Background: Nursing interventions tailored to the smoking triggers in patients with non-communicable chronic diseases are essential. However, these interventions are scant due to the nature of factors associated with smoking cessation and the poor understanding of the effect of nurse-led intervention in Iraq.Purpose: This study aimed to determine the dominant smoking triggers and examine the effects of a tailored nursing intervention on smoking behavior in patients with non-communicable chronic diseases.Methods: Convenience samples of 128 patients with non-communicable chronic diseases, male and female patients, who were 18-70 years old, were recruited in this quasi-experimental, randomized comparative trial in the outpatient clinic in one major teaching hospital in Baghdad City, Iraq. The intervention included simple yet specific instructions that were given both orally and in written form to the study samples to enable them to manage their craving to smoke for 6 weeks. The smoking triggers were assessed using Why Do You Smoke questionnaire. Participants were randomly allocated to receive either the nurse-led intervention or standard care. Data were analyzed using descriptive statistics, independent sample t-tests, logistic regression, and two-sided tests.Results: Stress reduction was the dominant smoking trigger among subjects. The percentage of participants who were either able to completely quit smoking or reduce the number of smoked cigarettes per day (n=19, 29.7%; n=28, 43.8%, respectively) was greater in the study group than those in the control group (n=5, 5.8%; n=5, 5.8%, respectively). Study findings demonstrated significant differences in the inability to improve readiness to quit smoking between the intervention group and control group (p=0.000) at the sixth-week follow-up.Conclusion: The tailored nursing intervention was effective for a successful achievement of smoking reduction and cessation among patients with non-communicable chronic diseases, and a potential to equip nurses in clinical settings to support patients to achieve this is recommended.
Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
... Show MoreThis researchs the preparation of particulate polymer composites from Alkyd resin and Iraqi Burn Kaolin which were added as (20%,30%,40%,50%)and comparing with the polymer. It studied Thermal conductivity and Dielectric strength for both of the Alkyd resin and the Composite Material. The result showed an increase in Dielectric strength after adding the Iraqi Burn Kaolin , also the Thermal conductivity was increased by adding the Iraqi Burn Kaolin .
The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr
This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s
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