THE DIAGNOSIS OF BIPOLAR DISORDER NR326 MENTAL HEALTH Scholarly Article Review RUA

Running Head: THE DIAGNOSIS OF BIPOLAR DISORDER 1

The delay in the diagnosis of bipolar disorder

Chamberlain College of Nursing

NR 326: Mental Health

00/ 2018

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BIPOLAR DISORDER 2

Introduction

Bipolar disorder has a significant cause to morbidity and mortality rate. Although we

have an active treatment, there is an extensive wait before diagnosis and treatment are initiated.

This research was done to examine factors associated with the delay of bipolar disorder before

the diagnosis and the onset of treatment. Bipolar disorder is also called manic depression. This

disorder is characterized with the events of mood swings ranging from depressive lows to manic

highs. The history of bipolar disorder presents with depression, so initial episodes look very

similar to a major depressive disorder. Therefore, there is often a prolonged delay in the exact

diagnosis of bipolar disorder, and any significant wait influence the initiation of appropriate

treatment. This paper investigates whether the delay in the diagnosis of bipolar disorder is

inescapable. This means is the delay in diagnosing bipolar disorder unavoidable or unpreventable

(Fritz et al, 2017).

Article summary

Bipolar disorder frequently beings with an early diagnosis of depression. This creates a

delay in the exact judgement and treatment of bipolar disorder. Although research has focused on

predictors in the analytic change from the depression stage to bipolar disorder. The research on

this prolonged diagnosis is scant. These researchers examine the time it took to diagnose one

with bipolar disorder after an early diagnosis of major depressive disorder to understand the

patient features and psychological factors that may explain the delay. However, when manic

signs are evident, the diagnosis changes to be bipolar disorder. Research shows that the time

from diagnosing a major depressive disorder to the time of diagnosing bipolar disorder is about

10 years. This means before the optimal treatment for bipolar disorder can be made, there might

be a delay in treatment for almost a decade. This is one of many reasons why it is important to

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BIPOLAR DISORDER 3

investigate the cause, and the delay from the diagnosis of major depressive disorder to time of

bipolar disorder (Fritz et al., 2017).

One of the most common predictors of exploratory conversion from major depressive

disorder to bipolar disorder is with antidepressant treatment resistance. There is a rise in the rate

of diagnostic conversion to bipolar disorder after a failure to respond to two treatments with the

use of antidepressant. Another factor that is associated with the diagnostics change from major

depressive disorder to bipolar disorder is with the initial onset of depression. Studies show that

patients who were formerly diagnosed with major depressive disorder are likely to be diagnosed

with bipolar disorder if they had an early onset of depression and were unresponsive to

antidepressant treatment. Also, the conversion to bipolar disorder has been found related to the

patient family history, but the findings are not truly reliable (Fritz et al., 2017).

The information from the article could be used in nursing practice because it educates the

nurse on the factors that might affect the early diagnosis of bipolar disorder. For example, some

statistical data from this research proves the delay as it was stated in this article. The conversion

time from major depressive disorder to bipolar disorder was about 42.8% lesser in female than it

was in male. Also, for every 1-year increase in the initial diagnosis of major depressive disorder,

the time for bipolar disorder conversion decrease by 2.8%. This data was made after a clinical

evaluation of 382 patients by a psychiatrist and with the of use series of questionnaires. When

there is an increase in the diagnosis of major disorder there is a decrease in the diagnosis of

bipolar and verse versa. Another example is to understand those factors associated with the delay

in bipolar disorder which will help the nurse better understand why some patients are diagnosed

with bipolar and other patients showing the same behavior have not been diagnosed. This article

will help the nurse better understand the diagnosis and the delayed process of bipolar disorder

(Fritz et al, 2017).

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BIPOLAR DISORDER 4

Article critique

Based on the study done, the delay is due to the disease process and other factors that

prolong the diagnosis. This article is informative about the process it takes to diagnose bipolar

disorder. The researchers put together resources from various aspect from their research to

provide why the delay is present. For example, Fritz et al. (2017) found an undesirable

correlation between the age at which the disease is initialed to the time of diagnostic conversion.

This means the younger the age of the patient, the longer the delay in diagnosing the patient.

Therefore, understanding the patient’s features and psychological behavior are also reasons that

may delay bipolar disorder from being diagnosed after an early diagnosis of a major depressive

disorder (Fritz et al, 2017).

Weakness

I feel that although the article did tell us about the factors that are associated with the

delay to diagnose bipolar disorder, the researchers did not show how those factors can be

evitable. Within the article there should have been a clear picture or graph explaining ways to

reduce the long process to diagnosing one with bipolar disorder. The weakness I believe in this

article is not especially from the article presentation, but it is from the disease process. The

weakness in this article is seen in the length of time it takes to diagnose one with bipolar.

Recommendations

I will recommend this article to a colleague because it gave a detailed explanation of the

aim of this research. This article is a good starting point to know why there is a prolonged wait in

the diagnosis of bipolar disorder. As a nursing student, this article makes me understand why

most people who exhibit similar behavior with people diagnosed with bipolar disorder have not

been medically diagnosed. As it was explained in the article, age makes a big difference to

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BIPOLAR DISORDER 5

diagnose a person with bipolar disorder because of patient characteristics and psychological

factors. Younger patients are not mentally developed as an adult patient would be.

Conclusion

In conclusion, this study shows that certain individuals experience a significant delay in

diagnosis and treatment of bipolar disorder which varies depending on different factors. I believe

when there is a better understanding of the factors associated with the delay to diagnose bipolar

disorder, then there will be developmental strategies to reduce them. These findings indicate the

need for an early recognition and initiation of active treatment of bipolar disorder which will

most likely diminish disability and improve outcomes.

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BIPOLAR DISORDER 6

References

Fritz, K., Russell, A., Allwang, C., Kuiper, S., Lampe, L., Malhi, G., (2017). Bipolar disorder: Is

a delay in the diagnosis of bipolar disorder inevitable? 19, 396–400. doi:10.1111/bdi.12499.

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ORIGINAL ARTICLE

Screening for autism spectrum disorder in children with Down syndrome: An evaluation of the Pervasive Developmental Disorder in Mental Retardation Scale Vincent Pandolfia, Caroline I. Magyarb and Charles A. Dillc

aPsychology Department, Rochester Institute of Technology, Rochester, NY, USA; bDepartment of Paediatrics, Division of Neurodevelopmental and Behavioural Paediatrics, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA; cPsychology Department, Hofstra University, Hempstead, NY, USA

ABSTRACT Background Children with Down syndrome (DS) are at risk for autism spectrum disorder (ASD). They are often diagnosed later than other children in part due to difficulty differentiating ASD-related impairment from that associated with DS. The psychometric properties of the Pervasive Developmental Disorder in Mental Retardation Scale (PDD-MRS) were examined with the aim of informing ASD screening guidelines for children with DS. Method Analysis of archival data from children aged 3 to 15 years with DS (N = 386) evaluated the reliability and validity of the PDD-MRS. Results Factor analyses yielded 2 factor-based scales: ASD and Emotional and Behavioural Problems. ASD reliably assessed ASD-specific symptoms, correlated with other ASD measures, and demonstrated good diagnostic accuracy. Emotional and Behavioural Problems assessed problems not diagnostic of ASD but may reflect part of the behavioural phenotype of DS and ASD. Conclusion The PDD-MRS appears to have utility in ASD screening for this population.

KEYWORDS autism; ASD; Down syndrome; PDD-MRS; assessment

Introduction

Research suggests the prevalence of autism spectrum dis- order (ASD) in children with Down syndrome (DS) may be higher than that observed in the general population. Estimates range from 5% to 39% (for a review, see Moss & Howlin, 2009; Reilly, 2009); many children with DS are diagnosed at a later age relative to other chil- dren and some may not be identified at all (e.g., Howlin, Wing, & Gould, 1995; Rasmussen, Börjesson, Wentz, & Gillberg, 2001). This situation is concerning, particularly as research indicates that children with DS and co-occur- ring ASD have lower cognitive, language, and adaptive levels, and have more behaviour problems than children with DS only (e.g., Magyar, Pandolfi, & Dill, 2012; Mol- loy et al., 2009), suggesting that the co-occurrence of ASD conveys additional morbidity. If not identified with a co-occurring ASD, then the child is unlikely to receive ASD-specific treatment.

Although the exact reasons for the late or lack of ASD diagnosis is unknown, it has been speculated that the sig- nificant delays and impairments seen in children with DS in the areas of communication and behaviour are attrib- uted to the child’s level of intellectual disability (ID) and associated speech and language impairments. These pro- blems are not viewed as symptomatic of a co-occurring ASD, a phenomenon called diagnostic overshadowing

(Reiss, Levitan, & Szyszko, 1982). However, the literature containing descriptions of children with DS and co- occurring ASD (DS + ASD) and those without ASD (DS) suggests that (a) heightened severity of impairment, and (b) differences in the form of the social communi- cation and repetitive behaviour can distinguish ASD- related impairments from those related to ID. This is more likely if a developmental approach to ASD assess- ment is applied (Dosen, 2005; Hepburn, Philofsky, Fidler, & Rogers, 2008) and if reliable and valid ASD assessment measures are used (e.g., Magyar et al., 2012).

The distinction between ASD-related symptomatol- ogy and DS-related impairment can be seen in both the social communication and repetitive behaviour domains of an ASD diagnosis. These include the pres- ence of more stereotyped and repetitive speech forms (when speech is present), limited or no gesturing for communicative purposes, limited interest in peers, increased probability of aggression in response to social approaches by peers, the absence of pretend and imagi- native play, the absence of functional play, such as demonstrating the tendency to line objects up, and pre- occupation with parts of objects (e.g., see Channell et al., 2015; Hepburn et al., 2008; for a review, see Reilly, 2009). These findings contribute greatly to advancing our knowledge of the potential clinical indicators that can

© 2017 Australasian Society for Intellectual Disability, Inc.

CONTACT Vincent Pandolfi [email protected]

JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY, 2018 VOL. 43, NO. 1, 61–72 https://doi.org/10.3109/13668250.2016.1271111

distinguish children with DS + ASD from children with DS only. Nevertheless, the challenge involved in accu- rately and systematically assessing for these indicators highlights the need for reliable and valid ASD screening measures.

A review of the ASD screening and health surveillance guidelines for all children published in 2007 (Johnson, Myers, & the Council on Children With Disabilities, 2007) and for children with DS published in 2011 by the American Academy of Pediatrics (Bull & the Com- mittee on Genetics, 2011), however, indicates that neither document provides sufficient research-based guidance to practitioners on the selection or use of reliable and valid ASD screening measures for children with DS. For example, the 2007 document recommends that all chil- dren be screened at the 18 and 24 month well-child visits using a standardised ASD screening measure. However, this recommendation was designed to assist practitioners in screening the general population of children. Although children with DS may be subsumed under this rec- ommendation, the timing of the screening assessment may not be consistent with the emergence of distinguish- able ASD symptoms in children with DS because of the developmental delays in the areas of language, communi- cation, and play. If screened at these very young ages for ASD, the practitioner may attribute relevant develop- mental impairments to the child’s intellectual and language impairments associated with the DS and not to the presence of ASD (i.e., diagnostic overshadowing). This may preclude further assessment at later ages when changes in the child’s development may lead to bet- ter differentiation of the manifest ASD symptoms.

The 2011 health surveillance guideline for children with DS includes a recommendation for ASD screening and anticipatory guidance beyond the 24-month level, but it does not include a recommendation for a specific ASD screening measure validated for use in children with DS. This is problematic because of the finding that of those practitioners who report using a standar- dised ASD screening measure per the 2007 American Academy of Pediatrics guidelines (Johnson et al., 2007), the Modified Checklist for Autism in Toddlers (M-CHAT; Robins, Fein, Barton, & Green, 2001) is the most commonly used ASD screening measure in the United States (Arunyanart et al., 2012), but this measure has not been validated for use with children with DS. This may limit its usefulness in screening children with DS who may require periodic screening throughout childhood for the emergence of ASD symptoms.

To our knowledge the only ASD general population screening measure to receive at least one thorough evalu- ation of its psychometric properties including diagnostic accuracy in children with DS is the Social

Communication Questionnaire – Lifetime Version (SCQ-L; Rutter, Bailey, & Lord, 2003), a 40-item care- giver-completed paper-and-pencil questionnaire. Magyar et al. (2012) evaluated the SCQ-L in a large (N = 447), well-characterised sample of children with DS aged 4 to 14 years 11 months, with and without ASD, and found that the measure was not only reliable but also that it discriminated between children with DS alone and those with DS + ASD. But although sensitivity was found to be good, specificity was not as robust. This suggests that practitioners may need to use an additional ASD screening measure or a different approach, such as an interview with the caregiver, to better specify the nature of the identified social communication and behavioural impairments. This might improve prac- titioners’ confidence in their decision on whether to refer a child for an ASD diagnostic assessment. This approach to assessment is consistent with the rec- ommendation that information from multiple sources is needed to improve clinical decision-making in ASD evaluation (Pandolfi & Magyar, 2014; Risi et al., 2006).

Present study

In the present study we aimed to expand the evidence base on psychometrically sound ASD screening measures for children with DS. This would provide prac- titioners an opportunity to consider more than one measure with evidence to support its use, enabling them to tailor the selection of measures to client charac- teristics and need. This may improve the chances of early ASD detection within this population.

We evaluated the psychometric properties of the Per- vasive Developmental Disorder in Mental Retardation Scale (PDD-MRS; Kraijer, 2006) in a large sample of children with DS. The PDD-MRS evaluates behaviours within the past 2–6 months consistent with an ASD diag- nosis. It was developed specifically for children and adults (2–70 years) with an ID and features a flexible administration format: data may be collected via clinical interview or through caregiver paper-and-pencil self- report. The PDD-MRS can be used for initial screening or for subsequent checks on a previous assessment out- come. In this study we specifically examined (a) internal structure of the scale through exploratory and confirma- tory factor analyses of the items, (b) scale reliability, (c) convergent and discriminant correlations with measures of ASD and cognition, (d) criterion validity indicated by differences in mean PDD-MRS scores between groups of children with and without ASD, and (e) diagnostic accu- racy through receiver operating characteristic (ROC) and predictive discriminant analyses. All analyses were com- pleted to better understand the extent to which PDD-

62 V. PANDOLFI ET AL.

MRS scores could be interpreted as indicators of ASD in children with DS.

Method

Design

Data collection Archival PDD-MRS data were used in this study (N = 386). Data were obtained from a statewide preva- lence study of medical and behavioural comorbidities of children with DS aged 3 years 4 months to 15 years 5 months. The prevalence study was approved by the University of Rochester’s institutional review board (RRRB12774) and written informed consent was obtained from the parents of all children. All data were coded and stored so that participant confidentiality was ensured and only those researchers with university approval were authorised to access the data.

The prevalence study used a three-tiered ascertainment procedure. Tier 1 assessment procedures included the mailing and completion of ASD screening measures: the M-CHAT (Robins et al., 2001; N = 440), the SCQ-L (Rut- ter, Bailey, & Lord, 2003; N = 438), telephone adminis- tration of the PDD-MRS (Kraijer, 2006; N = 386), as well as a medical history questionnaire. All children who screened positive (defined as positive on one or more ASD screening measures) and an approximately equal number of children who screened negative were evaluated at Tier 2 (N = 221) using the Autism Diagnostic Interview – Revised (ADI-R; Rutter, Le Couteur, & Lord, 2003), the Vineland Adaptive Behavior Scales – Second Edition – Parent/Caregiver Form (Sparrow, Cicchetti, & Balla, 2005), and the Repetitive Behaviour Scale – Revised (RBS-R; Bodfish, Symons, & Lewis, 1999). All children who screened positive on the ADI-R and an approxi- mately equal number of children who screened negative participated in the Tier 3 assessment (N = 71), which included administration of the Autism Diagnostic Obser- vation Schedule (ADOS; Lord, Rutter, DiLavore, & Risi, 2002), the Leiter International Performance Scale – Revised (Leiter-R; Roid & Miller, 1997), a norm-refer- enced measure of nonverbal intelligence, and the Child Behavior Checklist 1.5–5/6–18 (Achenbach & Rescorla, 2000, 2001), a parent-completed checklist to screen for common emotional and behavioural problems in children.

ASD diagnoses were made by an experienced evalu- ation team that included clinicians with extensive clinical and research experience in ASD and developmental dis- ability: a developmental paediatrician, a licensed clinical psychologist, and several trained clinical evaluators. A developmental approach to diagnosis (Dosen, 2005; Hep- burn et al., 2008) was used whereby an ASD diagnosis was

based on all data collected across all tiers on the child, eval- uated within the context of the child’s IQ and level of expressive language (verbal/nonverbal), and summarised ona Diagnosticand Statistical Manual of Mental Disorders (4th ed., text rev., DSM-IV-TR; American Psychiatric Association [APA], 2000) ASD checklist using clinical consensus guidelines developed bytheteam. Child partici- pants were diagnosed witheither DS only (n = 38) or DS + ASD (i.e., autistic disorder or pervasive developmental disorder not otherwise specified [PDD-NOS]; n = 33).

Participant characteristics

Data from all three tiers were used in the analyses. The total participant pool (N = 386) was divided to allow for exploratory (EFA) and confirmatory factor analyses (CFA) on separate matched groups. Participants were matched by age and then randomly assigned to either the EFA (n = 193) or CFA (n = 193) subgroup, and par- ticipants with Level 3 data (n = 71) were then used for the convergent and discriminant analyses. SPSS Version 21 software was used to generate descriptive data for the EFA and CFA subgroups, which are presented in Table 1.

Table 1. Descriptive data for model development and replication subgroups.

Variable

EFA subgroup CFA subgroup

n M SD n M SD

Age (years) 193 8.95 3.18 193 8.95 3.18 Vineland Adaptive Behavior Composite

102 68.09 11.90 111 65.85 11.84

Autism Diagnostic Interview – Reviseda

Reciprocal Social Interaction

106 7.25 5.46 114 8.03 5.63

Communication-Verbal 106 3.52 3.82 114 4.22 4.33 Communication- Nonverbal

106 2.34 3.77 114 2.23 3.62

Restrictive, Repetitive, and Stereotyped Behaviour and Interests

106 3.46 2.78 113 3.80 2.96

n No. % n No. %

Gender (male) 193 101 52.33 193 106 54.92 Raceb 190 192 White 173 91.05 180 93.75 Black 7 3.68 7 3.65 Asian 2 1.05 2 1.04 American Indian 1 0.53 2 1.04 > 1 category 7 3.68 1 0.52

Ethnicity Hispanic 187 11 5.88 190 6 3.16 Parent education 193 193 Less than high school 1 0.52 5 2.59 High school 26 13.47 28 14.51 Some college/ specialised training

40 20.73 35 18.13

College 126 65.28 124 64.25 Graduate degree 0 0.00 1 0.52

Note. EFA = exploratory factor analysis; CFA = confirmatory factor analysis. n = 193 for EFA and CFA subgroups. When n < 193, this was due to missing data.

aCurrent behaviour algorithm scores. bPercentages for EFA subgroup do not sum to 100 because of rounding error.

JOURNAL OF INTELLECTUAL & DEVELOPMENTAL DISABILITY 63

The groups were similar across all demographic and developmental variables. Significance tests were not con- ducted on these variables because of the use of matching and random assignment. The quantitative data were very similar across the EFA and CFA subgroups: the minor differences were not substantively meaningful and any statistically significant differences that occurred through random assignment could be attributed to Type I error. Thus, the subgroups had participants of the same age, approximately equal numbers of males and females, were composed mostly of participants who were white, had parents with college-level education, had similar ADI-R scores, and had Vineland adaptive behaviour scores that were well below the population mean.

Demographic data for Level 3 participants have been published elsewhere (Magyar et al., 2012) and those results are only summarised here. The group with DS (n = 38, M = 7.92 years, SD = 3.19 years) was slightly younger than the group with DS + ASD (n = 33, M = 8.97, SD = 2.51), but this difference was not significant at α < .05 (p = .132). As might be expected, the group with DS + ASD exhibited more developmental impairment than the group with DS only. The group with DS only showed significantly higher IQ scores (MDS = 52.38, SD = 14.57 vs. MDS + ASD = 41.93, SD = 6.74) and Vineland Adaptive Behavior Composite scores (MDS = 69.65, SD = 9.87 vs. MDS + ASD = 60.12, SD = 10.91) with both ps < .001. The DS + ASD group evidenced higher scores on the ADI-R Social Interaction (p < .001), Communication-Verbal (p = .004), and Repeti- tive Behaviour domains (p < .001), which indicated that these children demonstrated more ASD symptoms.

Instruments

This section contains a description of the measures used for the main data analyses (PDD-MRS, ADI-R, and the Leiter-R) and for subject characterisation (Vineland Adaptive Behavior Scales – Second Edition).

Pervasive Developmental Disorder in Mental Retardation Scale The PDD-MRS (Kraijer, 2006) is a 12-item ASD screen- ing measure developed for persons with ID. Item content was informed by several sources. They included the DSM-III-R (3rd ed., rev.; APA, 1987) criteria for the per- vasive developmental disorders of autistic disorder and PDD-NOS. It also included a literature review and file review of individuals with known ID and PDD. Items assess the quality of social interactions with adults and peers, language and speech problems, and several other behaviours such as obsessive interests, stereotyped beha- viours, self-injury, and erratic/unpredictable behaviour. Items are scored as present or absent during the

preceding 2–6 months, and the differentially weighted items are summed to provide a total score that indicates the likelihood of ASD. The test author reported that the differential weighting increased the instrument’s discri- minant validity, although no explanation was provided in the manual as to how the specific weights were deter- mined. Three qualitative ranges describe the total score’s screening outcome: “non-PDD” (Total Score = 0–6), “Doubtful PDD/non-PDD” (Total Score = 7–9), reflect- ing diagnostic uncertainty, and “PDD” (Total Score = 10–20).

The technical manual contains psychometric findings from the test development sample, which included chil- dren and adults with DS (see Kraijer, 2006). Internal consistency, interrater reliability, and test score stability were favourable. An EFA was completed on the 12 PDD-MRS items along with several developmental and demographic variables. It yielded the following four fac- tors: PDD, functioning level, gender, and age. However, factor analyses that only included the test items them- selves were not reported. The measure was found to gen- erally discriminate persons with the then-current diagnosis of PDD from persons without it. Despite the favourable reliability and validity data reported in the manual, independent replications of these findings have not been reported, and no independent study has examined the psychometric properties of the scale specifically in children with DS.

Social Communication Questionnaire – Lifetime Version The SCQ-L (Rutter, Bailey, & Lord, 2003) is a paper- and-pencil ASD screening measure that contains 40 items. Item content is related to the ADI-R. The measure assesses for qualitative impairments in recipro- cal social interaction and communication, and restricted, repetitive, and stereotyped behaviours. The measure is completed by a caregiver who is familiar with the child’s developmental history. The SCQ-L was included because it demonstrated favourable psychometric properties in a previous study of children with DS (see Magyar et al., 2012).

Autism Diagnostic Interview – Revised The ADI-R (Rutter, Le Couteur, & Lord, 2003) is a diag- nostic interview used to assess individuals suspected of having an

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