Sentences with phrase «outcome variables including»

For the first analysis of data from the principal survey, our outcome variables included (1) the diversity of membership on school - site councils, and (2) the level of principals «and teachers «openness to community and parental involvement in schools.

Not exact matches

Secondary outcomes included neonatal and maternal morbidities, maternal interventions, and mode of birth (see appendix 1 on bmj.com for a complete list of pre-specified outcomes and appendix 2 for details of the derivation of outcome variables requiring clinical review).

Lynch concluded «It would be helpful for this system to include more variables surrounding birth outcomes, for example VBAC (vaginal birth after caesarean section), maternal morbidity, setting, lead carer, use of syntocinin for augmentation of established labour and breastfeeding rates.

To correct for limitations, Bauchner et al suggested four standards for breast feeding studies.22 These include avoidance of detection bias, clear definition of the outcome event, clear definition of breast feeding, and adjustment for potential confounding variables.

Contributions include discussions on racial disparities in special education placements, the intersection of disability with other identity variables such as gender and sexuality; the exploitation of disabled bodies to generate resources for humanitarian projects; and suggestions for how a human rights framework can promote inclusivity and better health outcomes.

The USIDNET registry gathers variables including clinical, laboratory and outcome data, which together provide a health survey of the relatively small number of patients affected by primary immunodeficiency disorders.

Researchers increasingly recognize that latent TB infection includes diverse responses to infection with Mycobacterium tuberculosis (the pathogen that causes TB) and thus variable outcomes.

The primary outcome is in - hospital mortality, and secondary outcomes include the complications of BSI such as septic shock, acute kidney injury (AKI), acute lung injury (ALI) / acute respiratory distress syndrome (ARDS), disseminated intravascular coagulation (DIC), ischemic liver injury, and a collapsed dependent variable of «poor clinical outcome» that is defined as the presence of any of the above complications.

To identify methodological categories, the outcome of each paper was classified according to a set of binary variables: 1 - outcome measured on biological material; 2 - outcome measured on human material; 3 - outcome exclusively behavioural (measures of behaviours and interactions between individuals, which in studies on people included surveys, interviews and social and economic data); 4 - outcome exclusively non-behavioural (physical, chemical and other measurable parameters including weight, height, death, presence / absence, number of individuals, etc...).

Several variables, including those we can't see, affect outcomes.

The limitations include the lack of adjustment made for secondary outcome variables and a relatively short 3 - week period of intervention.

For the study, the patients self - reported outcomes in a 36 - item physical component survey that also included variables such as: fatigue, depression, and quality of sleep.

CIV is generally prevalent when a test measures too many variables, including extraneous and uncontrolled variables that ultimately impact test outcomes and test - based inferences (Haladyna & Downing, 2004)[and the statistics, no matter how sophisticated they might be, can not control for or factor all of this out].

These systems included measures of school context (resources, student background variables, and so on); processes (curriculum coherence, leadership and teaching, and so on); and outcomes (student achievement, graduation rate, school safety, and so on).

Furthermore, all contain important features that can be useful for CCIAV studies; with some exercises (e.g., MA and GEO - 3) going one step further than the original SRES scenarios by not only describing possible emissions under differing socio - economic pathways but also including imaginable outcomes for climate variables and their impact on ecological and social systems.

First, people are now used to relying on computerization for everything (which, in the legal area, can include research and online dispute resolution, as well as mathematical calculations of probable outcomes given a set of variables).

Moreover, we relate the outcomes of those cases to a host of variables, including variables related to the parties, the patents, and the court in which the case was litigated.

Legal analytics provides lawyers and clients with a means to objectively assess the likely outcomes of different scenarios by performing a series of searches and adjusting search parameters to evaluate and compare likely outcomes, including variables like remedies and damages awarded.

Outcomes and successes are affected by many external variables including market volatility, local and national economies, market saturation for a particular industry, and a client's level of experience, adaptability to workforce changes, skill sets, or continued motivation.

Since we found baseline differences in race / ethnicity and clinic site by treatment group, we also conducted multivariate analyses to control for these variables on outcomes including EC use, unprotected intercourse, contraceptive method change, frequency of condom use, and condom use at last intercourse.

Consistent with a hypothesis that data are missing at random, several baseline demographic, but not outcome, variables predicted missingness including marital status (odds ratio [OR] = 3.4), parent age (OR = 0.92), child age (OR = 1.96), and non-white or Hispanic race / ethnicity (OR = 2.6).

Covariates included in the meditational analyses were parallel with prior analyses and were only applied to outcome variables.

In the final comorbidity or adjusted model, the prior disorder that corresponded to the outcome variable and all other prior disorders were included.

We also hypothesized that key variables associated with poverty and known to negatively impact child development outcomes, including caregiving support, caregiver education, and stressful life events, would mediate the association between poverty and brain volumes.

The best predictor of all outcomes was a combined score including all predictor variables.

It has been shown that inferences resulting from this analysis are virtually identical no matter which of these outcome measures is used.30 In addition to the covariates previously noted, the regression analysis was repeated to include annual household income, mother's treatment setting (primary vs psychiatric outpatient care), and treatment status of child during the 3 - month follow - up period in order to investigate the further potential confounding effects of these variables.

Chapter Three includes the core variables of helping groups to develop and to work as coordinated units to maximize outcome, group dynamics and group processes.

To that end, Imago Relationship International supports research that involves the use of Imago Therapy and any aspect of Imago Therapy that is explicitly described by its founder, research that evaluates the impact Imago Therapy has on individuals, couples, and other systems over a wide range of impact variables including outcome studies of workshops and in - office treatment regimes, neuroscience and biological studies involving Imago Relationship Therapy; and the use of Imago Relationship Therapy with specific diagnostic categories and its effect on positive outcomes.

Short, or accelerated, courtships are a risk factor for poor marital outcomes, including divorce (i.e., «the quicker they rise, the harder they fall»).1 The reasons for this association are fairly obvious: it is very hard for two individuals to truly get to know each other and gauge long - term compatibility in a short amount of time, and very often individuals base their relationships on feelings of passion that are highly variable (see «Am I in love?»).

We estimated models by using dependent variables previously associated with significant treatment effects in the follow - up study.10, 20 These included life - course outcomes for the mother, such as number of subsequent children, months on welfare, impairments due to substance use, and number of arrests, as well as life - course outcomes for the study children, such as number of runaway episodes and number of arrests or convictions.

When these demographic variables were not included, only two of the 14 outcomes variables were statistically significant (at p < 0.05): children's physical health was better in comparison sites than in CfC sites, and the reverse was true for maternal mental health at wave 1.

Two multilevel models were estimated, one without baseline functioning and one including baseline outcome variables when they were collected with the first multilevel model similar to the analysis conducted in Sure Start.

Personality: While individual differences have been accounted for previously in the DRIVE model by including coping style and attributional style variables, personality variables represent a significant omission in this area, particularly when considering subjective well - being outcomes where personality has been cited as potentially the most important predictor (Diener et al., 2003).

Generalized regression models (logistic regression for dichotomous outcomes, linear regression for continuous outcomes) were used to estimate the overall adjusted effects of Healthy Steps.26, 27 These models included site variables to account for the fact that families within sites tend to respond more similarly than those at different sites.

Summary: (To include comparison groups, outcomes, measures, notable limitations) The aim of this study was to conduct a evaluation of the effectiveness of Circle of Security - Parenting (COS - P), with mothers in residential substance abuse treatment and (b) to examine what demographic variables, including other risk factors for child maltreatment, may influence the impact of the program with these mothers.

There was also some variation in data collection across sites, including differences in how each pilot site defined certain outcome variables.

Control variables in the multilevel modeling and multiple - linear regression analyses included gender, race, and pretest scores on the outcome being predicted.

It includes demographic variables, and information on maternal health, the pregnancy, labour, birth and perinatal outcomes.

Limitations included small sample size, low inter-rater reliability on treatment outcome variables, and lack of follow - up.

Garrard and Lipsey (2007) included additional tests — called moderator analyses — to see whether any factors, such as student variables, strengthened the likelihood that conflict resolution education (CRE) programs improved outcomes.

This study replicates the pilot study of De Bruin et al. (2015) in a larger participant group with a broader age range, including additional outcome variables and a 1 - year follow - up.

Other variables (maternal parity, housing stability, hospitalization, perceived health status, employment, use of the Women, Infants, and Children Supplemental Nutrition Program, and cigarette smoking; whether the mother was living with a partner; and infant gestational age, birth weight, need for transfer to an intensive care nursery, health insurance, special needs, health status as perceived by the mother, and age at the time of the survey) were included if the adjusted odds ratio differed from the crude odds ratio by at least 10 %, which is a well - accepted method of confounder selection when the decision of whether to adjust is unclear.42, 43 Any variable associated with both the predictor (depression) and the outcome (infant health services use, parenting practices, or injury - prevention measures) at P <.25, as suggested by Mickey and Greenland, 42 was also included.

Adolescent sex, age, time since diagnosis, and diabetes regimen (pump vs. multiple daily injections) were also included as covariates in all regression analyses because each was correlated with at least one outcome variable.

This data set allowed us to address longitudinal research questions, employ a comparison group, expand sexual distress outcomes beyond frequency and specific sexual symptoms (e.g., ED), and consider a broad array of contributing factors because it includes a myriad of physical, social, emotional, and contextual variables.

Of these, 13 focused on adolescent mental health, and all included depression as an outcome variable.

Pazdera et al. (2013) conducted a multiple mediation model which included CSA as predictor, parenting sense of competence and depression as mediators, and parenting stress and maltreatment behaviour as outcome variables.

Papers included in this review were those reporting empirical research (cross sectional or longitudinal in design) exploring associations between a psychosocial variable and emotional adjustment, or the predictive effect of, at least one psychosocial variable on an emotional adjustment outcome measure.

Socioeconomic factors are possible confounding variables that are known to predict physical health outcomes and were therefore included as control variables.

The aim of the present study was to examine whether treatment fidelity scores obtained for PMTO certification purposes prior to the intervention would be associated with treatment completion and with larger treatment effects on various outcome variables, including child externalizing behavior problems, parenting practices, parental psychopathology, parenting stress, working alliance.

Next, to establish mediation, we tested for a significant reduction in the direct effect between the predictor and the outcome, when each mediating variable was included in the model.