Natural disasters can cause widespread death and extensive physical devastation, but also harmfully impact individual and community health following a disaster event. Nature-based recovery approach can positively influence the mental health of people and community’s post-natural disasters. In response to the Australian bushfire season of 2019-2020, Zoos Victoria, in partnership with the Arthur Rylah Institute, worked with local communities in East Gippsland to support people’s recovery through experiencing, supporting, and witnessing nature’s recovery.

This mixed-method study explored how nature improved the recovery of remote and rural communities affected by the Black Summer bushfires in East Gippsland. The research studied the individuals’ feelings about being involved in nature-based community events and their lived experiences. Data were collected from June to September 2023 through a nature-based community recovery project survey and community interviews.

The findings demonstrated that engagement with natural environments promotes positive psychological, mental, and general well-being of people from bushfire-affected communities. Positive feedback from participants indicated the success of the Nature-Based Community Recovery Project in East Gippsland after the Black Summer bushfire.

This research provides insights for future recovery projects and ensures that sustainable nature-based recovery solutions for bushfire-impacted communities can be established.

The Personality Assessment Inventory (PAI; Morey, 1991; 2007) is a 344 item self-report measure of personality, psychopathology, and factors affecting treatment. The PAI short form (PAI-SF) contains the first 160 items of the PAI and is often favoured as a screening tool or brief version to mitigate respondent burden and fatigue. The PAI has been psychometrically validated among numerous populations (Slavin-Mulford et al., 2012), while psychometric research on the PAI-SF is gradually emerging. The psychometric properties of the PAI-SF range from adequate to strong in psychiatric (Sinclair et al., 2009), forensic (Sinclair et al., 2010), outpatient and nonclinical (Ward et al., 2018), and stroke (Udala et al., 2020) samples. To advance research validating the PAI-SF among diverse populations, this project investigated the psychometric comparability between the PAI and the PAI-SF in a neuropsychiatric population. Based on previous literature, it was hypothesized that the PAI-SF would produce congruent results to the PAI in this sample.

For this study, participant files (N=214) were collected retrospectively from short- and long-term residential psychiatric and substance use treatment facilities in Minnesota for patients with neurological and cognitive concerns referred for neuropsychological evaluation. The PAI-SF was scored using the first 160 items from a patient’s long-form PAI protocol. To determine the psychometric comparability of long- and short-forms, paired-samples t-tests, intraclass correlations, and percent agreement in clinical classification between forms were analyzed.

Analyses of participant data found that intra-class correlations ranged from .87 to .98 for each subscale on the PAI when compared to the PAI-SF, demonstrating good to excellent reliability between forms. Symptoms are considered clinically elevated when they exceed the clinical significance threshold for a subscale (typically a T-score of 70+). Agreement between the PAI and PAI-SF subscales in the classification of clinically elevated scores ranged from 86% to 100%. When forms did not agree, the PAI-SF was more likely to be clinically significant relative to the PAI. A comparison of subscale means between forms was examined by independent samples T-tests with a Bonferroni correction. Results revealed significant differences between the PAI and PAI-SF on one validity scale (Negative Impression Management), three clinical scales (Anxiety; Depression; Antisocial Features), and one treatment scale (Treatment Rejection).

Results demonstrated that the PAI and PAI-SF have high reliability between forms in a neuropsychiatric population. Although mean scores differed on a small number of subscales between the PAI and PAI-SF, differences did not appear sufficiently large enough to shift clinical classifications, as the two forms performed similarly in their identification of clinically elevated scales. Findings align with previous literature and suggest that the PAI-SF may perform adequately in a neuropsychiatric population if brevity or participant burden is of concern. However, caution is warranted when making clinical decisions with the PAI-SF as more research is needed.

Hypersomnolence has been considered a prominent feature of seasonal affective disorder (SAD) despite mixed research findings. In the largest multi-season study conducted to date, we aimed to clarify the nature and extent of hypersomnolence in SAD using multiple measurements during winter depressive episodes and summer remission.

Sleep measurements assessed in individuals with SAD and nonseasonal, never-depressed controls included actigraphy, daily sleep diaries, retrospective self-report questionnaires, and self-reported hypersomnia assessed via clinical interviews. To characterize hypersomnolence in SAD we (1) compared sleep between diagnostic groups and seasons, (2) examined correlates of self-reported hypersomnia in SAD, and (3) assessed agreement between commonly used measurement modalities.

In winter compared to summer, individuals with SAD (n = 64) reported sleeping 72 min longer based on clinical interviews (p < 0.001) and 23 min longer based on actigraphy (p = 0.011). Controls (n = 80) did not differ across seasons. There were no seasonal or group differences on total sleep time when assessed by sleep diaries or retrospective self-reports (p's > 0.05). Endorsement of winter hypersomnia in SAD participants was predicted by greater fatigue, total sleep time, time in bed, naps, and later sleep midpoints (p's < 0.05).

Despite a winter increase in total sleep time and year-round elevated daytime sleepiness, the average total sleep time (7 h) suggest hypersomnolence is a poor characterization of SAD. Importantly, self-reported hypersomnia captures multiple sleep disruptions, not solely lengthened sleep duration. We recommend using a multimodal assessment of hypersomnolence in mood disorders prior to sleep intervention.

The Coronavirus Disease 2019 (COVID-19) pandemic has had substantial global morbidity and mortality. Clinical research related to prevention, diagnosis, and treatment of COVID-19 is a top priority. Effective and efficient recruitment is challenging even without added constraints of a global pandemic. Recruitment registries offer a potential solution to slow or difficult recruitment.

The purpose of this paper is to describe the design and implementation of a digital research recruitment registry to optimize awareness and participant enrollment for COVID-19-related research in Baltimore and to report preliminary results.

Planning began in March 2020, and the registry launched in July 2020. The primary recruitment mechanisms include electronic medical record data, postcards distributed at testing sites, and digital advertising campaigns. Following consent in a Research Electronic Data Capture survey, participants answer questions related to COVID-19 exposure, testing, and willingness to participate in research. Branching logic presents participants with studies they might be eligible for.

As of March 24, 2021, 9010 participants have enrolled, and 64.2% are female, 80.6% are White, 9.4% are Black or African American, and 6% are Hispanic or Latino. Phone outreach has had the highest response rate (13.1%), followed by email (11.9%), text (11.4%), and patient portal message (9.4%). Eleven study teams have utilized the registry, and 4596 matches have been made between study teams and interested volunteers.

Effective and efficient recruitment strategies are more important now than ever due to the time-limited nature of COVID-19 research. Pilot efforts have been successful in connecting interested participants with recruiting study teams.

Antibiotic treatment for asymptomatic bacteriuria (ASB) is prevalent but often contrary to published guidelines.

To evaluate risk factors for treatment of ASB.

Retrospective observational study.

A tertiary academic hospital, county hospital, and community hospital.

Hospitalized adults with bacteriuria.

Patients without documented symptoms of urinary tract infection per Infectious Diseases Society of America (IDSA) criteria were classified as ASB. We examined ASB treatment risk factors as well as broad-spectrum antibiotic usage and quantified diagnostic concordance between IDSA and National Healthcare Safety Network criteria.

Among 300 patients with bacteriuria, ASB was present in 71% by IDSA criteria. By National Healthcare Safety Network criteria, 71% of patients had ASB; within-patient diagnostic concordance with IDSA was moderate (kappa, 0.52). After excluding those given antibiotics for nonurinary indications, antibiotics were given to 38% (62/164) with ASB. Factors significantly associated with ASB treatment were elevated urine white cell count (65 vs 24 white blood cells per high-powered field, P<.01), hospital identity (hospital C vs A, odds ratio, 0.34 [95% CI, 0.14–0.80], P =.01), presence of leukocyte esterase (5.48 [2.35–12.79], P<.01), presence of nitrites (2.45 [1.11–5.41], P=.03), and Escherichia coli on culture (2.4 [1.2–4.7], P=.01). Of patients treated for ASB, broad-spectrum antibiotics were used in 84%.

ASB treatment was prevalent across settings and contributed to broad-spectrum antibiotic use. Associating abnormal urinalysis results with the need for antibiotic treatment regardless of symptoms may drive unnecessary antibiotic use.

Infect. Control Hosp. Epidemiol. 2016;37(3):319–326

Despite documented associations between stunting and cognitive development, few population-level studies have measured both indicators in individual children or assessed stunting’s associations with other developmental domains.

Meta-analysis using publicly available data from fifteen Multiple Indicator Cluster Surveys (MICS-4) to assess the association between stunting and development, controlling for maternal education, family wealth, books in the home, developmentally supportive parenting and sex of the child, stratified by country prevalence of breast-feeding (‘low BF’<90 %, ‘high BF’ ≥90 %). Ten-item Early Childhood Development Index (ECDI) scores assessed physical, learning, literacy/numeracy and socio-emotional developmental domains. Children on track in three or four domains were considered ‘on-track’ overall.

Fifteen low- and middle-income countries.

Publically available data from 58 513 children aged 36–59 months.

Severe stunting (height-for-age Z-score <−3) was negatively associated with on-track development (OR=0·75; 95 % CI 0·67, 0·83). Any stunting (Z-score <−2) was negatively associated with on-track development in countries with high BF prevalence (OR=0·82; 95 % CI 0·75, 0·89). Severe and any stunting were negatively associated with physical development (OR=0·77; 95 % CI 0·66, 0·89 and OR=0·82; 95 % CI 0·74, 0·91, respectively) and literacy/numeracy development in high BF countries (OR=0·45; 95 % CI 0·38, 0·53 and OR=0·59, 95 % CI 0·51, 0·68, respectively), but not low BF countries (OR=0·93; 95 % CI 0·70, 1·23 and OR=0·95, 95 % CI 0·79, 1·12, respectively). Any stunting was negatively associated with learning (OR=0·79; 95 % CI 0·72, 0·88). There was no clear association between stunting and socio-emotional development.

Stunting is associated with many but not all developmental domains across a diversity of countries and cultures. However, associations varied by country breast-feeding prevalence and developmental domain.