Rapee Cover Letter

© Ugur Akinci

Transmittal letters (a.k.a. cover letters) are so universal. God knows how many millions of transmittal letters are written and sent every day.

Every proposal, application, resume, and document package needs a transmittal letter. It’s a must.

Yet most people do not feel comfortable in whipping up a cover letter on the spot. There is usually a resistance in writing such business letters since people usually don’t know what to say in it. They are concerned that they’ll end up saying either too little or too much and perhaps even damage the business relationship, all because of a one-page letter.

Here are some guidelines to make your job easier.

Here are the main parts of a transmittal letter:

Heading (Your Address)
Recipient Address
Body (which includes 4 sub-parts)
1. Reason for the letter
2. Statement of facts
3. Request or follow-up
4. Contact information

(Source: Writing and Speaking for Technical Professionals)

Here is a sample letter:


ACME Corporation
123 Broad Street
Seattle, WA 87778

September 22, 2010

Rahul Bagrawani
Project Manager
Starcast Software
1167 Montezuma Drive
Arlington, VA 23312

Dear Mr. Bagrawani,

As ACME Corporation we are pleased submit for your consideration the enclosed proposal in response to your RFP #234-RT to upgrade your client-server architecture. Our proposal offers the latest technology to upgrade your legacy systems with ample room to accommodate any cloud-computing applications as well.

We look forward to hearing from you and answering any questions that you might have. Please feel free to contact me at (934) 555-1234 ext. 55 or by email at jwilliams@123.com


[Your signature]

Johannesen Williams
Vice President, Marketing


In the aftermath of exposure to traumatic events, about 70% of children develop symptoms of Post-Traumatic Stress Disorder (PTSD) within the first month after the incident (Aaron, Zaglul & Emery, 1999) and almost 20–30% will meet full diagnostic criteria for PTSD within the first 12 months (Dyregrov & Yule, 2006; Schnurr et al., 2007). When children with PTSD are left untreated, the disorder can persist for years limiting their psychosocial functionality and increasing risk for other disorders (Bolton et al., 2000; Weber et al., 2008; Yule et al., 2000). Trauma can also produce marked neurobiological consequences and impaired cognitive development that can reduce academic and social performance in a young person’s life (Teicher et al., 2003; Yasik et al., 2007). In the long run, the impact on individual levels of productivity across the life-span increases burden on the whole society. To help reduce this long-term impact, early identification of post-traumatic stress reactions is very important (Cohen et al., 2010).

Unfortunately traumatic events are more common in the lives of children from developing or low and middle income countries than those of developed countries creating a greater vulnerability to mental health problems (Matzopoulos et al., 2008; Patel & Kleinman, 2003; Whetten et al., 2011). Despite the frequency of traumatic events in developing countries, a lack of standard assessment and screening tools to identify young people suffering distress is a common problem that limits the efficiency of service delivery. Direct interviews and more importantly, structured diagnostic interviews require resources that are simply not available in most developing countries, especially following large-scale traumas (e.g., Ahmed et al., 2011; Rousham, 1996). Therefore, increased availability of free and well validated measures that have been translated and evaluated in developing countries, is vitally important.

Bangladesh is one developing country where children’s lives are continually affected by a variety of traumatic events. The range of traumatic events includes natural traumas, accidents, and man-made traumas. Bangladesh is well known to the rest of the world for its frequent natural disasters and has been identified as the country with the highest number of natural disasters in the world (Government of the People’s Republic of Bangladesh, 2008). Young people are typically most severely affected by natural disasters through death, disability, loss of family, and displacement. A large number of subsequent problems add to the vulnerability of children including, neglect, abuse, human trafficking, or loss of education (UNICEF, 2008). In addition to frequent natural traumas, large numbers of children in Bangladesh are traumatised each year due to a variety of accidents (Linnan et al., 2007). More than 82 children die every day in Bangladesh as a result of unintentional traumatic injury, one of the highest rates in the world (Rahman, 2005). Many young people also face a range of man-made traumatic events, including trafficking (Ali, 2005), rape (Al-Azad et al., 2012), acid attack (Zafreen et al., 2010) and many other serious forms of violence (UNICEF, 2012).

Despite mounting recognition of the quantity of traumatic events in the lives of young Bangladeshi people which point to the need for both physical and mental health support, there are few reliable data in the country regarding childhood post-traumatic stress reactions. In one large-scale survey, children showed higher levels of aggression and enuresis following a major flood compared to levels before the flood (Durkin et al., 1993). Similarly, high levels of traumatic reactions were reported following a tornado (13 May 1996) where among 150 victims (both adults and children), 66% were found to be psychologically traumatized (Choudhury, Quraishi & Haque, 2006).

Given the high frequency of trauma in the country and the particular vulnerability of children, it is highly likely that a significant proportion of Bangladeshi children will suffer post-traumatic stress reactions. Yet no formal reports are currently available that quantify levels of traumas in the country. This gap in knowledge partly reflects the decreased importance given by policy makers and the public to mental health issues, combined with a lack of resources to address these problems. Being able to quantify psychological reactions to trauma through the use of brief, valid and easily administered self-report measures would assist in redressing this situation (Ohan, Myers & Collett, 2002). Availability of such measures will not only be useful for epidemiological surveys, but would also be of value for clinical practice or research.

Well-developed self-report screening tools to assess children’s psychological symptoms require several key characteristics. Such tools need to be brief to ensure that they can be quickly completed with minimum disruption to the individual (Brewin et al., 2002; Stallard, Velleman & Baldwin, 1999) and items need to be easily understood by children (Yule, 1992). Within communities with few resources, it is also important that instruments are easily administered and able to be scored by non-professionals (Brewin et al., 2002). Several widely used measures of post-trauma reactions among children fail to meet all of these criteria. Among the measures of childhood PTSD, the Children’s Revised Impact of Events Scale (CRIES; Children and War Foundation, 2005) fulfils the criteria for good screening instruments and has been used across a large number of countries and cultures (both Western and Eastern). This measure has been translated into more than 15 languages and has been used in a number of countries following various large and small scale disasters. Examples include its use with children and adolescents affected by war in Bosnia-Hercegovina (Smith et al., 2001), earthquakes in Greece (Giannopoulou et al., 2006b) and China (Zhao et al., 2009), tsunami in Sri-Lanka (Ketumarn et al., 2009), and also following road-traffic accidents or other emergency medical injuries in the UK (Perrin, Meiser-Stedman & Smith, 2005) and Australia (Kenardy, Spence & Macleod, 2006). The CRIES has shown good reliability, satisfactory face and construct validity, a stable factor structure, and has been used to screen large samples of at-risk children following a wide range of traumatic events (Smith et al., 2003). Particular advantages of the CRIES include its brevity, simple scoring that requires minimal training, clear adherence to PTSD diagnostic criteria in the DSM, and it can be used even with children as young as five (e.g., Malmquist, 1986). Above all, the CRIES is a free resource that is made available through the website of the Children and War Foundation, a Norwegian-based non-profit organisation.

Although the original 15-item CRIES (Malmquist, 1986; Yule & Williams, 1990) was designed to cover the three components of PTSD, intrusion, avoidance, and emotional numbing, confirmatory factor analyses failed to support a three-factor structure. Several studies found that most items loaded onto two factors (intrusion and avoidance), and several items did not load on either factor or on more than three factors (Dyregrov, Kuterovac & Barath, 1996; Sack et al., 1998; Yule, Bruggencate & Joseph, 1994). In response, Yule (1997) removed seven items from the original scale and developed a short, eight-item version, the CRIES-8 comprised of the two factors, intrusion and avoidance. Finally, to better reflect DSM-defined PTSD symptoms (American Psychological Association, 2000), five additional items were added to the CRIES-8 to represent the third cluster of PTSD symptoms, arousal (Perrin, Meiser-Stedman & Smith, 2005; Smith et al., 2003). These additional items completed the CRIES-13 and the three sub-scales were labelled Intrusion, Avoidance and Arousal (Children and War Foundation, 2005).

The factor structure of the CRIES-13 across several studies has been slightly inconsistent, variously showing a two-factor structure (intrusion and arousal vs avoidance) (Chen et al., 2012), three distinct but inter-correlated factors (intrusion, arousal and avoidance) (Zhang et al., 2011), and a three-factor structure loading onto a single higher order factor (intrusion, arousal, and avoidance loaded onto PTSD) (Giannopoulou et al., 2006b). Nonetheless, psychometric properties (for instance, reliability and validity, please see method for detail) for both the CRIES-8 and CRIES-13 have been solid.

Both versions of the CRIES have shown good utility when used as screening tools for children exposed to traumatic events (Dow et al., 2012; Perrin, Meiser-Stedman & Smith, 2005). A cut-off score of 17 on the CRIES-8 and a cut-off score of 30 on the CRIES-13 were found to produce the best balance between sensitivity (.94 and .91) and specificity (.59 and .65) to identify PTSD in a group of children referred for assessment, and sensitivity (1.0 and .86) and specificity (.71 and .73) to identify PTSD in a group of children assessed in a hospital accident and emergency department (Perrin, Meiser-Stedman & Smith, 2005).

Although symptoms of PTSD and post-traumatic reactions have been argued to be universally consistent (Giannopoulou et al., 2006b), it remains possible that different language and cultural groups will demonstrate differences in perceptions and reactions to a given event (e.g., Anthony & Michael, 2004). Given the importance of having a brief and inexpensive instrument to assess post-traumatic reactions among young people in Bangladesh, the present study aimed to establish the psychometric properties (that is, confirmatory factor analyses, internal consistency, reliability and validity) of the CRIES-8 and CRIES-13 in a large sample of children and adolescents from Bangladesh.



A total of 1,342 children and adolescents from a larger sample of 1,383 participants for a different study (F Deeba & RM Rapee, 2014, unpublished data) who reported on at least 90% of the items of the CRIES 13 were included in the current sample (Males = 467, 34.68% and Females = 875, 65.32%). Children were recruited from 10 schools (primary, secondary and high) and 39 social support centres for children with traumatic experiences, across rural and urban (slum and non-slum) areas from the six districts of Bangladesh. The social support services participating in the study comprised a broad group of organizations, both government and non-government that aimed to provide social welfare (for example, shelter, educational, health, legal and other support) for disadvantaged or vulnerable children in residential or non-residential forms. We provided detailed information about inclusion and exclusion criteria to social support staff and class teachers, before conducting any assessment session. Support staff and teachers then selected children for the assessment session based on this information if they believed that the child did not suffer psychosis or attention deficit hyperactivity disorders, and had no major vision, hearing or intellectual problems. Children from schools comprised a group of community children (N = 562, 41.88%) while those who were collected through support centres run by government and non-government organizations constituted an “at-risk” group (N = 780, 58.12%).

A wide variety of traumatic events were reported by children, including natural disasters (e.g., flood, cyclone, tornado, avalanches, arsenic exposure, suffering from terminal disease, and others), accidents (e.g., hit by a road transport vehicle, boat or launch accidents, train/plane accidents, building collapse, fire, fall from highs, drowning, explosions and others) and man-made traumas (e.g., hit by others, suffocated, attempt to kill, acid attack, bombing, verbal abuse, bullying (peers), threat to hurt, stalking, sexual abuse (penetrative and non-penetrative), trafficking, mugged/robbed, and others). The majority of children in both groups had experienced at least one trauma (see Table 1). The two sub-groups of the sample differed significantly on the number of traumatic events experienced, χ2(4, N = 1,342) = 27.37, p < .001. Over half of the children in at-risk group had 7 and more traumatic experience, whereas the community children were just under 40% of 7 and more traumatic events exposure (for more detail see, F Deeba & RM Rapee, 2014, unpublished data).

Children from the social support centres mostly lived in slum areas or shelter homes. Participation from children approached in social support centres (90%) was higher than among children from the community group (75%). The age range of the sample was 9–17 years (mean age = 12.3 years, SD = 2.12). There were 756 (56.34%) children aged 9–12 years and 586 (43.66%) adolescents aged 13–17 years. Demographic information about the two sub-samples is given in Table 1.

A subsample of 135 children (Males = 49, 40.83%) from four schools in Dhaka completed the same measures 3–4 weeks (average 3.5 weeks) following initial assessment. Their mean age was 12.92 years (SD = 1.96). Among them 120 children completed 90% of the total items and were included in the analysis.


Children’s Revised Impact of Events Scale-13 (CRIES-13)

As described above, the CRIES-13 and CRIES-8 (Children and War Foundation, 2005) share the same eight items that constitute two subscales, Intrusion and Avoidance, and the CRIES-13 includes an additional five items that constitutes a third sub-scale, Arousal. Items are scored on a non-linear scale as follows: 0 (not at all), 1 (rarely), 3 (sometimes) and 5 (often). Scores range from 0 to 40 for the CRIES-8 and 0 to 65 for the CRIES-13, and higher scores indicate more PTSD symptoms.

Internal consistencies range from .75 to .87 for the total CRIES-13, .75–.84 for the total CRIES-8 and for the three subscales; Intrusion: .70–.90; Avoidance: .62–.82 and Arousal .60–.74 (Dyregrov, Kuterovac & Barath, 1996; Giannopoulou et al., 2006a; Lau et al., 2013; Smith et al., 2003; van der Kooij et al., 2013; Yule, Bruggencate & Joseph, 1994; Zhang et al., 2011). Test retest reliability up to 7-day is good for the total CRIES-13 (rs = .76–.85) (Panter-Brick et al., 2011; Verlinden et al., 2014), and r = .75 for CRIES-8 (Verlinden et al., 2014). However, it is less acceptable for the subscales; Intrusion r = .58; Avoidance: r = .68 and Arousal: r = .53 (van der Kooij et al., 2013).

Validity for both the CRIES-8 and CRIES-13 has also proven satisfactory (Perrin, Meiser-Stedman & Smith, 2005). For instance, children experiencing symptoms of PTSD have been shown to score higher on the CRIES-8 than children without PTSD (Stallard, Velleman & Baldwin, 1999). Similarly, in a large sample of children affected by war (N = 2,976) in Bosnia-Hercegovina, scores on the CRIES-13 and all subscales showed small positive correlations (r = .05–.36) with self-reported level of traumatic event exposure, and depression (Smith et al., 2002) and also with ratings of children’s distress from parents and teachers and with mothers’ levels of trauma exposure and distress (Smith et al., 2001).

Spence Children’s Anxiety Scale-20 (SCAS-20)

SCAS-20 (SH Spence, pers. comm., 2010) is a simple, brief self-report questionnaire to assess symptoms of anxiety. The SCAS-20 is a short form of the more commonly used 38-item SCAS (Spence, 1998). Items are rated on a 4-point Likert-type scale as 0 (never), 1 (sometimes), 2 (often) and 3 (always) and summed to obtain a total score where higher scores indicate higher levels of anxiety. Items for the short version were selected from factor analyses of the full version (Spence, 1998; Spence, Barrett & Turner, 2003). Although the psychometric properties of the short version have not yet been published, an unpublished evaluation of the SCAS-20 demonstrated strong internal consistency of .89 (Coysh, 2011). The psychometric properties of the SCAS-20 among a group of Bangladeshi children and adolescents showed good internal consistency (Cronbach’s alpha .84) and satisfactory construct validity for the scale (F Deeba, RM Rapee & T Prvan, 2014, unpublished data).

Short Moods and Feelings Questionnaire (SMFQ)

SMFQ (Angold et al., 1995) was developed to identify DSM-IV-based signs and symptoms of depressive disorders in children and adolescents aged 6–17 years. The scale is scored on a 3-point Likert-type response scale 0 (Never); 1 (Sometimes true) and 2 (Always true). The total score is the sum of all items providing possible scores ranging from 0 to 26 with higher scores reflecting lower mood and risk of clinical level depression. The SMFQ has been shown to comprise a single factor and has good criterion-related validity and discriminant validity to identify clinical levels of depression in children and adolescents (Angold et al., 1995; Thapar & McGuffin, 1998). Cronbach’s alpha for the SMFQ has been reported ranging from .87 to .90 (Angold et al., 1995). For the Bangladeshi children and adolescents, Cronbach’s alpha was strong at .80 (F Deeba, RM Rapee & T Prvan, 2014, unpublished data).

Translation of measures

Standard guidelines accepted for the successful translation of instruments for research purposes (e.g., Brislin, 1986) were used. The bilingual investigator translated the English version of the CRIES to Bangla. Then another bilingual professional psychologist not associated with the measure translated it back from Bangla to English. Back translation was checked by the second author of the study, who is a native English speaker. Differences in the two versions were resolved by joint agreement of both translators.


Ethical issues in the study were reviewed and approval granted by the Macquarie University Human Research Ethics Committee (Ref no. 5201001017 dated 5/11/2010). Written permission was sought from every institution and organization where the study was to be conducted. Individual consent was collected for each child from their parents or caregivers and children provided assent, before all assessment tasks. Issues of voluntary participation, freedom to respond independently, confidentiality and seeking clarification during assessment were discussed with the children at the beginning of the assessment sessions. Assessments were conducted at a time decided by the organisation, in groups of up to 30 children unless children were aged less than 12 years or were illiterate. In such cases the maximum number of children in the assessment group was 10 and items were read aloud by the researcher (along with items for another study, see F Deeba & RM Rapee, 2014, unpublished data). A psychology post-graduate research student was recruited to assist the first author to conduct assessment sessions. The assistant was trained in administering the measures and the ethical issues involved with assessment. The test-retest reliability of the measure was checked after 3.5 weeks following the same procedure stated above with 120 school children from four schools in the capital city. For clarity, distributions of participants and samples sizes for particular analyses are shown in Fig. 1.

Statistical analysis

All analyses were conducted using SPSS V.21 and its extension AMOS V.21. Missing data were handled by the Person Mean Substitution method (PMS, Downey & King, 1998) due to the non-linear scoring of the items. Confirmatory Factor Analysis (CFA) with the 13-item CRIES compared three different measurement models based on previous studies (e.g., Giannopoulou et al., 2006b; Smith et al., 2003; Zhang et al., 2011). The models were: Model 1—single-factor (PTSD) model, Model 2—two inter-correlated latent factors, [(i) intrusion/arousal and (ii) avoidance], Model 3—three inter-correlated latent factors [(i) intrusion (ii) avoidance and (iii) arousal] and Model 4—three latent factors [(i) intrusion (ii) avoidance and (iii) arousal] loading onto a single higher-order factor (PTSD). We did not run a separate CFA for the CRIES-8 since the items and subscales are embedded in the CRIES-13.

Maximum Likelihood (ML; Byrne, 2010) tests were used on the whole sample (N = 1,342) for model identification, and then two separate multiple group confirmatory factor analyses (MCFA) were run on the best fitting model to evaluate model invariance between gender and age-groups (younger/older) by group affiliation (community and at-risk) following Byrne (2004). Standardized parameter estimates are reported. Model fit statistics in the present study were selected from suggestions by Jackson, Gillaspy & Purc-Stephenson (2009) and cut-offs for model fit indices were selected as per Kline (2005) and Worthington & Whittaker (2006) as best for clinical measures. These included the goodness-of-fit index (GFI), for which values greater than .90 are acceptable (Hu & Bentler, 1999), the comparative fit index (CFI), and the Tucker-Lewis index (TLI) where values equal to or greater than .90 are considered a good fit (Dumenci & Achenbach, 2008). To observe differences between observed and predicted covariances, the Root Mean Square Error of Approximation (RMSEA) was chosen. RMSEA values less than .06 (Hu & Bentler, 1999) or .08 (Dumenci & Achenbach, 2008) have been proposed as indicating a good–fitting model, though RMSEA values of .06–.08 are often reported as acceptable or reasonable rather than good (Kline, 2005; McDonald, 2002). To determine the optimal and most parsimonious model, the Akaike Information Criterion (AIC; Akaike, 1973) and Bayes Information Criterion (BIC; Schwarz, 1978) were checked as per suggestions by Bozdogan (1987) that lower values indicate better fit. Factor loadings on items found not to be invariant across groups in MCFA were reported.

Reliability of the measures was evaluated by examining both internal consistency and test-retest reliability. Convergent validity was determined by calculating Pearson’s product moment correlation coefficients between the CRIES, SCAS-20 and SMFQ and discriminant validity was determined by comparing scores from at-risk children (from support services) and community children (from schools). Finally, to understand the influence of age and sex on the measure, 2 (gender) X 2 (age group) ANCOVAs were conducted on the CRIES-13 and CRIES-8 total and sub-scale scores controlling for group affiliation (at-risk and community children).


Confirmatory factor analysis

All hypothesised models for the CRIES were identified in the measurement model specification analyses. Results are reported in Table 2. The χ2 value was significant at p < .001 for all the models which is common for any large sample (Byrne, 2010), therefore, we considered the other fit indices to decide the best structural model for both the long and short versions of the measure.

As can be seen in Table 2, the modification indices for Models 3 and 4 were identical and these two models for the CRIES-13 produced a better fit than either Model 1 or Model 2. Therefore, based on the “Principle of Parsimony” (Bollen, 1989), we selected Model 3 (see Fig. 2), with three correlated factors as the most suitable representation of the factor structure of the CRIES-13. The correlations shown by the double headed arrows between the three factors also represent the correlations between the three sub-scales of the measure. All items were positively correlated and correlation coefficients for the three latent factors were moderate to strong (.52–.81). All items had standardized estimates that ranged from .36–.58. None of the multiple R2 values were below .02 although Item 3 (Do you have sleep problems?), Item 11 (Do you get easily irritable?) and Item 12 (Are you alert and watchful even when there is no obvious need to be?) did not load strongly on their relevant latent factor (arousal; R2 = .13–.16). Factor loadings for items on intrusion (.47–.58) and avoidance (.44–.57) were generally higher than for arousal (.36–.47). Based on the covariance matrices, a free parameter was needed between the error terms of Item 3 (Do you have difficulties paying attention or concentrating?) and Item 13 (Do you have sleep problems?). When these error terms were permitted to vary together (constrained under the same latent variable) improvements were shown in the fit for Model 3: CMIN = 132.33, DF = 61, GFI =.98, CFI =.96, TLI =.95, RMSEA =.03 (95% CI [.02–.04]), AIC = 192.22, BIC = 348.28. Therefore, it was evident that a slightly modified Model 3 provided the best factor structure for the measure.

Consequently we decided to use the modified Model 3 as the hypothesised baseline model to examine model invariance with gender and age-group, within each sample (community/at-risk). Initially, we tested model invariance with the four different groups of gender (community boy, community girl, at-risk boy and at-risk girl) and then with the age-groups (community-younger, community older, at-risk younger, and at-risk older). The results of the model invariance tests for the baseline model and constrained models are reported in Table 3 with both gender and age-groups. Results failed to demonstrate complete structural invariance across gender and age, which is not unusual. Importantly, however, for all models (i.e., unconstrained, constrained with measurement weights, structural covariances and measurement residuals) tests for the modified Model 3 yielded an acceptable range of model fit indices for each subgroup. Factor loadings for individual items on the three factors (Intrusion, Avoidance and Arousal) were reasonable for community males (.27–.64), community females (.24–.64), at-risk males (.22–.59), and at-risk females (.26–.64) and also for community younger (.29–.55), community older (.11–.67), at-risk younger (.15–.60), and at-risk older (.35–.65) children. Hence these results indicate that the modification of Model 3 provided the best fit for the data consistently across all subgroups.


Cronbach’s alpha for the total CRIES-13 was alpha =.74 and for the total 8-item version was alpha =.70. Internal consistencies for the three subscales of the two versions of the CRIES were moderate: Intrusion (alpha =.60), Avoidance (alpha =.58) and Arousal (alpha =.50). Cronbach’s alphas within the different sub-groups are reported in Table 4.

Pearson product moment correlation coefficients were calculated between questionnaire scores on the two versions of the measure separated by 3.5 weeks within a sub-group of community children (N = 120). Results showed a significant moderate relationship for the total score on the CRIES-13 (r = .72, p < .001), and for the CRIES-8 (r = .62, p < .01). Test-retest reliability for each sub-scale was also moderate (Intrusion .67 [p < .01], Avoidance .50 [p < .01], and Arousal .67 [p < .01]).


Convergent validity

The relationship between scores on the two versions of the CRIES and the SCAS-20 and SMFQ were calculated. All correlations were positive and significant at p < .01. Specifically the following correlations were demonstrated with the SCAS-20: CRIES-13 (r = .58), CRIES-8 (r = .48), Intrusion (r = .36), Avoidance, (r = .20), Arousal (r = .41). Similarly, correlations with the SMFQ were as follows: CRIES-13 (r = .42), CRIES-8 (r = .34), Intrusion (r = .44), Avoidance, (r = .34), Arousal (r = .53).

Discriminant validity

Scores on the CRIES-13 and CRIES-8 (as well as each subscale) were compared between the two samples of children: community children (selected primarily from schools in the general community) and at-risk children (selected from social support centres). In each case, at-risk children scored significantly higher on the various measures than community children (all p’s <.01), see Table 5.

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