students.
RESUMO
BACKGROUND: Patient-ventilator asynchrony (PVA) is a prevalent and often underrecognized problem in mechanically ventilated patients. Ventilator waveform analysis is a noninvasive and reliable means of detecting PVAs, but the use of this tool has not been broadly studied. METHODS: Our observational analysis leveraged a validated evaluation tool to assess the ability of critical care practitioners (CCPs) to detect different PVA types as presented in three videos. This tool consisted of three videos of common PVAs (i.e., double-triggering, auto-triggering, and ineffective triggering). Data were collected via an evaluation sheet distributed to 39 hospitals among the various CCPs, including respiratory therapists (RTs), nurses, and physicians. RESULTS: A total of 411 CCPs were assessed; of these, only 41 (10.2%) correctly identified the three PVA types, while 92 (22.4%) correctly detected two types and 174 (42.3%) correctly detected one; 25.3% did not recognize any PVA. There were statistically significant differences between trained and untrained CCPs in terms of recognition (three PVAs, p < 0.001; two PVAs, p = 0.001). The majority of CCPs who identified one or zero PVAs were untrained, and such differences among groups were statistically significant (one PVA, p = 0.001; zero PVAs, p = 0.004). Female gender and prior training on ventilator waveforms were found to increase the odds of identifying more than two PVAs correctly, with odds ratios (ORs) (95% confidence intervals [CIs]) of 1.93 (1.07-3.49) and 5.41 (3.26-8.98), respectively. Profession, experience, and hospital characteristics were not found to correlate with increased odds of detecting PVAs; this association generally held after applying a regression model on the RT profession, with the ORs (95% CIs) of prior training (2.89 [1.28-6.51]) and female gender (2.49 [1.15-5.39]) showing the increased odds of detecting two or more PVAs. CONCLUSION: Common PVAs detection were found low in critical care settings, with about 25% of PVA going undetected by CCPs. Female gender and prior training on ventilator graphics were the only significant predictive factors among CCPs and RTs in correctly identifying PVAs. There is an urgent need to establish teaching and training programs, policies, and guidelines vis-à-vis the early detection and management of PVAs in mechanically ventilated patients, so as to improve their outcomes.