Log In Sign up
The largest database of trusted experimental protocols
> Disorders > Mental or Behavioral Dysfunction > Disorder, Delusional

Disorder, Delusional

Delusional disorder is a mental health condition characterized by the presence of one or more delusions, which are firmly held beliefs that are not based in reality.
Individuals with delusional disorder may experience a range of delusions, including persecutory, grandiose, jealous, or somatic in nature.
These delusions can significantly impair the individual's daily functioning and interpersonal relationships.
Delusional disorder is a distinct diagnostic category within the broader spectrum of psychotic disorders, and it is important to differentiate it from other conditions such as schizophrenia or bipolar disorder.
Effective treatment often involves a combination of psychotherapy and medication, tailored to the specific needs of the individual.
Researchers and clinicians can utilize PubCompare.ai's AI-driven platform to enhance the reproducibility and accuracy of their work on delusional disorder, locating the best protocols from literature, pre-prints, and patents to identify the most reliable methods and products.
This can help improve research outcomes and advance our understanding of this complex mental health condition.

Most cited protocols related to «Disorder, Delusional»

1
Neurocognitive Assessment of Schizophrenia Families
Cited 10 times
Participants completed a computerized neurocognitive test battery designed to evaluate abstraction and mental flexibility (ABF), attention (ATT), verbal memory (VME), face memory (FME), spatial memory (SME), language and reasoning (LAN), spatial processing (SPA), sensorimotor dexterity (SM) (10 (link),11 (link)), and emotion processing (EMO). The EMO task included emotion intensity discrimination (9 (link),12 (link)) and an emotion identification task for happy, sad, anger, fear, and neutral (13 (link)). The computerized battery automatically scores both the number of correct responses on the task (i.e. accuracy) and the median time for correct responses in msec (i.e. speed). From these two measures we also calculated a measure of efficiency, the ratio of accuracy to speed. For sensorimotor dexterity, accuracy and efficiency were not analyzed as > 75% of participants had perfect scores, resulting in too little variation in these traits within the sample. Neurocognitive domain scores were transformed to their standard equivalents (Z-scores) based on the normative control sample. Further details regarding the individual tests on the computerized neurocognitive battery and its administration in this sample are provided in Gur et al. (9 (link)).
DSM-IV clinical diagnoses were obtained through a standard consensus diagnosis process based on information from the Diagnostic Interview for Genetics Studies (DIGS, version 2.0) administered to each participant, the Family Interview for Genetics Studies (FIGS), and a review of any available medical records. Each case was reviewed by two investigators who were blind to the family relationships among the participants to arrive at lifetime best estimate final diagnoses for the participant. Best estimate diagnoses for cases with psychotic features and disagreement between the two raters were discussed in diagnostic meetings at each site and particularly difficult cases were discussed between the investigators at the two ascertainment sites. Inter-rater reliability within and across sites was evaluated using videotaped interviews to maintain a Kappa > 0.8.
There were 106 individuals in these families with schizophrenia or schizoaffective disorder, depressed type. Most families had two affected individuals, due to the ascertainment on an affected relative pair. However, nine families had three affected individuals; two families had four affected individuals; and three families had five affected individuals. Additionally, 22 individuals in these families had cluster A diagnoses, 4 were schizoaffective-bipolar, 2 had delusional disorder, and 1 person was diagnosed with brief psychotic disorder.
Of the individuals with schizophrenia or schizoaffective disorder, depressed type, 75% were receiving treatment at the time of assessment, some of them with multiple medications. These treatments included first generation (typical) antipsychotics (33%), second generation antipsychotics (48%), mood stabilizers (15%), and benzodiazepine (10%). Among the 25% of affected individuals not being treated at the time of assessment, approximately one third had never been medicated, one third had been off treatment for six months or more, and one third had discontinued treatment within the last six months. Effects of medications on the neurocognitive measures have been examined extensively in previous studies and were found to be negligible or subtle (14 (link)-17 (link)). Therefore, medication status was not considered in the present analyses.
Almasy L., Gur R.C., Haack K., Cole S.A., Calkins M.E., Peralta J.M., Hare E., Prasad K., Pogue-Geile M.F., Nimgaonkar V, & Gur R.E. (2008). A genome screen for QTLs influencing schizophrenia and neurocognitive phenotypes. The American journal of psychiatry, 165(9), 1185-1192.
Publication 2008
Anger Antipsychotic Agents Attention Benzodiazepines Discrimination, Psychology Disorder, Delusional Emotions Face Family Member Fear Figs Memory Mental Disorders Mood Pharmaceutical Preparations Psychosis, Brief Reactive Schizoaffective Disorder Schizophrenia Spatial Memory Visually Impaired Persons
2
Meta-analysis of Violence Risk Factors in Psychosis
Cited 9 times
Studies were included if: (a) diagnosis was made using either the Diagnostic and Statistical Manual (DSM) or International Classification of Diseases (ICD) criteria; (b) more than 95% of study participants were diagnosed with schizophrenia, schizophreniform disorder, schizoaffective disorder, delusional disorder, schizotypal disorder, psychosis not otherwise specified (but not transient psychoses such as drug-induced psychoses), and bipolar disorder [21] (link); (c) more than 95% of sample participants were aged eighteen years or older; (d) the study used a cohort, case-control, cross-sectional (including correlation and regression studies), or randomized-controlled trial (RCT) design; and, (e) the study investigated factors associated with a range of violent outcomes (aggression, hostility, or violent offending). The decision to use a 95% cut-off for criteria (b) and (c) was intended to make the findings specific to adults with psychosis rather than other psychiatric diagnoses and enabled the inclusion of 17 large-scale studies that would not have qualified for inclusion had a 100% cut-off been utilised. Once we took into account these criteria, our approach was inclusive in relation to study designs and samples order to gather the totality of evidence on this topic, and to use tests of heterogeneity to examine subgroups.
Given our emphasis on clinically relevant risk and protective factors, we have not reviewed studies of genetic and epigenetic associations with violence in psychosis. Studies were also excluded if they investigated only risk factors for childhood violence. Lastly, as the aim of this meta-analysis was to identify risk and protective factors for violence rather than for criminal offending, we excluded studies where samples did not differentiate between violent and non-violent offenders.
Through correspondence we were able to include new information from the following studies: Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) [22] (link), Schizophrenia Care and Assessment Project (SCAP) [23] (link), MacArthur Prevalence [24] (link), 5 Site [25] (link), the UK-700 [26] (link), and one other recent report [27] (link).
Witt K., van Dorn R, & Fazel S. (2013). Risk Factors for Violence in Psychosis: Systematic Review and Meta-Regression Analysis of 110 Studies. PLoS ONE, 8(2), e55942.
Full text: Click here
Publication 2013
Adult Antipsychotic Agents Bipolar Disorder Diagnosis, Psychiatric Disorder, Delusional Genetic Heterogeneity Hostility Inclusion Bodies Offenders Pseudopsychopathic Schizophrenia Psychoses, Drug Psychotic Disorders Schizoaffective Disorder Schizophrenia Schizophreniform Disorders Transients
3
Early Intervention for Psychosis Study
Cited 8 times
A total of 65 individuals were enrolled in RAISE Connection Program services across two sites, one in Baltimore, MD and one in Manhattan, NY. Community stakeholders helped develop systematically applied strategies to identify participants, including web-based recruitment, outreach to hospitals, clinicians, community agencies, and advertisements. A description of recruitment and outreach strategies used in the study is publicly available in an online manual (28 ).
Participants were individuals 15–35 years old (16 and older in NY) who met Structured Clinical Interview for DSM-IV (SCID) criteria for a diagnosis of schizophrenia, schizoaffective disorder, schizophreniform disorder, delusional disorder, or psychosis not otherwise specified (NOS) (29 ). To be eligible for inclusion, individuals must have experienced psychotic symptoms of at least one week’s duration with onset within the prior 2 years, be able to speak and understand English, and be available to participate in the intervention for at least 1 year. Individuals were ineligible if they met any of the following exclusion criteria: non-psychiatric medical condition impairing functioning, psychosis due solely to another condition, mental retardation. All participants (and, for minors, participant’s parent/guardian) provided informed consent; minors provided assent. The Institutional Review Boards of New York State Psychiatric Institute and University of Maryland approved study procedures. The NIMH Data and Safety Monitoring Board provided study oversight. A consort diagram and description of participant flow is provided in an on-line appendix.
Dixon L.B., Goldman H.H., Bennett M., Wang Y., McNamara K., Mendon S.J., Goldstein A.B., Choi C.W., Lee R.J., Lieberman J.A, & Essock S.M. (2015). Implementing Coordinated Specialty Care for Early Psychosis: The RAISE Connection Program. Psychiatric services (Washington, D.C.), 66(7), 691-698.
Publication 2015
Clinical Trials Data Monitoring Committees Diagnosis Disorder, Delusional Ethics Committees, Research Intellectual Disability Legal Guardians Mental Disorders Parent Psychotic Disorders Schizoaffective Disorder Schizophrenia Schizophreniform Disorders
4
Diagnostic Validity of Severe Mental Disorders
Cited 7 times
Differences in demographic and clinical data between the four diagnostic groups were analyzed using Kruskall-Wallis equality-of-populations rank test with Dunn’s post-hoc pairwise comparison. The number of registrations in the NPR with each of the selected ICD-10 categories was calculated for each of the four DSM-IV diagnostic groups.
Diagnostic agreement was calculated as the proportion of patients who were either correctly classified as having the diagnosis in question (schizophrenia, delusional disorder, schizoaffective disorder, or bipolar disorder), or correctly classified as not having the diagnosis in question. The precision of diagnoses in NPR compared to TOP was further evaluated using Cohen’s unweighted nominal kappa (κ), a metric that estimates overall agreement while taking into account the possibility of the agreement occurring by chance [16 (link)]. To evaluate the predictive properties of severe mental disorder diagnoses in NPR, sensitivity (i.e. the probability that an ill person will receive the correct diagnosis), specificity (i.e. the probability that a person without the illness will not receive the diagnosis), positive predictive value (PPV, i.e. the probability that a person diagnosed as ill is truly ill) and negative predictive value (NPV, i.e. the probability that a person not registered with the disorder truly did not have the disorder) were calculated. In the analyses of agreement, kappa, sensitivity, specificity, PPV, and NPV, the total group of 1111 patients were considered to be the target population, patients within one of the four DSM-IV diagnostic categories under scrutiny were considered to be truly ill, while patients with the remaining three diagnostic categories were considered to be “not ill”. The occurrence of the equivalent ICD-10 diagnostic category at least once in the NPR was considered to be a positive test, while absence of registrations in NPR with the equivalent ICD-10 diagnostic category was considered to be a negative test.
Diagnostic consistency was calculated as the percentage of all registered contacts in NPR with a severe mental disorder diagnosis (i.e. ICD-10 codes F20–F29, F30–F31, F32.3, or F33.3) that included the primary DSM-IV diagnosis assigned when recruited to the TOP-study.
To investigate if diagnostic agreement or consistency differed between sexes, we performed supplementary analyses of men and women separately. Since patients were usually recruited to the TOP study while in treatment in specialized health care, the diagnostic data from the TOP study and the NPR are not completely independent. The degree of dependency is presumably higher for patients recruited during the period NPR-data were available (2008–2013) than for patients recruited prior to this period. To test if time of recruitment affected the estimates of diagnostic agreement and consistency, we performed supplementary analyses after splitting the sample into two groups: patients recruited to TOP before NPR-data were available, i.e. before 01.01.2008, and patients recruited when subject-specific NPR-data were available, i.e. after 01.01.2008. All statistical analyses were performed in STATA 14 (StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.)
Nesvåg R., Jönsson E.G., Bakken I.J., Knudsen G.P., Bjella T.D., Reichborn-Kjennerud T., Melle I, & Andreassen O.A. (2017). The quality of severe mental disorder diagnoses in a national health registry as compared to research diagnoses based on structured interview. BMC Psychiatry, 17, 93.
Full text: Click here
Publication 2017
Bipolar Disorder Diagnosis Disorder, Delusional Gender Health Services Administration Hypersensitivity Mental Disorders, Severe NPR1 protein, human Patients Schizoaffective Disorder Schizophrenia Target Population Tests, Diagnostic Woman
5
Cognitive Control Deficits in Psychiatric Disorders
Cited 7 times
Articles were identified by searching PubMed for functional neuroimaging experiments of cognitive control tasks published through June 2015 that compared patients with Axis I disorders to matched control participants (Figure 1). Experiments were eligible if they (1 (link)) examined cognitive control tasks with functional neuroimaging, (2 (link)) performed whole-brain analysis, (3 (link)) included a comparison between patients with Axis I disorders and matched healthy control participants during cognitive challenges, and (4 (link)) reported coordinates in a defined stereotaxic space (e.g., Talairach or Montreal Neurological Institute (MNI) space).
Experimental procedures must have included diagnostic interview of Axis I patients and control participants, with patient groups exceeding clinical threshold for diagnosis. A psychotic disorders category comprised schizophrenia, schizoaffective, schizophreniform, and delusional disorders. A non-psychotic disorders category comprised bipolar, unipolar (major depression, dysthymia) depressive, anxiety (including obsessive compulsive and posttraumatic stress disorders), and substance use (mixed substance abuse and/or dependence) disorders. Experiments of fully remitted patient samples were excluded.
While individuals with principal depressive or bipolar disorders may also present with psychotic features, these were excluded by criteria in the original experiments. Across disorders, patient participants included those with first episode and chronic disorder manifestations, including inter-episode states of bipolar and psychotic disorders. The substance use disorders included chronic users of a range of substances currently active or abstinent, but not in acute withdrawal. Experiments were selected to capture lifespan patterns and thus included participants ranging from childhood through older adulthood. Axis I diagnoses presenting predominantly in childhood (e.g., attention deficit/hyperactivity disorder) or those associated with altered developmental trajectories of brain structures inherent to expression of disorder phenotypes (e.g., autism spectrum disorders) were excluded.
Articles with experimental tasks probing a wide range of processes related to cognitive control were included, categorized into eight domains: conflict monitoring, performance monitoring, response inhibition, response selection, set shifting, verbal fluency, recognition memory, working memory. A ninth category (“other”) included 18 disparate experiments that did not cohere with one of these domains (Supplementary Table 1). To target substrates of higher order cognitive control, experiments that focused on simple processing speed or orienting in the context of passive perception (e.g., oddball discrimination) were excluded. Cognitive processing experiments with embedded affective manipulations (e.g., affective stimuli, mood induction) were also excluded.
Peak coordinates for whole-brain between group comparisons under cognitive challenge were required. Interactions were included if follow-up tests clarified patterns of patient hyper- versus hypoactivation during cognitive challenge. Experiments reporting results only for small-volume correction or within a region of interest were excluded. Articles with reported contrasts that did not reflect cognitive demand were excluded. If multiple contrasts were reported in a single paper only those pertaining to the most challenging condition were included. All coordinates reported in Talairach space were converted into MNI space (27 (link)).
McTeague L.M., Huemer J., Carreon D.M., Jiang Y., Eickhoff S.B, & Etkin A. (2017). Identification of Common Neural Circuit Disruptions in Cognitive Control Across Psychiatric Disorders. The American journal of psychiatry, 174(7), 676-685.
Publication 2017
Anxiety Disorders Autism Spectrum Disorders Bipolar Disorder Brain Cognition Contrast Media Diagnosis Discrimination, Psychology Disease, Chronic Disorder, Attention Deficit-Hyperactivity Disorder, Delusional Drug Abuser Dysthymic Disorder Epistropheus Healthy Volunteers Major Depressive Disorder Memory, Short-Term Mental Disorders Mood Patients Phenotype Post-Traumatic Stress Disorder Psychological Inhibition Psychotic Disorders Recognition, Psychology Schizophrenia Substance Abuse Substance Use Substance Use Disorders

Most recents protocols related to «Disorder, Delusional»

1
Mental Health Service Utilization During Pandemic

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2023
Anti-Anxiety Agents Antidepressive Agents Antipsychotic Agents Anxiety Disorders Diagnosis Diagnosis, Psychiatric Disorder, Delusional Emergencies Gender Hypnotics Inclusion Bodies Mental Health Mental Health Services Mood Disorders Pandemics Patient Acceptance of Health Care Patients Pharmaceutical Preparations Physical Examination Psychotic Disorders Psychotropic Drugs Schizophrenia Sedatives Sleep Disorders Somatoform Disorder Therapeutics
2
Epidemiological Study of OCD and Schizophrenia
The data analysed were acquired from the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC) of the National Health Insurance Service (NHIS) between 2002 and 2013. The Korean NHIS provides researchers with all data on claims collected under the NHIS for academic investigation and policy making. The NHIS-NSC data include all medical claims from 1 025 340 individuals, accounting for 2% of the South Korean population by random sampling. The NHIS-NSC database provides information on socioeconomic status and clinically determined International Classification of Diseases, 10th revision (ICD-10) codes. The NHIS-NSC data were de-identified. Thus, the institutional review board waived the need for informed consent. All patients in the cohort were followed up unless they were excluded because of death or migration.
Patients who sought treatment for OCD (F42) or schizophrenia, schizotypal and delusional disorder (F2X) in 2002 were excluded as this study aimed to investigate patients with newly developed OCD and schizophrenia. The database started in 2002. Thus, patients diagnosed in 2002 could be diagnosed initially before the study period. We excluded patients from the analysis with a difference of less than 1 year between the diagnosis date of OCD and schizophrenia to reduce the possibility of reverse causality and initial misdiagnosis of the two diseases. The sensitivity analysis for the period between the date of diagnosis is presented in online Supplementary Table 1. The OCD patients were included in the study population when they first received the diagnostic code for OCD. They were followed up until they died or received a diagnostic code for schizophrenia or the end of the study period (2013.12.31). After these exclusions, 2509 patients were included in the OCD group. A control group was included based on 1 : 3 propensity score matching using logistic regression to calculate the probability with covariates of sex, age group, insurance, index year, income status and OneToManyMTCH macro run in SAS (Parsons, 2004 ). The c-statistics of the propensity model was 0.601.
Kim H., Kim S.H., Jeong W., Park Y.S., Kim J., Park E.C, & Jang S.I. (2023). Association between obsessive-compulsive disorder and the risk of schizophrenia using the Korean National Health Insurance Service-National Sample Cohort: a retrospective cohort study. Epidemiology and Psychiatric Sciences, 32, e9.
Full text: Click here
Publication 2023
Age Groups Diagnosis Disorder, Delusional Ethics Committees, Research Hypersensitivity Koreans MLL protein, human National Health Insurance Patients Schizophrenia
3
Mental Illness Inclusion Protocol
Consenting adults (aged ≥18 years) with a clinical diagnosis of SMI as defined by the ICD-10 (schizophrenia, schizotypal and delusional disorders (F20–F29); bipolar affective disorder (F30, F31) or severe depression with psychotic symptoms (F32.3, F33.3)), and able to provide informed consent as assessed by the treating clinician, were eligible.
Zavala G.A., Haidar-Chowdhury A., Prasad-Muliyala K., Appuhamy K., Aslam F., Huque R., Khalid H., Murthy P., Nizami A.T., Rajan S., Shiers D., Siddiqi N., Siddiqi K, & Boehnke J.R. (2023). Prevalence of physical health conditions and health risk behaviours in people with severe mental illness in South Asia: multi-country cross-sectional survey. BJPsych Open, 9(2), e43.
Full text: Click here
Publication 2023
Adult Bipolar Disorder Depressive Symptoms Diagnosis Disorder, Delusional Mental Disorders Schizophrenia
4
Identifying Childhood Psychiatric Disorders from Health Registries
We retrieved any records of diagnosed child or adolescent psychiatric disorder from the Danish health registries. All live-born children in Denmark are assigned a unique civil registration number that is linked to the National Patient Register.14 (link) We obtained data on psychiatric disorders from both in-patient admissions and out-patient contacts. We were interested first in main diagnoses in any of the following diagnostic groups: any psychiatric disorder (ICD-10: F00-F99); schizophrenia, schizotypal and delusional disorders (ICD-10: F20 – F29); mood disorders, anxiety, dissociative, stress-related, somatoform and other nonpsychotic mental disorders (ICD-10: F30-F45, F48, F93); autism spectrum disorders (ICD-10: F84 not: F84.2-F84.4); personality disorders (F60-F69); hyperkinetic disorders (ICD-10: F90, F98.9); and conduct disorders (ICD-10: F91, F90.1).15 Thus, the disorder-specific diagnostic groups were not mutually exclusive. We formed a group of children and adolescents with, presumably, milder mental disorders16 (link) who had redeemed two or more prescriptions of psychotropic drugs without being registered with a psychiatric diagnosis (ACT groups: N05, N06A, N06B, N06C).17 (link)
Rasmussen I.S., Wilson P., Overbeck G, & Strandberg-Larsen K. (2023). Association of self-reported mother–infant relationship with child and adolescent mental health. BJPsych Open, 9(2), e39.
Full text: Click here
Publication 2023
Adolescent Anxiety Disorders Autism Spectrum Disorders Child Childbirth Conduct Disorder Diagnosis Diagnosis, Psychiatric Disorder, Attention Deficit-Hyperactivity Disorder, Delusional Mental Disorders Mood Disorders Outpatients Patient Admission Patients Personality Disorders Prescriptions Psychotropic Drugs Respiratory Diaphragm Schizophrenia
5
Factors Influencing Self-Management Interventions for SMI
Inclusion criteria. Participants: Staff facilitating the self-management intervention in a secondary mental health service, or people with a clinical diagnosis of non-affective psychosis (schizophrenia, schizophreniform disorder, schizoaffective disorder, delusional disorder, psychotic disorder not otherwise defined), bipolar disorder, or major depression who are receiving the intervention.
Interventions: The criteria used to define supported self-management were as in a previous review of effectiveness of supported self-management interventions conducted by members of the same research group [7 (link)]. To be included in the review, the intervention was required to include all of the following three domains, which are three of four domains that Mueser and colleagues [6 (link)] described as “effective areas of self-management”:
Comparator(s)/control: A comparator or control group was not required.
Exposures: Any primary data on factors which influence the implementation of self-management interventions for people with SMI in secondary mental health services.
Design: Full-text journal articles with primary qualitative or quantitative data (or both). If the primary focus of the study was not an investigation of the barriers or facilitators to the use of self-management interventions but the results section included data relevant to the research question, the study was included.
Islam S., Appleton R., Hutchings-Hay C., Lloyd-Evans B, & Johnson S. (2023). A systematic review of influences on implementation of supported self-management interventions for people with severe mental health problems in secondary mental health care settings. PLOS ONE, 18(2), e0282157.
Full text: Click here
Publication 2023
Affective Disorders, Psychotic Bipolar Disorder Diagnosis Disorder, Delusional Major Depressive Disorder Mental Health Services Psychotic Disorders Schizoaffective Disorder Schizophrenia Schizophreniform Disorders Self-Management

Top products related to «Disorder, Delusional»

1
Ge signa scanner by GE Healthcare
Sourced in United States
The GE Signa scanner is a magnetic resonance imaging (MRI) system designed for diagnostic imaging in healthcare settings. It uses a strong magnetic field and radio waves to generate detailed images of the body's internal structures. The Signa scanner's core function is to capture high-quality images that enable healthcare professionals to diagnose and monitor medical conditions.
2
Sample size calculator by Raosoft
Sourced in United States
The Sample size calculator is a tool that determines the minimum number of samples required for a statistical study or experiment. It calculates the appropriate sample size based on factors such as the desired level of confidence, margin of error, and population size. This tool provides a straightforward way to ensure the statistical validity of research findings.

More about "Disorder, Delusional"