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> Disorders > Mental or Behavioral Dysfunction > Disorder, Depressive

Disorder, Depressive

Depressive Disorder is a mental health condition characterized by persistent feelings of sadness, loss of interest, and a range of physical and cognitive symptoms that can significantly impair daily functioning.
This disorder is often associated with changes in mood, energy levels, sleep patterns, appetite, and concentration.
Individuals with Depressive Disorder may experience episodes of major depression, dysthymia, or other subtypes, and may be at an increased risk of suicidal thoughts or behaviors.
Effective treatment approaches often involve a combination of psychotherapy, medication, and lifestyle modifications.
Researchers and clinicians can optimize their work on Depressive Disorder by utilizing PubComapre.ai's AI-driven protocol comparison tools, which help locate the most effective research approaches from the literature, pre-prints, and patents.

Most cited protocols related to «Disorder, Depressive»

1
Antenatal and Postpartum Depression Screening
Cited 91 times
Datasets from studies that met the following criteria were deemed eligible: they administered the EPDS; diagnostic classification for current major depressive disorder or major depressive episode used Diagnostic and Statistical Manual of Mental Disorders (DSM)24
25
26 or international classification of diseases (ICD)27 criteria based on a validated semi-structured or fully structured interview; the EPDS and diagnostic interview were conducted no more than two weeks apart; participants were adult women aged at least 18 years who completed assessments during pregnancy or within 12 months of giving birth; and participants were not recruited because they were receiving psychiatric assessment or care, or because they were identified as having possible depression because screening seeks to identify women with otherwise unrecognised major depression.28 (link) Studies in which some participants did not meet eligibility criteria were included in the IPDMA if primary data allowed for the selection of eligible participants.
Levis B., Negeri Z., Sun Y., Benedetti A., Thombs B.D., He C., Krishnan A., Wu Y., Bhandari P.M., Neupane D., Imran M., Rice D.B., Azar M., Sanchez T.A., Chiovitti M.J., Saadat N., Riehm K.E., Boruff J.T., Kloda L.A., Cuijpers P., Gilbody S., Ioannidis J.P., McMillan D., Patten S.B., Shrier I., Ziegelstein R.C., Comeau L., Mitchell N.D., Tonelli M., Vigod S.N., Aceti F., Alvarado R., Alvarado-Esquivel C., Bakare M.O., Barnes J., Bavle A.D., Beck C.T., Bindt C., Boyce P.M., Bunevicius A., Correa H., Couto T.C., Chaudron L.H., Chorwe-Sungani G., de Figueiredo F.P., Eapen V., Favez N., Felice E., Fellmeth G., Fernandes M., Field S., Figueiredo B., Fisher J.R., Garcia-Esteve L., Giardinelli L., Green E.P., Helle N., Honikman S., Howard L.M., Kettunen P.A., Khalifa D.S., Kohlhoff J., Kusminskas L., Kozinszky Z., Lelli L., Leonardou A.A., Maes M., Marsay C.Y., Martínez P., Meuti V., Nakić Radoš S., Navarro García P., Nishi D., Okitundu Luwa E-Andjafono D., Pawlby S.J., Robertson-Blackmore E., Rochat T.J., Rowe H.J., Sharp D.J., Siu B.W., Skalkidou A., Smith-Nielsen J., Stein A., Stewart R.C., Su K.P., Sundström-Poromaa I., Tadinac M., Tandon S.D., Tendais I., Thiagayson P., Töreki A., Torres-Giménez A., Tran T.D., Trevillion K., Tungchama F.P., Turner K., Væver M.S., van Heyningen T., Vega-Dienstmaier J.M., Wynter K, & Yonkers K.A. (2020). Accuracy of the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression among pregnant and postpartum women: systematic review and meta-analysis of individual participant data. The BMJ, 371, m4022.
Publication 2020
Adult Childbirth Diagnosis Eligibility Determination Major Depressive Disorder Pregnancy Woman
2
Diagnostic Assessment of DSM-5 Disorders
Cited 77 times

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Publication 2014
Agoraphobia Alcohol Use Disorder Anxiety Disorders Cannabis Central Nervous System Stimulants Club Drugs Cocaine Conduct Disorder Diagnosis Disorder, Depressive Drug Use Disorders Dysthymic Disorder Hallucinogens Heroin Inhalation Drug Administration Manic Episode Mood Disorders Opioids Panic Disorder Pharmaceutical Preparations Phobia, Social Phobia, Specific Post-Traumatic Stress Disorder Sedatives Solvents Tobacco Products Tobacco Use Disorder Tranquilizing Agents
3
SCAN Depression Module: Validated Psychiatric Diagnostic Tool
Cited 61 times

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Publication 2013
Adult Diagnosis Mental Disorders Population Group Psychometrics Radionuclide Imaging
4
Depression Screening Accuracy Assessment
Cited 61 times
Descriptive statistics were completed for the full sample and stratified by depression status. Three categories of depression status were used based on algorithms from the DISC-IV: major depression, “intermediate depression”, or no depressive disorder.12 (link) Youth with “intermediate depression” reported at least 3 of the 9 symptom criteria for major depression but did not meet diagnostic criteria for major depression in the past year. Chi-square analyses and F-test analyses were used to compare categorical and continuous variables, respectively, among depressed and non-depressed individuals based on PHQ-9 score. The area under the ROC curve was calculated as a quantification of the sensitivity and specificity of the ability of the self-report questionnaires to classify youth into the past month major depression category based on the DISC-IV. Results were interpreted based on standards that have been set for interpreting the area under the curve.18
Richardson L.P., McCauley E., Grossman D.C., McCarty C.A., Richards J., Russo J.E., Rockhill C, & Katon W. (2010). Evaluation of the Patient Health Questionnaire (PHQ-9) for Detecting Major Depression among Adolescents. Pediatrics, 126(6), 1117-1123.
Publication 2010
Diagnosis Major Depressive Disorder Youth
5
Screening and Assessing Depression in Children
Cited 59 times
The child phone interview included the Patient Health Questionnaire 9-item (PHQ-9) screener and the Diagnostic Interview Schedule for Children depression modules (DISC-IV). The PHQ-9 was completed prior to other depression and mental health measures.
The PHQ-9 is a self-administered version of the depression portion of the PRIME-MD interview,11 (link) which uses DSM-IV criteria to assess for mental disorders in primary care.8 (link) It can be scored to provide a dichotomous diagnosis of probable major depression and to grade symptom severity via a continuous score. The PHQ-9 has been found to have high sensitivity (73%) and high specificity (98%) for the diagnosis of major depression in adult populations.8 (link), 11 (link) Among adults, scores on the PHQ-9 have also been used to define severity for probable diagnoses in the following manner: a score of 5-9 is considered minimal depression, 10-14 is considered mild major, 15-19 is moderate major, and ≥20 is severe major.8 (link) The PHQ-9 also has a functional impairment question (item 10) that asks how much the symptoms they endorse in the first 9 items interfere with daily functioning.
The DISC-IV is a reliable and valid structured interview designed for lay interviewers, which includes algorithms to diagnose DSM-IV disorders in children and adolescents.12 (link) Telephone versions of structured psychiatric interviews have been found to have a high correlation with in-person interviews.13 (link), 14 (link) In order to decrease patient burden, only the depression modules (major depression and dysthymia) were used. All interviewers received 12 hours of classroom and hands-on training and additional project-specific training on the DISC-IV.
Richardson L.P., McCauley E., Grossman D.C., McCarty C.A., Richards J., Russo J.E., Rockhill C, & Katon W. (2010). Evaluation of the Patient Health Questionnaire (PHQ-9) for Detecting Major Depression among Adolescents. Pediatrics, 126(6), 1117-1123.
Publication 2010
Adolescent Adult Child Diagnosis Dysthymic Disorder Hypersensitivity Interviewers Major Depressive Disorder Mental Disorders Mental Health Patients Population Group Primary Health Care

Most recents protocols related to «Disorder, Depressive»

1
Rapid Antidepressant Effects of CN2097 and dR7-2097
Not available on PMC !

Example 3

The discovery of rapidly acting antidepressants, such as ketamine, has transformed our ideas about depression treatment. Based on the above-described data (FIGS. 2-4), CN2097 elicits rapid antidepressant effects that merits further testing. Moreover, although dR7-2097 is a stable analog that is not cleared rapidly like CN2097, its functional efficacy remains to be determined and compared to CN2097 in an animal model of depression. Accordingly, the effects of CN2097 and dR7-2097 on memory recall were assessed in the Contextual Fear Conditioning (CFC) test.47

Mice received i.p. injections of 1, 5, or 10 mg/kg CN2097 or 1 or 5 mg/kg dR7-2097.

As shown in the FIG. 5, dR7-2097 was more efficacious than CN2097 in significantly increasing memory recall in the CFC test. These results show that it is possible to modify CN2097 with (D)-amino acids and not only maintain the efficacy but enhance it. The suggests that the increased stability will enable the administration of lower doses (10 fold or more) while maintaining anti-depressive properties.

US11879020B2. Cyclic peptidomimetic for the treatment of neurological disorders (2024-01-23). Brown University [US]. Inventors: John Marshall [US].
Full text: Click here
Patent 2024
Amino Acids Animal Model Antidepressive Agents CN2097 Fear of disease Ketamine Memory Mental Recall Mus
2
Recruiting Adult Outpatients for Depression
Patients between 18 and 65 years of age referred to a treatment package for single-episode depression will be recruited (Table 1) with minimal exclusion criteria to recruit representative adult outpatients who would typically receive treatment in routine practice (Table 1), of which the majority are women (71%) and aged 18–35 (68%) (S. Figure 1). Patients over 65 (approximately 0.7% of the target population) are excluded because of potential age-related cognitive decline, concomitant medical conditions, or medications that could interact with assessments or treatment (S. Figure 1). Allocation into the subcohorts is based on eligibility, e.g., MRI compatibility, scheduling, and patient willingness to participate.

Inclusion and exclusion criteria for patients

Patient inclusion criteria:

• Fulfilment of ICD-10 diagnostic criteria for a primary depressive episode (i.e., not secondary to known organic or other psychiatric disorder)

• Referral to a treatment package for single-episode depression

• Age between 18 and 65 years

Exclusion criteria:

• Psychosis or psychotic symptoms

• History of severe head trauma involving hospitalization or unconsciousness for more than 5 min

• Known, substantial structural brain abnormalities

• Insufficient Danish language skills to complete questionnaires and cognitive testing

Additional exclusion criteria for subcohort I:

• Severe somatic disease

• Contraindications for MRI (e.g., metal implants, claustrophobia, or back problems)

Additional exclusion criteria for subcohort I:

• Use of psychotropic drugs

• Exposure to radioactivity > 10 mSv within the last year

• Pregnancy or breastfeeding

The primary depressive episode, consistent with the International Statistical Classification of Diseases and Related Health Problems version 10 (ICD-10) criteria for MDD without psychotic features (F32.1, F32.2, F32.8 and F32.9), is confirmed by a specialist in psychiatry at the central diagnostic and referral centre.
Jensen K.H., Dam V.H., Ganz M., Fisher P.M., Ip C.T., Sankar A., Marstrand-Joergensen M.R., Ozenne B., Osler M., Penninx B.W., Pinborg L.H., Frokjaer V.G., Knudsen G.M, & Jørgensen M.B. (2023). Deep phenotyping towards precision psychiatry of first-episode depression — the Brain Drugs-Depression cohort. BMC Psychiatry, 23, 151.
Full text: Click here
Publication 2023
Adult Brain Claustrophobia Cognition Congenital Abnormality Craniocerebral Trauma Diagnosis Diploid Cell Disorders, Cognitive Eligibility Determination Hospitalization Mental Disorders Metals Outpatients Patients Pharmaceutical Preparations Pregnancy Psychotic Disorders Psychotropic Drugs Radioactivity Satisfaction Target Population Woman
3
Depression Treatment Outcomes Evaluation
The primary clinical outcomes are categorical: improvement defined as ≥ 50% reduction in QIDS and remission after the treatment package defined as a QIDS ≤ 5. The secondary outcome is change in depression severity as measured by QIDS.
Jensen K.H., Dam V.H., Ganz M., Fisher P.M., Ip C.T., Sankar A., Marstrand-Joergensen M.R., Ozenne B., Osler M., Penninx B.W., Pinborg L.H., Frokjaer V.G., Knudsen G.M, & Jørgensen M.B. (2023). Deep phenotyping towards precision psychiatry of first-episode depression — the Brain Drugs-Depression cohort. BMC Psychiatry, 23, 151.
Full text: Click here
Publication 2023
4
Biomarker Profiling in Depression
Venous blood samples will be collected for serum, plasma, DNA, and RNA extraction. Identifying biomarkers relevant to the course of depression is an area of research that is evolving rapidly. Thus, based on an ongoing critical literature review, the search for and analysis of specific biomarkers may change during the study period. Currently, the blood biomarkers include inflammation parameters (e.g., high sensitivity CRP) [61 (link), 62 (link)] and neurotrophic factors (e.g., BDNF and S100B) [63 , 64 (link)].
DNA from blood samples will be used for microarray-based genotyping of MDD candidate genes, genes of relevance for MDD (e.g., rs41271330, 5-HTTLPR, COMT, and BDNFval66met), drug metabolism (e.g., CYP2D6, CYP2C19, UGT1A1, ABCB1, ABCC1) and to compute polygenic risk scores in all participants after genome-wide genotyping in the future. DNA will also be used for epigenetic analysis, and circular extrachromosomal DNA, a form of decomposed free DNA [65 (link)], will be extracted and characterised. RNA will be extracted for gene transcription profiles using microarray or TAG-based methods (mRNA and microRNA).
DNA from blood samples will be used for microarray-based genotyping of MDD candidate genes, genes of relevance for MDD (e.g., rs41271330, 5-HTTLPR, COMT, and BDNFval66met), drug metabolism (e.g., CYP2D6, CYP2C19, UGT1A1, ABCB1, ABCC1) and to compute polygenic risk scores in all participants after genome-wide genotyping in the future. DNA will also be used for epigenetic analysis, and circular extrachromosomal DNA, a form of decomposed free DNA [65 (link)], will be extracted and characterised. RNA will be extracted for gene transcription profiles using microarray or TAG-based methods (mRNA and microRNA).
Gene analyses will be based on a priori models of genetic variations known to modulate pharmacotherapy and psychotherapy responses. The results will be used to calculate a polygenic risk score for diagnosis and treatment response and meta-analyses with established polygenic risk scores for MDD and those currently developed for anxiety and anxiety disorders, including treatment response [66 (link)].
Jensen K.H., Dam V.H., Ganz M., Fisher P.M., Ip C.T., Sankar A., Marstrand-Joergensen M.R., Ozenne B., Osler M., Penninx B.W., Pinborg L.H., Frokjaer V.G., Knudsen G.M, & Jørgensen M.B. (2023). Deep phenotyping towards precision psychiatry of first-episode depression — the Brain Drugs-Depression cohort. BMC Psychiatry, 23, 151.
Full text: Click here
Publication 2023
ABCB1 protein, human ABCC1 protein, human Anxiety Anxiety Disorders Biological Markers BLOOD COMT protein, human CYP2C19 protein, human Cytochrome P-450 CYP2D6 Diagnosis DNA, A-Form DNA, Circular Genes Genetic Diversity Genome Hypersensitivity Inflammation Metabolism Microarray Analysis MicroRNAs Nerve Growth Factors Pharmaceutical Preparations Pharmacotherapy Plasma Psychotherapy RNA, Messenger Serum Transcription, Genetic UGT1A1 protein, human Veins
5
Long-Term Longitudinal Psychiatric Outcomes
After the last 18-month follow-up, the study dataset will be sent to Statistics Denmark with a list of all invited participants to allow a non-participant analysis and long-term follow-up. The study data will be linked with data from the Danish Civil Registration System [76 (link)] e.g., the DNPR [57 (link)], the Danish National Prescription Registry [55 (link), 56 ], and other registries indexing, e.g., hospital admittance, diagnosis- and treatment codes, prescription medications, employment status, living situation (e.g., partner information), and income. We will also examine diagnostic stability [77 (link)], e.g., change of primary diagnosis from first episode depression to an anxiety or personality disorder or later recurrent depressive episode or conversion to bipolar affective disorder.
Jensen K.H., Dam V.H., Ganz M., Fisher P.M., Ip C.T., Sankar A., Marstrand-Joergensen M.R., Ozenne B., Osler M., Penninx B.W., Pinborg L.H., Frokjaer V.G., Knudsen G.M, & Jørgensen M.B. (2023). Deep phenotyping towards precision psychiatry of first-episode depression — the Brain Drugs-Depression cohort. BMC Psychiatry, 23, 151.
Full text: Click here
Publication 2023
Anxiety Disorders Diagnosis Disorder, Dissociative Personality Disorders Prescription Drugs

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More about "Disorder, Depressive"

Depressive Disorder, also known as Major Depressive Disorder (MDD) or Clinical Depression, is a prevalent mental health condition characterized by persistent feelings of sadness, hopelessness, and loss of interest.
Individuals with this disorder may experience a range of physical and cognitive symptoms, such as changes in sleep patterns, appetite, energy levels, and concentration.
The disorder can manifest in different subtypes, including Major Depression, Persistent Depressive Disorder (Dysthymia), and Seasonal Affective Disorder (SAD).
Effective treatment approaches often involve a combination of psychotherapy, medication, and lifestyle modifications, such as regular exercise, stress management, and social support.
Researchers and clinicians can optimize their work on Depressive Disorder by utilizing powerful AI-driven tools like PubCompare.ai, which help locate the most effective research approaches from the literature, pre-prints, and patents.
These tools can be particularly useful when working with data from statistical software like SAS version 9.4, SPSS version 26, Stata version 14, and their earlier versions.
By leveraging these advanced analytics and comparison capabilities, researchers can discover the most effective protocols and products, leading to improved outcomes for individuals struggling with this debilitating mental health condition.
Experiance the difference today with PubCompare.ai's intuitive and AI-powered tools!