486 research outputs found
Adherence to Blended or Face-to-Face Smoking Cessation Treatment and Predictors of Adherence:Randomized Controlled Trial
Background: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity.Objective: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment.Methods: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics.Results: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R2=0.049; face-to-face R2=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R2=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R2=0.164).Conclusions: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research
Adherence to Blended or Face-to-Face Smoking Cessation Treatment and Predictors of Adherence:Randomized Controlled Trial
Background: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. Objective: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. Methods: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. Results: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R-2 =0.049; face-to-face R-2 =0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R-2 =0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R-2 =0.164). Conclusions: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research
Performance and application of an open source automated magnetic optical density meter for analyzing magnetotactic bacteria
We present a spectrophotometer (optical density meter) combined with
electromagnets dedicated to the analysis of magnetotactic bacteria. We have
ensured that our system, called MagOD, can be easily reproduced by providing
the source of the 3D prints for the housing, electronic designs, circuit board
layouts, and microcontroller software. We compare the performance of this novel
system to existing adapted commercial spectrophotometers. In addition, we
demonstrate its use by analyzing the absorbance of magnetotactic bacteria as a
function of their orientation with respect to the light path and their speed of
reorientation after the field has been rotated by 90o. We continuously
monitored the development of a culture of magnetotactic bacteria over a period
of five days, and measured the development of their velocity distribution over
a period of one hour. Even though this dedicated spectrophotometer is
relatively simple to construct and cost-effective, a range of magnetic
field-dependent parameters can be extracted from suspensions of magnetotactic
bacteria. Therefore, this instrument will help the magnetotactic research
community to understand and apply this intriguing micro-organism
An open-source automated magnetic optical density meter for analysis of suspensions of magnetic cells and particles
We present a spectrophotometer (optical density meter) combined with electromagnets dedicated to the analysis of suspensions of magnetotactic bacteria. The instrument can also be applied to suspensions of other magnetic cells and magnetic particles. We have ensured that our system, called MagOD, can be easily reproduced by providing the source of the 3D prints for the housing, electronic designs, circuit board layouts, and microcontroller software. We compare the performance of our system to existing adapted commercial spectrophotometers. In addition, we demonstrate its use by analyzing the absorbance of magnetotactic bacteria as a function of their orientation with respect to the light path and their speed of reorientation after the field has been rotated by 90°. We continuously monitored the development of a culture of magnetotactic bacteria over a period of 5 days and measured the development of their velocity distribution over a period of one hour. Even though this dedicated spectrophotometer is relatively simple to construct and cost-effective, a range of magnetic field-dependent parameters can be extracted from suspensions of magnetotactic bacteria. Therefore, this instrument will help the magnetotactic research community to understand and apply this intriguing micro-organism
Accuracy of bone mineral density quantification using dual-layer spectral detector CT: a phantom study
Large-scale ICU data sharing for global collaboration: the first 1633 critically ill COVID-19 patients in the Dutch Data Warehouse
Multidifferential study of identified charged hadron distributions in -tagged jets in proton-proton collisions at 13 TeV
Jet fragmentation functions are measured for the first time in proton-proton
collisions for charged pions, kaons, and protons within jets recoiling against
a boson. The charged-hadron distributions are studied longitudinally and
transversely to the jet direction for jets with transverse momentum 20 GeV and in the pseudorapidity range . The
data sample was collected with the LHCb experiment at a center-of-mass energy
of 13 TeV, corresponding to an integrated luminosity of 1.64 fb. Triple
differential distributions as a function of the hadron longitudinal momentum
fraction, hadron transverse momentum, and jet transverse momentum are also
measured for the first time. This helps constrain transverse-momentum-dependent
fragmentation functions. Differences in the shapes and magnitudes of the
measured distributions for the different hadron species provide insights into
the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any
supplementary material and additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb
public pages
Study of the decay
The decay is studied
in proton-proton collisions at a center-of-mass energy of TeV
using data corresponding to an integrated luminosity of 5
collected by the LHCb experiment. In the system, the
state observed at the BaBar and Belle experiments is
resolved into two narrower states, and ,
whose masses and widths are measured to be where the first uncertainties are statistical and the second
systematic. The results are consistent with a previous LHCb measurement using a
prompt sample. Evidence of a new
state is found with a local significance of , whose mass and width
are measured to be and , respectively. In addition, evidence of a new decay mode
is found with a significance of
. The relative branching fraction of with respect to the
decay is measured to be , where the first
uncertainty is statistical, the second systematic and the third originates from
the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb
public pages
Measurement of the ratios of branching fractions and
The ratios of branching fractions
and are measured, assuming isospin symmetry, using a
sample of proton-proton collision data corresponding to 3.0 fb of
integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The
tau lepton is identified in the decay mode
. The measured values are
and
, where the first uncertainty is
statistical and the second is systematic. The correlation between these
measurements is . Results are consistent with the current average
of these quantities and are at a combined 1.9 standard deviations from the
predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb
public pages
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