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Depression

Depression is a common and serious mental health condition characterized by persistent feelings of sadness, hopelessness, and loss of interest in activities.
It can affect an individual's mood, thoughts, behaviors, and physical well-being.
Depression often co-occurs with other medical conditions and can have a significant impact on a person's quality of life.
Researchers and clinicians strive to develop effective treatments and interventions to manage this complex disorder.
The PubCompare.ai platform can assist in this effort by optimiziing depression research protocols for reproducibility and accuracy, providing a valuable tool for the scientific community.

Most cited protocols related to «Depression»

Potential labels for the EQ-5D-5L were identified from a review of existing health-related quality-of-life instruments, a review of the literature on response scaling, hand searching of dictionaries and thesauruses, and informal interviews with native speakers of the target languages to establish how they described different severities of health problems. The same process was carried out in English and Spanish and, where possible, equivalent terms were sought in both languages. Labels included in the initial pool clearly had to fit with the lexical structure used in the EQ-5D-3L, such as ‘I have no problems doing my usual activities’ and ‘I have some problems doing my usual activities’.
In order to select labels from the pool for the new levels, an interviewer-administered response scaling exercise similar to those used in previous studies [14 (link), 19 , 20 (link)] was adopted to estimate the severity represented by each label. For this exercise, respondents were shown a rating scale in the form of a vertical, hash-marked, 40 cm visual analog scale (VAS) with end points of 0 and 100 to be used as a visual aid in grading label severity. For the Mobility, Self-Care and Usual Activities dimensions, the same set of labels was used. The interviewer placed a card labeled ‘No problems’, ‘No pain/discomfort’, or ‘No anxiety/depression’ as appropriate at the bottom of the scale (0) to act as the lower anchor and a card labeled ‘Unable to, ‘The worst pain or discomfort I can imagine’, ‘As anxious or depressed as I can imagine’ as the upper anchor (100). The respondent was then shown other labels from the pool singly in a quasi-random order and asked to assign a score between 0 and 100 to indicate label severity in relation to the lower and upper anchors.
The interviewer noted all scores, and when the respondent had rated all labels for a particular dimension, the interviewer laid them out in rank order alongside the VAS and asked the respondent to review the ranking and make any changes he or she thought necessary. If labels were reordered at this point, the respondent was asked to assign a new score to the relevant labels. Final scores assigned were recorded in an answer booklet. The scaling task was repeated for each dimension. Before finishing with the cards, the respondent was asked whether any of the labels sounded unusual, or should not be used in relation to a particular dimension.
Respondents rated labels for all five dimensions. The three functional dimensions (Mobility, Self-Care and Usual Activities) were always interspersed by the Pain/Discomfort and Anxiety/Depression dimensions, so that the respondent did not rate the same label types consecutively. Before rating the actual labels, respondents performed a practice task based on levels of overall health to get used to the study requirements. Data on age, level of education, main activity, and use of any current treatment for health problems, together with the existing EQ-5D-3L descriptive system and EQ-VAS, were collected after the response scaling task.
Before the main response scaling task, a pilot test was performed to test study procedures and materials. Based on the results of the pilot study, some labels were eliminated from the initial pool to achieve a more manageable number for the response scaling task. In particular, any labels using additional modifiers such as ‘very’ or ‘quite’ were eliminated as were any that were considered excessively colloquial or too high a level of language. After pilot testing, it was concluded that the feasible limit was about 10–12 labels per dimension for an individual respondent.
Responses to the scaling task were analyzed by calculating means and medians and the corresponding standard deviations and interquartile ranges (IQR). Labels to go forward for further testing were selected based on criteria that had been identified before data collection started. These included selecting labels close to or at the 25th, 50th, and 75th centiles on the VAS, ensuring consistency across dimensions and coherence with wording in the descriptive system. No quantitative comparison of label scores was carried out in deciding which labels to carry forward to the next stage; median scores were simply used as a guide to determine which labels fell closest to the 25th, 50th, and 75th centiles. Labels were also required to be in colloquial language. The choice of labels and their appropriateness was discussed by the task force at several meetings during the course of the study.
Publication 2011
Anxiety Hispanic or Latino Interviewers Marijuana Abuse Pain Range of Motion, Articular Visual Analog Pain Scale
A frailty index counts deficits in health. These deficits were defined as symptoms, signs, disabilities and diseases [5 ]. All health deficits, including continuous, ordinal and binary variables, were taken from the PEP survey data dictionary. Restricted activity, disability in Activities Daily Living (ADL) and Instrumental ADL, impairments in general cognition and physical performance (e.g. impaired grip strength, impaired walking), co-morbidity, self-rated health, and depression/mood were evaluated.
Variables can be included in a frailty index if they satisfy the following 5 criteria:
1) The variables must be deficits associated with health status. Attributes such as graying hair, while age-related, are attributes and therefore not included. 2) A deficit's prevalence must generally increase with age, although some clearly age-related adverse conditions can decrease in prevalence at very advanced ages due to survivor effects. 3) Similarly, the chosen deficits must not saturate too early. For instance, age-related lens changes resulting in problems with accommodation (presbyopia) are nearly universal by age 55; in other words, as a variable, presbyopia saturates too early to be considered as a deficit here. 4) When considering the candidate deficits as a group, the deficits that make up a frailty index must cover a range of systems – if all variables were related to cognition, for example, the resulting index might well describe changes in cognition over time, but would be a cognitive impairment index [18 (link)] not a frailty index. 5) If a single frailty index is to be used serially on the same people, the items that make up the frailty index need to be the same from one iteration to the next [19 (link)]. The requirement to use the same items need not apply to comparisons between samples – i.e. samples that use difference frailty indexes appear to yield similar results [5 ].
Deficits should be added until there are at least 30–40 total deficits. There needs to be a minimum number of deficits. In general, the more variables that are included in a frailty index, the more precise estimates become. Similarly, estimates are unstable when the number of deficits is small – about 10 or less. Even so, an index with 30–40 variables has been shown to be sufficiently accurate for predicting adverse outcomes [6 (link),14 (link)]. Furthermore, a frailty index can be constructed using information that is readily available in most health surveys, and is clinically tractable – i.e. it uses an amount that would be gathered in many routine health assessments of older adults [5 ].
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Publication 2008
Aged Cognition Disabled Persons Disorders, Cognitive Hair Lens, Crystalline Mood Ocular Accommodation Performance, Physical Presbyopia Survivors
Final construction of items involved careful consideration of time frames, response sets, verb tense, grammatical structure, and demands on literacy (see DeWalt et al., 2007 (link)). We examined precedents for alternative time frames, response sets, and number of response options among the questionnaires in the instrument library. The most common time frame for instruments assessing emotional distress was 7 days (33%), and the most common response sets were severity (52%), frequency (22%), or the presence versus absence of symptoms—for example, “yes/no” or “true/false” (19%). A total of 63% of scales used four or five response options. Based on these data and prior experience with the use of IRT models in assessment of health-related constructs (Bode, Lai, Cella, & Heinemann, 2003 (link)), four to six response levels appeared to be optimal. In the area of emotional distress, we adopted a 7-day time frame and a 5-point scale for frequency (never, rarely, sometimes, often, always). The 7-day time frame was consistent both with precedents from the research literature and with decisions made for other PROMIS domains, where sensitivity to change in the context of potentially brief clinical trials was a consideration. There was no definitive guidance available from the research literature about the choice between response options reflecting severity or intensity versus those for frequency or duration. There were suggestions, however, that frequency scaling may provide broader coverage (reducing floor and ceiling efforts) for health-related assessment (Chang et al., 2003 (link)) and that frequency scaling is more appropriate for short intervals, given the usual “conversational” inferences of respondents, who assume that short reference periods pertain to frequent experiences and that long periods pertain to rare and intense experiences (Winkielman, Knäuper, & Schwarz, 1998 (link)).
Based on these considerations, the 457 items in the reduced pool were rewritten in a common format: first person singular, past tense, with a 7-day time frame and a 5-level ordinal scale of frequency for response options (In the past 7 days, I felt depressed: never, rarely, sometimes, often, always). The majority of self-report measures of depression and anxiety are written at a reading-grade level that exceeds the mean proficiency in the United States (McHugh & Behar, 2009 (link)). We strived to reduce the literacy demand of our items by minimizing the number of words per sentence and choosing simpler rather than more demanding synonyms. More than 50% of items contained five or fewer words, and more than 20% were even simpler, three-word sentences (e.g., I felt sad). The Lexile Framework for Reading (MetaMetrics, 2008 ), a method for measuring the literacy demands of text, confirmed that the items were easy to read. Lexile text analyses documented that the items required an average first-grade reading level, with a standard deviation of 1.5 grades (Lexile M = 180.2, SD = 263.7).
Publication 2011
Anxiety cDNA Library Feelings Hypersensitivity Maritally Unattached Psychological Distress Reading Frames Sadness
The 3L version of the EQ-5D is the initial version that has been used in many clinical trials and methodological studies published in the peer-reviewed literature [1 (link)]. It is a brief self-reported generic measure of current health that consists of five dimensions (Mobility, Self-Care, Usual Activities, Pain/Discomfort, and Anxiety/Depression), each with three levels of functioning (no problems, some problems, and unable to/extreme problems). This health state classification describes 243 unique health states that are often reported as vectors ranging from 11111 (full health) to 33333 (worst health). Societal value sets have been derived from population-based valuation studies around the world that, when applied to the health state vectors, result in preference-based index values that typically range from states worse than dead (<0), to 1 (full health), anchoring dead at 0. In addition, the EQ-5D includes an EQ-VAS where own health “today” is rated on a scale from 0 (worst imaginable health) to 100 (best imaginable health).
In developing the 5L, the five-dimensional structure of the 3L was retained, but the descriptors within each dimension were adapted to a 5-level system based on qualitative and quantitative studies conducted by the EuroQol group [19 (link)]. The labels for 5L followed the format no problems, slight problems, moderate problems, severe problems, and unable to/extreme problems for all dimensions. For Mobility, the description of “confined to bed” was changed to “unable to walk about.” Additionally, for Usual Activities, the word “performing” was changed to “doing” (English for UK version). The official EQ-5D-3L and EQ-5D-5L language versions for each country were used.
For the purposes of the current study, respondents also rated their own health “today” on five dimension-specific rating scales, one for each of the EQ-5D dimensions. Each scale consisted of a horizontal hash-marked line (from 0 to 100) with corresponding numbers (0, 10, 20, …, 100). The descriptive anchors at each end of the scales were the same anchors as used in the 3L and 5L, that is, no problems and unable to/extreme problems.
Convergent validity was assessed by comparing the 3L and 5L dimensions to the WHO-5 Well Being questionnaire. The WHO-5 captures well-being and was developed from the World Health Organization-Ten Well-Being Index [24 (link), 25 (link)]. It was conceptualized as a unidimensional measure that contains five positively worded items: “I have felt cheerful and in good spirits”; “I have felt calm and relaxed”; “I have felt active and vigorous”; “I woke up feeling fresh and rested”; and “My daily life has been filled with things that interest me,” all operationalized using a six-point Likert scale ranging from 0 (not present) to 5 (constantly present). A sum-score can be calculated as a summary measure.
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Publication 2012
Anxiety BAD protein, human Cloning Vectors Generic Drugs Marijuana Abuse Pain Range of Motion, Articular
The Treatment of Adolescent Suicide Attempters study was a National
Institute of Mental Health multisite feasibility study designed to develop
and evaluate treatments to prevent suicide reattempts in adolescents.
Participants were 124 male and female patients 12–18 years of age
with a suicide attempt or interrupted attempt during the 90 days before
enrollment (34 (link)–36 (link)). Participants were evaluated at
baseline and at treatment weeks 6, 12, 18, and 24, as well as during
intervening unscheduled visits. Evaluations included the C-SSRS, the
Columbia Suicide History Form, the Scale for Suicide Ideation, and
Beck’s Lethality Scale. All instruments were administered by
independent evaluators, who were Ph.D.-, R.N.-, or master’s-level
clinicians. Assessment of participants also included the self-report Beck
Depression Inventory (BDI) at the same visits, as well as ratings by the
treating psychopharmacologist (who was not the independent evaluator) on the
Montgomery-Åsberg Depression Rating Scale (MADRS). Any potential
suicidal events in the study were rated by the suicide evaluation board,
which was an independent panel of suicidology experts uninvolved in the
day-to-day management of the trial. The board, which was blind to original
event classifications, treatment status, and other potentially biasing
information, rated narratives according to predetermined criteria and
definitions of potential suicidal events. Unanimous consensus was reached in
cases where there was any initial disagreement.
Most participants (N=96, 77.4%) were assessed at
week 12; 87 (70.2%) were evaluated at week 18, and 83
(66.9%) at week 24. Attrition between the study visits was due to
participants refusing to continue study treatment or assessments.
Participants who refused treatment but continued with assessments were
included in the analyses. There was one death by suicide in the study during
the follow-up period. As previously reported (36 (link)), participants who remained in the study for
longer than the median duration were similar to those who were followed for
less than the median duration on all baseline predictors of suicidal events
except income.
Publication 2011
Adolescent Males Mental Health Patients Suicide Attempt Tooth Attrition Visually Impaired Persons Woman

Most recents protocols related to «Depression»

Example 2

A 28 year-old woman experienced severe anger and depression one day a month, right before her period, every month. She took two capsules of 100 mg anhydrous enol-oxaloacetate on that day. She reported that while the anger and depression were not completely resolved, they were reduced in intensity to the point where she could manage the symptoms easily.

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Patent 2024
Anger Capsule Oxaloacetate Woman
Not available on PMC !

Example 5

In Fabrication method examples 1 to 4, the structure body provided with the uneven structure in the depression is used; however, one embodiment of the present invention is not limited thereto. For example, a structure body not provided with an uneven structure in a depression may be used. In that case, after the battery unit 120 is covered with the member 109 with rubber elasticity whose surface is flat, the member 109 with rubber elasticity can be shaved with a sharp cutter or the like to form an uneven structure. The uneven structure can be formed with a hot-wire cutter or an ultrasonic cutter, for example.

As described above, the fabrication method described in this embodiment allows the battery unit or the light-emitting unit to be covered with the member with rubber elasticity. This can suppress entry of impurities such as moisture from the air, increasing the reliability of a device. Furthermore, a device that is not easily broken even after being repeatedly bent and stretched can be fabricated.

This embodiment can be combined with any of the other embodiments as appropriate.

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Patent 2024
Elasticity Enzyme Multiplied Immunoassay Technique Human Body Medical Devices Rubber TNFSF14 protein, human Ultrasonics
The following patients were eligible for analysis: (1) CR, the diagnostic criteria: Clinical symptoms, physical examination, and confirmation of the unilateral disc herniation via cervical CT or magnetic resonance imaging (MRI); (2) Patients aged >18 years; (3) Lower cervical radicular pain lasting ≤3 months; (4) Numerical rating scale, NRS≥ 4.
The following patients were excluded from analysis: (1) Severe heart disease; (2) Severe spinal deformity; (3) Hypersensitivity to local anesthetics or hormones; (4) Coagulation dysfunction; (5) Systemic infection or skin infection at the puncture site; (6) Patients with abnormal mental behavior, severe anxiety, or depression; (7) Lactating and pregnant women; (8) History of cervical surgery; (9) Cervical spondylotic myelopathy; (10) Moderate and severe foraminal stenosis.
Publication 2023
Anxiety Cellulitis Coagulation, Blood Congenital Abnormality Diagnosis Heart Diseases Hormones Hypersensitivity Intervertebral Disk Displacement Local Anesthetics Mentally Ill Persons Neck Neck Pain Operative Surgical Procedures Patients Physical Examination Pregnant Women Punctures Sepsis Spinal Cord Diseases Spondylosis, Cervical Stenosis Tooth Root
We described differences in baseline demographics between our analytic sample and excluded individuals, and by hearing group using χ2 (categorical variables) and Kruskal–Wallis analysis of variance (continuous variables). Given the discrete nature of our data we estimated a discrete-time proportional hazard model using a cloglog model to estimate hazard ratios (HRs) (22 ) and 95% confidence intervals (CIs) for losing USOC. We verified the proportional hazard assumption by looking at the correlation between Schoenfeld residuals and survival times.
We performed unweighted and weighted (using 2011 enrollment weights) estimations to account for NHATS’ complex survey design. All main analyses were adjusted for participant’s baseline characteristics including: age, sex, race/ethnicity, marital status, education, household income, self-reported health, number of chronic conditions, dementia status, additional health coverage, and depression. All covariates were treated as time-invariant in our analyses. Survival functions by hearing group were estimated for the unweighted unadjusted model.
In secondary analyses, we explored the potential moderation effect of (i) depression and (ii) transportation barriers on the association between hearing groups and self-reported loss of USOC. These secondary analyses were driven by previous findings showing the importance of unmet transportation needs and depression as risk factors for loss of USOC. For the case of analyses pertaining to transportation barriers, a sample of N = 320 was used due to missing data.
Finally, as a sensitivity analysis we estimated our main model including all study participants who satisfied our inclusion criteria (community-dwelling, having a USOC, full set of covariates), but who were lost to follow-up during the study period. As participants in residential care facilities were assumed to have a USOC, we excluded at-risk participants who transitioned into residential care from this analysis. All our estimations were performed using Stata/SE 17.0.
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Publication 2023
Chronic Condition Dementia Ethnicity Households Hypersensitivity Transitional Care
Covariate selection was guided by previous literature on sociodemographic and health characteristics associated with having a USOC or HL (10 (link),11 (link)). These include baseline, age, race/ethnicity (White, Black, Hispanic, and other), sex, marital status (married/living with partner, and single/never married/divorced/widow), education (less than high school, high school diploma or equivalent, and some college or more), household income (under the poverty line, 100%–199% the poverty line, and ≥200% of the poverty line), number of chronic health conditions among heart attack, heart disease, high blood pressure, arthritis, osteoporosis, diabetes, lung disease, stroke, or cancer (0, 1–2, 3–5, or 6+), self-reported health status (Likert scale, 1 = Excellent, …, 5 = Poor), number of activities of daily living (ADLs) for which the respondent reported needing help (none, 1–2 ADLs, and 3≤ ADLs), dementia (probable, possible, and no dementia) (20 ), additional health coverage (Medigap/Medicare supplement, Medicaid, or Tricare), and depression status (based on Patient Health Questionnaire-2 scores ≥3) (21 (link)).
Despite being identified as a risk factor for loss of USOC, experiencing transportation barriers (reporting that a transportation problem restricted any activity participation in the month before the interview) was not included in the main analyses due to data availability, as a total of N = 1 804 participants had missing information.
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Publication 2023
Arthritis Cerebrovascular Accident Dementia Diabetes Mellitus Dietary Supplements Ethnicity Heart Diseases High Blood Pressures Hispanics Households Insurance, Medigap Lung Diseases Malignant Neoplasms Myocardial Infarction Osteoporosis Training Programs Widow

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More about "Depression"

Depression is a widespread and serious mental health condition characterized by persistent feelings of melancholy, hopelessness, and disinterest in activities.
It can influence an individual's mood, thoughts, behaviors, and physical well-being.
Depressive disorder often co-occurs with other medical conditions and can significantly impact a person's quality of life.
Researchers and clinicians strive to develop effective treatments and interventions to manage this complex disorder.
Utilizing statistical software like SAS version 9.4, SAS 9.4, SPSS version 25, SPSS version 22.0, SPSS version 20, SPSS version 24, SPSS version 21, SPSS version 26, and Stata version 14, researchers can analyze data and optimize research protocols for depression studies.
These tools can help improve the reproducibility and accuracy of depression research, providing valuable insights for the scientific community.
The PubCompare.ai platform is designed to assist in this effort by optimizing depression research protocols.
By leveraging AI-driven comparisons, researchers can identify the best protocols and products from literature, pre-prints, and patents, streamlining their depression research.
This platform can be a valuable resource for clinicians, researchers, and individuals interested in understanding and managing depressive disorders.
Whether you're struggling with persistent sadness, low mood, or a loss of interest in activities, it's important to seek help from a mental health professional.
With the right support and interventions, the symptoms of depression can be effectively managed, improving your overall well-being.
Remember, you're not alone, and there are resources available to support you on your journey to better mental health.