scholarly journals First-Time Mothers’ Grit, Spousal Support, and Age, and Their Relationships with Nurturing Passion, Postpartum Depression, and Happiness

2021 ◽  
Vol 25 (3) ◽  
pp. 177-183
Author(s):  
Yerim Jeong ◽  
Yaebon Kim ◽  
Sujin Yang
Keyword(s):  
Postpartum Depression ◽  
Root Mean Square ◽  
Degrees Of Freedom ◽  
Pearson Correlation ◽  
Spousal Support ◽  
Child Rearing ◽  
Mean Square ◽  
Mimic Model ◽  
First Time Mothers ◽  
First Time

Purpose: This study aimed to examine whether first-time mothers’ grit, spousal support, and age can make significant differences in latent means of child-rearing passion, postpartum depression, and happiness. Methods: Data were collected from April 2 to July 16, 2019. Two hundred sixteen first-time mothers of infants and toddlers aged 0–2 years participated in a self-reported questionnaire study in which scales of nurturing passion, postpartum depression, happiness, grit, and spousal support were included. The collected data were analyzed with IBM SPSS ver. 18.0 (IBM Co., Armonk, NY, USA) for descriptive statistics and Pearson correlation analyses. In addition, Mplus (ver. 7.0) was used for the Multiple Indicators Multiple Causes (MIMIC) model approach. Results: The MIMIC model yielded an appropriate fit to the data (χ2=103.74, degrees of freedom=53, comparative fit index=0.96, root mean square error of approximation=0.07, standardized root mean square residual=0.05). The paths from grit and spousal support all had significantly positive beta coefficients (p<0.05) to child-rearing passion (β=0.3 and β=0.26, respectively) and happiness (β=0.22 and β=0.39, respectively), while the corresponding paths to postpartum depression were all negatively significant (β= -0.24 for both). These results suggest that unlike chronological maturity (i.e., age), grittier individuals with stronger spousal support display greater passion for child-rearing, as well as greater happiness. In a similar vein, they suffered less from postpartum depression. Conclusion: These results imply that grit can be employed to enhance first-time mothers’ child-rearing passion and happiness as it can also concurrently offset the effects of a negative labor and child-birth experience on first-time mothers’ mental health, e.g., in terms of reducing postpartum depression.

scholarly journals Calculation of Seven Photovoltaic Cells Parameters Using Parallelized Successive Discretization Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Adrian M. Deaconu ◽  
Daniel T. Cotfas ◽  
Petru A. Cotfas
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Photovoltaic Cell ◽  
Research Literature ◽  
Photovoltaic System ◽  
Mean Square ◽  
Solar Module ◽  
Discretization Algorithm ◽  
First Time

Some parameters must be calculated with very good accuracy for the purpose of designing, simulating, and evaluating the performance of a photovoltaic system. The seven parameters of the photovoltaic cell and panels for the two-diode model are determined using a parallelized metaheuristic algorithm based on successive discretization. The parameters obtained for a photovoltaic cell and four panels using the proposed algorithm are compared with the ones calculated through over twenty methods from recent research literature. The root mean square error is used to prove the superiority of the Parallelized Successive Discretization Algorithm (PSDA). The smallest values for root mean square error (RMSE) in both cases, photovoltaic cell and panels, are obtained for the algorithm presented in this paper. The seven parameters for three panels known in the specialised literature, Kyocera KC200GT, Leibold Solar Module LSM 20, and Leybold Solar Module STE 4/100 are determined for the first time using PSDA.

Correlates of Postpartum Depression in First Time Mothers Without Previous Psychiatric Contact

2016 ◽  
Vol 40 ◽  
pp. 4-12 ◽  
Author(s):  
S.M. Sylvén ◽  
T.P. Thomopoulos ◽  
N. Kollia ◽  
M. Jonsson ◽  
A. Skalkidou
Keyword(s):  
Risk Factors ◽  
Depressive Symptoms ◽  
Postpartum Depression ◽  
Path Analysis ◽  
Subjective Experience ◽  
Delivery Mode ◽  
Increased Risk ◽  
First Time Mothers ◽  
History Of ◽  
First Time

AbstractBackgroundPostpartum depression (PPD) is a common disorder after childbirth. The strongest known predictors are a history of depression and/or a history of PPD. However, for a significant proportion of women, PPD constitutes their first depressive episode. This study aimed to gain further insight into the risk factors for PPD in first time mothers without previous psychiatric contact.MethodsWomen delivering in Uppsala University Hospital, Sweden, from May 2006 to June 2007, were asked to participate and filled out questionnaires five days and six weeks postpartum, containing inter alia the Edinburgh Postnatal Depression Scale (EPDS). Univariate logistic regression models, as well as a path analysis, were performed to unveil the complex interplay between the study variables.ResultsOf the 653 participating primiparas, 10.3% and 6.4% reported depressive symptoms (EPDS ≥ 12 points) five days and six weeks postpartum, respectively. In the path analysis, a positive association between anxiety proneness and depressive symptoms at five days and six weeks postpartum was identified. For depressive symptoms six weeks after delivery, additional risk factors were detected, namely depressive symptoms five days postpartum and subjective experience of problems with the baby. Caesarean section and assisted vaginal delivery were associated with fewer depressive symptoms at 6 six weeks postpartum.ConclusionsIdentification of anxiety proneness, delivery mode and problems with the baby as risk factors for self-reported depressive symptoms postpartum in this group of primiparas can be important in helping health care professionals identify women at increased risk of affective disorders in the perinatal period, and provide a base for early intervention.

Experiences of postpartum depression among first-time mothers in mainland China

2010 ◽  
Vol 66 (2) ◽  
pp. 303-312 ◽  
Author(s):  
Ling-ling Gao ◽  
Sally Wai-chi Chan ◽  
Liming You ◽  
Xiaomao Li
Keyword(s):  
Postpartum Depression ◽  
Mainland China ◽  
First Time Mothers ◽  
First Time

scholarly journals THE ANALYSIS OF FACTORS AFFECTING THE AUTHORITY OF UNIVERSITY PROFESSORS: A CASE OF IRAN, THE ISLAMIC REPUBLIC OF

2021 ◽  
Vol 6 (2) ◽  
pp. 1-16
Author(s):  
Abdulali Ahmadi ◽  
Ali Moradi
Keyword(s):  
Root Mean Square ◽  
Relative Deprivation ◽  
Pearson Correlation ◽  
Significant Negative Correlation ◽  
Jel Classification ◽  
Mean Square ◽  
University Professors ◽  
Positive Effects ◽  
Minimum Discrepancy ◽  
Fit Index

The method employed in this study was a descriptive correlation in which two validated researcher-made questionnaires were used to collect data. The population involved 1770 university professors in the academic year 2019-2020. From the population, 240 were randomly selected. The data was analyzed using SPSS 21 and Amos 21. Pearson correlation was used to decide the relationship between variables, one-way ANOVA to compare means, Cronbach alpha to determine reliability, and factor analysis was to check the research model and substantiate construct validity. As a result, professor authority was found to have a significant negative correlation with relative deprivation. In addition, the academic status, age, and marital status of professors turned out to exert significant positive effects on their authorities. Furthermore, the chi-square minimum discrepancy value (CMIN) was equal to 523.414, the root mean square error of approximation (RMSEA) was 0.049, the root mean square of the residuals (RMR) was equal to 0.090, the minimum discrepancy per degree of freedom (CMIN/DF) in the model was 1.562, the comparative fit index (CFI) was 0.925, and finally, the parsimonious comparative fit index (PCFI) equaled 0.820. Thus, the comparative and parsimonious indices calculated to evaluate the solidarity of the constructs demonstrated that the collected data can be considered as supporting the research validity. JEL Classification Codes: I21, I23, I31, I32.

A validation scheme for homogenization techniques on a Swedish temperature network using artificial inhomogeneities (1950-2005)

2021 ◽  
Author(s):  
Giulio Nils Caroletti ◽  
Tommaso Caloiero ◽  
Magnus Joelsson ◽  
Roberto Coscarelli
Keyword(s):  
Missing Data ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Minimum Temperature ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Temperature Data ◽  
Physical Parameters ◽  
Mean Square

&lt;p&gt;Homogenization techniques and missing value reconstruction have grown in importance in climatology given their relevance in establishing coherent data records over which climate signals can be correctly attributed, discarding apparent changes depending on instrument inhomogeneities, e.g., change in instrumentation, location, time of measurement.&lt;/p&gt;&lt;p&gt;However, it is not generally possible to assess homogenized results directly, as true data values are not known. Thus, to validate homogenization techniques, artificially inhomogeneous datasets, also called benchmark datasets, are created from known homogeneous datasets. Results from their homogenization can be assessed and used to rank, evaluate and/or validate techniques used.&lt;/p&gt;&lt;p&gt;Considering temperature data, the aims of this work are: i) to determine which metrics (bias, absolute error, factor of exceedance, root mean squared error, and Pearson&amp;#8217;s correlation coefficient) can be meaningfully used to validate the best-performing homogenization technique in a region; ii) to evaluate through a Pearson correlation analysis if homogenization techniques&amp;#8217; performance depends on physical features of a station (i.e., latitude, altitude and distance from the sea) or on the nature of the inhomogeneities (i.e., the number of break points and missing data).&lt;/p&gt;&lt;p&gt;With this aims, a southern Sweden temperature database with homogeneous, maximum and minimum temperature data from 100 ground stations over the period 1950-2005 has been used. Starting from these data, inhomogeneous datasets were created introducing up to 7 artificial breaks for each ground station and an average of 107 missing data. Then, 3 homogenization techniques were applied, ACMANT (Adapted Caussinus-Mestre Algorithm for Networks of Temperature series), and two versions of HOMER (HOMogenization software in R): the standard, automated setup mode (Standard-HOMER) and a manual setup developed and performed at the Swedish Meteorological and Hydrological Institute (SMHI-HOMER).&lt;/p&gt;&lt;p&gt;Results showed that root mean square error, absolute bias and factor of exceedance were the most useful metrics to evaluate improvements in the homogenized datasets: for instance, RMSE for both variables was reduced from an average of 0.71-0.89K (corrupted dataset) to 0.50-0.60K (Standard-HOMER), 0.51-0.61K (SMHI-HOMER) and 0.46-0.53K (ACMANT), respectively.&lt;/p&gt;&lt;p&gt;Globally, HOMER performed better regarding the factor of exceedance, while ACMANT outperformed it with regard to root mean square error and absolute error. Regardless of the technique used, the homogenization quality anti-correlated meaningfully to the number of breaks. Missing data did not seem to have an impact on HOMER, while it negatively affected ACMANT, because this method does not fill-in missing data in the same drastic way.&lt;/p&gt;&lt;p&gt;In general, the nature of the datasets had a more important role in yielding good homogenization results than associated physical parameters: only for minimum temperature, distance from the sea and altitude showed a weak but significant correlation with the factor of exceedance and the root mean square error.&lt;/p&gt;&lt;p&gt;This study has been performed within the INDECIS Project, that is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).&lt;/p&gt;

scholarly journals Unintended Pregnancy and Postpartum Depression Among First-Time Mothers

2013 ◽  
Vol 22 (5) ◽  
pp. 412-416 ◽  
Author(s):  
Shahed Abbasi ◽  
Cynthia H. Chuang ◽  
Rada Dagher ◽  
Junjia Zhu ◽  
Kristen Kjerulff
Keyword(s):  
Postpartum Depression ◽  
Unintended Pregnancy ◽  
Pregnancy And Postpartum ◽  
First Time Mothers ◽  
First Time
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