text:
Some headlines are just made for comments threads, even if you feel a little bad about poking fun at a guy's name.
From Catholic News Agency: Bishop George Lucas appointed to Archdiocese of Omaha
"He'd better not take the Yub Yub song out of Revelation."
"I don't care what the archbishop says. Goliath did not shoot first!"
"All excommunications over the creation of Howard the Duck are hereby withdrawn."
"The good news: The archdiocese will no longer collect offerings. The bad news: It's retaining all merchandising rights."

domain: news


At Alacer, we believe big data analysis should result in significant yet understandable results. Exploratory analysis is often overlooked when working with big data because the data sets are messy, sensitive, and—as the label implies—too large to be easily approached. Renaissance is a simple-to-install, web-based viewing platform that allows an analyst to quickly and visually explore big data using natural subsets.
If you work at a financial institution, you know how many data points are generated by every customer interaction and every transaction you process. What you need is a way to quickly get at the trends and key insights in that data. You’re likely hitting the limits of your existing tools, but you don’t need a full-blown analytics suite (or the crew of trained engineers required to integrate it).
Renaissance will help you explore big data, share it safely with your analysis partners, and get the job done:
- View production statistics by employee or branch
- Create risk models on customers
- Forecast future risk in different countries
Big data analysis should result in significant yet understandable results.
Renaissance is an interactive, web-based viewing platform that allows users to quickly scan, filter, or sort through features of the data, focus on relevant questions, and understand smaller components of the data. Individual users can quickly create and save dashboard views that tell a story.
Alacer simplifies big data analysis.
Our team of experienced data scientists takes the time to understand your data and how it relates to your business, so they can customize analyses to your needs. Our team conducts cutting-edge analysis and presents the results back to you in Renaissance—your custom, visual dashboard for big data insights.
Try Renaissance today.
Call 800 414-5170 to arrange a demonstration.


text:
The trust was given the top “best performing” rating for its midwifery care in the Healthcare Commission review, which focused on whether trusts provided a high quality, value-for-money maternity service.
The review scored 25 key indicators covering care from when the mother first experiences maternity services to about 10 days after birth.
Frimley Park was one of only 38 trusts nationally that had an overall result of best performing. Its average score for the 25 indicators was the best in the London south east region which includes Surrey, Sussex and Kent.
Among the areas in which Frimley Park scored full marks was its antenatal screening programme. Women are offered a combined scan and a blood test which enables the risk of their baby having Downs syndrome to be calculated.
The review also incorporated the results of a survey of mothers who gave birth in the unit*, eight out of ten of whom rated their care as “good” or “excellent”.
Frimley’s head of midwifery Adrienne Price said: “We are delighted with the results and we realise it is the contribution of all women in our care who have given us our excellent mark.
“The report has been very helpful in highlighting those areas where we would wish to develop services. For example our patients told us the homeliness of our delivery rooms could be better [score 2 out of 5] and we are pleased to report that we are currently refurbishing and expanding our maternity facilities.
“People today want individual and quality care. Our board of directors have recognised our reputation and have invested in our future. For example we are currently recruited six more midwives.”
Chris Ball, general manager for women and children’s services, said: “Adrienne and her staff have worked very hard to provide the best possible service to women in our population.
“Everyone works as a team. From the executive director to the housekeeper, we adopt a team approach to ensure that the women in our care receive a high quality service. We also look to constantly improve and this review will help us plan our future priorities.”

domain: medical


text:
Good evening, everyone, and it is a mild one here on Long Island. At 5:30 the temperature is reading 56! I hope wherever you are you are enjoying the season, and not exhausted from all the busy ness!
I wanted to show you my new porch tree. Last year in January, I picked it up for 12.00 after all the discounts and coupons . I got it at BBB with the porch in mind. 7ft. pre lit.
It was an experiment, I didn’t know if the wind would constantly knock it over. So far so good, so next year I will add some ornaments.
My wreath is faux, with a French Horn wired in, and real greens from the yard. It is battery operated, so it lights up at dark. Look mom, no wires! I added pine cones, baby’s breath and some ornaments.
See the speaker under the tree? Christmas music fills the air!
Here’s how it looks at night.
I have a small one on the back deck so we can see it from the den. It kept blowing over, so I took it out of the stand, and put it in the umbrella stand.
Ta Da, problem solved. Next year I will do that on the front one too! In the background you can see my white bench adorned with a wreath and some battery operated lights . Did I mention that there is no one here in winter and it is so DARK!
Please excuse the cord, I will have to hide that tomorrow!
I bought one of those Bliss lights (QVC) like they have in Disney World to see how it would work on the tree in front. DH wasn’t up to climbing the ladder to put the lights on this year.
I wish they made them in white! It would be so much easier than putting lights up! If you look carefully, you can see the Holy Family in the lights. See them? If not you still have a few days to straighten up your act and get on the good list before Cmas!
Hope you have a wonderful weekend! I hope to post my special table Mon or Tues. for the Let’s Dish Christmas edition.
Tuesday the weather was a very different story, ice and snow. Our gkids Christmas Concert was 90 miles away, but it was the Kdgn gson’s first, and I didn’t want to miss it!
Another gson in 2nd grade…
The third graders do the Nativity…
Seeing the whole school from Kdgn to 8th grade perform is such a spirit booster. The grandparents eyes fill with tears as those little voices sing Silent Night!
Wishing you all the blessings of this holy season!
Hope your kitchen smells heavenly!
I am joining Alma for Seasonal Sunday. I am also joining Susan for Metamorphosis Mon. Please go over and visit!
Thanks for stopping by!

domain: hobby


text:
CORE-OM as a routine outcome measure for adolescents with emotional disorders: factor structure and psychometric properties
BMC Psychology volume 8, Article number: 86 (2020)
Instruments for monitoring the clinical status of adolescents with emotional problems are needed. The Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) according to theory measures problems/symptoms, well-being, functioning and risk. Documentation of whether the theoretical factor structure for CORE-OM is applicable for adolescents is lacking.
This study examined the factor structure and psychometric properties of the CORE-OM based on two samples of adolescents (age 14–18): youths seeking treatment for emotional problems (N = 140) and high school students (N = 531). A split half approach was chosen. An exploratory factor analysis (EFA) was performed on the first half of the stratified samples to establish the suitability of the model. A Confirmatory Factor Analysis (CFA) with the chosen model from the EFA was performed on the second half. Internal consistency and clinical cut-off scores of the CORE-OM were investigated.
The best fitting model only partially confirmed the theoretical model for the CORE-OM. The model consisted of five factors: 1) General problems, 2) risk to self, 3) positive resources 4) risk to others and 5) problems with others. The clinical cut-off score based on the all-item total was higher than in an adult sample. Both the all-item total and general problems cut-off scores showed gender differences.
The factor analysis on CORE-OM for adolescents resulted in a five-factor solution, and opens up for new subscales concerning positive resources and problems with others. A 17-item solution for the general problems/symptoms scale is suggested. We advise developers of self-report instruments not to reverse items, if they do not intend to measure a separate factor, since these seem to affect the dimensionality of the scales. Comparing means for gender in non-clinical samples should not be done without modification of the general emotional problem and the positive resources scales. Slightly elevated CORE-OM scores (up to 1.3) in adolescents may be normal fluctuations.
Emotional disorders represent the most prevalent mental health problem in adolescence, and the comorbidity among emotional disorders is high. The onset of emotional problems typically occurs in childhood and adolescence or early adulthood . There is a call for screening tools that can detect mental health problems in adolescents and determine their clinical status. Valid and reliable routine outcome measures are key tools in monitoring treatment effects and for detecting and preventing treatment failure . There is a need for transdiagnostic measures that address comorbidity and are sensitive to change to monitor the treatment of adolescents.
The self-report Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) is a 34-item questionnaire using a 5-point Likert scale from 0 (not at all) to 4 (most of the time). CORE-OM is widely used measure in outpatient mental health and counselling services and in psychotherapy research with adult patients [3,4,5]. The CORE-OM items were chosen based on their clinical significance and their sensitivity to change in psychological status [3, 4]. The CORE-OM theoretically covers four dimensions: Well-being (4 items); Functioning (12 items); Problems/symptoms (12 items); and Risk (6 items) [6, 7]. ‘Well-being’ refers to a patient’s sense of life quality and emotional health. ‘Problems/symptoms’ is associated with psychological health issues such as anxiety and depression symptoms, reactions to trauma, and physical complaints. ‘Functioning’ relates to interpersonal, social and general functioning in daily life. A high correlation has been found among these three domains [5, 8, 9], and combining them into a general psychological distress scale called All-items-minus Risk has been recommended . ‘Risk/harm’ includes items covering harm to self and suicidal ideation (risk-to-self items) and violent behaviour and threats towards other people (risk-to-others items) [6, 11]. It has been recommended that risk be monitored separately to help the clinician detect a patient’s thoughts and plans regarding self-harm, suicide and violence .
The original CORE-OM  has been translated into more than 20 languages and has good psychometric properties in adult samples [7, 8, 12,13,14,15]. The CORE-OM has been benchmarked in student counselling and primary care service users aged 16 to 24 , however, this study lacked a control group of non-service users.
One version of the CORE developed for young people aged 11–16 is the CORE-YP . However, the CORE-YP includes only ten of the CORE-OM items, phrased in simplified wording, and it is not adapted for the whole age span of adolescents (up to age 18) received in Norwegian child and adolescent mental health outpatient services. The CORE-OM, with its 34 items, gives more detailed information when needed; it addresses the most common comorbid symptoms in emotional disorders, is sensitive to change, and exists in a ten-item version (the CORE-10) that can be used session by session. Measures with these qualities are scarce in child and adolescent mental health services. For researchers and clinicians, it is more convenient to use one tool for adolescents, both for longitudinal research and to monitor treatment, without having to change tools due to changing age norms. In Norway youths up to age 18 are referred to child and adolescent mental health services, while individuals aged 18 and older are referred to adult outpatient services.
Since the CORE-OM addresses anxiety, depression, the aftermath of trauma, physical complaints, daily life functioning, subjective well-being, and risk to self and others, it is a highly relevant outcome measure, not only for adults but also for adolescent service users, and is particularly relevant for those with emotional problems. However, there is no existing validation of the full CORE-OM scale in high school age adolescent samples.
There is a need for knowledge about whether the test parameters for the CORE-OM in youths are comparable with those obtained in adult populations.
Previous research on the factor structure of the CORE-OM  has not fully confirmed the theoretically derived sub-scales but has rather indicated a structure constituted by a g-factor of psychological distress and residualized latent theoretically derived domains (Symptoms/Problems, Functioning and Well-being). ‘Risk-to-self’ correlates with the g-factor, while ‘risk-to-others’ has a poor fit in the structural models . Several factor analytic evaluations of the CORE-OM have been performed. The test developers  suggested a first component that explained 38% of the variance, a risk component and a positively worded component. In later factor analyses some of the same researchers  suggested a bifactor model with an overall g-factor, a method factor (with positively and negatively keyed items) and risk to self and others. But, their best fitting model included the well-being, psychological problems, and functioning domains, although most of the factor loadings associated with these three domains were small after the g-factor was accounted for. In the Norwegian version  a bifactor model was also suggested, but here the method factor did not contribute to improve model fit. The model considered best in that study was a bifactor model with a general distress factor and the four CORE-OM domains. Investigations on the British version suggested using “Mokken Scaling” . This scale is unidimensional resulting in a general distress factor, with items differentiating between more or less severe levels of stress. This approach result in the well-being items giving information about lower levels of stress, while the risk items covers higher levels of stress, with the other items in between. When the CORE-OM was constructed , the majority of items were statements about psychological distress or negative life situations, i.e., psychological distress. Most of the items were thus negatively keyed. However, eight items were positively keyed, allegedly to mitigate response bias . However, mixing negatively and positively keyed items may add method effects that threaten the construct validity of an instrument. Whether the method effects of negatively and positively keyed items are caused by responder error , by response bias , or because positive and negative utterances actually measure different constructs are, however, unclear. Lyne et al.  demonstrated that the positively and negatively keyed items in the CORE-OM formed two separate method factors across the theoretically defined domains. In the validation of the CORE-OM in adult Norwegian samples, these method factors were also observed but were deemed negligible .
The CORE-OM has the potential to discriminate between non-clinical and clinical adult populations [5, 7, 8, 12, 13, 15]. The recommended cut-off score for the CORE-OM in the adult population is 1.0 .
Gender effects have been found for the All-items score, with women generally scoring higher than men, and consequently, gender-specific cut-off scores have been recommended by some authors [5, 13]. Other validations of the CORE-OM have not recommended separate cut-off scores based on gender, suggesting that gender effects were small and negligible [7, 12].
CORE-OM and Beck Depression Inventory (BDI) scores correlate in clinical samples . Adolescents tend to have higher scores than adults on the BDI [22, 23]. Findings suggest that younger respondents generally score higher on the CORE-OM than older respondents [5, 7, 8, 14] and motivate the present authors to ask whether separate cut-off scores for adolescents are needed, as has been found for the BDI [22, 23].
Since no study has evaluated the factor structure of CORE-OM and the reliability of its factors in an adolescent population, there is a need for such studies. Since several studies have shown that girls score higher than boys do on emotional problems [24, 25] it is interesting to evaluate whether this also is observed when using the CORE-OM. To be able to do such a comparison, a requirement is that the factor structure for boys and girls are similar. In the factor analytic framework this can be done evaluating measurement invariance of the factors, and mean comparisons on gender require at least partial scalar invariance .
The aims of this paper were to study the psychometric properties of the Norwegian version of the CORE-OM in an adolescent clinical sample selected for emotional problems and a non-clinical sample by
Investigating the factor structure of the Norwegian CORE-OM in adolescents aged 14 to 18 years, by establishing the suitability of the model by Exploratory Factor Analysis (EFA), and performing Confirmatory Factor Analysis (CFA) with the chosen model of the EFA.
Evaluating the internal consistency on the scales from the chosen model.
Performing a measurement invariance analysis for gender based on the factor structure suggested by the factor analysis.
Comparing factor means for boys and girls in the non-clinical sample, if at least partial scalar invariance under (III) is achieved.
Calculating clinical cut-off scores.
A between-subjects cross-sectional survey study was used to examine the psychometric properties of the CORE-OM in samples of Norwegian adolescents aged 14–18 years.
Data were gathered from two separate samples: a non-clinical and a clinical sample. The non-clinical sample (n = 531) was recruited for the purpose of this paper from four junior high schools and four senior high schools in both urban and rural areas in North Norway. The schools were randomized and drawn, and data were collected until at least 65 participants from each class grade were included. In the non-clinical sample (age 14–18, M = 15.91, SD = 1.45), there were 273 (51.4%) boys and 258 (48.6%) girls. The response rate was between 71.4 and 83.3%. Although the sampling procedure was systematic, the non-clinical sample should be viewed as a convenience sample.
The clinical sample consisted of patients (n = 140) recruited at CAMHS (Child and Adolescent Mental Health Services) located in two North Norwegian towns and one community centre. In the CAMHS sample (age 14–17, M = 15.72, SD = 1.15), there were 13 boys (9.3%) and 127 girls (90.7%). The adolescents in this sample were enrolled as participants in a psychotherapy research project, the SMART study  (‘Evaluation of short-term treatment for adolescents with emotional disorders in five children and adolescent CAMHS—A randomized controlled trial’ (ClinicalTrials.gov Identifier: NCT02150265); Regional Committee for Medical and Health Research Ethics (REC North); Reference number 2011/1937). Data for the present study were collected at enrolment, before treatment.
The inclusion criterion for the non-clinical sample was being a student at a junior or senior high school, while the exclusion criterion was that the adolescent could not read or write Norwegian fluently. The inclusion criteria in the clinical sample were (1) age between 14 and 17 years; (2) a probable diagnosis of an emotional disorder as indicated by a score of at least 6 on the Strengths and Difficulties Questionnaire (SDQ) screening tool; and (3) maintenance of a maximum waiting time for necessary medical care of 6 weeks given by Norwegian health authorities. The exclusion criteria were (1) a diagnosis of pervasive developmental disorder (PDD); (2) psychotic symptoms; (3) anxiolytic or anti-depressant medication effects during the treatment period; and (4) inability to speak the Norwegian language.
Ethics and consent
The study was performed in compliance with the Helsinki Declaration for research on humans and was approved by the REC North (Reference number 2011/1937).
All participants participated and consented according to the regulations governing the research project, with written parental consent provided for those under age 16 (REC North, Reference number 2011/1937). High scores on symptom and risk items were addressed by the responsible therapist or counsellor.
All participants completed the CORE-OM in Norwegian translation  on paper with a pen or pencil. All participants provided information regarding age and gender. The scoring procedure for both samples followed the guidelines for scoring from Barkham et al. .
Descriptive data for each of the 34 items, separately for the clinical and non-clinical sample, have been provided as additional material.
The following procedure in evaluating the factor structure of the CORE-OM was performed: The sample was randomly split into two equally sized halves, stratified on sample (clinical/non-clinical) giving an equal proportion of cases from the clinical and non-clinical samples in each half. One of the sample halves was a training sample where an exploratory factor analysis (EFA) was done, and the other half was a testing sample where the chosen model from the EFA was tested using confirmatory factor analysis.
In the EFA, different solutions with varying number of factors was evaluated. Model fit information for each model, difference in model fit between subsequent factor solutions, and the meaningfulness of the Geomin rotated factor loadings was used to guide the choice of the number of factors.
The CFA was carried out on the chosen model from the EFA. The WLSMV estimator and delta parameterization was used . Model fit for the CFA was evaluated by the Chi-square test, the chi-square to degrees of freedom ratio, the RMSEA  and the CFI . A significant Chi-square test indicates significant model misfit, but the chi-square test is both a function of sample size and the amount of misfit so we rely mostly on the RMSEA and CFI for model fit evaluation. Models with a chi-square/df ratio < 2 . RMSEA below 0.05 and a CFI above 0.95 are typically considered to be well-fitting .
With the WLSMV estimator and using the default missing data handling method in Mplus, pairwise deletion is used to handle the missing observations. This means that a pair of observations is used in computing a polychoric correlation if both observations in the pair are observed. Overall, the covariance coverage percentage of data for the CFA part of the sample was between 96.1 and 100%, and with the highest proportion of missing observations for items 19 and 20 where 2.4 and 2.1%, respectively, were missing.
Outliers was evaluated by Cook’s d in the CFA analysis. The Cook’s d computes, for each subject, the overall influence that the subject has on the parameter estimates estimated in the analysis. Additional analyses without the individuals with the highest Cook’s d values was performed, and there was noted a very small improvement in the fit indices in the CFA analysis when those cases were removed. Since the overall results and conclusions were not affected to a large degree by the outliers, our results were based on the whole sample.
Reliability was evaluated by computing McDonald’s Omega [32,33,34] for ordinal items, reporting a 95% confidence interval for the reliability parameter . Omegas if item is deleted with 95% confidence intervals are also reported  We computed item to total (using the rest of the items) correlations by a procedure shown in Raykov & Marcoulides  computing polyserial correlations.
Measurement invariance for gender is necessary for gender mean comparisons on CORE-OM scales. Measurement invariance was evaluated for a configural and a scalar model for the non-clinical sample. The low number of clinical boys in our study made it impossible to assess measurement invariance for gender using the clinical sample. With ordinal indicators Muthen & Muthen  recommends that factor loadings and thresholds as a unity, so metric invariance holding only factor loadings invariant between genders were not carried out. We compared the difference in model fit between the configural model and the scalar model was tested using the DIFFTEST option in Mplus. Modification indices were assessed for partial scalar invariance if full scalar invariance was not achieved through the DIFFTEST. Even though the use of modification indices are controversial, it is often considered, and Muthen & Muthen  recommends that equality constraints for factor loadings and thresholds are relaxed in tandem. Following their recommendations, scale factors for items with freely estimated loadings and thresholds were fixed at one for identification purposes.
Mean gender differences on latent factors were evaluated in the final partial scalar model.
All factor analyses were performed in Mplus (version 7.4). Omega coefficients were computed within R using a procedure described by Peters .
The acceptability of the data was assessed by analysing missing data. Chi-squared tests were conducted to explore the relationship between the missing items and groups and missing items and gender. ANOVA was conducted to determine whether there was a significant relationship between the missing items and age.
Jacobson and Truax’s  formula was used to calculate the cut-off score for discriminating between a clinical and non-clinical sample:
A maximum omission of 10% of the items was used as an indication of acceptability for the CORE-OM. Nine participants (1.7%) with an omission rate greater than 10% were removed from the dataset: three from the junior high school sample and six from the senior high school sample.
Exploratory factor analysis on the CORE-OM
EFAs with from one to six factors was performed. Factor solutions with one and two factors did not show good model fit. Three factors gave significantly better model fit than two factors, four factors gave significantly better model fit than three, five had significantly better model fit than four, and six was better than five according to a Chi-square difference test (see Table 1 for model fit for the 1 to 6-factor solutions). The factor loadings for the five-factor solution are shown in Table 2.
The five-factor solution was chosen, since the six-factor solution did not seem to add anything of substance. In Table 2 the factor loadings above 0.30 for each item are shown in bold for the five-factor solution. Factor 1 is interpreted as a general problem factor. All items for this factor are negatively keyed, and is a mix of what the manual describes as symptoms of anxiety, depression, physical problems, trauma, functioning and subjective well-being. Factor 2 consists of four risk-to-self items, i.e. four of the six “risk” items load highest on this factor. In addition, items 23, 27 and 30 loaded nearly as high on this factor as on Factor 1. These items points to symptoms of depression. One option is to remove such cross-loading items, but it seems important to include questions about unhappiness and despair in a questionnaire measuring symptoms of depression or general emotional problems. The level of risk of self-harm and general emotional problems are likely correlated, and it is therefore natural to observe some cross-loadings for these items.
The eight items loading highest on the third factor were all positively keyed, so this latent variable can be interpreted as positive resources that the adolescent possesses.
Factor 4 has two high-loading items that are interpreted as risk-to-others items.
For the fifth factor, items 25, 26 and 33 are functioning items related to functioning/relations with other people. Item 31 and item 3 had a cross-loading on this factor that was nearly as high as the loading on the general factor. Both these items are related to relations to other people, but the positive framing of item 3 give a higher loading on the positive resources latent variable, while item 31 (irritability with others) can both be a result of problems with others but also something that is related to general problems.
This factor structure gave the most interpretable factors in our opinion. Even though we got a significantly better fit with six factors compared to five, the sixth factor loads highest only on item 8. This item has to do with physical problems or pain and is possibly related to somatic symptoms, which is not asked for in detail in CORE-OM. The six-factor solution is not shown here, but with very few exceptions, the items were loading on the same factors as in the five-factor solution.
The two-factor and three-factor solutions gave a general factor plus additional factors that were hard to interpret. The four-factor solution had a general factor, Risk to others, Positive items and Problems with others as possible interpretations, and the difference between this and the five-factor solution was mainly that the risk to self-items loaded on the general problems factor.
Confirmatory factor analysis
A CFA was performed on the five-factor model that was selected from the EFA, using the other half of the sample.
In this analysis, all factor loadings were significantly different from zero (see Fig. 1). Item 19 showed a loading that indicated a low association to the Positive resources latent variable.
Model fit information for this analysis showed a significant χ2(517) = 956.7 (p < .0005), and χ2/df = 1.85; RMSEA = 0.05 (90% CI: (0.045, 0.055)); CFI = 0.978. According to commonly used criteria for a “good” model, both the RMSEA and the CFI satisfy these benchmarks, as does the χ2/df ratio (< 2).
The estimated correlations between the latent variables showed high correlations among all factors except for the Risk-to-others latent variable.
Reliability evaluation for the five factors: symptoms and problems, positive resources, risk to self, risk to others, problems with others
The CORE-OM items are measured on an ordinal (5-point Likert) scale. Therefore, we computed internal consistency reliability using the ordinal Omega coefficient . Omega coefficients based on the CFA sample are shown in Table 3. The omega if item deleted and item to total correlations are shown in Table 4.
Deleting one item from the scale, produces a small decrease in the reliability score for most of the items. For the general problem scale, reliability is not affected much by deletion of a single item, partly because of the large number of items in this scale. Reliability is maximized if item 8 (“I have been troubled by aches, pains or other physical problems “) is deleted with an increase from .958 to .960. Also, for item 29 there is an increase in Omega if the item is deleted. For the positive scale, item 19 (“I have felt warmth and affection for someone “) performs worst. Dropping this item increases the Omega reliability score from .881 to .897. For the Risk to self-scale, deleting item 34 (“I have hurt myself physically or taken dangerous risks with my health“) increase the Omega coefficient slightly.
The item to total correlations gives similar results as the Omega if item deleted, with the same items as mentioned above associated with the lowest item-total correlations. Particularly item 19 may be problematic to include as an indicator of the positive resources latent variable.
Measurement invariance for gender on the non-clinical sample
The configural model that allows all parameters to be estimated freely for the genders showed good model fit (χ2(1034) = 1610.4 (p < .0005), RMSEA = 0.046 (90% CI: (0.041, 0.050)), CFI = 0.969). Reasonable model fit for the configural model is necessary for further measurement invariance testing. The scalar model holding factor loadings and thresholds invariant across the genders had model fit: χ2(1153) = 1751.9 (p < .0005), RMSEA = 0.044 (90% CI: (0.040, 0.048)), CFI = 0.968. The DIFFTEST in Mplus showed significantly worse model fit for the scalar model compared with the configural model (χ2(119) = 207.1; p < 0.0005), indicating that holding all loadings and thresholds to be equal across genders are not warranted, so the requirement of full scalar invariance does not hold. Similar CFI and RMSEA values for the configural and scalar model could indicate that there are problems with a relatively few loadings and thresholds. Partial scalar invariance was therefore evaluated using modification indices.
The largest modification index for the scalar model was associated with the lowest threshold for item 14 (“I have felt like crying”). This is the item with a large difference in the distribution for boys and girls. Relaxing the loading and the threshold constraints for this item made model fit slightly better, but still the DIFFTEST was significant: χ2(115) = 174.1 (p < 0.0005). Next, we relaxed the loading and thresholds for item 29, and the DIFFTEST was still significant: χ2(111) = 161.5 (p < 0.0005).
We did modify the scalar model by relaxing the constraints one by one according to the largest modification index. Table 5 shows the steps taken in this process:
The items that the data indicate might be most problematic to establish scalar invariance are shown in Table 5. Item 14 has very different distribution for boys and girls. Maybe including an item about crying is not a good idea when assessing differences on emotional problems for boys and girls. Admitting to crying is probably very different for the genders, and a boy and a girl with the same amount of problems might answer this question very differently (gender specific differences). Item 4 has the same tendency as for item 14 with a much higher proportion of boys reporting satisfaction with themselves than girls. Items 19 and 29 had the lowest standardized loadings both for boys and girls.
Gender differences on the latent factors
Based on the final partial scalar model (E), there was a significant gender difference in the factor means for the General problems latent variable (z = − 7.52; p < .0005; boys scoring lower than girls), Positive resources (z = 5.46; p < .0005; boys scoring higher than girls), Problems with others (z = − 5.02; p < .0005; boys scoring lower than girls), and Risk-to-others (z = 3.11; p = .002; boys scoring higher than girls). There were no significant differences between boys and girls on the latent Risk-to-self variable.
Clinical cut-off score
Clinical cut-off scores were estimated by employing Jacobson and Truax’  formula.
Before calculating the cut-off score, participants in the non-clinical sample that reported being in treatment were excluded (n = 23). The estimated CORE-OM all-items cut-off score according to Jacobson and Truax’ formula was 1.31 (girls: 1.44; boys: 1.02). For the 17-item general distress scale the cut-off was 1.51 (girls: 1.69; boys: 1.09).
The main findings in this validation of the CORE-OM in a mid-adolescent sample were a new factor solution and a higher cut-off score than reported in adult samples. The EFA resulted in a five factor solution, and the factor contents were interpreted as general problems, positive resources, risk to self, risk to others, and problems with others. The CFA model fit for this model was good. The measurement invariance analysis for gender should not be performed without modification of the scale. The clinical cut-off score based on the all-item total was higher than in an adult sample. Both the all item total and general problems cut-off score showed gender difference.
Factor analysis and reliability
From the exploratory factor analysis, based on the training part of the training sample, a five-factor model was interpreted to be the best candidate for model evaluation. In the EFA, this model had improved model fit over factor solutions with less factors, and had factors that were interpreted as General problems, Positive resources, Risk to self, Risk to others and Problems with others. In the following confirmatory factor analysis, done on the testing part of the sample, model fit for this model can be characterized as good.
The developers of the CORE-OM manual describes the instrument as a four-dimensional measure with dimensions of Subjective well-being, Problems, Functioning and Risk . There may be many reasons why data from the present youth sample yielded a different factor structure. We believe that one main reason for this is that eight of the 34 items are positively keyed. Lyne et al. (2006)  showed that for CORE-OM on an adult sample, method factors related to positive and negative wording of the items played a role in achieving acceptable model fit. In our sample, all the eight positively keyed items loaded on the same factor in the five-factor EFA. It seems that when the adolescents answer these items, the positive resources in their lives are prompted, rather than just negative aspects. This highlights that assuming that a low score on a positively keyed item reflects the same as a high score on a negatively keyed item is problematic. According to the tripartite theory of anxiety and depression  negative affect and lack of positive affect may represent separate dimensions of internalizing problems. The current factor solution supports that negative affect and lack of positive affect are not two sides of the same coin.
Combining all the positively keyed items to a separate subscale not only solves the problem of reversed items, but also produces a substantially easier subscale to interpret than the theoretically derived Well-being scale, since it reflects resources, wellbeing and self-efficacy.
Incidentially, one of the positively keyed items had a much lower factor loading in the CFA than the other items. Although item 19 (“I have felt warmth and affection for someone») is positively keyed it differs in content from the rest of the positive items. This item may measure traits like empathy or affection directed towards other people, and not necessarily positive feelings about themselves. Also, removing this item from the scale improves the Omega reliability score by nearly 0.02, and this item had an item to rest-correlation below 0.30. One other reason for the low factor loading for item 19 may be that the Norwegian translation of the word “affection” is a word that is probably not used among Norwegian adolescents nowadays. Thus, a revision of the Norwegian translation is recommended.
The risk items split into two distinct factors. The risk to others items (item 6 and 22) correlates highly with each other but little with the other items in the questionnaire. We also see this through low factor correlations between the latent Risk-to-others variable and the other four latent variables in the CFA. In the EFA, a Risk to other scale shows up early, although it is questionable whether these two items cover a large enough range of such a dimension.
The Risk to self-dimension seems more robust, having a high reliability score for the internal consistency. The factor correlation between Risk-to-self and General problems is very high (> 0.90), and this seems natural as having many symptoms of problems may impact self-harm and suicidal ideation. Cross-loadings between Risk-to-self and General problems were evident for the items “I have felt despairing or hopeless” and “I have felt unhappy”. Although such items may indirectly indicate risk of self-harm, we believe that these items are more direct indicators of the severity of of emotional problems.
The reliability analysis revealed that the Omega would increase slightly if item 34 “I have hurt myself physically or taken dangerous risks with my health” was removed from the scale. This item may or may not be related to intensions of self-mutilations or suicide. The other items within the Risk to self-scale are more directly associated with such intentions, while taking dangerous risks may be sensation-seeking behavior not directly associated with self-harm intentions.
For the General problems scale, half (17) of the CORE-OM items loaded highest on this variable in the EFA. For this scale, the Omega reliability would improve slightly if the items 8 and 29 were removed from the scale, and these two items had the lowest item to rest correlations for the items within the General problems scale. Item 8 (“I have been troubled by aches, pains or other physical problems “) may be caused by mental health issues but can also be a result of injuries, physical disease and other issues not related to emotional problems. Increased reliability removing this item from the general problem scale may be an indication of this. For item 29 (“I have been irritable when with other people”) was probably the item that was most difficult to place. It loaded moderately on the General problem latent variable, and cross-loaded on the Problems with others latent variable. To be irritable when with others can be an indicator of problems with the functioning with others, but can also be an indicator of emotional problems since irritability may be associated with several traits or conditions .
Finally, items 25, 26 and 33 loaded on the Problems with others factor. These items have to do with relationships with others. Lyne et al.  pointed at the same three items as belonging to a common factor. After accounting for a general distress factor, these three items were the only items that had meaningful loadings on their residualized Functioning factor. This highlights that feelings of humiliation or critique from others and having no friends may form a separate factor in the CORE-OM instrument.
Measurement invariance for gender
We did a measurement invariance analysis for gender, to evaluate whether it is reasonable to make mean comparisons between girls and boys using CORE-OM.
Comparing the configural model and full scalar model, we found that scalar model fit significantly worse than the configural model, and this indicates that one cannot compare means for boys and girls without modifications to the scales. After 4–5 steps of relaxing constraints in the scalar model, we found a partial scalar model that did not fit significantly worse than the configural model. In comparing means for boys and girls on the CORE-OM scales, one should probably be careful in using the items 14, 29, 4, 31 and 19.
Different researchers rely on different fit statistics when evaluating measurement invariance Putnick and Bornstein  show that many consider that a small change in CFI or RMSEA going from a configural to a scalar model could indicate scalar invariance. The change in CFI and RMSEA shown for gender invariance in the non-clinical sample in the present study, is very small, and within the limits of full scalar invariance mentioned by Putnick and Bornstein . However, it is problematic if one chooses the change in χ2 as criterion for invariance when it is non-significant and other criteria when it is significant. We used a data driven method (modification indices) instead to establish partial scalar invariance. Partial scalar invariance can be concluded when a large majority of the items on the factors is invariant  The use of modification indices is also controversial , but can be helpful in determining items that are problematic. For example, our analysis showed that item 14 in CORE-OM (“I have felt like crying”) may be an item that is problematic to include when symptoms of depression or anxiety are to be compared between the genders. Boys and girls report very differently on this item, and this difference cannot be attributed only to the amount of emotional problems on the latent scale the adolescents have but also to some gender specific traits.
Gender differences in the non-clinical sample
We compared factor means for male and female adolescents in the non-clinical group using the final partial scalar model. Boys and girls differed on four of the five latent variables. A non-significant difference between the genders was found for the risk to self-variable. For the non-clinical group few adolescents had thoughts of self-harm. The girls scored higher than boys did on the general factor, and that has also been shown in other studies [5, 13]. Boys scored significantly higher on the risk to others factor. This is consistent with other validations of the scale [7, 14] .
For the positive resources latent variable, girls scored significantly lower than boys. Finally, for the Problems with others factor the girls scored higher than boys. The items in this scale have to do with feelings of having been criticized, humiliated, made shameful or having no friends, and are as such about emotional relations with others. Girls tend to use emotional coping skills more often than boys, and help from others, while boys tend to devaluate such emotional expressions , hence stronger feelings related to emotional relationships can be the result. In the Japanese version of CORE-OM the female participants showed lower scores on “close relationships” subscales .
Factor correlations between the latent variables in the chosen factor solution were high, except for those involving risk to others. Similar gender differences for general emotional problems, positive resources and problems with others can be a sign that related concepts are being involved.
Mixing positive and negative items in a questionnaire
Lyne et al.  concluded their article, studying 2140 adult patients, that the most useful scoring method of the CORE-OM would be to compute a general total score based on the 28 non-risk items and a risk total based on the remaining six items. The main difference between the 17-item general problems scale from the present study and the 28-item non-risk scale is the exclusion of the positively keyed items from the 17-item version.
One of the reasons for including both positively and negatively keyed items in a questionnaire is to reduce acquiescence bias (response style bias, respondents tending to agree with statements) . However, positively and negatively keyed items may involve different cognitive processes [45, 46] and this is one of the reasons that a positive item latent variable showed up in the EFA. It is a paradox that including some positively keyed items in a questionnaire consisting mostly of negatively keyed items, in order to mitigate acquiescence bias, seems to confuse the responders and therefore makes the instrument less valid and scales less reliable.
Clinical cut-off score
The original validation of the CORE suggested a clinical cut-off of 1.2 , and later validations have suggested a cut-off point as low as 1.0  to define clinical caseness. However, in these adolescent samples, the cut-off score on the All-items CORE-OM was 1.31, 1.44 (girls) and 1.02 (boys). This finding needs to be replicated, but it corresponds well with the finding that youths also score higher than adults on the BDI [22, 23]. Consistent of the results from the present study we also recommend the 17-item factor as a measure of general problems. The positively keyed items do not interfere with this factor and the problem with others items are also excluded. In this way we have a more reliable measure on emotional problems and the cut-off scores for this factor is suggested as an alternative to the established All items minus Risk score. The rationale for this is that the All items minus Risk 28-item score includes all reversed items, and may thus actually underestimate the level of emotional distress experienced by patients. The cut-off scores for both All-items and the 17-items general distress factor show gender differences, with girls scoring higher than boys and a higher score than in adult samples . We suggest that the cut-off scores either is gender specific or that the cut-off for gender combined is set lower to accommodate for the boys lower scoring, as suggested by Connell et al. .
The clinical sample may not be representative of the entire CAMHS population due to the sample being preselected based on symptoms of emotional problems. Furthermore, patients evaluated as suicidal were excluded from the sample because they could not be subjected to the 6-week waiting condition. However, since the CORE-OM was mainly developed to monitor outpatient treatment and is not the outcome measure of choice for psychosis or conduct disorder, the present clinical sample probably has a high density of the phenomena that the CORE-OM was designed to monitor.
The age span in the non-clinical sample was 14–18, while the age range in the clinical sample was 14–17. The reason for this is that Norwegian CAMHS receives only those younger than age 18 as patients, while youths 18 and older are referred to mental health services for the adult population. However, in high school, enrolment in different grades is based on the year of birth. We decided not to exclude the 18-year-olds from the non-clinical sample. Furthermore, the mean age in the two samples is similar.
Due to the low rate of males in the clinical sample, the mean and standard deviation in the male clinical sample used in the Jacobson and Truax formula have large standard errors. Therefore, the clinical cut-offs for boys are encumbered with uncertainty.
Although the present version of CORE-OM shows promising psychometric properties, there are some challenges with the instrument. Leaning on van Sonderen et al.  and Suárez-Alvarez et al. , we believe that using a mix of positively and negatively keyed items should be avoided, if the intention is not to measure separate dimensions. However, the five-factor solution found in this validation both had a good model fit, and not the least, yielded clinically meaningful subscales. According to the factors found in this study we recommend the 17-item factor as a more reliable measure of general problems. Comparing means for gender in non-clinical samples should not be done without modification of the general emotional problem and the positive resources scales. This should be objectives for future revisions of the scale.
Availability of data and materials
The datasets generated and analysed during the current study and the full study protocol are available from the corresponding author on reasonable request.
Clinical Outcome in Routine Evaluation-Outcome Measure
Exploratory Factor Analysis
Confirmatory Factor Analysis
Becks Depression Inventory
Strengths and Difficulties Questionnaire
Child and Adolescent Mental Health Services
Analysis of Variance
Weighted Least Squares Means and Variance adjusted
Root Mean Square Residual
Comparative Fit Index
Kessler RC, Amminger GP, Aguilar-Gaxiola S, Alonso J, Lee S, Üstün TB. Age of onset of mental disorders: a review of recent literature. Curr Opin Psychiatry. 2007;20:359–64.
Lambert MJ, Whipple JL, Hawkins EJ, Vermeersch DA, Nielsen SL, Smart DW. Is it time for clinicians to routinely track patient outcome? A meta-analysis. Clin Psychol Sci Pract. 2003;10:288–301.
Barkham M, Evans C, Margison F, McGrath G, Mellor-Clark J, Milne D, et al. The rationale for developing and implementing core outcome batteries for routine use in service settings and psychotherapy outcome research. J Ment Health. 1998;7:35–47.
Barkham M, Leach C, Lucock M, Evans C, Margison F, Mellor-Clark J, et al. Service profiling and outcomes benchmarking using the CORE-OM: toward practice-based evidence in the psychological therapies. Clinical outcomes in routine evaluation-outcome. J Consult Clin Psychol. 2001;69:184–96.
Evans C, Connell J, Barkham M, Margison F, McGrath G, Mellor-Clark J, et al. Towards a standardised brief outcome measure: psychometric properties and utility of the CORE-OM. Br J Psychiatry. 2002;180:51–60.
Evans C, Mellor-Clark J, Margison F, Barkham M, Audin K, Connell J, et al. CORE: clinical outcomes in routine evaluation. J Ment Health. 2000;9:247–55.
Skre I, Friborg O, Elgarøy S, Evans C, Myklebust LH, Lillevoll K, et al. The factor structure and psychometric properties of the clinical outcomes in routine evaluation - outcome measure (CORE-OM) in Norwegian clinical and non-clinical samples. BMC Psychiatry. 2013;13:99.
Elfström ML, Evans C, Lundgren J, Johansson B, Hakeberg M, Carlsson SG. Validation of the Swedish version of the clinical outcomes in routine evaluation outcome measure (CORE-OM). Clin Psychol Psychother. 2013;20:447–55.
Lyne KJ, Barrett P, Evans C, Barkham M. Dimensions of variation on the CORE-OM. Br J Clin Psychol. 2006;45:185–203.
Bedford A, Watson R, Lyne J, Tibbles J, Davies F, Deary IJ. Mokken scaling and principal components analyses of the CORE-OM in a large clinical sample. Clin Psychol Psychother. 2010;17:51–62.
Barkham M, Mellor-Clark J, Connell J, Cahill J. A CORE approach to practice-based evidence: a brief history of the origins and applications of the CORE-OM and CORE system. Couns Psychother Res. 2006;6:3–15.
Kristjánsdóttir H, Sigursson BH, Salkovskis P, Ólason D, Sigurdsson E, Evans C, et al. Evaluation of the psychometric properties of the Icelandic version of the clinical outcomes in routine evaluation-outcome measure, its transdiagnostic utility and cross-cultural validation. Clin Psychol Psychother. 2015;22:64–74.
Palmieri G, Evans C, Hansen V, Brancaleoni G, Ferrari S, Porcelli P, et al. Validation of the Italian version of the clinical outcomes in routine evaluation outcome measure (CORE-OM). Clin Psychol Psychother. 2009;16:444–9.
Uji M, Sakamoto A, Adachi K, Kitamura T. Psychometric properties of the Japanese version of the clinical outcomes in routine evaluation-outcome measure. Compr Psychiatry. 2012;53:600–8.
Viliū nienė R, Evans C, Hilbig J, Pakalniškiene V, Danilevičiute V, Laurinaitis E, et al. Translating the clinical outcomes in routine evaluation outcome measure (CORE-OM) into Lithuanian. Nord J Psychiatry. 2013;67:305–11.
Connell J, Barkham M, Mellor-Clark J. Mental health CORE-OM norms of students attending university counselling services benchmarked against an age-matched primary care sample. Br J Guid Couns. 2007;35:41–57.
Twigg E, Cooper M, Evans C, Freire E, Mellor-Clark J, McInnes B, et al. Acceptability, reliability, referential distributions and sensitivity to change in the young person's clinical outcomes in routine evaluation (YP-CORE) outcome measure: replication and refinement. Child Adolesc Ment Health. 2016;21:115–23.
Conrad KJ, Wright BD, McKnight P, McFall M, Fontana A, Rosenheck R. Comparing traditional and rasch analyses of the Mississippi PTSD scale: revealing limitations of reverse-scored items. J Appl Meas. 2004;5:15–30.
Lindwall M, Barkoukis V, Grano C, Lucidi F, Raudsepp L, Liukkonen J, et al. Method effects: the problem with negatively versus positively keyed items. J Pers Assess. 2012;94:196–204.
Connell J, Barkham M. CORE-10 user manual, version 1.1. Rugby: CORE System Trust & CORE Information Management Systems Ltd; 2007.
Leach C, Lucock M, Barkham M, Noble R, Clarke L, Iveson S. Assessing risk and emotional disturbance using the CORE-OM and HoNOS outcome measures at the interface between primary and secondary mental healthcare. Psychiatr Bull. 2005;29:419–22.
Albert N, Beck AT. Incidence of depression in early adolescence: a preliminary study. J Youth Adolesc. 1975;4:301–7.
Teri L. The use of the beck depression inventory with adolescents. J Abnorm Child Psychol. 1982;10:277–84.
Bøe T, Hysing M, Skogen JC, Breivik K. The strengths and difficulties questionnaire (SDQ): factor structure and gender equivalence in Norwegian adolescents. PLoS One. 2016;11(5):e0152202.
Khesht-Masjedi MF, Shokrgozar S, Abdollahi E, Golshahi M, Sharif-Ghaziani Z. Comparing depressive symptoms in teenage boys and girls. J Family Med Prim Care. 2017;6(4):775–9.
Muthén LK, Muthén BO. Version 6 Mplus user's guide. Los Angeles: Muthén & Muthén; 2010.
Lorentzen V, Fagermo K, Handegård BH, Skre I, Neumer SP. A randomized controlled trial of a six-session cognitive behavioral treatment of emotional disorders in adolescents 14-17 years old in child and adolescent mental health services (CAMHS). BMC Psychol. 2020;8(1):25.
Steiger JH. Structural model evaluation and modification: an interval estimation approach. Multivariate Behav Res. 1990;25:173–80.
Bentler PM. Comparative fit indexes in structural models. Psychol Bull. 1990;107:238–46.
Schermelleh-Engel K, Moosbrugger H, Müller H. Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychol Res Online. 2003;8:23–74.
Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1–55.
McDonald RP. Test theory: a unified treatment. Mahwah: L. Erlbaum Associates; 1999.
Peters G-JY. The alpha and the omega of scale reliability and validity: why and how to abandon Cronbach’s alpha and the route towards more comprehensive assessment of scale quality. Eur Health Psychol. 2014;16(2):56–69.
Revelle W, Zinbarg R. Coefficients alpha, Beta, omega, and the GLB: comments on Sijtsma. Psychometrika. 2009;74:145–54.
Dunn TJ, Baguley T, Brunsden V. From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation. Br J Psychol. 2014;105:399–412.
Leppink J. Statistical methods for experimental research in education and psychology. Cham: Springer; 2019.
Raykov T, Marcoulides G. Introduction to psychometric theory. New York: Routledge; 2011.
Jacobson NS, Truax P. Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. J Consult Clin Psychol. 1991;59:12–9.
Clark LA, Watson D. Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. J Abnorm Psychol. 1991;100(3):316–36.
Leibenluft E, Stoddard J. The developmental psychopathology of irritability. Dev Psychopathol. 2013;25(4 Pt 2):1473–87.
Jager J, Putnick DL, Bornstein MH. II. More than just convenient: the scientific merits of homogeneous convenience samples. Monogr Soc Res Child Dev. 2017;82(2):13–30.
Byrne BM, Shavelson RJ, Muthén B. Testing for the equivalence of factor covariance and mean structures: the issue of partial measurement invariance. Psychol Bull. 1989;105(3):456–66.
Copeland EP, Hess RS. Differences in young adolescents' coping strategies based on gender and ethnicity. J Early Adolesc. 1995;15(2):203–19.
Suárez-Alvarez J, Pedrosa I, Lozano LM, García-Cueto E, Cuesta M, Muñiz J. Using reversed items in Likert scales: a questionable practice. Psicothema. 2018;30(2):149–58.
Marsh HW. Negative item bias in ratings scales for preadolescent children: a cognitive-developmental phenomenon. Dev Psychol. 1986;22(1):37–49.
Marsh HW. Positive and negative global self-esteem: a substantively meaningful distinction or artifactors? J Pers Soc Psychol. 1996;70(4):810–9.
Connell J, Barkham M, Stiles WB, Twigg E, Singleton N, Evans O, et al. Distribution of CORE-OM scores in a general population, clinical cut-off points and comparison with the CIS-R. Br J Psychiatry. 2007;190:69–74.
Van Sonderen E, Sanderman R, Coyne JC. Ineffectiveness of reverse wording of questionnaire items: Let’s learn from cows in the rain. PLoS ONE. 2013;8(7):e68967.
Solem, K. M., & Moen, C. M. (2015). Validation of the Norwegian version of the 10-item version of clinical outcomes in routine evaluations outcome measure (CORE-10) in a Norwegian adolescent population (aged 14–18) (Master's thesis, The Arctic University of Norway).
We would like to thank the clinicians and administrative staff management. We want to express our deep gratitude to all the participants.
The study was financed from the Northern Norway Regional Health Authority, through project number: PFP1110–13, PFP1112–13 and HNF1383–17, The pilot project received financial support from The Regional Centre for Child and Youth Mental Health and Child Welfare-North. The funding body had no role in designing the study or collection, analysis, and interpretation of data or in writing the manuscript.
Ethics approval and consent to participate
The study was performed in compliance with the Helsinki Declaration for research on humans and was approved by the Regional Committees for Medical and Health Research Ethics (REC North). Reference number 2011/1937. All participants participated and consented according to the regulations in the research project, also with written parental consent for those under age 16 (REC North, Reference number 2011/1937).
Consent for publication
Consent to publish was given from every participant and parents when warranted according with the Helsinki Declaration for research on humans and was approved by the REC North (Reference number 2011/1937).
The authors declare that they have no conflicts of interest.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Lorentzen, V., Handegård, B.H., Moen, C.M. et al. CORE-OM as a routine outcome measure for adolescents with emotional disorders: factor structure and psychometric properties. BMC Psychol 8, 86 (2020). https://doi.org/10.1186/s40359-020-00459-5

domain: literature


text:
The Santa Barbara Airport has erected a memorial site at Vista Point near the long-term parking Lot to commemorate certain World War II veterans. The memorial will be dedicated at 2 p.m. Thursday.
The memorial is a black granite obelisk bearing the names of local aviators that perished during WWII and the Marine squadrons that trained at the airport during the war. Situated in a reflective setting with slate walkways, olive trees, benches and interpretive signage, the memorial overlooks the east end of the airfield.
The program for the dedication event includes a Marine Corps Color Guard, a proclamation presentation by Mayor Marty Blum, the laying of wreaths, a speech by Brig. Gen. Frederick Lopez and a reading of the local aviator names by local high school student body presidents. A fly-by of a FUCorsair and T28 aircraft are expected, as well as a 21-gun salute.
The Santa Barbara Airport was quickly transformed in 1942 by the U.S. government from a sleepy local airport to a Marine Corps Air Station to support national defense. The Marines constructed 103 buildings and installed about 5.5 million square feet of pavement on the site, which included the present day airport and much of the land that is now UCSB.
“As the airport redevelops in the future, some of the street names bearing the local aviators’ names may be decommissioned, and the recognition associated with the street names lost,” airport Director Karen Ramsdell said. “The memorial will help ensure that these individuals continue to be honored and remembered for their sacrifice.”
— Terri Gibson represents the Santa Barbara Airport.

domain: history


text:
From Our Editors
Find the flavor that satisfies your sweet tooth at Simply Divine Cakes, a lovely ice cream shop in the Roanoke Rapids region of Roanoke Rapids.
At Simply Divine Cakes, you can safely park just around the corner.
You can fill up on Simply Divine Cakes' delicious fare without spending an arm and a leg ? in fact, typical items there run under $15. For innovative and creamy ice cream, look no further than the highly-rated Simply Divine Cakes.

domain: food


text:
The Stockholm Major (DreamLeague S11) open qualifiers are kicking off today
The Stockholm Major (DreamLeague S11) open qualifiers are kicking off today ⚡⚡⚡ Esports and gaming news, analytics, reviews on WePlay! The latest news on WePlay!
The DreamLeague Season 11 (aka the Stockholm Major) open qualifiers kick off today, and many teams barely formed rosters to be able to start to play. Interestingly enough, Dendi turned up in one of those teams though he needed to drastically change the place of residence and move to Malaysia.
Vanskor recently announced the stack of his own called Old but Gold. Here is the roster:
Each player is an experienced Dota 2 athlete with a lot of wins under his belt.
The regional qualifiers to the Major are held in a single elimination bracket with Bo1s up to the quarterfinals. Quarterfinals, semifinals and the final series are held in best of 3 series. The second round of open qualifiers will be taking place on January 26-27. Two teams from open qualifier are seeded to the closed qualifiers that kick off on February 1.
Many of the teams who have seeds reserved in the closed qualifiers, are in China right now, playing in the final rounds of the Chongqing Major.

domain: game


text:
The LSU AgCenter has announced another Louisiana Super Plant called Fireworks, a red-foliaged variety of purple fountain grass or pennisetum.
For many years, gardeners in Louisiana grew purple fountain grass. Now, new and improved fountain grasses are on the market, says LSU AgCenter horticulturist Allen Owings.
These are generally annuals in Louisiana. In warmer winters, however, you can have fountain grass return and be in perennial in the warmer locations of south Louisiana.
“The uniqueness of foliage on Fireworks, the low maintenance of this great ornamental grass and its spring-through-fall exceptional landscape performance make this plant a logical Louisiana Super Plant selection,” Owings says.
The foliage is dominantly red with white and green streaking.
Planted in full sun, Fireworks performs best in a raised bed with good drainage because most ornamental grasses don’t like standing water or waterlogged soils. Plants are very-drought tolerant, and hot weather is no problem for this Gulf Coast-adapted plant. Fireworks will grow to 48 inches tall by early fall with a spread of 30-36 inches. The attractive flower plumes are pale reddish purple and begin appearing by early summer and last until the first killing frost. This feature gives a nice vertical element to a landscape bed and adds height to a perennial or annual flower bed.
Fireworks has no insect or disease problems, and irrigation requirements are minimal.
I have not been very successful with tomatoes the past few years. What varieties do you recommend for planting in spring? Summer? Pat
Tribeca and Tribute are the top picks for spring tomatoes, with Amelia in second place. For summer, try planting heat-tolerant varieties such as Bella Rosa. These varieties may not produce really large tomatoes, but they produce a lot of medium-sized fruit. Heat-tolerant tomatoes are usually planted in June and will start to produce around August. Many cherry tomato varieties, such as Sun Gold and Sweet Cherry 100, will produce throughout the hotter parts of the year. Tribute and Tribeca are determinate varieties so they will stop producing at the end of their season, around June or so. Most cherry tomato varieties are indeterminate and will slow down production in the hotter parts of the year. — LSU AgCenter horticulturist Bobby Williams
Got a gardening question? Write to GardenNews@agcenter.lsu.edu.

domain: agronomy


A heat dome settled over the Central and Eastern US this week, potentially causing three deaths.
The heat closed schools and killed roughly 2,000 cattle. It's expected to continue next week.
Forecasters expect this summer to feature above-average temperatures for nearly the entire US.
It's been a hot week for millions of people across the US, and it's not over yet.
A heat wave has shattered daily temperature records across the Southwest, Central Plains, and Midwest this week. More than 100 million people in the US have been under some type of heat alert and advised to stay indoors.
Two people died in the Milwaukee area amid the extreme temperatures — a 39-year-old woman found in her home and an 89-year-old man who collapsed in his yard. The medical examiner's office said they were "probable" heat deaths, according to NBC News. Another man, 67, was found dead in California's Death Valley National Park, after he ran out of gas and walked through the heat.
Tens of thousands of people faced power outages. School districts in Michigan cancelled classes, and public schools in Pittsburgh, Pennsylvania, switched to half days to avoid the hottest hours, ABC News reported. In Odessa, Texas, a main water line broke, leaving residents to weather the heat without running water for more than 48 hours, The Texas Tribune reported.
In Kansas, an estimated 2,000 cattle died from heat stress as of Tuesday, according to Reuters.
"It's really a combination of the heat and the humidity which causes some of these impacts," Marc Chenard, a meteorologist with the National Weather Service, told Insider. "It really depends on how used to that type of weather these areas are, and also the time of year. So for some parts of the country, it might be a little bit early for some of this heat and humidity."
Humidity can make extreme temperatures feel even hotter, since it hinders the cooling process of sweat evaporating off people's skin. That's why humidity can push the heat index 10-15 degrees higher than the actual temperature.
Milwaukee's heat index hit a record June high of 109 degrees Fahrenheit on Tuesday. Las Vegas, too, reported 109 degrees. North Platte, Nebraska, snagged its own June record of 108 degrees. Phoenix, Arizona, rose even further to 114 degrees. Death Valley topped them all at 123 degrees.
The heat will likely continue into next week for many parts of the US, according to forecasts from the Climate Prediction Center, which is operated by NWS and the National Oceanic and Atmospheric Administration. The below map shows the center's projections.
"The prolonged nature of the well-above-normal temperatures and excessive heat has been impressive for early to mid June," Chenard said.
The Climate Prediction Center also produces a three-month outlook for temperatures nationwide. That forecast projects a summer of above-average heat across the entire US, with the exception of two small pockets in the north.
"I don't think we're going to have record temperatures continue every day or every week through the summer. But I think what this suggests is that the conditions will be favorable to see at least rounds of well-above-normal temperatures at times through the summer," Chenard said.
Heat waves are growing more common, severe, and lengthy as global temperatures rise. The 2018 National Climate Assessment found that the frequency of heat waves has tripled since the 1960s, and that the average heat-wave season has increased by 45 days.
This month's extreme temperatures came from a "heat dome" — a ridge of high pressure in the upper and middle layers of the atmosphere, trapping heat beneath it. The dome started in the Southwest and then parked itself over the Central and Eastern US.
"In this case, it's just persisted a long time," Chenard said, adding, "We just have this bubble of heat that's been over the central part of the country."
In Chicago, the heat wave arrived alongside hurricane-force winds and a rare instance of a circulation system threatening to become a tornado over the city. Two large tornadoes ripped through central Wisconsin this week, according to the La Crosse Tribune.
It's not clear whether the twisters were directly related to the heat wave, but Chenard said that storms typically brew around the fringes of heat domes, where they interact with other weather systems.
"It is common on the edges of these domes to get rounds of thunderstorms of varying intensity. They don't always have tornadoes," he said.


text:
Are you sick of seeing bumpy, orange-peel-like dimples on your body? Those lumps and bumps on your skin are likely cellulite, which unfortunately for you has a habit of being rather difficult to get rid of! Cellulite is fat cells stored between the connective tissue that is pushed towards the skin, creating that bumpy appearance we all loathe.
Although cellulite is technically fat, that doesn’t mean that fat is the only issue when trying the banish the bumps. Water retention, weak connective tissue, and poor skin tone can all contribute to how severe your cellulite looks. Despite keeping your calories low and exercising, it still might not be enough to move the cellulite. Luckily for you, we’ve found 10 foods that fight cellulite! So hop abroad the anti cellulite train, it’s time to get rid of those lumps and bumps once and for all!
When you think of anti cellulite superfoods, seaweed should be high up on your list! This plant is packed with a variety of minerals that are great for your body, including iodine. This mineral is vital for regulating your metabolism and keeping your body in check, as it stimulates your thyroid.
As well as smelling and tasting delicious, watermelon is a great fruit to help get rid of pesky cellulite. Watermelon holds a particularly potent antioxidant called lycopene. This is important for your anti cellulite efforts as it helps to fight against enzymes that destroy your body’s collagen. If you’re not familiar with collagen, it’s what keeps our skin firm, smooth, and strong – so we need as much of it as possible if we want to fight the lumps!
The appearance of your cellulite can highly depend on how bloated you are. If your body is retaining too much water, it will store the excess fluid in your fat cells – which can actually make your cellulite seem a lot more pronounced than it actually is. Artichoke, aside from being high in antioxidants, has a natural diuretic effect. This helps reduce bloat and water retention, which should take some stress off your connective tissue too!
Flaxseeds are a great source of essential fatty acids, which are excellent for the skin. Don’t be scared off by the sound of ‘fat’ in their name, as flaxseeds can actually help minimize the amount of fat our bodies store. Flaxseeds contain phytoestrogens, which help to regulate the hormones in the body, making sure they are correctly balanced – this is very important since excess estrogen can increase fluid retention and even promote fat storage!
Not a fan of garlic? You will be soon! Garlic is one of the top foods that fight cellulite, as it has so many benefits. It can relax blood vessels, increasing blood flow and in turn keeping your skin healthy. The vegetable is also an excellent source of sulfur, which is essential for our body’s collagen production. Remember, healthy circulation and lots of collagen equals smooth and supple skin! We’d much rather have to pop a breath mint or two than be stuck with cellulite, that’s for sure!
6. Dark chocolate
If you needed an excuse to eat chocolate, here it is! Cocoa has actually been proven to support the cardiovascular system, which means a healthier and stronger blood flow for your body. Now, don’t be grabbing any old chocolate you can get your hands on – it doesn’t quite work like that. If you want to see some proper anti cellulite effects, it has to be dark chocolate, as it contains the highest amount of cocoa and the least amount of dairy and sugar.
If you want to get rid of cellulite, you need to rid your body of any inflammation. Grapefruits are natural anti-inflammatory foods that can fight cellulite and its appearance by flushing out any unwanted fluid and toxins in the body that could be adding to your bumps. Pink and red grapefruits are rich in lycopene, too – this antioxidant can correct cell imbalances that lead to cellulite, so you can keep the bumps and lumps gone for good!
Another cellulite-fighting anti-inflammatory food is salmon. It contains omega-3 fatty acids – don’t worry, these are healthy fats! These fatty acids are packed with nutrients that can hydrate your skin and help to reduce skin cancer. Any fatty fish filled with omega-3 such as tuna, mackerel, and trout, are also great foods that fight cellulite.
9. Green tea
If you’re looking for more than just foods that fight cellulite, green tea could be for you! This warm beverage is well known for its health benefits and is a key ingredient in many weight loss tea detoxes. Green tea is a refreshing way to speed up your metabolism, and aid in fat absorption and glucose regulation.
Turmeric is an anti cellulite holy grail. It’s an antioxidant, which is great for fighting off free radicals that can harm your body’s cells. If you’re prone to bloating, turmeric can reduce swelling and aid in flushing out any toxins that have been trapped in the body due to water retention. The herb boosts circulation, too, and so boosts our collagen levels!
Enhance your results with the Bye Bye Cellulite Kit
Foods that fight cellulite are a great first step, but there’s more that needs to be done to get rid of cellulite permanently!
Along with a healthy diet of cellulite-busting superfoods, you need to incorporate some exercise into your lifestyle, too. Workouts such as HIIT and general cardio fitness are great for burning fat, couple this with some toning exercises for your trouble areas (like your underarms and butt) and you could be well on your way to ditching the dimples!
The final step is to address the skin itself. To get maximum results from your new diet and exercise, you need to take proper care of your skin with the Bye Bye Cellulite Kit. This kit contains Cheeky Cups cellulite cups to smooth connective tissue. Plus Contour Sleek firming body oil to detox skin and promote firmer, smoother skin.

domain: biology


The Department of Mines, Industry Regulation and Safety has issued a reminder on guarding against the effects of extreme temperatures on WA mine sites and remote areas.
DMIRS director Andrew Chaplyn said the extremes of Western Australia’s climate means that heat stress is a significant risk that needs to be managed across the State’s mining and exploration operations.
“Supervisors and workers need to understand the risks and symptoms of heat stress. Workers should report any signs of heat stress to a supervisor,” Mr. Chaplyn said.
“Heat stroke can cause permanent damage to the brain and other vital organs, and can even result in death.
“It is critical that urgent medical treatment is sought for anyone suspected of suffering heat-related illness.”
Some of the key risk factors for workers are:
- Lack of acclimatisation
- Low level of physical fitness
- Medical conditions (diabetes, cardiovascular disease, gastroenteritis)
- Some medications
- Drug and alcohol use
- Age (especially workers older than 60).
“Added to this danger is the fact that many mining operations are in remote areas in Western Australia where medical assistance is not easily available,” Mr. Chaplyn said.
“This is especially the case for exploration work and travel between mine sites.”


text:
Permanent Visiting Fellow
Jeffery Kaplan is the author or editor of 20 books and over 90 articles and anthology chapters on religious violence, millenarianism, terrorism and oppositional religious movements. His most recent monograph is Apocalypse, Revolution and Terrorism: From the Sicari to the American Revolt Against the Modern World, which was published by Routledge in 2019. He has also published the career retrospective Radical Religion and Violence: Theory and Case Studies, as the first volume in the Routledge Distinguished Author series. He is Book Review Editor for Terrorism and Political Violence. He is currently a Visiting Professor at the Doctoral School on Safety and Security Sciences, Óbudai University and a Visiting Fellow at the Danube Institute in Budapest.
Visiting Fellow, April 2021.
Rod Dreher is a writer of non-fiction books and is senior editor at The American Conservative magazine. His writing focuses on the intersections among religion, culture, and politics. Dreher has been a columnist for the New York Post, the Dallas Morning News, and National Review, among other publications. His books include two New York Times bestsellers The Benedict Option (2017) and The Little Way of Ruthie Leming (2013), as well as volumes on topics as diverse as Dante Alighieri, and traditional conservatism in the modern world. He lives in his native south Louisiana with his wife and children, and is an Orthodox Christian.
His latest book, New York Times bestseller Live Not By Lies: A Manuel for Christian Dissidents, will be published in Hungarian during his stay.
Visiting Fellow, November 2020.
Douglas Murray is a British author and journalist. Contributor and Social Editor at the Spectator magazine. He has also written regularly for numerous other outlets including, The Wall Street Journal, The Times, The Sun, The Evening Standard, and the New Criterion. He is a regular contributor to National Review and has been a columnist for Standpoint magazine since its founding. His first book came out in 2000 when he was an undergraduate at Oxford. Since then he has published three more full-length books — on politics history and current affairs — as well as shorter works on free speech and defence. Including, The Strange Death of Europe and The Madness of Crowds. A prolific debater, Murray has spoken on a variety of prominent platforms including at the British and European Parliaments and the White House.
Visiting Fellow, October 2020.
Charles Crawford retired from the Foreign and Commonwealth Office at the end of 2007 after nearly three decades in the UK’s Diplomatic Service. Charles Crawford has considerable senior operational experience in the diplomatic and policy aspects of the post-Cold War transition process in Russia/CIS and Poland as well as the complexities of the former Yugoslavia. He is now pursuing a private consultancy career, focusing on personal communication technique and negotiation/mediation.


text:
Cheap flights Lombok (LOP) to Denpasar Bali (DPS)
Quick info Lombok to Denpasar Bali
Best priceTHB 428The cheapest price for a flight on this route is THB 428
Latest Flight22:05The latest direct flight from Lombok to Denpasar Bali is at 22:05
Cheapest monthNovemberThe best month on the route Lombok to Denpasar Bali is November
Looking for a cheap flight from Lombok to Denpasar Bali (LOP-DPS)? Flights fares for Lombok to Denpasar Bali start at THB 428. Find the best and cheapest flights on this route and other relevant information.
Before you book a flight you can use Utiket to find the cheapest flights from Lombok to Denpasar Bali for Lion Air, Batik Air, Citilink, Wings Air, Garuda Indonesia, Sriwijaya Air. All flight data are real-time and accurate. Utiket finds all the cheapest flights from Lombok to Denpasar Bali.
Utiket Flight Analytics for Lombok - Denpasar BaliAverage prices, based on 2839 datapoints.
Best month to fly
The best month to fly between Lombok and Denpasar Bali is November and the most expensive month to fly is June.
Best day to fly
The best day to fly is Tuesday and if you can best to avoid Sunday, as prices are then on average 37.95% higher than on Tuesday.
Which airline is the cheapest?
The cheapest airline on the route Lombok to Denpasar Bali is Indonesia AirAsia. They are 61.18% cheaper than Garuda Indonesia.
About Lombok Lombok International Airport
With the landing on October 1, 2011 of a Garuda Boeing 737-800 ER on the 2750-meter runway the new Lombok International Airport (Bandara Internasional Lombok, BIL), which will replace the old Mataram Selaparang Airport, was officially opened.
Find cheap flights to Lombok or read more about
Lombok International Airport.
About Denpasar Bali Ngurah Rai International Airport
Bali's airport Ngurah Rai is named after I Gusti Ngurah Rai, an Indonesian National Hero who died in a puputan (fight to the death) against the Dutch at Marga during the Indonesian Revolution in 1946. The airport has undergone some major renovations lately significantly improving the congestion and facilities.
Find cheap flights to Denpasar Bali or read more about
Ngurah Rai International Airport.
Which airlines have direct flights between Lombok - Denpasar Bali?
See all flight departure times Lombok to Denpasar Bali

domain: geography


text:
Lisbon man charged with drug possession
LISBON — Robert J. Davis III, 33, West Washington Street, Lisbon, was served a secret indictment for possession of drugs for allegedly having hydrocodone on July 2, 2017. The indictment was issued by the Columbiana County Common Pleas Court grand jury in August.
Anthony C. Smith, 20, South Howard Street, Salem, was served a secret indictment for possession of drugs for allegedly having less than five grams of cocaine on March 21, 2018. The indictment was issued on August.

domain: law


As a member of NSTXL, STS has access to two additional avenues to provide access for their customers – the S2MARTS and TReX OTAs.
The Naval Surface Warfare Center (NSWC), Crane Division and the Department of Defense (DoD) created the Strategic and Spectrum Missions Advanced Resilient Trusted Systems (S2MARTS) OTA. The S2MARTS OTA (pronounced “SMARTS”) is designed to refine strategies, management planning activities, and implement integrated, complementary solutions that enable broader Department of Defense (DoD) access to commercial state-of-the-art EMS technologies, advanced microelectronics, radiation-hardened (RAD-HARD) and strategic missions hardware (HW).
The Training and Readiness Accelerator (TReX) expedites development, demonstration, and delivery of prototypes to increase Warfighter readiness. With a focus on modeling, simulation, and training, TReX provides the United States Government with an agile mechanism to iterate and refine critical technologies to keep pace with ongoing and emerging challenges. By actively incorporating structured operational user feedback, TReX will identify and develop innovative solutions to inform materiel procurement requirements and acquisition.


App Provides A Minute By Minute Weather Forecast
SkyMotion paves the way for reinventing weather forecasting.
The SkyMotion app updates the weather forecast every 5 minutes, providing accurate precipitation forecasts in a sleek and simplified interface. The app takes a step beyond traditional meteorological models and methods by focusing on a shorter time span, providing weather to the user's specific location (rather than a generalized area), and integrating image analysis.
Founded by André Leblanc, the Montreal-based company seeks to reinvent weather forecasting. In a statement by their founder he said that:


text:
In 2003, Linley was in the independent film When Zachary Beaver Came to Town and appeared in the movie Cheaper by the Dozen.
It’s not just her music that media focuses on rather even her love life is a topic of discussion.
The singer has been linked with numerous celebs and has been in a relationship with many Hollywood hunks.
So before disclosing Lovato’s relationship status in the year 2017 lets first check her dating history, which is quite interesting.
magazine, the singer opened up about her relationship with boyfriend, Wilmer Valerrama, and explained why the white men she's dated in the past don't measure up to Latino men when it comes to passion.
When it comes to Lovato's dating history, the "Stone Cold" singer has been linked to a string of white celebrities like DNCE frontman, Joe Jonas, Miley Cyrus' older brother Trace Cyrus, and former Disney star, Cody Linley.

domain: celebrity


text:
Podcast miniseries about the May 18 uprising in Gwangju, South Korea, in 1980 against the US-backed military dictatorship of Chun Doo Hwan. We speak with participants in the events as well as researcher Kap Su Seol.
Our podcast is brought to you by our patreon supporters. Our supporters fund our work, and in return get exclusive early access to podcast episodes, bonus episodes, free and discounted merchandise and other content. Join us or find out more at patreon.com/workingclasshistory
You can listen to our podcast on the below links, or on any major podcast app. Links to a few below.
- Part 1: Background, and the beginning of the revolt – currently available for early listening for our patreon supporters
- Parts 2 onwards: coming soon…
- E51: Jeon Tae-il and Lee So-sun – Episode about two important South Korean labour organisers, which contains background information to the political situation in the country in the run-up to the Gwangju uprising.
- Gwangju Diary: Beyond Death, Beyond the Darkness of the Age – Lee Jae-eui – The best history of the Gwangju uprising, translated by Kap Su Seol. Buy it here or read online here.
- Lee Jae-eui, trans Kap Su Seol, Gwangju Diary: Beyond Death, Beyond the Darkness of the Age (UCLA, 1999).
- Kim Dong Won et al, The May 18 Gwangju democratic uprising (May 18 History Compilation Committee of Gwangju, 2013).
- Kim Yoo-chul, “Defense chief apologizes over rapes during 1980 Gwangju crackdown,” Korea Times, November 7, 2018, accessed June 29, 2021, https://www.koreatimes.co.kr/www/nation/2018/11/356_258314.html.
- Michael Newton, Famous Assassinations in World History (ABC-CLIO, 2014).
- Thanks to our patreon supporters for making this podcast possible. Special thanks to Conor Canatsey, Shae, James and Ariel Gioia.
- Thanks also to the following people and groups for additional assistance with these episodes: Michael Choi, Rachel Min Park, Heung Coalition and Angela Lee.
- Photograph used in episode graphic courtesy Wikipedia Commons. Other photographs courtesy David Dolinger.
- Music used in this episode under fair use was “Marching For the Beloved” by Baek Ki-wan, Hwang Seok-young and Kim Jong-ryul.
- This episode was edited by Jesse French.

domain: library


text:
Lesson 1 (from Chapter 1)
Wool, by Hugh Howey, is the first book in a dystopian science-fiction series (the Wool Series) set in a post-apocalyptic underground world. The novel begins in Chapter 1 with the lines, “The children were playing while Holston climbed to his death; he could hear them squealing as only happy children do.” In this lesson, students will conduct research on author Hugh Howey and will define, analyze, and discuss the setting and tone established in Chapter 1 of Wool.
Research Activity: Conduct research on author Hugh Howey and the publication of Wool and the other novels within the Wool Series. How many literary works has Howey written? What genre is Wool?
Group Assignment: Assign students to groups of 3-4 each. As a group, read Chapter 1 and develop a presentation that illustrates and analyzes the setting of the story. When does this story take place? What clues in the...
This section contains 9,369 words
(approx. 32 pages at 300 words per page)


environmental protection agency
Explore all Articles
BY LIZ HANSON Defining the mission of the Environmental Protection Agency (EPA) seems like it should be fairly straightforward. It’s right there in the name: an agency to protect the environment. Of course, in a world of complex costs and benefits, and increasingly intense partisan rhetoric, nothing is quite so simple. Yet, I was still […]
BY MICHAEL ALTER Pope Francis was resolute in his opinion about the toll climate change is exacting on the planet when he released his encyclical on Thursday, June 18. Francis laid out his feelings quite bluntly: “the Earth, our home, is beginning to look more and more like an immense pile of filth.” While this […]
Call for Submissions
Join the HKS Student Policy Review—
to research, write, and learn about policy in a new way. We offer Harvard students an opportunity to engage with the most important policy issues of our time, across a whole range of topics and regions.


Chart current as of July 2020
More than 80 models of plug-in hybrid (PHEV), fully electric (BEV), and fuel cell electric vehicles (FCEV) are available now to consumers — and more are on the way. Automakers are providing our customers with record-breaking choice in energy-efficient models, while also providing even safer, more environmentally friendly, affordable vehicles. The automotive industry is investing more than $330 billion by 2025 in its commitment to vehicle electrification. Electric vehicles (EVs) are an important part of our mission, both in the U.S. and around the world.
Chart current as of July 2020
Consumers have more choice than ever before in electric vehicles (EVs). As recently as 2012, there were only a handful of EVs on sale. Today, there are more than 90 — including 47 battery electric, 42 plug-in hybrid electric vehicles, and 2 fuel cell vehicles — with more models in development. Today, consumers can buy EVs of all shapes and sizes — small cars, large cars, SUVs and minivans, in 2WD or AWD, with shorter and longer ranges, from economy vehicles to luxury models and everything in between. Yet, more work is needed to inform consumers about the benefits of going electric. Automakers and other stakeholders are spearheading consumer awareness campaigns, including Veloz in California and the Drive Change. Drive Electric. in northeastern states.
There are two types of plug-in electric vehicles on sale today.
Battery Electric Vehicles: All-electric cars powered solely by a battery on board the vehicle. Range varies from 85 miles to 250 miles. “Refueling” times to charge the battery depend on the level of charging used – typically, 30 minutes to 1 hour for fast charging and 4 to 6 hours using Level 2 charging (e.g., home charger).
Plug-in Hybrid Electric Vehicles: Vehicles powered by a combination of a battery on board the vehicles and a gasoline engine. Battery range varies between 15 and 50 miles, at which point the gasoline engine seamlessly operates to drive another 350-615 miles. Refueling time for the gasoline engine is 5 minutes (owners can drive a PHEVs indefinitely on gas only), and “refueling” time to charge the battery is typically 2-6 hours with Level 2 charging (e.g., home charger).
Fuel cell electric vehicles (FCEVs:) All-electric cars powered by the conversion of hydrogen into electricity. Range of FCEVs is typically 350 to over 400 miles. Refueling times are about 5 minutes.
ZEV Mandate States
Special provisions in the Clean Air Act allow states to either follow the federal requirements or adopt California’s vehicle emission regulations. Currently, ten states are following California and implementing the Zero Emission Vehicle (ZEV) regulations, including the requirements that about 7 to 10% of new vehicles must be electric vehicles in 2025. These states include Colorado, Connecticut, Maine, Maryland, Massachusetts, New Jersey, New York, Oregon, Rhode Island and Vermont.
ZEV purchases will need to increase dramatically in order to meet targets supported by California and ten other states with the ZEV mandate.
In 2021, ZEV sales represented just over 4% of total sales nationwide, or about 612,000 vehicles out of 14.9 million new vehicles sold. By 2025, sales of ZEVs are required to be about 7 to 10% of total sales.
Fleets: States Should Buy More EVs
Governments at all levels buy vehicles for official purposes, and these government fleets represent a potential source of ZEV sales. Governments can lead by example by increasing the number of all types of electric vehicles in their fleets.
From 2013 to 2017, government entities in California registered almost 90,000 new vehicles. Only 3.2% (2,885) were plug-in hybrids, fully electric vehicles or fuel cell electric vehicles. In 2017, the vast majority of new vehicles (96%) purchased by government entities in California remained traditional gas-powered vehicles.
Nationwide, new vehicle sales of electric vehicles were about 2% in 2019. About half of those sales were concentrated in California. Most of sales outside of California are in states with incentives.
...have something attractive for everyone:
...are also a great all-electric option, with:
...can be a great option for an EV, if you drive longer distances and hydrogen refueling stations are not available:


Maxform Vacuum Formed Shapes
MaxForm™ Shapes are processed from alumina and silica blends for applications with temperatures up to 3000°F (1650°C).
MaxForm™ Shapes are vacuum formed products that are made to resist high velocities. These products are ideal for furnace linings, boiler duct and stack linings due to their low thermal conductivity, low heat loss and storage.
MaxForm™ Shapes are available with special densities upon request and are available in a wide variety of shape configurations.
- Low Thermal Conductivity
- Low Heat Loss and Storage
- Resistance to High Velocity
- Easy to Install
- Resistant to Non-Ferrous Metals
- Contains No Asbestos
- Refractory Lining for Industrial Furnaces
- Combustion Chamber Liner, Boilers and Heaters
- Expansion Joints
- Board over Blanket Linings