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> Disorders > Mental or Behavioral Dysfunction > Apathy

Apathy

Apathy is a lack of motivation, interest, or emotional response.
It can be a symptom of various medical conditions, such as depression, Alzheimer's disease, or Parkinson's disease.
Apathy can make it difficult to engage in daily activities and can negatively impact quality of life.
PubCompare.ai's powerful AI-driven platform can help overcome apathy by locating the best protocols from literature, preprints, and patents to optimize your research and boost reproducibility.
Discover the most effective products and techniques to drive your research forward and overcome apathy in your work.

Most cited protocols related to «Apathy»

1
Discount rates and task completion time
For each task two outcome variables were of primary interest: discount rate and time to completion. Discount rates for the adjusting amount task were obtained by obtaining the best-fit parameters of Equation 1 drawn through the indifference points in Microsoft Excel 2010 (Redmond, WA, USA). A modification of criteria proposed by Johnson and Bickel (2008) (link) to evaluate logical consistency of discounting were used to exclude data: participants’ 1-day indifference point needed to be at least $100 greater than their 25-year indifference point and no more than one indifference point could be more than $200 greater than the indifference point preceding it. Five participants were excluded for failing to meet these criteria. All five of these participants’ data were also not well fit by Equation 1, with r2 values all < 0. One additional participant was excluded despite meeting the Johnson and Bickel (2008) (link) for also yielding an r2 < 0 since a k value obtained in such cases is not representative of a discount rate present in the underlying data, for 105 total participants for the adjusting amount task. Discount rates for the 5- trial adjusting delay task were calculated by taking the inverse of the obtained ED50 value, which is equivalent to the value of k in Equation 1 when fitted to this singular point. Discount rates were log-transformed for all data analyses, although the absolute discount rates are presented in this paper for clarity. Time to task completion was calculated from the moment the instruction screen was dismissed for each task to the time that the choice was made by the participant in the final choice trial.
Statistics were computed in IBM SPSS Statistics 21 (Armonk, NY, USA). Discount rates and time to completion for the different tasks were analyzed with generalized linear models using exchangeable correlation structures and generalized estimating equations to account for intrasubject correlation in repeated-measures data (Liang & Zeger, 1986 ). Participant gender, age, race, and number of drinks per week were entered into the statistical model along with task type. Cigarette smoking status was not entered into the model due to the low incidence of cigarette smoking in this sample (4%). Significance values for pairwise comparisons between tasks were adjusted with the sequential Bonferroni procedure to keep the family-wise Type 1 error rate to 0.05%. Reported p values reflect this adjustment. The principal component analysis was conducted in with the minimum Eigenvalue set to 1 and Varimax rotation.
Koffarnus M.N, & Bickel W.K. (2014). A 5-trial adjusting delay discounting task: Accurate discount rates in less than 60 seconds. Experimental and clinical psychopharmacology, 22(3), 222-228.
Publication 2014
Apathy Maritally Unattached
2
Staphylococcus DNA Microarray Profiling
The Alere StaphyType DNA microarray was employed using protocols and procedures
previously described in detail [29] (link); [ 96] (link). The DNA microarray covers 334 target sequences,
(approximately 170 distinct genes and their allelic variants) including species
markers, SCCmec, capsule and agr group typing
markers, resistance genes, exotoxins, and MSCRAMM genes. Primer and probe
sequences have been published previously [29] (link); [96] (link).
Target genes and information on primers and probes are provided in Supplemental
file
S1.
MRSA were grown on Columbia blood agar and incubated overnight at 37°C.
Culture material was enzymatically lysed prior to DNA preparation using
commercially available spin columns (Qiagen, Hilden, Germany). Purified DNA
samples were used as templates in a linear primer elongation using one primer
per target. All targets were amplified simultaneously, and within this step,
biotin-16-dUTP was incorporated into the resulting amplicons. An alternate
protocol was used for a few isolates in which amplification and labelling were
directed by random primers [139] (link); [244] . As this protocol does not rely on conserved primer
binding sites, it proved to be useful for characterisation of unusual strains
which are not fully represented by the published genome sequences
(e.g., ST75 strains).
Amplicons obtained using either protocol were hybridised to the microarray
followed by washing and blocking steps, and the addition of
horseradish-peroxidase-streptavidin conjugate. After further incubation and
washing steps, hybridisations were visualised by using a precipitating dye. An
image of the microarray was taken and analysed using a designated reader and
software (ALERE Technologies GmbH, Jena, Germany). Normalised intensities of the
spots were calculated based their average intensities and on the local
background [96] (link). Results were regarded as negative if the normalised
intensity for a given probe was below 25% of the median value of species
markers (coa, eno, fnbA, gapA, katA, nuc, rrn, sarA sbi, spa,
vraS) and a biotin staining control. If the normalised intensity of
a given probe was higher than 50% of this breakpoint, it was interpreted
positive. If it was between 25% and 50%, the result was regarded
as ambiguous. For some markers, for which allelic variants were to be
discriminated (bbp, clfA, clfB and fnbB as
well as some set/ssl genes, isaB, mprF and
isdA), a different approach was used because these alleles
differed only in single nucleotides. Here, only the probe with the strongest
signal value was regarded as positive, provided that it exceeded the 50%
breakpoint. All others were regarded as ambiguous or, if below the 25%
breakpoint, as negative. This allowed an easy and clear distinction of clonal
complex-specific variants of these genes. Genes which are not present in all
tested isolates are labelled as rare, variable or common in Figures 2 and 3 as well as in Supplement S2 (see
legends).
The affiliation of isolates to clonal complexes (CCs) or sequence types (STs) as
defined by MLST [25] (link) was determined by an automated comparison of
hybridisation profiles to a collection of reference strains previously
characterised by MLST [29] (link); [96] (link). Analysis of hybridisation patterns cannot
discriminate sequence types which differ only in single point mutations
affecting MLST genes (e.g., ST5 and ST225, or ST59 and ST952).
However, there are also sequence types which originate from chromosomal
replacements as previously described [170] (link); [173] . As these events result in
different hybridisation patterns, such STs can be easily identified. MRSA
strains which belong to these sequence types will be described separately from
the parental CCs.
Monecke S., Coombs G., Shore A.C., Coleman D.C., Akpaka P., Borg M., Chow H., Ip M., Jatzwauk L., Jonas D., Kadlec K., Kearns A., Laurent F., O'Brien F.G., Pearson J., Ruppelt A., Schwarz S., Scicluna E., Slickers P., Tan H.L., Weber S, & Ehricht R. (2011). A Field Guide to Pandemic, Epidemic and Sporadic Clones of Methicillin-Resistant Staphylococcus aureus. PLoS ONE, 6(4), e17936.
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Publication 2011
Acid Hybridizations, Nucleic Agar Alleles Apathy Biotin biotin-16-dUTP BLOOD Capsule Cardiac Arrest Clone Cells Crossbreeding Dietary Supplements DNA Chips Exotoxins Genes Genome Methicillin-Resistant Staphylococcus aureus Microarray Analysis Nucleotides Oligonucleotide Primers Parent Peroxidase Sequence Analysis Strains Streptavidin
3
Shirom-Melamed Burnout Questionnaire (SMBQ)
The Shirom-Melamed Burnout Questionnaire (SMBQ) contains 22 items in four subscales: "Physical Fatigue (PF)", "Cognitive weariness (CW)" [9 (link)] "Tension", and "Listlessness" [10 (link)]. The Physical Fatigue domain consists of 8 items, examples of which are "I feel tired" and "My batteries are dead." Six items measure Cognitive Weariness, examples of which are "I feel I am not thinking clearly" and "I have difficulty thinking about complex things." Four items measure Tension, and include "I feel tensed" and "I feel relaxed". Items measuring Listlessness include "I feel full of vitality" and "I feel alert". Each item is rated using a seven-point scale ranging from 1 'Never or almost never' to 7 'Always or almost always'. Five of the items have reversed scoring, one item in the tension domain, three in the listlessness domain and one in the physical fatigue domain. For each sub-domain, and the scale as a whole, the total score is averaged by dividing by the number of items in the domain.
Lundgren-Nilsson Å., Jonsdottir I.H., Pallant J, & Ahlborg G J.r. (2012). Internal construct validity of the Shirom-Melamed Burnout Questionnaire (SMBQ). BMC Public Health, 12, 1.
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Publication 2012
Apathy Burnout, Psychological Cognition Fatigue Feelings Physical Examination
4
Utility Values of Hypoglycemic Events in Diabetes
All statistical analyses were performed using SAS® version 9.2 statistical software. A utility value was assigned to each health state based on each individual response, derived from the midpoint of the indifference interval derived as described above. The average utility value was calculated for each health state, and a disutility per hypoglycaemic event derived by dividing the difference between the average utility and the baseline diabetes state utility by the number of annual events, to ensure that the resulting value reflected the effect of hypoglycaemia alone.
For each hypoglycaemic event class, up to four different event frequencies (health states) were evaluated (Additional file 2: Table S2). Unit values per hypoglycaemic incident type were calculated from the average TTO value for each frequency, weighted according to the distribution of those specific hypoglycaemic event frequencies among the participants with diabetes.
Statistical results for the type 1 and type 2 diabetes populations contain combined data from any general population respondents with type 1 or type 2 diabetes and data from the respective type 1 or type 2 diabetes populations.
As the response distribution was unknown but suspected to be non-normal, non-parametric bootstrapping was used to simulate standard errors and confidence intervals (CIs) for the mean TTO values. This method estimates the parameter’s distribution by repeatedly resampling the original data set with replacement [37 (link)-39 (link)]. For the present study, 10,000 iterations were performed.
Because it is rare for a patient with diabetes to experience severe hypoglycaemic events without non-severe events, some of the worries and limits to daily activities may already be accounted for by the disutility associated with non-severe events. Therefore, the initial disutility value (determined as the intercept in a regression model) for non-severe hypoglycaemic events was subtracted from the value obtained for severe hypoglycaemic events.
Evans M., Khunti K., Mamdani M., Galbo-Jørgensen C.B., Gundgaard J., Bøgelund M, & Harris S. (2013). Health-related quality of life associated with daytime and nocturnal hypoglycaemic events: a time trade-off survey in five countries. Health and Quality of Life Outcomes, 11, 90.
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Publication 2013
Apathy Diabetes Mellitus Diabetes Mellitus, Non-Insulin-Dependent Hypoglycemic Agents Hypoglycemic Effect Patients Population Group
5
Adjusting Delay Task for Discount Rate
The 5-trial adjusting delay task was created as a way to quickly assess an individual’s discount rate with the flexibility to be used with a variety of commodities and situations. This task directly measures the Effective Delay 50% (ED50) value for a given commodity, a value that is a simple inverse of the discount rate (Yoon & Higgins, 2008 (link)). This is done by presenting a series of questions between some amount of a delayed commodity and half that amount available immediately. These amounts remain stagnant while the delay to the larger amount is adjusted to determine the ED50 value. The delay series and other parameters are shown in Table 1. The specific delays were chosen to be those that are conveniently formatted as whole (or half when necessary) integers of common durations of time and to result in a series of ED50 values that is as evenly distributed as possible on a logarithmic scale. This second consideration was included because k values, and therefore ED50 values, are normally distributed in most populations when logarithmically transformed (e.g., Yi et al., 2006 (link)). The first choice trial is always between amount of the commodity delayed 3 weeks and _ of the same commodity available immediately. For the purpose of explanation, the discrete delays are assigned ordinal indexes in Table 1, with the first choice trial being index 16. Depending on the choice made by the participant, the delay either adjusts up (delayed choice) or down (immediate choice) by 8 delays (index 8 or 24) for the next choice trial. This continues for five choice trials, with the delay index adjusting by an amount half that of the previous adjustment. This results in 32 potential ED50 values (25) nearly evenly spaced (on a logarithmic scale) between 1 hour and 25 years, the same number of possible indifference points at each delay of the adjusting amount procedure above.
Participants completed this task six times for different commodities and delayed amounts. These included three versions where the delayed amount was altered: $10 delayed (vs. $5 now), $1,000 delayed (vs. $500 now), and $1,000,000 delayed (vs. $500,000 now). Fourth, participants completed a version presenting choices between $1,000 delivered at some point in the past and $500 delivered 1 hour ago. Fifth, an “explicit zero” version was also included, which presented choices between $1,000 delayed and $500 now, but with the options presented differently. In this version, delayed options were presented as “$1,000 in [delay] and $0 now” vs. “$500 now and $0 in [delay].” Sixth, a version of the task was completed presenting choices between 10 servings of the participant’s preferred snack food delivered after a delay vs. 5 servings now.
Koffarnus M.N, & Bickel W.K. (2014). A 5-trial adjusting delay discounting task: Accurate discount rates in less than 60 seconds. Experimental and clinical psychopharmacology, 22(3), 222-228.
Publication 2014
Apathy Population Group Snacks

Most recents protocols related to «Apathy»

1
Posterior Fossa Tumor Surgical Outcomes
Based on the consensus from the Delphi conference, CMS was defined as mutism or notably reduced speech after posterior fossa tumor removal. Hypotonia, behavior change, and dysphagia after surgery during hospital days were also acquired from medical records or telephone interviews to further depict the details of CMS manifestations. Due to the difficulties of assessing ataxia when patients are in a hypotonia status, we did not include this feature. Behavior change was defined as when the patient presented with irritability or apathy. The onset of mutism was defined as days after the surgery date, and the surgery date was set as day 0. The restoration of speech was defined as being able to speak at least one Chinese word, i.e., “Baba” (dad) or “Mama” (mum), rather than a conversational speech. The duration of mutism was the duration between mutism onset and speech restoration. The aforementioned were collected from medical records and a follow-up database.
Zhu K., Yang W., Ying Z., Cai Y., Peng X., Zhang N., Sun H., Ji Y, & Ge M. (2023). Long-term postoperative quality of life in childhood survivors with cerebellar mutism syndrome. Frontiers in Psychology, 14, 1130331.
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Publication 2023
Apathy Cerebellar Ataxia Chinese Conferences Deglutition Disorders Mutism Operative Surgical Procedures Patients Speech Tumor, Infratentorial
2
Antibiotic Checkerboard Microdilution Assay
Stocks of antibiotics to test were prepared by dissolving them according to CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing41 in the indicated solvent and diluent to a final concentration of 5.12 mg/ml. Salts were corrected for their mass. Used antibiotics: Ciprofloxacin hydrochloride monohydrate (Sigma-Aldrich; European Pharmacopoeia Reference Standard), piperacillin sodium (Sigma-Aldrich, analytical standard), imipenem (Sigma-Aldrich; European Pharmacopoeia Reference Standard), ceftazidime pentahydrate (Sigma-Aldrich; European Pharmacopoeia Reference Standard) and aztreonam (United States Pharmacopeia Reference Standard).
Working stocks were then prepared by serial dilution in MHB II medium. Plates for checkerboards were prepared by adding 25 µl of each antibiotic at 4x the final concentration to be tested in the respective well in a flat bottom, transparent 96 well plate (Greiner). In one column a growth control was prepared by adding 50 µl of MHB II medium. A sterility control was prepared in a second column by adding 100 µl of MHB II medium. Inocula of the strain to be tested were prepared by inoculating physiological NaCl solution to a McFarland standard of 0.5 from overnight cultures. In total, 125 µl of this solution were then added to 15 mL of MHB II medium and 50 µl of this inoculum added to the wells containing antibiotics as well as to the growth control wells. Plates were incubated for 20 h at 37 °C. After incubation the OD600 values were determined using a Tecan Infinite® 200 PRO. Each assay was prepared in duplicate. For each replicate, the ratio of signal for each well and the mean of the sterility control was calculated. The mean value of both replicates was calculated. If the value was smaller than 1.5, this concentration was considered to be inhibitive. From these values, the MIC and FIC-I for the tested antibiotics were calculated as follows: FICA=MICA(combined)/MICA(singleantibiotic) FICB=MICB(combined)/MICB(singleantibiotic) FIC-I=FICA+FICB
Interpretation of FIC-I: ≤ 0.5: Synergism; >0.5 to 1: additive effect; >1 to 4: indifferent effect; >4: Antagonism
Eggers O., Renschler F.A., Michalek L.A., Wackler N., Walter E., Smollich F., Klein K., Sonnabend M.S., Egle V., Angelov A., Engesser C., Borisova M., Mayer C., Schütz M, & Bohn E. (2023). YgfB increases β-lactam resistance in Pseudomonas aeruginosa by counteracting AlpA-mediated ampDh3 expression. Communications Biology, 6, 254.
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Publication 2023
antagonists Antibiotics Antibiotics, Antitubercular Apathy Aztreonam Biological Assay Ceftazidime Pentahydrate DNA Replication Europeans Hydrochloride, Ciprofloxacin Imipenem MICA protein, human Microbicides mutalipocin II physiology Psychological Inhibition Salts Sodium, Piperacillin Sodium Chloride Solvents Sterility, Reproductive Strains Susceptibility, Disease Technique, Dilution
3
Neuropsychiatric Symptom Assessment in Dementia
NPS were measured by using the NPI‐Q (31 (link)) which was administered as a structured interview to an informant, usually the spouse. The NPI‐Q is a shorter version of the Neuropsychiatric Inventory (NPI) and is a clinical instrument that is cross‐validated with the standard NPI (31 (link)). We considered the NPI‐Q an appropriate screening instrument because it assesses a broad variety of neuropsychiatric symptoms and was also selected by the Uniform Data Set Initiative of the National Institute on Aging (32 (link)). The NPI‐Q is designed to obtain information on 12 behaviors (i.e., agitation, delusion, hallucination, depression, anxiety, euphoria, apathy, disinhibition, irritability, aberrant motor behavior, sleep, and eating/appetite). A severity scale has scores ranging from 1 to three points (1 = mild; 2 = moderate; and 3 = severe) and a scale for assessing caregiver distress has scores ranging from 0 to five points (0 = no distress; 1 = minimal distress; 2 = mild distress; 3 = moderate distress; 4 = severe distress; and 5 = extreme distress).
Pink A., Krell‐Roesch J., Syrjanen J.A., Christenson L.R., Lowe V.J., Vemuri P., Fields J.A., Stokin G.B., Kremers W.K., Scharf E.L., Jack CR J.r., Knopman D.S., Petersen R.C., Vassilaki M, & Geda Y.E. (2023). Interactions Between Neuropsychiatric Symptoms and Alzheimer's Disease Neuroimaging Biomarkers in Predicting Longitudinal Cognitive Decline. Psychiatric Research and Clinical Practice, 5(1), 4-15.
Publication 2023
Anxiety Apathy Delusions Euphoria Hallucinations Sleep Spouse
4
Comprehensive Neuropsychological Assessment of bvFTD
Each participant underwent a standardized neuropsychological assessment battery. Global cognitive screening was performed using the MMSE, and disease severity was assessed using the CDR® and the 6 domains of CDR® plus the behaviour/comportment and language domains (CDR® plus NACC FTLD). The severity of behavioural abnormalities was assessed using the Frontal Behaviour Inventory (FBI), which can be separated into the negative apathy symptom subscale (first 12 items) and the positive disinhibition symptom subscale (last 12 items). Executive function was evaluated using the Trail Making Test (TMT) and the Stroop I and II tests. Language deficits were tested using the 30-item Boston Naming Test (BNT). Activities of living were assessed by the following scales: activities of daily living (ADL).
Controls in our plasma cohort did not complete the FBI, TMT, BNT and ADL scales. To clearly show how affected the patients truly are, we calculated the z scores by selecting another group of controls who were age- and sex-matched with bvFTD patients and completed the FBI, TMT, BNT and ADL scales.
Chu M., Wen L., Jiang D., Liu L., Nan H., Yue A., Wang Y., Wang Y., Qu M., Wang N, & Wu L. (2023). Peripheral inflammation in behavioural variant frontotemporal dementia: associations with central degeneration and clinical measures. Journal of Neuroinflammation, 20, 65.
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Publication 2023
Apathy Cognition Executive Function Frontotemporal Lobar Degeneration Mini Mental State Examination Neuropsychological Tests Patients Plasma Problem Behavior
5
Synergistic Antibiotic-Antioxidant Interactions
The synergistic activity between antibiotics (compound A) and antioxidants (compound B) was tested via checkerboard assay in accordance with Garcia and Isenberg [10 (link)]. Each antioxidant (compound B) was paired with one antibiotic (compound A); thus, eight combinations were employed per antioxidant (Table 2).
A twofold serial microdilution was prepared in Muller–Hinton (MH) broth (Sigma-Aldrich) for each compound and dispensed in the corresponding well in a microtitre plate (Fig. 1). All combinations were tested in triplicate. The lowest concentration preventing turbidity development after 24 h was regarded as the minimum inhibitory concentration (MIC). Microtitre plates were analysed via a Titertek Viewer plate reader (Titertek-Berthold, Germany).
The MICs of compounds A and B were determined in row H and column 12, respectively (Fig. 1). Bacterial inoculum at 1×105 colony-forming units (c.f.u.) ml−1 was added to the microtitre plates in accordance with the Clinical and Laboratory Standards Institute (CLSI) guidelines, and the well at 12 h served as a positive control [11 ].
The microtitre plates were incubated at 37 °C for 24 h to determine the fractional inhibitory concentration (FIC). The ∑FIC was calculated as follows:
ΣFIC=FICA+FICB=CAMICA+CBMICB
where MICA and MICB are the MICs of compound A and B alone, respectively; and CA and CB are the concentrations of the compounds in combination, respectively, in the well corresponding to an MIC.
Cutoffs of ∑FIC:
synergy = <0.5
antagonism = >4
additive or indifference=0.5–4
∑FICmin=the lowest calculated value of fractional inhibitory concentration
∑FICmax=the highest calculated value of fractional inhibitory concentration
AlSaleh A., Shahid M., Farid E., Kamal N, & Bindayna K. (2023). Synergistic antimicrobial effect of ascorbic acid and nicotinamide with rifampicin and vancomycin against SCCmec type IV methicillin-resistant Staphylococcus aureus (MRSA). Access Microbiology, 5(2), 000475.v4.
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Publication 2023
Antibiotics Antibiotics, Antitubercular Antioxidants Apathy Bacteria Biological Assay Clinical Laboratory Services Corticosterone mica MICA protein, human Minimum Inhibitory Concentration Psychological Inhibition

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More about "Apathy"

Apathy, a common symptom observed in various medical conditions, is characterized by a lack of motivation, interest, or emotional response.
This disengaged state can make it challenging to participate in daily activities and can negatively impact an individual's quality of life.
Researchers and clinicians often encounter apathy when studying or treating conditions such as depression, Alzheimer's disease, Parkinson's disease, and other neurological or psychiatric disorders.
Understanding the underlying causes and mechanisms of apathy is crucial for developing effective interventions.
In the field of biomedical research, apathy can hamper the progress and reproducibility of studies.
PubCompare.ai, an AI-driven platform, offers a powerful solution to overcome this challenge.
By leveraging advanced algorithms, PubCompare.ai can help researchers locate the most effective protocols from the vast array of literature, preprints, and patents.
This enables researchers to optimize their experimental designs, boost reproducibility, and drive their research forward, even in the face of apathy.
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The integration of Stata 13 for advanced statistical analysis and the use of microplate readers for high-throughput experimentation can also be valuable tools to consider.
By leveraging the comprehensive resources and AI-driven capabilities of PubCompare.ai, researchers can navigate the challenges posed by apathy and unlock new opportunities for their studies.
This holistic approach empowers researchers to enhance the reproducibility and impact of their work, ultimately contributing to the advancement of scientific knowledge and patient care.