Common Health Conditions Research Articles

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics.

Depression is a common mental health condition that affects millions of people worldwide. Care pathways for depression are complex and the demand across different parts of the healthcare system is often uncertain and not entirely understood. Clinical progression with depression can be equally complex and relates to whether or not a patient is seeking care, the care pathway they are on, and the ability for timely access to healthcare services. Considering both pathways and progression for depression are however rarely studied together in the literature. This paper presents a hybrid simulation modeling framework that is uniquely able to capture both disease progression, using Agent Based Modeling, and related care pathways, using a System Dynamics. The two simulation paradigms within the framework are connected to run synchronously to investigate the impact of depression progression on healthcare services and, conversely, how any limitations in access to services may impact clinical progression. The use of the developed framework is illustrated by parametrising it with published clinical data and local service level data from Wales, UK. The framework is able to quantify demand, service capacities and costs across all care pathways for a range of different scenarios. These include those for varying service coverage and provision, such as the cost-effectiveness of treating patients more quickly in community settings to reduce patient progression to more severe states of depression, and thus reducing the costs and utilization of more expensive specialist settings.

The American Psychiatric Association Practice Guideline for the Treatment of Patients With Eating Disorders.

The American Psychiatric Association Practice Guideline for the Treatment of Patients With Eating Disorders.

Development process of a clinical guideline to manage type 2 diabetes in adults by Ayurvedic practitioners.

Type 2 diabetes mellitus (T2DM), a common chronic health condition, has major health and socioeconomic consequences. In the Indian subcontinent, it is a health condition for which individuals commonly consult Ayurvedic (traditional medical system) practitioners and use their medicines. However, to date, a good quality T2DM clinical guideline for Ayurvedic practitioners, grounded on the best available scientific evidence, is not available. Therefore, the study aimed to systematically develop a clinical guideline for Ayurvedic practitioners to manage T2DM in adults. The development work was guided by the UK's National Institute for Health and Care Excellence (NICE) manual for developing guidelines, the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, and the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument. First, a comprehensive systematic review was conducted which evaluated Ayurvedic medicines' effectiveness and safety in managing T2DM. In addition, the GRADE approach was used for assessing the certainty of the findings. Next, using the GRADE approach, the Evidence-to-Decision framework was developed, and we focused on glycemic control and adverse events. Subsequently, based on the Evidence-to-Decision framework, a Guideline Development Group of 17 international members made recommendations on Ayurvedic medicines' effectiveness and safety in T2DM. These recommendations formed the basis of the clinical guideline, and additional generic content and recommendations were adapted from the T2DM Clinical Knowledge Summaries of the Clarity Informatics (UK). The feedback given by the Guideline Development Group on the draft version was used to amend and finalize the clinical guideline. A clinical guideline for managing T2DM in adults by Ayurvedic practitioners was developed, which focuses on how practitioners can provide appropriate care, education, and support for people with T2DM (and their carers and family). The clinical guideline provides information on T2DM, such as its definition, risk factors, prevalence, prognosis, and complications; how it should be diagnosed and managed through lifestyle changes like diet and physical activity and Ayurvedic medicines; how the acute and chronic complications of T2DM should be detected and managed (including referral to specialists); and advice on topics like driving, work, and fasting including during religious/socio-cultural festivals. We systematically developed a clinical guideline for Ayurvedic practitioners to manage T2DM in adults.

COVID-19 Mortality in the Colorado Center for Personalized Medicine Biobank.

Over 6.37 million people have died from COVID-19 worldwide, but factors influencing COVID-19-related mortality remain understudied. We aimed to describe and identify risk factors for COVID-19 mortality in the Colorado Center for Personalized Medicine (CCPM) Biobank using integrated data sources, including Electronic Health Records (EHRs). We calculated cause-specific mortality and case-fatality rates for COVID-19 and common pre-existing health conditions defined by diagnostic phecodes and encounters in EHRs. We performed multivariable logistic regression analyses of the association between each pre-existing condition and COVID-19 mortality. Of the 155,859 Biobank participants enrolled as of July 2022, 20,797 had been diagnosed with COVID-19. Of 5334 Biobank participants who had died, 190 were attributed to COVID-19. The case-fatality rate was 0.91% and the COVID-19 mortality rate was 122 per 100,000 persons. The odds of dying from COVID-19 were significantly increased among older men, and those with 14 of the 61 pre-existing conditions tested, including hypertensive chronic kidney disease (OR: 10.14, 95% CI: 5.48, 19.16) and type 2 diabetes with renal manifestations (OR: 5.59, 95% CI: 3.42, 8.97). Male patients who are older and have pre-existing kidney diseases may be at higher risk for death from COVID-19 and may require special care.

How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures

BackgroundThere is increasing interest in the validation of pediatric preference-based health-related quality of life measurement instruments. It is critical that children with various degrees of health-related quality of life (HRQoL) impact are included in validation studies. To inform patient sample selection for validation studies from a pragmatic perspective, this study explored HRQoL impairments between known-groups and HRQoL changes over time across 27 common chronic child health conditions and identified conditions with the largest impact on HRQoL.MethodsThe health dimensions of two common preference-based HRQoL measures, the EQ-5D-Y and CHU9D, were constructed using Pediatric Quality of Life Inventory items that overlap conceptually. Data was from the Longitudinal Study of Australian Children, a nationally representative sample with over 10,000 children at baseline. Seven waves of data were included for the analysis, with child age ranging from 2 to18 years. Impacts to specific health dimensions and overall HRQoL between those having a specific condition versus not were compared using linear mixed effects models. HRQoL changes over time were obtained by calculating the HRQoL differences between two consecutive time points, grouped by “Improved” and “Worsened” health status. Comparison among various health conditions and different age groups (2–4 years, 5–12 years and 13–18 years) were made.ResultsConditions with the largest statistically significant total HRQoL impairments of having a specific condition compared with not having the condition were recurrent chest pain, autism, epilepsy, anxiety/depression, irritable bowel, recurrent back pain, recurrent abdominal pain, and attention deficit hyperactivity disorder (ADHD) for the total sample (2–18 years). Conditions with largest HRQoL improvement over time were anxiety/depression, ADHD, autism, bone/joint/muscle problem, recurrent abdominal pain, recurrent pain in other part, frequent headache, diarrhea and day-wetting. The dimensions included in EQ-5D-Y and CHU9D can generally reflect HRQoL differences and changes. The HRQoL impacts to specific health dimensions differed by condition in the expected direction. The conditions with largest HRQoL impacts differed by age group.ConclusionsThe conditions with largest HRQoL impact were identified. This information is likely to be valuable for recruiting patient samples when validating pediatric preference-based HRQoL instruments pragmatically.

A Preliminary Examination of Treatment Barriers, Preferences, and Histories of Women with Symptoms of Social Anxiety Disorder

AbstractSocial anxiety disorder (SAD) is a common mental health condition that is characterised by a persistent fear of social or performance situations. Despite effective treatments being available, many individuals with SAD do not seek treatment or delay treatment seeking for many years. The aim of the present study was to examine treatment barriers, treatment histories, and cognitive behavioural therapy (CBT) delivery preferences in a sample of women with clinically relevant SAD symptoms. Ninety-nine women (Mage = 34.90, SD = 11.28) completed the online questionnaires and were included in the study. Participants were recruited from advertisements on community noticeboards and posts on social media. The results demonstrated that less than 5% of those who received psychological treatment in the past were likely to have received best-practice CBT. The most commonly cited barriers to accessing treatment for women with SAD related to direct costs (63%) and indirect costs (e.g., transport/childcare) (28%). The most preferred treatment delivery method overall was individual face-to-face treatment (70%). The study demonstrates a need to provide a variety of treatment options in order to enhance access to empirically supported treatment for women with SAD.

Health status of Syrian refugees in Ireland - research and routine data informing service provision.

The Irish government agreed to accept up to 4000 Syrian refugees for resettlement in Ireland in 2016. Prior to their arrival in Ireland, health screening was carried out by the International Organisation for Migration. GP assessments to address immediate health needs and facilitate integration into local primary care were conducted on arrival. Cross-sectional data from a self-completed questionnaire among Syrian Refugees aged 16 years and older resident in emergency reception centres (EROCs) are reported along with data from GP assessments. The questionnaire, comprising validated instruments, was developed for a similar study in Norway. From the research questionnaires, two-thirds of the respondents reported their overall health status to be good or very good. The most common health condition was headache and the most common medications used were painkillers. Those experiencing chronic pain were three times less likely to rate their general health as good compared with those without pain. From the GP assessment data, we identified that 28% had high blood pressure, 61% were assessed to be in need of dental care and 32% of refugees were found to have an issue with their vision. Our findings were communicated to the Health Service Executive via the Partnership for Health Equity and informed a change in service provision in relation to dental services in EROCs. In terms of further action, we conclude that pain is an important symptom to consider in terms of diagnosis and treatment, and impact on health status.

Impact of an Urban Project ECHO: Safety-Net Clinician Self-Efficacy Across Conditions

To mitigate the lack of specialty healthcare, Project ECHO (Extension for Community Health Outcomes) trains community-based primary care clinicians to better prevent the progression of, manage, and treat common health conditions. ECHO-Chicago launched in 2010 as the first urban-centered ECHO program, focusing on safety-net clinicians, and has trained over 5,175 community clinicians across 34 topic areas. This paper examines self-efficacy among ECHO-Chicago participants across 11 clinical series, including a novel use of qualitative themes from self-efficacy questions. Five years of baseline and postseries survey data were collected from 2014 to 2019, resulting in 951 participants. Paired t-tests assessed change from baseline survey to postsurvey, and Cohen's d determined effect size. Change was assessed by individual series, adult or pediatric focus, participants' prescription privilege status, and across series by qualitative question theme. Metrics included total change, any improvement, a 10% target, and a clinical competency threshold. Analysis occurred from July 2020 to January 2022. All clinical series achieved statistically significant improvement in self-efficacy, and most had a large effect size. A total of 80% had any improvement, 65% met the 10% target of 0.7 points, and 52% met the competency threshold of 5.0 in the postsurvey. Prescribers had a significantly greater increase in their self-efficacy scores than nonprescribers. With a comparison across series, each theme achieved statistical significance, with most reaching large effect sizes. ECHO-Chicago successfully increased participants' self-efficacy. This inquiry adds an urban focus, years of data, multiple series, and a novel qualitative theme component to enable comparisons across rather than solely within the ECHO series.

An Integrated System of Multifaceted Machine Learning Models to Predict If and When Hospital-Acquired Pressure Injuries (Bedsores) Occur

Hospital-Acquired Pressure Injury (HAPI), known as bedsore or decubitus ulcer, is one of the most common health conditions in the United States. Machine learning has been used to predict HAPI. This is insufficient information for the clinical team because knowing who would develop HAPI in the future does not help differentiate the severity of those predicted cases. This research develops an integrated system of multifaceted machine learning models to predict if and when HAPI occurs. Phase 1 integrates Genetic Algorithm with Cost-Sensitive Support Vector Machine (GA-CS-SVM) to handle the high imbalance HAPI dataset to predict if patients will develop HAPI. Phase 2 adopts Grid Search with SVM (GS-SVM) to predict when HAPI will occur for at-risk patients. This helps to prioritize who is at the highest risk and when that risk will be highest. The performance of the developed models is compared with state-of-the-art models in the literature. GA-CS-SVM achieved the best Area Under the Curve (AUC) (75.79 ± 0.58) and G-mean (75.73 ± 0.59), while GS-SVM achieved the best AUC (75.06) and G-mean (75.06). The research outcomes will help prioritize at-risk patients, allocate targeted resources and aid with better medical staff planning to provide intervention to those patients.

Prostat lazer cerrahileri sonrası erektil ve ejakülatuvar fonksiyonlar

Benign prostatic hyperplasia (BPH) is a common health condition in aging men resulting in lower urinary tract symptoms (LUTS) and poor quality of life. Until recently, transurethral prostatectomy (TUR-P) was considered the gold standard for prostate surgery, but prostate enucleation methods using advanced laser technologies have become a strong competitor to TUR-P and have become widely used. The effects of all surgical procedures performed for prostate on sexual functions have been the subject of many studies. In today’s world where quality of life is emphasized and technological advances are increasing, the search for treatment methods with minimal effect on sexual function in the surgical treatment of BPH has increased. In this review, the effects of laser surgeries in the treatment of BPH on erectile and ejaculatory function will be presented with the current literature. Keywords: benign prostatic hyperplasia, HOLEP, ThuFLEP, erectile function, ejaculatory function

Special Report: Measurement-Based Care—Using Data to Augment Psychotherapy

Special Report: Measurement-Based Care—Using Data to Augment Psychotherapy

Prevalence and Patterns of Self-Medication with Antibiotics among People Visiting Dental Clinic, Kabul, Afghanistan

‌Background: Self-medication with antibiotics is a global public health issue particularly in developing countries where over 50% of antibiotics are dispensed over the counter. This class of drugs, which is the most important success of modern medicine, and saved millions of lives, is now losing its effectiveness owing to microbial resistance. It is an emergency alarm for developing countries which are in the top of morbidity and mortality list of infectious diseases. This study aimed to determine the prevalence and patterns of self-medication with antibiotics among people attending the Dental Teaching Clinic of Kabul University of Medical Sciences, Kabul, Afghanistan, in 2020. Materials and Methods: A descriptive cross-sectional study was conducted among clients of the Dentistry Teaching Clinic of Kabul University of Medical Sciences. A census sampling method was used to select the participants for one month, November 2020. Data collection was done using a researcher-developed questionnaire to collect data on the prevalence and patterns of self-medication with antibiotics. Data were analyzed using IBM SPSS Statistics (Version 24). Findings: The prevalence of self-medication with antibiotics was 30.1% in the past twelve months. The common reasons for self-medication with antibiotics were having a successful experience with medication, cost-saving, and lack of time. Toothache, sore throat, and cough were common health conditions that were self-medicated with antibiotics. Amoxicillin, metronidazole, and azithromycin were common antibiotics that were used for self-medication. Conclusion: The prevalence of self-medication with antibiotics is high among people attending the Dental Teaching Clinic of Kabul University of Medical Sciences. Patterns of self-medication indicate the irrational practice of antibiotics.

Socio-demographic and clinical profile of a population of patients coming for consultation to the psychiatric department of a general hospital in southern Tunisia

mental disorders are a very common health condition and a major public health issue. The purpose of this study was to examine the epidemiological and clinical characteristics of patients coming for consultation to the psychiatric department of the Regional Hospital of Gabes, and to identify risk factors for the main mental disorders. we conducted a retrospective study, including all patients consulting the psychiatry department of Gabes for the first time between 01/01/2010 and 31/12/2013. Diagnoses were classified according to the 10th reversion of the WHO International Classification of Diseases (ICD10). one thousand one hundred and one consultation cases were included in this study. The sex ratio (M/F) was 0.96. The average age of patients was 34 years (IQR=24-47.5 years), the median time between symptom onset and consultation to the psychiatric department was 1 year (IQR=3months-2 years). The three most common diagnosed were depressive disorders (21%), followed by schizophrenia (10.6%) and mental retardation (9.7%). Depressive disorders were significantly more common among female patients (p<0.001), married patients (p<0.001) and middle-aged adults (40-65 years) (p<0.001). The prevalence of these disorders was not significantly associated with either educational level, professional activity or socio-economic level. the knowledge of the socio-demographic and clinical profile of the most frequent mental disorders and factors associated with them would make it possible to better adapt the supply of care to the demand and to identify the needs in terms of mental health training in South-East Tunisia.

Machine Learning Techniques, Applications, and Potential Future Opportunities in Pressure Injuries (Bedsores) Management: A Systematic Review.

Pressure Injuries (PI) are one of the most common health conditions in the United States. Most acute or long-term care patients are at risk of developing PI. Machine Learning (ML) has been utilized to manage patients with PI, in which one systematic review describes how ML is used in PI management in 32 studies. This research, different from the previous systematic review, summarizes the previous contributions of ML in PI from January 2007 to July 2022, categorizes the studies according to medical specialties, analyzes gaps, and identifies opportunities for future research directions. PRISMA guidelines were adopted using the four most common databases (PubMed, Web of Science, Scopus, and Science Direct) and other resources, which result in 90 eligible studies. The reviewed articles are divided into three categories based on PI time of occurrence: before occurrence (48%); at time of occurrence (16%); and after occurrence (36%). Each category is further broken down into sub-fields based on medical specialties, which result in sixteen specialties. Each specialty is analyzed in terms of methods, inputs, and outputs. The most relevant and potentially useful applications and methods in PI management are outlined and discussed. This includes deep learning techniques and hybrid models, integration of existing risk assessment tools with ML that leads to a partnership between provider assessment and patients' Electronic Health Records (EHR).

The role of ketamine as an antidepressant agent

The role of ketamine as an antidepressant agent

Assessment of depression, anxiety, and stress in COVID-19-positive patients with chronic illness – A comparative study

Background: The physical, social, and emotional difficulties posed by chronic illnesses can result in depression, anxiety, and stress, which are common mental health conditions. The severe acute respiratory syndrome-CoV-2 virus, which causes the novel respiratory illness COVID-19, has had a significant impact on the global population, especially those who already have underlying chronic illnesses. In this study, we tried to evaluate the psychological stress, depression, and anxiety experienced by COVID-positive patients with and without chronic health conditions, while they are quarantined as a result of the COVID-19 pandemic. Aim and Objectives: The objectives of this study were to assess the prevalence of depression, anxiety, and stress among COVID-positive patients and to compare the prevalence of depression, anxiety, and stress among COVID-positive patients with and without chronic illness in a district in North Kerala. Materials and Methods: This observational and cross-sectional study was carried out in a district in the northern state of Kerala, India. A study population of 251 individuals who had positive COVID tests participated in the study. Out of this group, 117 people had chronic health problems such as high blood pressure, diabetes, and heart disease, while the remaining 134 people were without any chronic illness. An online questionnaire including sociodemographics and depression, anxiety, and stress scale -21 was used to evaluate depression, anxiety, and stress among the participants. Results: COVID patients with chronic illnesses experienced severe depression at a rate of 77.8% compared to 20.1% in those without any chronic illness. Patients with chronic illnesses who tested positive for COVID-19 also experienced severe anxiety in 77.8% of cases, compared to the 23.8% of really severe cases of anxiety among COVID patients who do not have any chronic illnesses. Moderate stress levels were observed in 76.06% of COVID patients with chronic illness when compared to 22.4% in those with no comorbidities. Conclusion: According to the study’s findings, people with chronic illnesses experience higher levels of stress, anxiety, and depression than those who do not have those conditions. The existence of such a high prevalence and severity of psychological issues among quarantined patients with COVID-19 underscores the need for serious attention to the mental health status of these patients.

The Veterans Health Administration's integrated model of care increases accessibility and delivery of mental health services.

Depression and posttraumatic stress disorder (PTSD) are two of the most common mental health conditions experienced by veterans. It is unclear what individual and system level factors are associated with receiving mental health treatment for these concerns. Using a national sample of Gulf War Era veterans who endorsed lifetime diagnoses of either depression or PTSD (N = 425), regression analyses were used to predict past-year treatment utilization. Predictor variables were those indicated in the behavioral model of health care utilization, including predisposing demographic variables (e.g., age, race), enabling variables (e.g., service connection, enrollment in Veterans Health Administration [VHA]), and need-based variables (e.g., current symptom severity). VHA enrollment was associated with a three- and five-times higher odds of being treated for depression or PTSD, respectively. Income and symptom severity were also positively associated with treatment utilization. Among individuals with diagnoses of depression and/or PTSD, VHA enrollment was the strongest predictor of receiving mental health treatment for these diagnoses, controlling for all other variables in the model including recent contact with the health care system, current symptom severity, and the presence of other enabling resources. Results suggest that the VHA's integrated model of care increases accessibility and delivery of effective mental health services. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Frequency and Correlates of Depression in Hemodialysis Patients versus Apparently Healthy Population in Egypt

Background: Depression is the most common mental health condition in the general population. Additionally, depression is common in hemodialysis patients and is associated with a lower quality of life. The social causes of depression have been ignored for a long time. We aimed to assess the severity and correlates of depression in HD patients and compare them to a group of apparently healthy individuals in Egypt. Methods and Subjects: The study was conducted in four dialysis units in Egypt where 234 patients and 242 healthy individuals were recruited. The depression scoring, demographic data, and associated comorbidities were recorded. Depression was measured using the Center for Epidemiologic Studies Depression Scale (CES-D), NIMH. The higher scores indicated the presence of more symptomatology. Results: The total studied groups were 234(136 males, 98 females) patients on dialysis with a mean age of 55.6±13.6 years (range 21–79 years), and 242(157 males, 85 females) healthy individuals with a mean age of 33.6±13.3 years (range 18–70 years). Females both in dialysis patients as well as in the controls had statistically significantly higher depression scores indicating more depressive symptoms, than their male counterparts. Depression scores were significantly negatively correlated with the ages of control individuals, while they had non-significant positive correlations with ages and BMIs in cases. More depressive symptoms were associated with better socioeconomic status and higher education in the control group, although depressive symptoms increased with lower socioeconomic status and lower level of education in HD patients. In HD patients, the severity of depressive symptoms was significantly related to the presence of diabetes mellitus and ischemic heart disease. On the other hand, the more depressive symptoms in HD patients without associated comorbidities were not statistically significantly different from that in the apparently healthy group. Conclusion: The severity of depressive symptoms was different demographically between hemodialysis patients and the apparently healthy individuals, and was more pronounced in patients with more advanced age, lower socioeconomic status, and lower education, necessitating more consideration of social and psychological care for these patients.

Effects of Transcutaneous Trigeminal Electrical Stimulation and Sound Therapy in Patients with Tinnitus.

Tinnitus is one of the most common health conditions worldwide. Although various methods of treatment have been used, the condition is still difficult to manage or cure. This study aimed to evaluate the therapeutic effects of transcutaneous trigeminal electrical stimulation (TTES) combined with notched sound therapy (NST) on patients with tinnitus. A clinical trial was conducted prospectively from September 2020 to September 2021 at a single center in South Korea. In total, 14 patients took part in this trial. Periodic visits and tele-monitoring were used to assess treatment compliance and collect data, including electroencephalography (EEG), photoplethysmography (PPG), tinnitus handicap inventory (THI), tinnitus magnitude index, Beck Depression Inventory (BDI), Pittsburgh Sleep Quality Index (PSQI), and 36-item short-form survey (SF-36) results. Changes after intervention were analyzed with paired t-test. This study showed that alpha waves in the left hemisphere measured by EEG (p=0.024), autonomic nervous system balance (p=0.007), and stress level (p=0.022) measured by PPG significantly changed after intervention. Also, THI scores especially emotional symptoms (p=0.029) and catastrophic symptoms (p=0.043) decreased after treatment. The SF-36 score, both mental component summary and physical component summary score (each p<0.001), increased significantly, whereas the PSQI score (p<0.001) and BDI score (p<0.001) decreased after TTES and NST. Based on the results of our study, we could confirm that TTES combined with NST can significantly improve tinnitus, catastrophic symptoms, and the overall quality of life of patients.

Physical Activity Beliefs and Behaviors during Pregnancy and their Association with Provider Counseling among Women in the Southern United States

<strong>Background:</strong> Physical inactivity, obesity, and chronic disease rates during pregnancy are strikingly high in the Southern United States. The present study examined sociodemographic factors related to the beliefs and behaviors of women in the South regarding physical activity (PA) during pregnancy and whether women’s beliefs and behaviors during pregnancy were associated with provider counseling. <strong>Methods:</strong> A sample of 292 women in the South completed an online survey. Participants provided sociodemographic data and recalled health beliefs and PA from their recent pregnancy. Descriptive statistics and correlation analyses were used to describe and assess relationships between variables. Linear regressions examined the association between women’s beliefs and behaviors during pregnancy and provider counseling while controlling for sociodemographic factors. <strong>Results:</strong> There was large agreement among the sample. Feeling tired and lacking motivation were the main barriers to PA, and improved health was the primary benefit. Participants felt most susceptible to anxiety and depression. Providers were the leading source of support for PA, although provider counseling was not significantly correlated with increased PA. Participants engaged primarily in light household and caregiving activities. Sociodemographic factors had a stronger association with beliefs and behaviors than provider counseling. <strong>Conclusion:</strong> Participants viewed PA as beneficial; however, they had specific barriers to exercise during pregnancy and did not perceive themselves as susceptible to common health conditions. Participants looked to providers as their primary support for PA, although provider counseling appears ineffective. Providers should encourage patients to be active using established counseling techniques such as motivational interviewing to support PA.