Health workers are one of the work groups that have the biggest role in overcoming the crises that occur with disasters. It is very critical for health care workers to be healthy, happy and productive both for overcoming crises with minimal damage and for a healthy society. This study aimed to examine the anxiety levels of health care workers after the Kahramanmaraş earthquake and to evaluate the effect of earthquake anxiety on the level of perceived stress and work-family conflict.

It is a cross-sectional study. The sample of this study, which was conducted approximately 9 months after the earthquake, consisted of 150 health care workers working in a private hospital in Gaziantep.

It was observed that the post-earthquake anxiety levels of health care workers were above average. It has been found that earthquake anxiety significantly affects both perceived stress and the level of work-family conflict. Additionally, it was determined that the explanatory nature of the model increased by 4.5% with the inclusion of perceived stress and educational level on the effect of earthquake anxiety on work-family conflict.

More research is needed to evaluate the mental state of health care workers after the earthquake, to ensure positive development and to put forward appropriate strategies.

This study aims to determine the effect of death anxiety on the life satisfaction of individuals living in 11 provinces declared as earthquake zones in Turkey.

This cross-sectional and correlational study was conducted with 435 participants in earthquake zones in Turkey. Data were collected online through Google Forms using a sociodemographic form, the Revised Death Anxiety Scale (RDAS), and the Satisfaction with Life Scale (SWLS).

In this study, it was determined that 48.5% of the participants exhibited moderate levels of death anxiety. The participants’ average score on the RDAS was 53.97 (SD = 16.21), and their mean score on the SWLS was 12.30 (SD = 4.33).

This study showed that death anxiety adversely affects life satisfaction. Higher death anxiety among participants was associated with lower satisfaction with life. Consequently, health care professionals should offer increased psychological and communication support to individuals who have experienced significant disasters like earthquakes.

As the use of guided digitally-delivered cognitive-behavioral therapy (GdCBT) grows, pragmatic analytic tools are needed to evaluate coaches’ implementation fidelity.

We evaluated how natural language processing (NLP) and machine learning (ML) methods might automate the monitoring of coaches’ implementation fidelity to GdCBT delivered as part of a randomized controlled trial.

Coaches served as guides to 6-month GdCBT with 3,381 assigned users with or at risk for anxiety, depression, or eating disorders. CBT-trained and supervised human coders used a rubric to rate the implementation fidelity of 13,529 coach-to-user messages. NLP methods abstracted data from text-based coach-to-user messages, and 11 ML models predicting coach implementation fidelity were evaluated.

Inter-rater agreement by human coders was excellent (intra-class correlation coefficient = .980–.992). Coaches achieved behavioral targets at the start of the GdCBT and maintained strong fidelity throughout most subsequent messages. Coaches also avoided prohibited actions (e.g. reinforcing users’ avoidance). Sentiment analyses generally indicated a higher frequency of coach-delivered positive than negative sentiment words and predicted coach implementation fidelity with acceptable performance metrics (e.g. area under the receiver operating characteristic curve [AUC] = 74.48%). The final best-performing ML algorithms that included a more comprehensive set of NLP features performed well (e.g. AUC = 76.06%).

NLP and ML tools could help clinical supervisors automate monitoring of coaches’ implementation fidelity to GdCBT. These tools could maximize allocation of scarce resources by reducing the personnel time needed to measure fidelity, potentially freeing up more time for high-quality clinical care.

Anxiety disorders are among the most common mental disorders worldwide, and most previous studies have focused solely on alcohol drinking or tobacco smoking as risk factors for anxiety.

This study investigated the associations of alcohol drinking and tobacco smoking with anxiety.

The data of 30 836 individuals in the Taiwan Biobank were retrieved and analysed in our study. To investigate the associations of tobacco and alcohol use with anxiety, we analysed Patient Health Questionnaire 4 (specifically scores for the first two questions assessing generalised anxiety disorder) results of the included participants and data on their tobacco and alcohol use, and other covariates.

Participants who used only tobacco and those using both tobacco and alcohol were more likely to experience anxiety than were those who did not use tobacco or alcohol. Among men, the use of alcohol and/or tobacco was associated with a significantly higher risk of anxiety. Among women, the use of both alcohol and tobacco was associated with a significantly higher risk of anxiety. Older age was associated with a lower risk of anxiety.

Tobacco and alcohol use significantly influence the risk of anxiety, particularly in men, and older age also influences this risk. The associations of anxiety with tobacco and alcohol use in women may change because of the increasing prevalence of their use among women in Taiwan in recent years.

Late-life affective disorders (LLADs) are common and are projected to increase by 2050. There have been several studies linking late-life depression to an increased risk of dementia, but it is unclear if bipolar affective disorder or anxiety disorders pose a similar risk.

We aimed to compare the risk of LLADs progressing to all-cause dementia, and the demographic and clinical variables mediating the risk.

We used the South London and Maudsley National Health Service Foundation Trust Clinical Records Interactive Search system to identify patients aged 60 years or older with a diagnosis of any affective disorder. Cox proportional hazard models were used to determine differences in dementia risk between late-life anxiety disorders versus late-life depression, and late-life bipolar disorder versus late-life depression. Demographic and clinical characteristics associated with the risk of dementia were investigated.

Some 5695 patients were identified and included in the final analysis. Of these, 388 had a diagnosis of bipolar affective disorder, 1365 had a diagnosis of an anxiety disorder and 3942 had a diagnosis of a depressive disorder. Bipolar affective disorder was associated with a lower hazard of developing dementia compared to depression (adjusted model including demographics and baseline cognition, hazard ratio: 0.60; 95% CI: 0.41–0.87). Anxiety disorders had a similar hazard of developing dementia (adjusted hazard ratio: 1.05; 95% CI: 0.90–1.22). A prior history of a depressive disorder reduced the risk of late-life depression progressing to dementia – suggesting the new onset of a depressive disorder in later life is associated with higher risk – but a prior history of anxiety disorders or bipolar affective disorder did not alter risk.

LLADs have a differential risk of developing all-cause dementia, with demographic- and illness-related factors influencing the risk. Further prospective cohort studies are needed to explore the link between LLADs and dementia development, and mediators of the lower risk of dementia associated with late-life bipolar disorder compared to late-life depression.

Because pediatric anxiety disorders precede the onset of many other problems, successful prediction of response to the first-line treatment, cognitive-behavioral therapy (CBT), could have a major impact. This study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT anxiety symptoms.

Two datasets were studied: (A) one consisted of n = 54 subjects with an anxiety diagnosis, who received 12 weeks of CBT, and (B) one consisted of n = 15 subjects treated for 8 weeks. Connectome predictive modeling (CPM) was used to predict treatment response, as assessed with the PARS. The main analysis included network edges positively correlated with treatment outcome and age, sex, and baseline anxiety severity as predictors. Results from alternative models and analyses are also presented. Model assessments utilized 1000 bootstraps, resulting in a 95% CI for R2, r, and mean absolute error (MAE).

The main model showed a MAE of approximately 3.5 (95% CI: [3.1–3.8]) points, an R2 of 0.08 [−0.14–0.26], and an r of 0.38 [0.24–0.511]. When testing this model in the left-out sample (B), the results were similar, with an MAE of 3.4 [2.8–4.7], R2−0.65 [−2.29–0.16], and r of 0.4 [0.24–0.54]. The anatomical metrics showed a similar pattern, where models rendered overall low R2.

The analysis showed that models based on earlier promising results failed to predict clinical outcomes. Despite the small sample size, this study does not support the extensive use of CPM to predict outcomes in pediatric anxiety.

The cumulative effects of long-term exposure to pandemic-related stressors and the severity of social restrictions may have been important determinants of mental distress in the time of COVID-19.

This study aimed to investigate mental health among a cohort of Chinese university students over a 28-month period, focusing on the effects of lockdown type.

Depression, anxiety, stress and fear of COVID-19 infection were measured ten times among 188 Chinese students (females 77.7%, meanage = 19.8, s.d.age = 0.97), every 3 months: from prior to the emergence of COVID-19 in November 2019 (T1) to March 2022 (T10).

Initially depression, anxiety and stress dipped from T1 to T2, followed by a sudden increase at T3 and a slow upward rise over the remainder of the study period (T3 to T10). When locked down at university, participants showed greater mental distress compared with both home lockdown (d = 0.35–0.48) and a no-lockdown comparison period (d = 0.28–0.40). Conversely, home lockdown was associated with less anxiety and stress (d = 0.19 and 0.21, respectively), but not with depression (d = 0.13) compared with a no-lockdown period.

This study highlights the cumulative effects of exposure to COVID-19 stressors over time. It also suggests that the way in which a lockdown is carried out can impact the well-being of those involved. Some forms of lockdown appear to pose a greater threat to mental health than others.

To develop effective mental health interventions for children and adolescents, it is essential to understand the intricate link between functional disability and mental well-being in this group.

To explore the network connections between various aspects of functional disability and mental well-being in young people with disabilities.

We analysed data from the Multiple Indicator Cluster Surveys in 47 low- and middle-income countries, tracking progress towards health-related sustainable development goals. Our focus was on children and adolescents aged 5–17 with functional disabilities. Mental well-being was gauged using carer-reported signs of depression, anxiety and disability on the Child Functioning Module. Network-analysis techniques were used to examine links between mental well-being and functional disability domains.

The study included 32 669 eligible children aged 5–17 with functional disabilities (14 826 females and 17 843 males). The core domains of disability with the strongest connections to poor mental well-being were difficulties in accepting change, making friends, behavioural control (controlling own behaviour) and remembering/concentrating. These associations remained largely consistent across different genders and developmental stages. However, there were notable gender differences and age-related shifts in the relationships between specific disabilities and mental well-being. In particular, signs of anxiety in males and depression in females were most associated with functional disability overall, while signs of depression had the closest links to disability in adolescents.

The network perspective may enable the design of tailored interventions and support services that consider age and gender differences. Further research should continue to explore these complex relationships, incorporating novel methodologies like network-analysis to enhance the understanding of these associations.

Patients with advanced cancer and their caregivers experience a substantial amount of anxiety and distress. The purpose of this study was to assess the feasibility, acceptability, and preliminary effects of an 8-week, remotely delivered Resilient Living Program (RLP) for adult patients with advanced cancer and their caregivers.

Eligible patients included adults (≥18 years) with advanced cancer. Their caregiver had the option to participate. The RLP components included online modules, a print journal, and 4 video-telehealth-delivered sessions. Content focused on techniques for managing stress and building resilience (mindful presence, uplifting emotions, reframing experiences through practicing principles of gratitude, compassion, acceptance, meaning, and forgiveness). Feasibility and acceptability were assessed quantitatively and with semi-structured interviews conducted with a subset of participants. Effectiveness measures (anxiety, stress, quality of life [QOL], sleep, resiliency, and fatigue) were administered at baseline, week 5, week 9, and week 12.

Of the eligible patients, 33/72 (46%) were enrolled. In all, 15 caregivers enrolled. Thirty participants (21 patients/9 caregivers) completed at least 3 video-telehealth sessions (63% adherence). For patients, there were statistically significant improvements in anxiety and fatigue at week 12 (p = 0.05). Other effectiveness measures (stress, QOL, sleep, resiliency) showed positive trends. Eleven participants were interviewed and qualitative analysis revealed 4 themes: Easy to Use, Learning Key Principles, Practice is Essential, and Examples of Benefits.

Participation in the RLP was feasible and acceptable for patients with advanced cancer and their caregivers. Participants tended to indicate that the practices were easy to integrate into their everyday lives, engendered their ability to focus on the positive, and would recommend the RLP to other individuals living with advanced cancer. Preliminary effectiveness data suggest the program may positively impact anxiety, stress, QOL, sleep, resiliency, and fatigue. A larger randomized clinical trial is warranted to confirm these preliminary findings.

Data from an RCT of IAPT Norway (“Prompt Mental Health Care” [PMHC]) were linked to several administrative registers up to five years following the intervention. The aims were to (1) examine the effects of PMHC compared to treatment-as-usual (TAU) on work-related outcomes and health care use, (2) estimate the cost–benefit of PMHC, and (3) examine whether clinical outcomes at six-month follow-up explained the effects of PMHC on work−/cost–benefit-related outcomes.

RCTs with parallel assignment were conducted at two PMHC sites (N = 738) during 2016/2017. Eligible participants were considered for admission due to anxiety and/or depression. We used Bayesian estimation with 90% credibility intervals (CI) and posterior probabilities (PP) of effects in favor of PMHC. Primary outcome years were 2018–2022. The cost–benefit analysis estimated the overall economic gain expressed in terms of a benefit–cost ratio and the differences in overall public sector spending.

The PMHC group was more likely than the TAU group to be in regular work without receiving welfare benefits in 2019–2022 (1.27 ≤ OR ≤ 1.43). Some evidence was found that the PMHC group spent less on health care. The benefit–cost ratio in terms of economic gain relative to intervention costs was estimated at 5.26 (90%CI $ - $1.28, 11.8). The PP of PMHC being cost-beneficial for the economy as a whole was 85.9%. The estimated difference in public sector spending was small. PMHC effects on work participation and cost–benefit were largely explained by PMHC effects on mental health.

The results support the societal economic benefit of investing in IAPT-like services.

Fear of cardiac arrest among parents of infants with heart disease can cause stress and anxiety. Literature is scarce on the effects of cardiopulmonary resuscitation training (CPRt) on anxiety and stress of parents. We analysed the impact of CPRt on anxiety, stress, and comfort levels on parents of infants with heart disease.

Cardiopulmonary resuscitation (CPR) and choking relief manoeuvre (CRM) comfort level, Parental State-Trait Anxiety Inventory (STAI), and Parenting Stress Index (PSI) scores were prospectively collected pre-, immediately post-, and 3 months post-CPRt.

There were 97 participants: 80% (n = 78) mothers/grandmothers and 20% (n = 19) fathers. The mean (SD) age of participants was 28.7 (5.6) years old. There was a significant decrease in STAI across the three time points collected; STAI decreased by 12% from baseline to immediately post-CPRt and 19% from baseline to 3 months post-CPRt (p < .0001). There were no significant changes in PSI across the time points. Baseline to immediately post-teaching, we found that CPRt significantly increased comfort performing CPR, CRM, and comfort in knowing what to do (p=< .001, p=< .001, p=< .001, respectively). Comfort levels persisted elevated when comparing pre- to 3 months post-CPRt (p=< .001, p= .002, p= .001, respectively), maintaining at least a 177% average increase up to 3 months post-CPRt for all aspects.

CPRt can aid in improving anxiety and comfort levels of parents of infants with heart disease around hospital discharge. Parental preparedness and reassurance to know what to do in emergency situations can be enhanced by a simple intervention such as CPRt.

Sleep problems are common in palliative care patients. In addition, psychological problems can affect sleep quality. The aim of this study was to investigate sleep quality, anxiety, and depression in palliative care patients.

The study was conducted between May 1, 2023 and October 31, 2023 in Turkey. The patient information form, the Pittsburgh Sleep Quality Index (PSQI), and the Hospital Anxiety and Depression Scale (HADS) were used to collect data. The data were analyzed using the Pearson correlation and multiple linear regression test.

A total of 59.3% of patients were male, 76.7% were married, 89.3% had poor sleep quality, 61.3% had anxiety, and 86.7% were at risk of depression. A positive moderate correlation was found between HADS-anxiety, HADS-depression, and HADS total with subjective sleep quality. A positive moderate correlation was found between HADS-anxiety, HADS depression, and HADS total with the PSQI total. Sleep latency, sleep duration, sleep disturbances, use of sleep medication, and daytime dysfunction showed a weak positive correlation with HADS-depression and HADS total. In the regression analysis, anxiety proved to be a statistically significant predictor of sleep quality, while depression was not a significant predictor. These variables were found to explain 22% of the total variance in sleep quality.

The patients’ sleep quality was poor. Anxiety and the risk of depression were high. A positive moderate correlation was found between the total score of sleep quality and anxiety and depression. Anxiety was found to be a statistically significant predictor of sleep quality.