Does Olfactory Training Improve Brain Function and Cognition? A Systematic Review.

Olfactory training (OT), or smell training,consists of repeated exposure to odorants over time with the intended neuroplastic effect of improving or remediating olfactory functioning. Declines in olfaction parallel declines in cognition in various pathological conditions and aging. Research suggests a dynamic neural connection exists between olfaction and cognition. Thus, if OT can improve olfaction, could OT also improve cognition and support brain function? To answer this question, we conducted a systematic review of the literature to determine whether there is evidence that OT translates to improved cognition or altered brain morphology and connectivity that supports cognition. Across three databases (MEDLINE, Scopus, & Embase), 18 articles were identified in this systematic review. Overall, the reviewed studies provided emerging evidence that OT is associated with improved global cognition, and in particular, verbal fluency and verbal learning/memory. OT is also associated with increases in the volume/size of olfactory-related brain regions, including the olfactory bulb and hippocampus, and altered functional connectivity. Interestingly, these positive effects were not limited to patients with smell loss (i.e., hyposmia & anosmia) but normosmic (i.e., normal ability to smell) participants benefitted as well. Implications for practice and research are provided.

Predictors of an Active Lifestyle in Middle-Aged and Older Adults with HIV in the United States Deep South.

Background and Purpose: An active lifestyle is important for health maintenance and disease prevention. This study was to examine what factors predict an active lifestyle in HIV+ and HIV- adults from the United States Deep South. Methods: The sample included 279 participants (174 HIV+ and 105 HIV-) who completed a comprehensive assessment. An active lifestyle composite was created using variables of employment status, level of social support, level of physical activity, and diet. Correlations and regression analyses were conducted between the active lifestyle composite and possible predictors for all (HIV+ and HIV-), HIV+, and HIV- participants, respectively. Results: Lower levels of depression, higher socioeconomic status (SES), and younger age were significant predictors of a more active lifestyle for the full sample, HIV+, and HIV- participants, respectively. Conclusion: SES and depression represent important factors influencing engagement in an active lifestyle in PLWH. Such factors should be considered when developing and implementing lifestyle interventions.

Using a tele-behavioral health rapid intake model to address high demand for psychotherapy at an academic medical center during COVID-19.

Background: Long wait times for mental health appointments have been a chronic dilemma for academic medical centers. This problem intensified worldwide with the onset of the COVID-19 pandemic. Approximately 70% of mental health services experienced pandemic-related disruption in care provision, while simultaneously experiencing a substantial increase in patient demand. Wait times for mental health appointments also increased, varying across populations from 3 to 18 months. As prolonged wait time is positively associated with severity of psychiatric symptoms and negative outcomes, the authors implemented a novel rapid intake telemedicine clinic model to shorten wait time and increase patient access to psychological care at an academic medical center. Methods: To address an overwhelming influx of mental health referrals and a growing wait-time-until-first appointment at an academic medical center serving as a lone safety net hospital during the COVID-19 pandemic, a 5-provider Psychology Rapid Intake Team was established using a hybrid of telehealth and in-person appointments based on patient preference. Data on new patient volumes, wait time for 1st appointment, and wait time to begin therapeutic intervention were compared during the same calendar 3-month period immediately prior to and following implementation of the rapid intake clinic. Results: A paired-samples t-test was conducted to compare new patient volumes pre- vs. post- intervention. Results revealed a significant increase in the number of new patients the providers were able to accommodate in the post-implementation (M = 62.00, SD = 7.21) compared to the pre-implementation (M = 31.00, SD = 2.61) condition; t(2) = -8.60, p < 0.05. There was a significant decrease in the average wait times for 1st appointment post-implementation (M = 24.99, SD = 2.38) compared to the pre-implementation (M = 37.32, SD = 1.47) condition; t(2) = 5.56, p < 0.05. In addition, days to begin therapeutic intervention decreased dramatically (394%) from the pre- (M = 142.50) to post-implementation (M = 28.84) period. Conclusion: The COVID-19 pandemic strained a mental healthcare system which led to increasingly long wait times for intake appointments and delayed psychotherapy interventions. The Psychology Rapid Intake Team initiative served to improve access, reduce patient risk related to prolonged wait times, and accelerated patient engagement with psychotherapy services. The model can serve as a unique, sustainable infrastructure for behavioral health delivery for low acuity mental health problems in large health care systems.