Background Social anxiety disorder (SAD) is associated with dysfunctions in face processing, a critical aspect of social interaction. However, there is a dearth of biomarkers that could facilitate precise diagnosis and targeted treatment. Aims This meta‐analysis seeks to investigate abnormalities in P1, N170, LPP, and N2pc during face processing in individuals with SAD. It also aims to examine the role of potential moderators. Methods A systematic review of the literature yielded 32 relevant studies, encompassing the aforementioned ERP components: P1 (21 studies), N170 (16 studies), LPP (11 studies), and N2pc (6 studies). We performed a random‐effects meta‐analysis to calculate Hedges′ g and assessed publication bias using the trim‐and‐fill method. Risk of bias was evaluated across five domains using an adapted Downs and Black checklist. Results Risk of bias was generally low, with some concerns regarding external validity. Primary analysis showed enhanced P1 ( g = 0.92) and LPP ( g = 1.07) amplitudes in SAD. However, the P1 effect became nonsignificant ( g = 0.20) after adjusting for publication bias, whereas the LPP enhancement remained robust. No significant differences were found for N170 or N2pc. Mixed‐model analysis indicated that P1 and N2pc exhibited the largest absolute effect sizes. No significant moderators (age, clinical status and task type) were identified. Conclusions The findings highlight the LPP as the most robust neural correlate of face processing deficits in SAD, reflecting impaired late‐stage attentional disengagement. Although P1 amplitudes appear enhanced, this effect is likely inflated by publication bias. Current evidence does not support consistent alterations in N170 or N2pc. LPP may serve as a promising potential biomarker for the clinical diagnosis and treatment monitoring of SAD.
Background Family caregivers play a crucial role in the utilisation of mental healthcare for relatives with mental illness. However, their varied perceptions of mental illness influence treatment‐seeking options. Aims The study explored family caregivers′ perceptions of mental illness and treatment‐seeking behaviours regarding the utilisation of mental healthcare at the Ankaful Psychiatric Hospital in the Central Region of Ghana. The social construction theory underpinned the study. Methods Guided by the exploratory design, the study was purposively selected and conducted in‐depth semistructured interviews with 20 family caregivers who had relatives receiving treatment at the facility. Data were analysed thematically using Braun and Clarke′s six‐phase framework, with member checking and peer debriefing employed to enhance trustworthiness. Results The study found that family caregivers largely attributed mental illness to supernatural causes (such as witchcraft and spiritual attacks), social causes (including relationship difficulties, trauma and substance abuse) and biological causes (particularly genetic factors). These perceptions shaped caregivers′ treatment decisions. Family caregivers combined hospital medication with spiritual consultations and traditional herbal treatment to manage the condition of their relatives, which reflects the pluralistic nature of healthcare in Ghana. Treatment pathways included orthodox treatment only, sequential movement from nonbiomedical to biomedical care, simultaneous use of multiple approaches and mixed patterns that combined sequential and concurrent strategies. Conclusion The perceptions that family caregivers at the Ankaful Psychiatric Hospital hold about mental illness influence their treatment‐seeking decisions and behaviours. Caregivers′ explanatory models, which encompass supernatural, social and biological understandings, produce pluralistic treatment pathways that may delay, complement or complicate biomedical care. The study contributes to understanding how culturally shaped perceptions influence mental healthcare utilisation in Ghana and highlights the need for interventions that acknowledge and work within caregivers′ existing belief systems whilst fostering collaboration between biomedical and community‐based systems of care.
Introduction Spirituality, by connecting individuals to a higher power and providing life with meaning, is considered a key factor in alleviating death anxiety. This study is aimed at examining the effect of spiritual reminiscence therapy on death anxiety among patients hospitalized in the cardiac intensive care unit (CICU). Methods This randomized clinical trial was conducted on 70 cardiac patients admitted to the CICUs of Larestan and Jahrom Hospitals in 2024. Participants were conveniently sampled and randomly assigned to either the control group (usual care) or the intervention group (spiritual reminiscence therapy). Patients in the intervention group received a spiritual reminiscence program delivered in three sessions. The program was based on spiritual themes from MacKinlay′s study and aligned with Erikson′s psychosocial developmental stages. Data were collected before and immediately after the intervention using a demographic checklist and the Templer Death Anxiety Scale. Data were analyzed using SPSS Version 23, employing descriptive and inferential statistical tests. Results The mean age of participants in the intervention and control groups was 54.66 ± 11.86 and 57.66 ± 9.19 years, respectively ( p = 0.362). The majority of participants in both groups were male (57.10% and 62.90%, respectively; p = 0.626). There was no significant difference in baseline death anxiety scores between the groups ( p = 0.094). After the intervention, the intervention group showed a significant reduction in death anxiety compared with the control group ( p = 0.004). After controlling for confounding variables, the intervention significantly reduced the mean death anxiety score by 2.195 points ( p = 0.008). Conclusion Spiritual reminiscence therapy effectively reduces death anxiety in cardiac patients hospitalized in intensive care units. It is recommended to incorporate this therapy into comprehensive nursing and spiritual care in hospital settings. Trial Registration: Iranian Registry of Clinical Trials: IRCT20250716066512N1
Background This study is aimed at exploring relationships among misophonia, psychological distress, obsessive‐compulsive (OC) symptoms, and aggression in undergraduate nursing students through a chain mediating model. Methods A cross‐sectional study was carried out with 201 undergraduate nursing students from Larestan University of Medical Sciences in southern Iran. Participants were selected through convenience sampling. Data were gathered via face‐to‐face surveys between November 2023 and January 2024. The study utilized a demographic questionnaire, a misophonia questionnaire, the DASS‐21, the Yale‐Brown Obsessive‐Compulsive Scale (Y‐BOCS), and the Aggression Questionnaire. Data analysis was performed using SPSS Version 27.0 and the PROCESS macro for SPSS Version 3.5. Results The findings from the serial multiple analysis indicated that misophonia had a significant overall impact on aggression ( B = 1.233, SE = 0.172, t = 7.162, p < 0.001). Additionally, psychological distress, as the first mediator, had a significant direct effect on OC symptoms, the second mediator ( B = 0.362, SE = 0.027, t = 13.250, p < 0.001). Moreover, there was a notable serial indirect effect of misophonia on aggression through both psychological distress and OC symptoms ( B = 0.282, SE = 0.071; 95% CI [0.153, 0.435]). Conclusion Given the role of misophonia, psychological distress, and OC symptoms in predicting aggression in students, the design of interventions based on improving these characteristics is suggested as a basis for improving the quality of life of this group of people.
A growing number of adolescents between the ages of 14 and 16 are reporting symptoms of “AI anxiety” as a result of the rapid proliferation of deepfakes and generative AI technology. This study investigated the associations between AI anxiety and three important developmental outcomes: cognitive engagement, learning performance, and self-confidence. Drawing upon social cognitive theory and the stimulus–organism–response framework, this study examines a moderated mediation model in which digital literacy moderates the relationship between AI anxiety and cognitive engagement, and self-confidence mediates the association between AI anxiety and learning performance. The results indicated that AI anxiety significantly and negatively predicted learning performance (β=−0.186, p<0.01), self-confidence (β=−0.360, p<0.001), and cognitive engagement (β=−0.336, p<0.01). Self-confidence and cognitive engagement were also positively associated with learning performance (β=0.260, p<0.001; β=0.151, p<0.05). Digital literacy significantly moderated the AI anxiety–cognitive engagement pathway (β=0.219, p<0.001), such that higher digital literacy attenuated this negative association. Self-confidence partially mediated the AI anxiety–learning performance link (indirect effect=−0.077, p<0.01). The conditional indirect effect of AI anxiety on learning performance through cognitive engagement suggests that digital literacy reduces this negative impact. These findings have implications for educators, policymakers, and mental health practitioners regarding the importance of promoting digital literacy and self-efficacy as protective factors against the adverse associations of AI anxiety.
Music-based interventions may offer accessible adjunctive support for several mental conditions, but average treatment effects are heterogeneous and objective outcomes are often inconsistent. Artificial intelligence (AI) can select or generate music at scale, yet tailoring the musical stimulus alone does not establish a biologically individualized treatment. This conceptual perspective distinguishes three levels of individualization: the patient's clinical and cultural context, the neural or psychophysiological target, and the musical stimulus and dose. Group-level disorder-network findings should serve only as provisional priors. Before an AI system adapts music to presumed target, the candidate target should demonstrate within-person reliability, relevance to the intended symptom or function, directional interpretability, and modifiability by music relative to an active control. We refine two development pathways: theory-driven AI selection and data-driven AI composition. Both require patient-specific calibration, prespecified falsification criteria, held-out and external validation, subgroup fairness analyses, clinician oversight, and confirmation that changes in a neural surrogate correspond to clinically meaningful outcomes. Electroencephalography is currently the most feasible primary signal for a real-time feedback loop; peripheral physiology and functional near-infrared spectroscopy may provide complementary information, whereas functional magnetic resonance imaging is more practical for offline target discovery and calibration. Individualized music therapy should not be defined as AI-generated music optimized toward a group-average disorder signature. A defensible model must individualize both the therapeutic target and the musical intervention, place patient goals and culture within the optimization process, and remain falsifiable, equitable, and clinician supervised.
Background: Research has confirmed the association of self-efficacy with social participation and other health outcomes, but to the best of our knowledge, no study has assessed a potential moderation of the association of self-efficacy with illness avoidance through life engagement by functional capacity. Aim: This study is aimed at assessing a potential moderated mediation by life engagement in the association of self-efficacy with functional capacity and illness avoidance. Methods: This study employed a cross-sectional design and multistage sampling to select 4147 middle-aged and older adults (mean age = 60 years). Standardised scales were used to measure constructs, and Hayes ' PROCESS Macro was utilised to test a moderated mediation model. The regression coefficients were stratified by age and chronic disease status. Results: Self-efficacy was positively associated with illness avoidance directly (beta = 0.105; t = 6.335; CI: 0.074-0.135; p < 0.001) and indirectly through life engagement (beta = 0.124; CI: 0.107-0.141; p < 0.001). Self-efficacy was more strongly associated with life engagement at higher functional capacity (beta = 0.047; t = 4.813; CI: 0.028-0.066; p < 0.001). Moderated mediation was confirmed (beta = 0.020; CI: 0.010-0.031; p < 0.001), implying that the indirect association of self-efficacy with illness avoidance through life engagement was stronger at higher functional capacity. The results were consistent across age groups and chronic disease statuses, but the standardised moderated mediation effect size appeared slightly larger in older adults aged over 60 years and those with chronic diseases. Conclusion: Illness avoidance is more strongly associated with self-efficacy through life engagement amongst adults with higher functional capacity. Higher self-efficacy can be associated with functional capacity and illness avoidance. The results support the rationale for future experimental and longitudinal studies.
Abstract Given the wide variety of symptoms and diagnoses of mental illness, one may think that just about anything might be considered a mental illness. However, this is definitely not the case. Although the boundaries of what is and what is not a mental illness can sometimes seem vague, and also can change over time, there are also some aspects of human behavior that are certainly not mental illness, despite being considered so by some, or even by many. This chapter discusses some of the more common human traits and behaviors that are often (mistakenly) considered to be mental illnesses.
Abstract Mental illness is a harrowing journey. When symptoms first appear, it can bring out many emotions. It is not uncommon to feel scared, confused, and disoriented when symptoms begin. If symptoms persist, and especially if they worsen, it is essential to get help. Once individuals find a treatment regimen that works to manage their symptoms, it becomes important to stick with it. With the help of treatment, the journey can move from a place of fear and a lack of control to a point of stability and increased confidence in their ability to maintain good mental health. There are no cures for mental illnesses. And these are typically lifelong disorders, even if the symptoms are not always present. So it is important for affected individuals and their families to learn strategies that can help them successfully manage the illness and achieve optimal health. This chapter discusses some of the tools that have been proven effective for coping with a mental illness.
Abstract Mental illnesses are very common. But just how common are they? Are they 1% of the population, or 100%, or 1 in a million? The real value is a bit difficult to pinpoint precisely. And the rate of mental illness depends on factors like age, sex, and location. This chapter summarizes the best scientific evidence available to provide a sense of the frequency of mental illness. It also talks about a range of specific disorders, because not all mental illnesses are equally frequent. And it talks about those factors that increase or decrease the rate of mental illnesses as well. This chapter allows for a better sense of where mental illnesses occur, in whom, and with what frequency.
Abstract The prior chapter covered the genetic basis for mental illnesses. That chapter was careful to point out that these are not “genetic disorders.” They have genetic risk factors, but they are not 100% due to genes. Genetic risk factors interact with environmental risk factors to determine one’s overall risk for a mental illness. This chapter turns to the “nurture” side of the equation and reviews some of what is known about the environmental factors that influence risk for mental illnesses. Just as no mental illness is caused entirely by genetic factors, no mental illness can be fully attributed to the environment either. Typically, mental illness is caused by unique combinations of both genes and environmental factors.
Abstract The way people talk about mental illness has the potential to do harm or good, depending on the choices they make. In its worst form, using slang terms or outdated phrases might do further harm to people who have a mental illness. Words can hurt their self-esteem, push them to the margins of society, or cause them enough shame that they don’t want to ask for help. But when the right words are used, the opposite can be true. Using fair and sensitive words can show people with a mental illness that they are loved, welcomed, and understood. That acceptance may be enough to encourage a person to get help for their illness. The words people choose and use could make a big difference in the health and wellness of someone living with a mental illness. This chapter helps increase understanding of what words to use and which ones to avoid when talking about mental illness, or when speaking with someone who has a mental illness.
Abstract Generally, mental illness arises from the interplay of genetic and environmental risk factors. These factors work together to make changes in the way the human body expresses proteins, which are then used to build cells, tissues, and organs. The differences in the brain made by genes and environmental risk factors can include structural changes in the size, shape, volume, and density of brain structures. These factors can also cause changes in the functionality of the brain and the connections between brain regions. This chapter describes some of the ways that clinicians undo, repair, or compensate for those brain changes. These methods can include medications, psychotherapy, brain-based interventions, and other forms of therapy.
Abstract According to the DSM-5, which is the main diagnostic guide for mental disorders in the United States, a mental illness is defined as a “clinically significant disturbance in an individual’s cognition, emotion regulation, or behavior that reflects a dysfunction in the psychological, biological, or developmental processes underlying mental functioning.” In simpler terms, this means that a mental illness is a group of symptoms that affect the way people think, feel, and act to a degree that it causes them distress and disrupts their lives. The specific symptoms of mental illness can vary from person to person, even among those with the same disorder. But there are a few general signs that often show up in people living with a mental illness. This chapter describes those most common symptoms, as well as the more commonly diagnosed disorders that show those symptoms.
Abstract Everyone struggles with mental health sometimes. It is incredibly common to feel stressed, overwhelmed, sad, or anxious from time to time. But some people have such severe or long-lasting difficulties that they seek help from a professional. Those who have ever sought help for symptoms of a mental illness already know that it can be a challenge to get a diagnosis. But for those who have never struggled to that degree, it may be surprising to learn that it is not easy to identify mental illness. This chapter answers common questions about the process of diagnosing mental illness and explains some of these difficulties.
Abstract The prior two chapters introduced the genetic and environmental factors that increase risk for mental illness. How do those factors increase our risk? Genes and environments don’t directly make mental illnesses. Instead, those factors change the proteins that are made in human cells. Those changes to cells, in turn, change tissues. And those changes in tissues make changes to the organs. When the affected organ is the brain, symptoms of mental illness appear. And when those brain changes are severe enough, and last long enough, they may result in mental illness. This chapter discusses some of what we know about the changes in the brain that relate to mental illness.
Abstract Most people have their own ideas about what it is like to live with a mental illness. Maybe that is from firsthand experience, having lived with a diagnosis. Maybe the view is secondhand, from living with an affected relative or other loved one. Or maybe the concept is only formed thirdhand by witnessing mental illness from afar or through depictions in media. So most people have some notion of what the course of mental illness looks like and how it affects lives. What may not be widely known—but should be—is the scope of what is possible with a mental illness. This chapter addresses some common questions people have about living, struggling, and thriving with a mental illness.
Abstract This chapter begins to describe the ways in which things can go awry when people develop the symptoms of a mental illness. It maps out the range of behaviors, emotions, and thoughts that can be impacted by a mental illness. The chapter focuses on the most common ways that society and people who study and treat mental illness think about these disorders, and how those ideas have changed over time. It also describes the ways in which mental illnesses can impair a person’s ability to carry out the functions of daily life. The chapter then highlights some notable individuals who have shared their stories and struggles with mental illness. By the end of this chapter, the reader will have a solid sense of what mental illness really is.
Abstract A mental health crisis or emergency occurs when someone is overwhelmed by intense emotional distress or when someone experiences severe changes in behavior, which may put them or others at risk. These situations often involve feelings of hopelessness or thoughts of self-harm or suicide. These emergencies can also involve extreme anxiety or panic attacks. Alternatively, a mental health emergency might involve a sudden disconnection from reality, such as hallucinations or delusions. In these moments, the individual may not be able to think clearly or make safe decisions. Immediate intervention is necessary to prevent an individual in crisis from being harmed or doing harm to others. This chapter will increase understanding about mental health emergencies.
