Integrating technology into cognitive behavior therapy for adolescent depression: a pilot study

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Integrating technology into cognitive behavior therapy for adolescent depression: a pilot study

Kenneth A. Kobak1*, James C. Mundt1 and Betsy Kennard2

Author Affiliations

1 Center for Telepsychology, 22 North Harwood, Madison 53717, WI, USA

2 UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas 75390, TX, USA

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Annals of General Psychiatry 2015, 14:37  doi:10.1186/s12991-015-0077-8

The electronic version of this article is the complete one and can be found online at:

Received: 22 May 2015
Accepted: 20 October 2015
Published: 3 November 2015

© 2015 Kobak et al.

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Rapid advances in information technology and telecommunications have resulted in a dramatic increase in the use of mobile devices and the internet to enhance and facilitate access to treatment. Cognitive behavior therapy (CBT) is an empirically based treatment that is well suited for enhancement by new technologies, particularly with youth. To facilitate the dissemination of this evidence-based treatment, we developed a technology-enhanced CBT intervention for the treatment of adolescent depression consisting of (1) online therapist training (2) in-session use of tablets for teaching clients CBT concepts and skills, and (3) text messaging for between session homework reminders and self-monitoring.


Eighteen licensed clinicians (social workers n = 7, psychologists n = 9) were randomized to have their patients receive either the intervention (CBT) or treatment as usual (TAU). Each clinician treated four adolescents for 12 weeks. Clinicians in the CBT arm completed an online tutorial on CBT treatment of adolescent depression, then received an iPad with access to patient education materials for teaching CBT concepts to patients during sessions. Individualized text messages were integrated into treatment for homework reminders, support, and outcomes measurement. Outcome measures included a 49-item multiple choice test for tutorial effectiveness; the system usability scale (SUS) for user satisfaction; quick inventory of depressive symptomatology–adolescent version (QIDS-A-Pat); and clinician and patient ratings on the therapeutic alliance scale for adolescents (TASA).


A significant increase in knowledge of CBT concepts was found after completing the tutorial, t(8) = 7.02, p < 0.001. Clinician and patient ratings of user satisfaction were high for both the iPad teaching tools, and the text messaging. Ninety-five percent of teens said reviewing their text messages with their therapist was helpful, and all said they would use text messaging in treatment again. Ratings of the therapeutic alliance were higher in the CBT arm t(131) = 4.03, p = 0.001. A significant reduction in depression was found in both groups [t(34) = 8.453, p < 0.001 and t(29) = 6.67, p < 0.001 for CBT and TAU, respectively). Clinical ratings of improvement were greater on all outcome measures for the CBT arm; however, none reached statistical significance. Effect sizes (Cohen’s d) ranged from small (QIDS-A) to large (TASA).


Results support the feasibility of this technology-enhanced CBT intervention as a means of improving CBT treatment of adolescent depression and may help address the critical shortage of therapists trained on empirically based treatments.


Cognitive therapy; Internet; Training; Depressive disorder; Adolescent; Dissemination; Evidence based


The use of technology for the psychological treatment of mental disorders is on a rapid ascent. While the potential ways of using technology to enhance treatment have been discussed for decades [1], [2], the recent explosion in information technology and telecommunications, and the widespread use of mobile devices have resulted in a dramatic increase in the use of both mobile devices and the internet to enhance and facilitate access to treatment. Several review articles have been published summarizing the bourgeoning body of data being generated [3]–[7]. Results have generally been supportive of both efficacy and feasibility, though several issues have been identified, such as confidentiality, privacy, crisis management, technological competence, and ethical issues [3], [8]. As with all innovations, new practice guidelines have been developed to address the unique challenges presented [9]–[11].

Cognitive behavior therapy (CBT) is an empirically based treatment that is uniquely suited to enhancement by new technologies [5], [12]. It is highly structured, typically manualized, follows a sequential progression, emphasizes self-responsibility, self-monitoring and homework, and includes ongoing outcome measurements. A variety of technology-enhanced CBT applications across a range of mental disorders have been reported. These include computer-administered CBT self-treatment (stand alone, no therapist contact), computer-assisted CBT treatment (computer-administered with some clinician guidance or contact), mobile monitoring and communication, psychoeducation, remote live treatment via videoconference, and online therapist training [12]–[18].

The use of technology is particularly well suited for psychological interventions with youth and teens. Nine in ten teens in the USA (93 %) have access to a computer, 78 % have cell phones, and 74 % have mobile access to the internet via a cell phone, tablet or other device [19]. Text messaging has become the preferred mode of communication among teens, with two-thirds reporting they are more likely to use their cell phones to text their friends than to talk with them. Half of teens in the USA send 50 or more texts per day [20]. Mobile phone use by teens cuts across socio-demographic backgrounds, as more US families replace traditional land lines with mobile phones (e.g., 41 % of households have only wireless according to a 2013 survey by the National Center for Health Statistics; among poor households, the figure is 56 %) [21]. Teens in both the USA and abroad have both the technical expertise with these technologies, and a favorable attitude toward their use in mental health care [4], [22]. Three quarters of lifetime mental disorders begin in adolescence and young adulthood, making it a critical target age for prevention and intervention efforts [23]–[25].

Given the compatibility between CBT and new technologies, and the affinity for new technologies by youth, the integration of new technologies into CBT treatment of youth has been rapidly increasing [5], [7]. Applications have been developed for the treatment of a variety of disorders, including simple phobias, social anxiety disorder, generalized anxiety disorder, obsessive–compulsive disorder, encopresis, autism, eating disorders, depression, and substance abuse [26]–[39].

Mobile applications such as text messaging [i.e., short messaging services (SMS)] are particularly well suited for youth and can help clinicians implement CBT treatment more effectively through the use of homework reminders, real-time self-monitoring and between session communication and feedback [17]. Among mental health patients, text messaging is the most popular feature, and a higher percentage of mental health patients text compared to the general population [40], [41]. Self-monitoring in particular has been found to improve treatment outcomes, both by itself and when added to therapy [42], [43] and accounts for a significant portion of the variance in treatment outcomes [44]. Text messaging may help overcome non-compliance (a primary reason for lack of treatment efficacy) by enabling encouragement and support between sessions. Interacting with each adolescent on a daily basis to encourage compliance with homework assignments, evaluate progress, monitor side effects, etc., would be prohibitively expensive if clinicians were required to personally send and receive the messages themselves. Fortunately it is not necessary, given the demonstrated feasibility of automating those functions. There is a large body of literature on the efficacy of text messaging for improving heath behavior and treatment outcomes in other areas of health care (e.g., diabetes, asthma, hypertension, obesity), with positive outcomes in 93 % of the published studies [45]. Text messaging is also used in the treatment of psychiatric and substance use disorders in adults [46], [47]. Data on the use of SMS in the psychological treatment of youth and young adults are beginning to emerge [3], [48]–[52]. Teens have generally reacted favorably to use of SMS technology in treatment and prevention programs, with good compliance rates [22], [53].

In response to the National Institute of Mental Health’s call for research on the use of technology to facilitate the dissemination of evidence-based treatments [54], we developed a technology-enhanced intervention protocol to facilitate CBT treatment of adolescent depression. The program consists of three components, each using technology for a particular purpose: (1) online therapist training, (2) in-session use of tablets for teaching clients CBT concepts and skills, and (3) text messaging for between session homework reminders and self-monitoring. These three components help disseminate training to therapists, help therapists implement CBT with patients more effectively, and improve CBT treatment outcomes, respectively. The goal of this study was to evaluate the feasibility, user satisfaction, and effectiveness of this technology-enhanced approach for treating adolescent depression.



Eighteen licensed clinicians who work with depressed adolescents participated in the study. Clinicians were recruited through advertisements in professional journals and through direct mail (i.e., Psychology today listing of clinicians working with depressed adolescents). Clinicians came from 13 states and various disciplines, including social work (n = 7), clinical or counseling psychology (n = 9), educational psychology (n = 1) and behavioral mental health (n = 1). Fifteen had master’s degrees and three doctoral degrees. The mean age was 44.2 years (range 31–58 years, SD = 8.4), and 56 % (n = 10) were female. Thirteen were Caucasian, four African American, and one was multiracial. Fifteen (83 %) reported some prior exposure to CBT, primarily through group lectures (78 %). None were accredited or formally trained as CBT practitioners. Mean number of years working with adolescents was 12.2 (range 2–20 years, SD = 5.59).


Sixty-five adolescents, aged 12–17 (mean age = 15.4, SD = 1.52) with a DSM-5 mood disorder [major depressive disorder (n = 31), persistent depressive disorder (n = 20), both major and persistent depressive disorders (n = 3), other specified depressive disorder (n = 6), unspecified depressive disorder (n = 5)] and a minimum score of 11 on the quick inventory of depressive symptomatology–adolescent-patient report (QIDS-A-Pat) (mean = 14.5, SD = 3.28, range 10–22) [55] were recruited. Subjects were excluded if they had bipolar disorder, severe conduct disorder, substance dependence, pervasive developmental disorders, thought disorder, severe suicidal/homicidal ideation or behavior requiring inpatient treatment. Diagnoses were determined via clinical interview using a DSM-5 symptom checklist. Non-English speakers and adolescents without daily access to a cell phone were also excluded. Patients represented diverse races and ethnicities, including Caucasian (n = 27), African American (n = 24), American Indian (n = 3), Asian (n = 1), Biracial (n = 5) and other (n = 5). Fifteen percent (n = 10) were Hispanic and two-thirds (n = 43) were female.


Clinicians were randomly assigned to have all their subjects receive either the technology-enhanced CBT intervention arm (CBT), or treatment as usual (TAU). Each clinician recruited four adolescents from their clinical practice who were initiating treatment for depression. Three clinicians dropped out of the study before completing enrollment and were replaced. Clinicians in the CBT arm completed a pre-test on CBT knowledge and then took the online tutorial on CBT treatment for adolescent depression. After completing the tutorial, clinicians took a post-test, then received an iPad containing a link to the online CBT interactive teaching materials and text-messaging system. A brief (1 h) orientation session was held with each clinician to review how to use the iPad for teaching CBT concepts to patients and for setting up text messages. Each patient was treated for 12 weeks, using the skills learned in the tutorial, and the in-session teaching tools. Individualized text messages were integrated into treatment. Clinicians in the TAU arm also recruited patients initiating treatment for depression from their clinical practice, and treated them for 12 weeks using usual care. After completing the study, clinicians in the TAU arm were offered access to the CBT training and intervention tools. Since both patients and therapists were considered research subjects, each signed informed consent statements approved by the Allendale Institutional Review Board. Patient flow and study completion rates by treatment arm are shown in Table 1.

Table 1. Patient recruitment and study completion by treatment arm

Description of the technology-enhanced CBT intervention

Online therapist training tutorial

The online training tutorial was developed as a way to address the critical shortage of clinicians trained in CBT, due in large part to a lack of training available [56], [57]. Putting the training online makes the training more accessible, cost-effective, and obviates the need for travel to one of the limited number of centers that offer CBT training. Trainees are not bound by time limitations, and can work at their own pace and schedule (a recent study found time and cost the strongest predictor of unwillingness to obtain training on empirically based treatments) [57]. The quality of the training is also enhanced using principles of instructional design to deliver multi-modal, interactive learning, both of which have been found to increase knowledge retention [58]. Standardizing the training helps insure the quality of the instruction, which is important as several studies have found that much of the CBT that is being delivered is not being administered properly [59], [60]. The tutorial was modeled after the cognitive behavior therapy manual used in the NIMH funded treatment of adolescents with depression study [61] and consisted of nine modules (overview, theoretical principals of CBT, explaining the nature of depression to Clients and the therapeutic relationship, explaining treatment rationale to clients, mood monitoring, goal setting, behavioral activation, problem solving, and cognitive restructuring). Trainees worked at their own pace, and could email us with any questions. The tutorial took about 5.5 h to complete (see for examples of tutorial content). Animations, graphical illustrations, interactive exercises, and video illustrations of an expert clinician (Dr. Kennard) applying the techniques were used as teaching tools. Session agendas and a treatment protocol were provided to assist clinicians in treatment implementation.

Online interactive patient educational materials

The second component consisted of online instructional materials to help clinicians explain CBT concepts to patients. Patient understanding of treatment rationale and treatment concepts is a critical part of effective treatment, as the more sense a treatment makes to a client, the more likely they are to comply with it [62], [63]. In CBT, there is a collaborative relationship between the therapist and client, with the client seen as both capable of, and responsible for, change. To empower clients with the skills necessary for change, it is critical that both (the client and the depressed adolescents parents) have an basic understanding of the nature of depression, the CBT treatment rationale, and, CBT concepts and skills, such as mood monitoring, identifying and challenging automatic thoughts, and activity scheduling. Therapists typically teach this using a combination of verbal instruction and paper and pencil forms. We created a series of online, interactive education materials to (1) help novice CBT therapists structure sessions, (2) insure that the concepts are covered thoroughly and accurately, (3) engage and involve the youth and personalize the material, and (4) create personalized goals and homework assignments. For example, in teaching clients about automatic thoughts, the therapist first displays a hypothetical scenario on the tablet PC (in our case, an iPad), to teach the relationship between thoughts, emotions, and behaviors. The teen then generates two or three possible thoughts they might have in that situation and the different feelings associated with those thoughts. Once the concept is understood, i.e., that different thoughts lead to different feelings, the therapist goes through the process again using a situation from the client’s real life. Finally, homework is collaboratively set up, e.g., to monitor one’s mood and thinking at specific intervals during the day. In another example, the client may be learning problem-solving skills. In this case, the tablet plays a pre-recorded scenario of a typical teen problem, after which the client goes through the problem-solving process using the tablet. Finally, the process is repeated with a real-life problem the client has, followed by setting up problem-solving practice between sessions.

Interactive text messaging

The third part of the intervention consists of text messages the client receives between sessions to remind them of their homework goals, and to record results of homework practice (see for an illustration). These are set up as the final step in the patient education process previously described. Typically, the client would receive two texts each day: a reminder text call in the morning and a text later in the day to record results. For example, if the goal was to increase pleasant activities, the morning text would say “remember to do at least one pleasant activity today’. Do you remember the activity you were going to do?” If they said no, they would receive a text back reminding them what the activity was. In the evening, they would receive a text asking them if they did the pleasant activity, get a reinforcing message if they did, and a text back asking them to describe what they did and how it affected their mood. If they did not do the activity, they would receive a text back saying “Making yourself do something when you do not feel like it is hard. Sometimes just doing something nice helps you feel better” followed by “Tell me what kept you from doing the activity today. We can talk about it next session.” A report of all texts sent and received is sent to the therapist for review with the client at their next session, as a way to process together how the homework went and to troubleshoot problems and reinforce learning. Timing and frequency of texts are determined collaboratively by the therapist and teen. For example, the teen may say that 9 pm is the best time to receive evening texts, as that is when he has some down time. Or a therapist may want to increase or decrease the frequency of mood monitoring, depending on the clinical status of the teen. Examples of texts are shown in Table 2.

Table 2. Examples of text messages and response options by therapeutic module

Outcome measures

Online tutorial

Effectiveness of the online tutorial in improving clinician’s knowledge of CBT concepts was evaluated using a 49-item multiple choice pre- and post-test covering the tutorial content. The test had good internal consistency reliability (coefficient alpha = 0.821). Technical feasibility of the tutorial was evaluated with the system usability scale (SUS) [64], [65]. The SUS is a reliable, well-validated 10-item scale designed to evaluate the usability and user satisfaction with web-based applications and other technologies. The SUS has good internal consistency reliability (coefficient alpha: r = 0.86 in our sample) in assessing usability across diverse types of user interfaces (e.g., web, interactive voice response, cell phone, etc.) It provides quantitative feedback on a 0–100 scale. In a cross-validation study of the SUS using an anchored adjective scale, systems with “Good” usability had mean score of 71.4. [66] This criterion was used for successful system design in the current study. In addition to the SUS, ratings were also obtained on whether the stated learning objectives of the tutorial were met, and a set of questions evaluating satisfaction with the clinical content of the tutorial.

Online teaching materials and text messaging

Technical feasibility with the online teaching materials and text-messaging system was evaluated with the SUS. Open-ended feedback was also solicited on user satisfaction with the system from both clinicians and patients.

Clinical outcomes

Clinical outcome measures were obtained at the end of 6 and 12 weeks of treatment. The primary clinical outcome measure was pre-to-post treatment changes in patient ratings of depression on the quick inventory of depressive symptomatology–adolescent version (QIDS-A-Pat) [55]. Secondary outcomes included clinician global ratings of improvement (CGI-I) and severity (CGI-S) [67], and clinician and patient ratings on the therapeutic alliance scale for adolescents (TASA) [68].

Statistical analyses

Categorical and ordinal variables, such as gender and percent responders were tested by Chi-square tests of distributional independence. Interval and ratio level measurements, such as age, and depression severity scores were compared with two-tailed, between group t tests for equivalence of means. When the sample size in each of two groups is 32, a 0.05 level Chi-square test will have power of 0.7–0.97 to distinguish between the groups when the proportions in the two categories are characterized by effect sizes of 0.1 to 0.25. Samples of 32 per group have statistical power of 0.50–0.88 to detect moderate to large mean differences (effect sizes of 0.5–0.8) in two group t tests using two-sided alphas of 0.05. The sample size estimate was based on the QIDS-A-Pat.


Clinicians and patients

There were no significant differences between clinicians randomized to CBT and TAU in terms of age [t(16) = 0.42, p = 0.678), gender (X 2 (1) = 1.90, p = 0.168], or years’ experience [t(16) = 0.10, p = 916]. There were also no significant differences between patients in the CBT and TAU arms on age [t(63) = 0.076, p = 0.940], gender (X 2 (1) = 0.94, p = 0.432), or baseline depression severity (QIDS-A-Pat) [t(63) = 0.27, p = 0.787).

Online tutorial

Increase in didactic knowledge

We examined changes in scores on the 49-item pre-and post-tests of knowledge of CBT concepts covered in the tutorial. A significant increase was found in the number of correct items from the pre-test (24.4, SD = 4.42) to the post-test (33.9, SD = 5.11), t(8) = 7.02, p < 0.001.

Learning objectives

Twenty-three learning objectives were identified a priori as learning goals for the online tutorial (Table 3). After completing the tutorial, 97 % of the learning objectives were rated as met. The mean rating of how much they learned as a result of taking the tutorial was 4.4 (rated on a 1–5 scale (1 = very little and 5 = a great deal).

Table 3. Learning objectives: CBT tutorial

User satisfaction: technical aspects

The means score on the SUS for the online tutorial was 78.4 (SD = 20.44) (Table 4). This corresponds to a score of good user satisfaction on the SUS. Mean global rating of user-friendliness (rated scale range from 1 (worst imaginable) to 7 (best imaginable)) was 5.6, which is halfway between “good” and “excellent”.

Table 4. System usability scale scores for the online tutorial and teaching/text system

User satisfaction: clinical content

Descriptive statistics were obtained on user satisfaction with the online tutorial (Table 5). All that subjects agreed or strongly agreed that the material was presented in an interesting manner, was clearly presented and easy to understand, and was useful and relevant to treating adolescent depression. All would recommend the online tutorial to others.

Table 5. Mean satisfaction ratings on tutorial scale clinical content

Online teaching materials and text messaging

User satisfaction: clinicians

The means score on the SUS for the online CBT teaching materials and text-messaging system was 84.4 (SD = 13.80). This corresponds to a score between good and excellent. Ratings on individual SUS items are presented in Table 6. The mean rating for all items was between “agree” and “strongly agree”. Clinicians found the system ‘user friendly’ in terms of understanding how to utilize the system for teaching CBT skills, setting up text messages, and receiving text reports.

Table 6. Mean ratings on system usability scale items: online teaching materials and text messaging

User satisfaction: patients

Feedback was also solicited from adolescents on how helpful the teaching and text message system was. Eighty-five percent of patients felt the teaching materials presented on the iPad during sessions were helpful in learning new skills, 90 % felt the text messages between sessions were helpful, and 95 % said reviewing their text message responses on their homework and mood at the next session with their therapist were helpful. All patients said they would be willing to use text messaging again to communicate their feelings to their clinician between sessions.

Clinical outcomes

Both treatment groups significantly improved with treatment, with mean improvements on the QIDS-A of 6.09 (SD = 4.26) and 5.73 (SD = 4.71) for the CBT and TAU groups [t(34) = 8.453, p < 0.001 and t(29) = 6.67, p < 0.001 respectively]. Clinical outcome measures comparing the CBT and TAU groups are presented in Table 7. Therapist ratings of the therapeutic alliance (TASA) were significantly higher in the CBT intervention arm than in the TAU arm, t(131) = 4.03, p = 0.001. Measures of symptomatic improvement were greater on all other outcome measures for the CBT arm; however, none reached statistical significance. Effect sizes (Cohen’s d) [69] ranged from small (QIDS-A) to large (TASA).

Table 7. Clinical outcome measures: CBT vs. TAU

Text messaging

A total of 9,613 text messages requiring a response were sent. Of these, 3658 (38.1 %) were responded to. The correlation between improvement on the QIDS-A and percent of texts responded to was not significant (r = 0.165, p = 0.343).

Dropout rate

Seven subjects dropped out prior to week 12 in the TAU arm, compared to 4 subjects in the CBT arm.


Results of this study provide support for the feasibility of this technology-enhanced CBT Intervention as a means of improving CBT treatment of adolescent depression. User satisfaction, a critical component of feasibility, was high for both adolescents and therapists on all components. The program was successful in increasing therapists’ knowledge of CBT concepts and principles. Teens found the online teaching tools useful for learning CBT concepts and skills. They also found the text messaging between sessions helpful, particularly for reviewing work done between sessions with their therapist. All teens indicated they would be willing to use the system again. Rather than put a barrier between the teen and the therapist, the technology improved the therapeutic bond, a critical factor in treatment outcomes. Improving the therapeutic relationship may help to keep teens in treatment, a critical factor for successful outcomes.

From a system delivery perspective, the use of this technology-enhanced intervention is designed to augment rather than replace existing one to one clinician care. As such it is not a low intensity intervention (i.e., an intervention designed to limit therapist time) [70]—and keeps the same number and lengths of session as usual. This approach contrasts recent “stepped-care” models of treatment, which start with the least restrictive treatment with minimal therapist support. Future research can examine the use of this (and similar) technologies within a stepped-care model. This could include examining factors such as length of treatment, use of online self-help combined with therapist and non-therapist support, both with and without text-messaging augmentation.

Effect sizes on the clinical outcomes in the current study were small to medium. According to Cohen, a small effect size is one in which there is a real effect, but can only be seen through careful study. The current study used community clinicians (vs. academic research centers) to see how well the intervention works in a sample of community therapists that not had formal training in CBT. Taken in this light, small effects are encouraging. As the training continues to be evaluated and refined, the impact of additional follow-up training, or live applied training may further improve results. Prior studies with remote CBT training found the addition of live remote observation through a videoconference of trainees conducting CBT, with immediate feedback in real time significantly improved clinical skills [16]. The addition of this applied training component may have improved clinical outcomes. A follow-up study is underway to examine the impact of the addition of live training on post-training treatment outcomes with community patients.

The current program utilized technology to integrate three components as part of a single intervention: therapist training, client education, and treatment implementation and outcomes. As the use of technology continues to be adopted and integrated into clinical treatment, more empirical evidence will help shed light on which components are useful and under what circumstances. At a minimum, the current intervention helps address the critical shortage of training on empirically based treatments. The potential ways in which technology such as text messaging and use of interactive educational tools can enhance treatment are at the start of a new era of clinical research. New possibilities are rapidly emerging, and to some extent, are outpacing our ability to empirically evaluate these new innovations [71]. Some recent data suggest that the explosion of mental health apps has resulted apps of poor quality, or apps that do not reflect clinical practice guidelines or evidence-based practices [72], [73]. However, while presenting many challenges, they also present exciting opportunities. Continued research should continue to generate empirical data to help guide both clinical practice as well as future research in this area.


In the current study, a technology-enhanced CBT Intervention was effective in improving symptoms of depression in adolescents. User satisfaction with the technology was high for both therapists and patients. The therapeutic alliance was stronger in the cohort receiving the technology-enhanced intervention. Effect sizes comparing clinical outcomes between CBT and TAU were small.

Authors’ contributions

JCM and KAK were responsible for developing study design, instrument development, data analysis, and manuscript development. BK provided oversight of clinical content of tutorial, provided input into study design, and manuscript development. All authors read and approved the final manuscript.


The authors would like to acknowledge the contribution of Tracy Reyes for project management, general support, critical review, and subject recruitment, Alison Deep for managing and developing the technology utilized in text messaging and online teaching tools, Rich DeVuono for filming vignettes and photography, and Hal Stokes and Illumnia for tutorial development.

Study funding

This study was supported in part by a Grant from the National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, under Small Business Innovation Research (SBIR) Grant Number R44MH086152.

Competing interests

KAK, JCM, and BK have a proprietary interest in the computer-assisted technology that is under study in the manuscript, and will receive royalties on sales of the program.


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Prevalence of chronic kidney disease among the high risk population in South-Western Ghana; a cross sectional study

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Prevalence of chronic kidney disease among the high risk population in South-Western Ghana; a cross sectional study

Richard KD Ephraim1*, Sylvester Biekpe1, Samuel A. Sakyi23, Prince Adoba1, Hope Agbodjakey1 and Enoch O. Antoh2

Author Affiliations

1 Department of Medical Laboratory Technology, School of Allied Health Sciences, University of Cape Coast, Cape Coast, Ghana

2 Department of Molecular Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

3 Noguchi Memorial Institute for Medical Research, Legon, Ghana

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Canadian Journal of Kidney Health and Disease 2015, 2:40  doi:10.1186/s40697-015-0076-3

The electronic version of this article is the complete one and can be found online at:

Received: 29 April 2014
Accepted: 28 August 2015
Published: 3 November 2015

© 2015 Ephraim et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Chronic Kidney Disease (CKD) is a major global health problem. CKD is one of the most common complications of diabetes mellitus and hypertension and carries a risk of cardiovascular morbidity and mortality and progression to end-stage kidney disease.


This study sought to use the 2012 Kidney Disease Improving Global Outcomes (KDIGO) definitions to establish the prevalence and risk factors for CKD among a high risk population in the Sekondi-Takoradi metropolis.


Cross sectional study.


Effia-Nkwanta regional and the Takoradi Government hospitals in South Western Ghana.


Two hundred eight consecutive adults with diabetes, hypertension or both.


Serum creatinine and urine albumin-creatinine ratio respectively. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) was used to estimate glomerular filtration rate (GFR).


CKD was classified according to KDIGO.


The prevalence of CKD was 30 %: 27 % in patients with diabetes, 22 % in patients with hypertension only and 74 % in patients with both diabetes and hypertension. GFR category G3a CKD was most prevalent stage (9 %). Albuminuria was highest among people with diabetes (39 %).


A convenience sample of patients attending clinics.


CKD was prevalent in these high-risk patients.



L’insuffisance rénale chronique (IRC) est un problème majeur de santé globale. Elle se révèle l’une des plus fréquentes complications du diabète sucré et de l’hypertension. De plus, l’IRC pose un risque accru pour les patients de souffrir, voire de mourir de cardiopathie, ou alors de voir leur état progresser vers l’insuffisance rénale terminale.

Objectifs de l’étude

L’étude a cherché à établir la prévalence et les facteurs de risque de l’IRC dans la population prédisposée de la métropole de Sekondi-Takoradi (Ghana) en utilisant les définitions proposées par « Kidney Disease Improving Global Outcomes » (KDIGO) en 2012.

Type d’étude

Il s’agit d’une étude transversale.

Contexte de l’étude

L’étude a été effectuée sur des patients de l’hôpital régional Effia-Nkwanta et de l’hôpital gouvernemental de Takoradi, dans le sud-ouest du Ghana.


L’étude était constituée d’une cohorte de 208 adultes atteints de diabète, d’hypertension ou d’une comorbidité.


Le rapport albumine-créatinine dans l’urine ainsi que le taux de créatinine sérique ont été mesurés, puis le débit de filtration glomérulaire (GFR) a été déterminé à l’aide de l’équation du « Chronic Kidney Disease Epidemiology Collaboration » (CKD-EPI).


L’IRC a été déterminée selon les critères de KDIGO.


À la suite de cette étude, la prévalence d’IRC a été établie à 30 % parmi les patients de la cohorte. Elle s’établissait à 27 % chez les patients atteints de diabète seulement, 22 % chez les patients atteints d’hypertension seulement et de 74 % chez les patients présentant à la fois du diabète et de l’hypertension. Le stade d’IRC (9 %) le plus prévalent était de catégorie G3a. La prévalence d’albuminurie était plus élevée chez les patients diabétiques (39 %).

Limites de l’étude

Il s’agit d’un échantillon de commodité formé de patients fréquentant les deux cliniques mentionnées plus haut.


La prévalence d’insuffisance rénale chronique était plus élevée chez ce groupe de patients considérés à haut risque.


Chronic Kidney Disease (CKD) is defined as abnormalities of kidney structure or function, present for more than 3 months, with implications for health [1], [2]. It is characterized by either decreased glomerular filtration rate (GFR) or albuminuria, or both, and carries a risk of cardiovascular morbidity and mortality and progression to end-stage renal disease (ESRD) [3]. Chronic kidney disease is thought to be prevalent in sub-Saharan Africa and to be a major public health problem [4]. Resources for recognition and management aiming at reduction in progression are limited, and resources for the treatment of ESRD severely limited [4].

Chronic kidney disease (CKD) is one of the most common complications of diabetes mellitus [5] and hypertension [5]. Screening for CKD is not routinely performed in many diabetic clinics in sub-Saharan Africa because of limited human resource, diagnostic facilities and the cost of the tests [5]–[7].

Several studies within sub-Saharan Africa have examined the prevalence of CKD in people at high risk, including those with diabetes and hypertension. Janmohamed et al., [7] recorded 84 % prevalence in adult outpatients with diabetes in Tanzania, and Osafo et al. [8] showed a CKD prevalence of 47 % among Ghanaian patients, mainly from the Greater Accra region, with hypertension. In addition, Sumaili et al., [9] recorded 44 % prevalence in patients with hypertension, 39 % in those with diabetes; 16 % in people with obesity and 12 % in those who had human immunodeficiency virus (HIV) or acquired immunodeficiency syndrome (AIDS). We used the 2012 guidelines of the kidney disease improving global outcomes (KDIGO) to classify CKD among patients with diabetes, hypertension and both and also identified the associated risk factors for CKD in the Sekondi-Takoradi metropolis in south western Ghana.


Study design and study site

A cross-sectional study was conducted at the outpatient diabetes and hypertension clinics of the Effia-Nkwanta Regional hospital (ERH) and the Takoradi Government Hospital (TGH) in the Sekondi-Takoradi metropolis between December 2012 and May 2013. These serve as the major healthcare facilities in the metropolis providing primary, secondary and tertiary healthcare services for a population of 445,000. The healthcare system is accessible to those who contribute or pay the minimum of GH 20.0 yearly premium, equivalent to about three times the daily minimum wage of GH 6.0; about 66 % of the population is covered. In Ghana, patients with diabetes or hypertension receive specialized care in teaching, regional or municipal hospitals since they are the only facilities with the capacity to diagnose and manage this condition. Sekondi-Takoradi is the administrative capital of the Western Region. It has a land area of 385 km 2 and is located in the South-Western part of Ghana and about 242 km west of Accra, the capital city of Ghana.

Inclusion and exclusion criteria

We enrolled eligible adult (>18 years) outpatients receiving medical care at the diabetes and hypertension clinics of the hospitals during the study period. Patients diagnosed with high blood pressure or on anti-hypertensive drugs, diabetes or both hypertension and diabetes were included in this study. We excluded patients with other kidney diseases (such as glomerulonephritis, vasculitis, kidney infection, connective tissue disease or adult polycystic kidney disease), those undergoing peritoneal or hemodialysis, and those with inflammatory bowel disease or rheumatoid arthritis. We also excluded people with known hepatitis B or C and HIV/AIDS.

Patient screening, recruitment and data collection

We screened 382 consecutive patients with diabetes, hypertension or both who visited the outpatient department of the two hospitals for routine evaluation. Diabetes was defined as a diagnosis of diabetes or taking a hypoglycaemic drug, and hypertension as a diagnosis of hypertension or taking an anti-hypertensive drug. Information on age, gender, fasting blood glucose, body mass index (BMI), systolic blood pressure and diastolic blood pressure, medication used, duration on medication, and duration of diabetes was obtained using a pre-tested questionnaire and the patient medical records.

Measurement of blood pressure

Trained personnel used a mercury sphygmomanometer (ACCOSON, England) with a standard or a large cuff, appropriate to the patient’s size, to measure blood pressure after patients rested for 5 min, in accordance with recommendations of the American Heart Association Council on High Blood Pressure Research [10]. We report mean values of duplicate measurements.

Body mass index (BMI)

Height (nearest centimetre) and weight (nearest 0.1 kg), without shoes and in light clothing were measured. Participants were weighed on a bathroom scale (Zhongshan Camry Electronic Co. Ltd, Guangdong, China) and their height measured with a wall-mounted ruler. BMI was calculated by dividing weight (kg) by height squared (m 2 ), and categorized according to WHO criteria into normal weight (BMI 18.5–24.9), underweight (<18.5), overweight (25.0–29.9), obese (30.0–39.9) [11].

Blood sample collection and processing

A 4 ml venous blood sample was collected from each participant and 1 and 3 ml were dispensed into a fluoride oxalate tube and a serum gel separator tube respectively. After centrifugation at 1500 g for 3 min, the plasma and serum were stored in cryovials at −80 °C until assays were performed.

Biochemical analysis

Plasma fasting blood sugar (FBS), serum urea and creatinine were estimated using automated chemistry analyzer (Selectra JR). Estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation using the coefficients for black ethnicity in all [12].

Urine sample collection and processing

Urine protein was quantitatively estimated using the method of [13]. Estimation of urine creatinine was done using automated analyzer (ENVOY500/BT 3000 chemistry analyzer. Urine protein-creatinine ratio (uPCR) was calculated by the following formula: uPCR (mg/mmol = urine protein (mg/dl)/urine creatinine (mmol/dl). The urine protein/creatinine ratio (uPCR) was reported as mg/mmol. Resources were not available to measure albuminuria. The relationship between uACR and uPCR is not a simple one, so we did not attempt to convert between the two [14]. Instead we report uPCR in uACR categories, recognizing that this leads to overestimation of the proportions of patients with problems.

Statistical analysis

Analysis was performed using Graphpad prism version 5.0 (GraphPad software, San Diego California USA, Two-sample Student’s t test and chi-squared or Fisher’s exact test, as appropriate, and one-way analysis of variance (ANOVA) were used to compare groups. A P-value ≤0.05 was considered statistically significant.

Ethical considerations

The study was approved by the University of Cape Coast institutional review board (UCC/IRB) and the committee of ethics of TGH and ERH. Written informed consent was obtained from all participants.


Study procedures including collection of clinical data and the laboratory tests were funded by the authors.


We screened 382 consecutive patients, of whom 76 were less than 18 years, and 67 declined to participate: of the 239 consenting participants, 208 provided both blood and urine samples (i.e., 87 % with complete data) and are the subject of this report. Mean age was 60 and 71 % were female (Table 1); blood pressure was higher in participants with known hypertension. The distribution of body weight did not vary with diagnosis (diabetes, hypertension or both) (Table 1). Figures 1 and 2 report the types of medication used by participants and the types of medications used by hypertensives and diabetics respectively.

Table 1. Demographic, clinical and biochemical characteristics of study participants stratified by clinical conditions

thumbnailFig. 1. Types of medications used by participants

thumbnailFig. 2. Medications used by participants with diabetes and hypertension

Overall, 13 of 208 participants (6.2 %) had GFR less than 30, and 50 (24 %) had eGFR less than 60 mL/min/1.73 m 2 (Table 2); 4 of 40 participants (10 %) had uPCR > 30 mg/mmol, and 43 (96 %) had uPCR 3–30 mg/mmol. GFR less than 30 mL/min/1.73 m 2 and uPCR > 3 were more prevalent in those with both diabetes and hypertension than in patients with just one diagnosis (Table 3). Age and gender were similar across eGFR categories, but patients with the lowest eGFR had the highest systolic and diastolic blood pressures, and systolic blood pressure was above 140 in 17 and 26 % respectively of those in eGFR categories 3a and 3b, and in 36 % of those in eGFR category 4 (eGFR less than 30 mL/min/1.73 m 2 ).

Table 2. Prevalence of albuminuria, estimated glomerular filtration rate (eGFR) and stages of CKD stratified by clinical conditions

Table 3. Prevalence of albuminuria and estimated glomerular filtration rate (eGFR) stratified by clinical conditions

Table 3 show the distribution of patients by GFR and albuminuria categories, for those with hypertension, diabetes and both diabetes and hypertension. Overall, 30 % of participants fell into the category defined by KDIGO as ‘very high risk’: 23 % of patients with hypertension, 27 % of patients with diabetes and 74 % of those with both diabetes and hypertension.

Multivariable predictors of the presence of CKD were diagnosis category and duration on medication, both with odds ratios around 10, but not age, gender or BMI (Table 4).

Table 4. Multivariable associations of clinical variables with CKD in high-risk population


We identified a prevalence of CKD in patients with hypertension of 22 % and in patients with diabetes of 27 %. In patients with both hypertension and diabetes, the prevalence was 74 %, and 26 % had category G4 CKD. Clinical factors associated with a greater risk of CKD were the presence of both hypertension and diabetes, and duration on medication (antidiabetic and antihypertensive).

Osafo and colleagues [8] reported a 47 % prevalence of CKD among patients with hypertension in Ghana, in a multicenter study conducted predominantly among people with hypertension in the Greater Accra area (known for a high prevalence of hypertension). This is higher than the overall prevalence of 30 % among our study participants, and 22 % in people with hypertension. The difference may, in part, be owing to our having used the CKD-Epi [12] equation rather the MDRD equation, which was used in the study by Osafo and colleagues. MDRD is known to overestimate the prevalence of CKD compared with CKD-Epi, and this has also been shown by Kitiyakara and colleagues in their study of the high risk population in South East Asia [15]. In all patients with diabetes (with or without hypertension) we observed a prevalence of 48 %, which is lower than the 80 % prevalence observed among African adults with diabetes in a cross-sectional study conducted in Tanzania by Janmohamed and colleagues [7]. Again this is not directly comparable, with differences arising from their use of Cockroft-Gault equation to calculate the eGFR (which overestimates true GFR and underestimates prevalence); and urine albumin concentration as a measure of proteinuria (which is the recommended method of assessing proteinuria; our use of uPCR overestimates prevalence) but both these differences would result in a tendency for our prevalence by our methods to be higher than by their methods; so it may be that true differences exist. However, neither study used IDMS calibrated creatinine measurement and the direction of biases resulting from this limitation cannot be assessed.

Osafo and colleagues [8] observed a 51 % prevalence of CKD in patients with coexistent diabetes and hypertension, based on data from 712 participants in a multicenter study in Accra, Ghana, and we observed 74 % prevalence of CKD in our participants. Since their use of the MDRD formula would have biased their findings towards a greater incidence of CKD, it is possible that the prevalence is truly higher in this group in Ghana.

Good blood pressure control and ACE inhibitors are known to have a reno-protective effect, particularly in people with albuminuria [16]. In our study, 30 % overall, 11.1 % of people with diabetes and hypertension, 9.2 % of people with albuminuria and hypertension received ACE inhibitor therapy. We are unable to determine from our study to what extent this relatively low prevalence represents true contraindications or previous adverse effects, or whether this is a possible missed treatment opportunity that results from the economic costs of the drug (most of which are borne by the patients) or a reluctance on the part of physicians to prescribe ACE inhibitors without access to repeated monitoring of renal function (laboratory tests are paid for by the patient).

Our study has several limitations. First our findings cannot be generalized to other low income and low resource countries because it was not community based and was conducted within a population at risk of developing CKD with genetic and cultural differences. Further, there may be differences in the practices that lead to a patient being identified as having hypertension or diabetes, and differences in access to treatments for, and monitoring of those conditions. The study was conducted in the Sekondi-Takoradi metropolis. It is likely that there would be significant variation in prevalence rates in other urban and rural towns in the Western region and across Ghana as a whole. This study is also limited by the small sample size, use of the single measurement of serum creatinine (whereas to truly fulfill definitions of CKD, two measurements at least 3 months apart are needed), and by our lack of standardization of serum creatinine to isotope mass dilution spectrophotometry (IMDS). Third, although the CKD-EPI eGFR equation has been used in previous studies in this population [8], [18], [19] it has not been validated for use in the black Ghanaian population. Strengths of our study are the consecutive sampling and completeness of data collection.


CKD was detected among 30 % of this high-risk population. Further research is needed into optimal approaches to screening and treatment, including research on the effects of lowering economic barriers to known effective treatments. This is particularly important in resource-constrained practice settings such as ours, because the impact of the development of end-stage renal disease when dialysis cannot be provided is so much greater.

Competing interests

The authors declare that there is no conflict of interest associated with this manuscript.

Authors’ contributions

RKDE, SB, SAS and HA were involved in conception of the idea and study design and data analysis. RKDE, SB, PA and EOA were involved in recruitment of participants, data collection and compilation. RKDE, SB, SAS and EOA were involved in laboratory work, literature search and drafting of the manuscript. RKDE, PA and HA were involved in revision and final approval of the manuscript. All authors read and approved the final manuscript.


The authors appreciate the contributions Mr. Samuel K. Danquah and the staff and management of the Effia Nkwanta Regional Hospital (ENRH) and the Takoradi Government Hospital (TGH) especially the Laboratory Department in making this work a success. We also appreciate the contributions of the humble people of the Sekondi-Takoradi metropolis for availing themselves for this research.


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The effectiveness of interventions to improve uptake and retention of HIV-infected pregnant and breastfeeding women and their infants in prevention of mother-to-child transmission care programs in low- and middle-income countries: protocol for a systematic review and meta-analysis

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The effectiveness of interventions to improve uptake and retention of HIV-infected pregnant and breastfeeding women and their infants in prevention of mother-to-child transmission care programs in low- and middle-income countries: protocol for a systematic review and meta-analysis

Lisa M. Puchalski Ritchie123, Monique van Lettow45*, Mina C. Hosseinipour67, Nora E. Rosenberg67, Sam Phiri8, Megan Landes39, Fabian Cataldo4, Sharon E. Straus12 and For the PURE consortium

Author Affiliations

1 Department of Medicine, University of Toronto, Toronto, ON, Canada

2 Li Ka Shing Knowledge Institute, St. Michaels Hospital, University of Toronto, Toronto, ON, Canada

3 University Health Network, Toronto, ON, Canada

4 Dignitas International, Zomba, Malawi

5 Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

6 Division of Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA

7 University of North Carolina Project, Lilongwe, Malawi

8 Lighthouse Trust, Lilongwe, Malawi

9 Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada

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Systematic Reviews 2015, 4:144  doi:10.1186/s13643-015-0136-x

The electronic version of this article is the complete one and can be found online at:

Received: 5 June 2015
Accepted: 15 October 2015
Published: 3 November 2015

© 2015 Puchalski Ritchie et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Despite recent improvements, uptake and retention of mothers and infants in prevention of mother-to-child transmission (PMTCT) services remain well below target levels in many low- and middle-income countries (LMICs). Identification of effective interventions to support uptake and retention is the first step towards improvement. We aim to complete a systematic review and meta-analysis to evaluate the effectiveness of interventions at the patient, provider or health system level in improving uptake and retention of HIV-infected mothers and their infants in PMTCT services in LMICs.


We will include studies comparing usual care or no intervention to any type of intervention to improve uptake and retention of HIV-infected pregnant or breastfeeding women and their children from birth to 2 years of age attending PMTCT services in LMICs. We will include randomized controlled trials (RCTs), cluster RCTs, non-randomized controlled trials, and interrupted time series. The primary outcomes of interest are percentage of HIV-infected women receiving/initiated on anti-retroviral prophylaxis or treatment, percentage of infants receiving/initiated on anti-retroviral prophylaxis, and percentage of women and infants completing the anti-retroviral regimen/retained in PMTCT care. The following databases will be searched from inception: Ovid MEDLINE and EMBASE, The WHO Global Health Library, CAB abstracts, EBM Reviews, CINAHL, HealthSTAR and Web of Science databases, Scopus, PsychINFO, POPLINE, Sociological Abstracts, ERIC, AIDS Education Global Information System, NLM Gateway, LILACS, Google Scholar, British Library Catalogue, DARE, ProQuest Dissertation & Theses, the New York Academy of Grey Literature, Open Grey, The Cochrane Library, WHO International Clinical Trials Registry, Controlled Clinical Trials, and Reference lists of included articles will be hand searched and study authors and content experts contacted to inquire about eligible unpublished or in progress studies. Screening, data abstraction, and risk of bias appraisal using the Cochrane Effective Practice and Organization of Care criteria will be conducted independently by two team members. Results will be synthesized narratively and a meta-analysis conducted using the DerSimonian Laird random effects method if appropriate based on assessment of clinical and statistical heterogeneity.


Our findings will be useful to PMTCT implementers, policy makers, and implementation researchers working in LMICs.

Systematic review registration

PROSPERO CRD42015020829


HIV; Prevention of mother-to-child transmission; Interventions; Retention; Uptake


Although the incidence of pediatric HIV acquisition is falling, over 240,000 children were newly infected with HIV in 2013, primarily through mother-to-child transmission [1]. Prevention of mother-to-child transmission (PMTCT) therapeutic regimens have been proven to reduce the risk of mother-to-child transmission from 20–45 % to 2 % in non-breastfeeding populations and 5 % or less in breastfeeding populations [2]. However, despite recent improvements in PMTCT clinical service coverage in low- and middle-income countries (LMICs) from 10 % in 2004 to 67 % in 2013, uptake and retention of mothers and newborns in PMTCT clinical services remain well below target levels in many LMICs [1], [2]. PMTCT services begin with maternal HIV testing and counseling and for HIV-infected women include the following: initiation and maintenance of pregnant and nursing women and their infants on PMTCT medication regimens for the duration of treatment as defined by the specific regimen employed; and completion of appropriate infant HIV testing. As a result of the 2010–2015 PMTCT strategic vision, the World Health Organization (WHO) has called for renewed commitment and effort towards achieving universal PMTCT coverage. The identification of interventions to support PMTCT uptake and retention is the first step towards improvement.

To date, two systematic reviews have been published that specifically evaluated the effectiveness of interventions to improve PMTCT coverage. Both were limited to specific interventions—male involvement [3] and integration of services [4] —and found too few studies meeting inclusion criteria to assess or make recommendations regarding effectiveness. A third systematic review indentified nine completed studies and five ongoing trials which examined initiation of antiretroviral (ARV) treatment in pregnant women [5]. While the authors report several promising interventions for improving ARV initiation, the quality of evidence was insufficient to support recommendations. In addition, results for ARV initiation in pregnant women were not independently examined, and maternal retention in PMTCT care and exposed infant care were not assessed. However, in our preliminary search, we identified a number of additional interventions including integration of HIV and antenatal care, peer-based programs, and community health worker programs [6]–[8] that have been evaluated to improve PMTCT uptake and retention in LMICs.

Given the paucity of synthesized evidence to date, we propose to complete a systematic review to identify what interventions are effective in improving uptake and retention of HIV-infected mothers and their infants in PMTCT services in LMICs. While we anticipate a relatively small number of evaluations of any given intervention type, which may preclude meta-analysis, a narrative synthesis of the evidence to date is urgently needed to inform LMIC PMTCT program development and policy. With the exception of Option B+ (lifelong triple ARV therapy for all HIV+ pregnant and breastfeeding women, regardless of clinical stage or CD4 count) recommended by WHO in April 2012 for which evidence is not yet available, the effectiveness of PMTCT regimens is well established and will therefore not be included in the present search [9].



A preliminary systematic review protocol was developed based on the Cochrane Handbook [10]. The protocol was revised with input from the PURE Malawi Consortium, a research partnership of governmental, non-governmental, and academic organizations working to improve PMTCT programming in Malawi. The final protocol was registered with the PROSPERO database (CRD42015020829, available at:, with reporting of the protocol guided by the PRISMA-P [11].

Eligibility criteria

We will include studies of HIV-infected pregnant and breastfeeding women and their children from birth to 2 years of age or termination of breastfeeding in LMICs. For the purpose of this review, we will utilize the EPOC filter to identify low- and middle-income countries [12] updated using the most recent World Bank World Country and Lending group classification [13] to define LMICs. Based on the unique challenges facing PMTCT health services in LMICs and intended use of the findings of this review to inform PMTCT service development in Malawi and other LMICs, we chose to limit the review to studies conducted in LMICs. Studies conducted only in high-income countries or where LMIC results cannot be separated will not be eligible for inclusion.

We will include studies comparing usual care or no intervention to any type of intervention (including patient, provider, or health system level interventions) to improve uptake and retention of HIV-infected pregnant or breastfeeding women and their children from birth to 2 years of age in PMTCT services. Patient level interventions are those focused on the patient and may include patient education programs, peer support programs, or efforts to improve patient support through engagement of partners or family members. Provider level interventions may include provider training, incentive programs, or tools to improve care provided. Health system level interventions may include restructuring of services and task shifting or other mechanisms to address human resource shortages.

The primary outcomes of interest are percentage of HIV-infected women receiving or initiated on ARV prophylaxis or treatment, percentage of infants born to HIV-infected mothers receiving or initiated on ARV prophylaxis, and percentage of women and infants retained in PMTCT care/completing the ARV regimen as defined by the PMTCT regimen utilized. Secondary outcomes of interest include the following: percentage of infants completing post-exposure HIV testing at 4–6 weeks after birth and percentage of infants completing post-exposure HIV testing at 6 weeks following termination of breastfeeding for all infants with known HIV exposure as recommend by the WHO [14]; percentage of HIV-exposed infants testing positive for HIV; and adverse events including negative impact(s) on resources/delivery and/or effectiveness of other health care programs (including economic impact), major (e.g., heart defects, neural tube defects, major limb malformations, hypospadias) or minor (e.g., syndactyly, cutis aplasia, accessory digit) congenital malformations, small for gestational age, premature delivery, still birth, and infant death within the first 2 years of life).

We will include controlled experimental studies (randomized controlled trials, cluster randomized controlled trials, non-randomized controlled trials) and controlled quasi-experimental studies (interrupted time series). We chose to include non-randomized controlled trials and quasi-experimental designs based on the results of our scoping searches, in which we found few randomized controlled trials that evaluated interventions to improve uptake and retention of HIV-infected women and their children in PMTCT services conducted in LMICs. Language of publication will be restricted to the language spoken by the study team and includes English only. No restrictions will be placed on publication status, study time frame, or duration of follow-up.

Information sources and literature search

Our search strategy was developed in consultation with an experienced information specialist and peer reviewed by two additional information specialists with expertise in systematic reviews using the Peer Review of Electronic Search Strategies checklist [15].

We will search the following electronic databases from inception to June 2015 using medical subject headings (MeSH) and text words related to HIV, pregnancy, breastfeeding, mother-to-child transmission, interventions, treatment uptake and retention, and low- and middle-income countries, using MEDLINE (OVID interface, 1946 to July Week 4 onwards), EMBASE (OVID interface, 1974 onward), The WHO Global Health Library (, CAB abstracts (OVID interface, 1973 onward), EBM Reviews (OVID interface, 1991 onward), CINAHL (EBSCOhost Research Databases interface, 19,814 onward), HealthSTAR (OVID interface, 1966 onward) and Web of Science databases (Thompson Reuters interface, 1975 onward), Scopus (Elsevier Interface, 1823 onward), PsychINFO (OVID interface, 1806 onward), POPLINE (, 1970 onward), Sociological Abstracts (Proquest interface, 1953 onward), ERIC (EBSCOhost Research Databases interface, 1966 onward), AIDS Education Global Information System (, NLM Gateway (, LILACS (, Google Scholar (, British Library Catalogue (, DARE (LexisNexis Academic interface, 2010 onward), ProQuest Dissertation & Theses (Proquest Interface, 1637 onward), the New York Academy of Grey Literature (, OpenGrey (, The Cochrane Library (, WHO International Clinical Trials Registry (, Controlled Clinical Trials (, and ( In addition, we will search reference lists of included articles and will contact experts in the field to inquire about eligible unpublished or in progress studies. Low- and middle-income countries will be searched utilizing the EPOC LMIC filter [12], updated based on the most recent World Bank LMIC list [13], see Additional file 1 for full MEDLINE search strategy. We will employ the Cochrane highly sensitive search strategy for identifying randomized trials in OVID MEDLINE: sensitivity and precision maximizing version [16], with the following two changes: Random* was used in place of randomized or randomly and trials ti was not used as an isolated term.

Study selection process

All titles and abstracts identified by the database search will be entered into a reference manager and duplicates removed manually into the duplicate folder, with companion papers for the same study retained for further evaluation at the full article phase of the review. Citations will be screened in two phases, level 1 (titles and abstracts) and level 2 (full-text review). A screening checklist will be developed and pilot tested by the reviewers on a random sample of 50 citations for each screening phase. Inter-rater agreement will be calculated for the pilot test and the form revised and re-piloted if percent agreement is <90 %. Once adequate agreement has been achieved, two team members will independently screen citations using the screening checklist. Differences at each stage will be resolved by consensus and if necessary through discussion with a third team member who is a content expert. Reference lists of included studies will be reviewed independently by the same two team members and again differences resolved through consensus and if necessary consultation with a third team member. A review log will be maintained in order to provide a record of resolution of discrepancies, decisions regarding studies described in >1 report, and reasons for exclusion.

Data abstraction and management

Data abstraction forms will be developed and pilot tested. Two team members will independently abstract directly into excel spreadsheets, corresponding to outcome tables, with additional space for comments and reasons for exclusion. Inter-rater reliability will be measured for data abstraction on a sample of excluded and included articles (approximately 10 %), and if percent agreement is found to be below 90 %, abstraction is conducted by a third team member. All discrepancies will be reviewed and consensus reached through discussion.

Data abstraction will be based on the PICOST [17] format including population, intervention, comparator, context, outcomes, study DESIGN, and time frame. Population characteristics to be abstracted include maternal age, number of children, marital status, place of residence (rural/urban), level of education, primary language, first infant HIV testing (4–6 weeks), and at end of study. Study characteristics of interest include study design, country and geographical location within country (rural/urban), setting (home, hospital or health center clinic, maternity ward), detailed description of intervention and comparator (usual care/no intervention), number of participants per group at study baseline and follow-up, duration of intervention and follow-up period, source of data (self-report, clinical records, pill counting), and publication status. Outcome data to be abstracted include percentage of HIV-infected women and their infants receiving or initiating PMTCT treatment, retained in or completing PMTCT as defined by the PMTCT regimen(s) used. Where data necessary for analysis are missing, corresponding authors will be contacted.

Although improved in recent years, examples of cluster trails inappropriately analyzed (without adjustment for cluster randomization) may be found among older trials. Data on appropriateness of analysis will be abstracted and reported as part of the review findings.

Methodological quality/risk of bias appraisal

Risk of bias assessment will be conducted using the Cochrane Effective Practice and Organization of Care (EPOC) criteria for assessing risk of bias [18]. Categories of bias assessed by this tool for randomized controlled trials, and non-randomized controlled trails include: allocation concealment, measurement of baseline characteristics and outcomes, management of incomplete data, blinding of outcome assessment, protection against contamination, selective reporting, and other categories of bias [18]. Categories of bias assessed by this tool for interrupted time series and repeated measures studies include independence of intervention from other changes, pre-specification of the intervention effect shape, effect of data collection on the intervention, allocation concealment, management of incomplete data, selective reporting, and other sources of bias [18]. Two team members will independently assess the studies for risk of bias at both study and outcome levels with disagreement resolved by consensus and discussion with a third team member if necessary. Studies will not be excluded based on risk of bias assessment, but the information will be used in the analysis and reporting of findings. Risk of bias will be categorized as low, high, or unclear risk of bias, using the EPOC-suggested risk of bias criteria [18]. We have elected not to use GRADE for this review given that the review findings are urgently needed to inform PMCTC program development and policy and that the need to build capacity in the use of grade across the team which would significantly prolong the review timeline.

Risk of publication bias will be examined using funnel plots. For studies in which selected reporting bias is suspected, planned outcomes will be reviewed for registered trials and authors contacted for missing outcomes and for unregistered trials, and risk of selected reporting bias rated as unclear if response not received within 8 weeks of our initial email request.

Evidence synthesis

A flow diagram will be utilized to visually present the results of the search strategy and reasons for exclusion of articles. Included articles will be synthesized and reported narratively and in tabular form to provide an overview of findings, assessment of bias and its potential impact on reported findings, and strengths and weaknesses of included studies. Summary statistics for continuous outcomes will be expressed as mean difference and standardized mean difference with 95 % CIs, for outcomes reported using the same and different scales, respectively. Summary statistics for dichotomous data will be expressed as risk ratio with 95 % CI.

If meta-analysis is possible, it will be conducted using the DerSimonian Laird random effects method. Summary statistics will be expressed as risk ratios with 95 % confidence interval. Clinical heterogeneity will be determined based on patient, intervention, and outcome characteristics of included studies. Statistical heterogeneity will be determined visually and the impact of heterogeneity assessed using the I 2 test, with I 2 of 75 % considered significant. Given the time constraints for this review, re-analysis for unit of analysis errors will not be conducted and cluster trials with unit of analysis errors will be excluded from the primary meta-analysis, and their impact assessed with sensitivity analysis comparing meta-analysis with and without studies with unit of analysis errors included. Interventions at the patient, provider, and health system level will be reported separately and analyzed separately if possible to do so.


The findings of this review will have significant implications for PMTCT program development and policy in LMICs. If high-quality evidence of intervention effectiveness is identified, this will provide important guidance to ongoing efforts to address low rates of uptake and retention of HIV-infected mothers and their infants in PMTCT services in LMICs. If high-quality evidence is not identified, findings of the systematic review may identify gaps in evidence and promising interventions providing direction for future intervention research.

To ensure our findings reach audiences who may benefit from the review findings, we plan to disseminate the results through publication in open access peer-reviewed journals, presentations at relevant international conferences, and direct communication within the professional networks of PURE consortium members.


ARV: anti-retroviral

EPOC: Effective Practice and Organization of Care

HIV: human immunodeficiency virus

LMIC: low- and middle-income country

MeSH: medical subject headings

PMTCT: prevention of mother-to-child transmission

WHO: World Health Organization

Competing interests

LPR was funded by a KT Canada Strategic Training Initiative in Health Research Fellowship award in 2014. SS is funded by a Tier 1 Canada Research Chair in Knowledge Translation and Quality of Care. The authors have declared that no competing interests exist. The authors alone are responsible for the writing and content of the paper.

Authors’ contributions

LPR and MvL conceived the study. LPR and SS were responsible for developing the search strategy. LPR was responsible for preparing and registering the protocol and for manuscript preparation. LPR, MvL, and SS were responsible for finalizing the protocol. MCH, NER, SP, ML, and FC provided content expertise and assisted with preparation of the protocol and manuscript. All authors provided critical revision of the protocol and manuscript. All authors read and approved the final manuscript.

Additional file

Additional file 1:. Ovid MEDLINE search strategy. (DOC 39 kb)

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We thank Melanie Anderson for her assistance with developing the search strategy and Elise Cogo and Becky Skidmore for peer reviewing our MEDLINE search strategy.


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  3. Brusamento S, Ghanotakis E, Tudor Car L, van-Velthoven MHMMT, Majeed A, Car J. Male involvement for increasing the effectiveness of prevention of mother-to-child HIV transmission (PMTCT) programmes (Review). The Cochrane library, 2012, issue 10. accessible at. http://www. OpenURL
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Increased circulating follicular helper T cells with decreased programmed death-1 in chronic renal allograft rejection

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Increased circulating follicular helper T cells with decreased programmed death-1 in chronic renal allograft rejection

Jian Shi1, Fengbao Luo1, Qianqian Shi1, Xianlin Xu1, Xiaozhou He1* and Ying Xia2*

Author Affiliations

1 Third Clinical College of Soochow University, Changzhou, Jiangsu, China

2 The University of Texas Medical School at Houston, Houston, TX, USA

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BMC Nephrology 2015, 16:182  doi:10.1186/s12882-015-0172-8

The electronic version of this article is the complete one and can be found online at:

Received: 26 May 2015
Accepted: 19 October 2015
Published: 3 November 2015

© 2015 Shi et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Chronic antibody-mediated rejection is a major issue that affects long-term renal allograft survival. Since follicular helper T (Tfh) cells promote the development of antigen-specific B cells in alloimmune responses, we investigated the potential roles of Tfh cells, B cells and their alloimmune-regulating molecules in the pathogenesis of chronic renal allograft rejection in this study.


The frequency of Tfh, B cells and the levels of their alloimmune-regulating molecules including chemokine receptor type 5 (CXCR5), inducible T cell co-stimulator (ICOS), programmed death-1 (PD-1), ICOSL, PDL-1 and interleukin-21 (IL-21), of peripheral blood were comparatively measured in 42 primary renal allograft recipients within 1–3 years after transplantation. Among them, 24 patients had definite chronic rejection, while other 18 patients had normal renal function.


Tfh-cell ratio was significantly increased with PD-1 down-regulation in the patients with chronic renal allograft rejection, while B cells and the alloimmune-regulating molecules studied did not show any appreciable change in parallel.


The patients with chronic renal allograft rejection have a characteristic increase in circulating Tfh cells with a decrease in PD-1 expression. These pathological changes may be a therapeutic target for the treatment of chronic renal allograft rejection and can be useful as a clinical index for monitoring conditions of renal transplant.


Chronic renal allograft rejection; Tfh cells; PD-1


Renal transplantation remains an effective treatment for end-stage renal dysfunction [1], facilitating a return to normal health and prolonging life. However, antibody-mediated rejection is a major issue that affects long-term renal allograft survival. Despite the rapid development of new immunosuppressive drugs for attenuating acute rejection, improving the long-term survival of grafts is still a challenge mainly because of chronic allograft rejection. The features of chronic renal allograft rejection are hypertension, proteinuria, progressive deterioration of graft function, peritubular capillary C4d deposition, presence of donor-specific antibodies (DSA) and morphological changes with transplant vasculopathy, glomerulopathy, fibrosis and lymphocyte infiltration. However, the causes leading to chronic rejection are complex and not well understood yet [2].

Allograft rejection is characterized by an increase in activated CD4+ T-lymphocytes, especially regulatory and cytotoxic T cells, leading to an imbalance of immune responses in the transplant recipients [3], [4]. Functionally, CD4+ T helper cells that interact with antigen-specific B cells are required for the production of alloantibodies [5]. Among them, Tfh cells, a recently defined subset of CD4+ T cells, play a particular role in mediating B cell-driven allogeneic responses. Tfh cells can migrate into germinal centers and promote B-cell activation and differentiation into immunoglobulin-producing plasmablasts or plasma cells [5]. They can express PD-1, CXCR5, ICOS, IL-21 and the transcription factor B-cell lymphoma 6 (Bcl-6) [6], [7], thereby displaying their regulatory functions.

Circulating Tfh cells, peripheral counterparts of conventional Tfh cells, express PD-1, CXCR5, ICOS and IL-21, but not Bcl-6 [5]–[7]. They play an important role in human humoral immunity through these functional molecules. Their abnormal activities are critically involved in the onset of several human diseases such as autoimmune disorders, cancer and infective diseases [7]–[10]. Therefore, an alteration in circulating Tfh cells may be correlated with disease conditions and might be used as a biomarker of certain diseases [11]–[13]. Moreover, recent clinical studies have shown that peripheral Tfh cells in the kidney transplant recipients with acute rejection can regulate B-cell alloreactivity and the number of these Tfh cells alters the immunization status and DSA levels [14]. However, their function and relevance to chronic renal allograft rejection are not known yet.

This study was conducted to explore the potential association between circulating Tfh cells and chronic rejection in kidney transplant recipients. The outcome results may provide a useful hint for clinical prediction of renal status after transplantation and for a potential new therapy for chronic allograft rejection.


This study was approved by the Institutional Ethics Committee of Third Affiliated Hospital of Soochow University, Jiangsu Province, China. Written-informed consent was obtained from all participants of the study.


The patients with primary renal transplantation for 1–3 years were enrolled from October 2013 to December 2014. Totally 42 recipients were studied in this work, including 24 patients with chronic rejection (CR group) and 18 patients with normal renal function as the normal control (NC group). All of them received the treatment with cyclosporine A, methylprednisolone and mycophenolate mofetil or azathioprine after the renal transplantation. The diagnosis for chronic allograft rejection was confirmed by renal biopsy, biochemical measurements and immunological assays, including DSA as described in other studies [15]–[18]. In specific,the diagnostic criteria included 1) clinical evidence of slowly deteriorating graft function; 2) biopsy evidence and diffuse deposition of C4d; and 3) the presence of circulating DSA at the time of biopsy. Their peripheral blood samples were collected in a standard way by the clinical laboratory of the hospital. All the subjects had no infective disease when sampling blood.

Surface staining and flow cytometry analysis

The whole blood was subjected to flow cytometry detection by a BD bioscience FACSCantoII cytometer with FACSDiva software for measuring the frequency of circulating Tfh cells and B cells as well as the expression of their surface markers. The following conjugated monoclonal antibodies were used to stain the cells: CD4-FITC, CXCR5-APC, ICOS-PE, PD-1-PE, CD19-PE-Cy5.5, ICOSL-PE and PDL-1-APC. The cells were incubated with the antibodies for 30 min at room temperature in the dark. Totally 50,000 lymphocytes were acquired in each sample. Data were analyzed using Flow Jo software 7.6.1.

Enzyme-linked immunosorbent assay (ELISA)

The levels of serum IL-21 were quantified by using the human IL-21 ELISA kit (eBioscience) according to the manufacturer’s instructions. The concentration in each individual sample was calculated according to the standard curve.

Statistical analyses

All experimental data were analyzed by Graph Prism version 5.0. The results were expressed as mean ± SD and subjected to t test for statistical comparisons between the NC and CR groups. If a p-value was found to be less than 0.05, the result would be considered statistically significant.



The general information of the renal transplant recipients was summarized in Table 1. Gender and age were similar between CR and NC groups. The mean serum creatinine (sCr) and blood urea nitrogen (BUN) were almost three-fold higher in the CR patients than those of NC group (p < 0.001).

Table 1. General information of the renal transplant patients

Increased circulating Tfh cells in the CR patients

To determine if chronic rejection was associated with an alteration in circulating Tfh cells in the renal transplantation recipients, we first evaluated the frequency of CD4 + CXCR5+ Tfh cells through flow cytometry. As shown in Fig. 1, the percentage of CD4 + CXCR5+ Tfh cells among total CD4+ T cells was significantly increased in the CR group as compared to that of the NC group (35.3 ± 8.5 % vs.19.0 ± 5.0, P < 0.001).

thumbnailFig. 1. Frequency of Tfh cells in the patients with renal allograft. a, representative contour plots of the ratio of Tfh cells in the NC and CR groups, b, mean values of the frequency of Tfh cells in the two groups. ***, P < 0.001. Note a significant increase in Tfh cells in the CR group compared to that of the control group

Differential changes in PD-1, CXCR5, ICOS, and IL-21 of Tfh cells in the CR patients

We further detected the changes of PD-1, CXCR5 and ICOS in the high frequency of Tfh cells and found that PD-1 was significantly down-regulated in these Tfh cells (Fig. 2a). In sharp contrast, there were no significant changes in CXCR5 and ICOS in the CR group as compared to the NC group (Fig. 2b and c).

thumbnailFig. 2. Comparative changes in PD-1, CXCR5 and ICOS expression on Tfh-cell surfaces. a,PD-1. b, CXCR5. c, ICOS. * P < 0.05. Note a significant decrease in PD-1 expression with no appreciable changes in CXCR5 and ICOS expression in the CR patients as compared to the NC group

IL-21 is a biological hallmark of Tfh cells because this immune cytokine is produced by Tfh cells and is involved in mediating Tfh-B-cell interaction [6]. Therefore, we further measured the concentration of IL-21 in the serum of the CR patients (Fig. 3). Similarly as the changes in CXCR5 and ICOS, serum IL-21 did not show any significant change in the CR patients as compared to that of the control group (406.9 ± 123.9 pg/ml vs. 449.1 ± 101.7 pg/ml, P > 0.05).

thumbnailFig. 3. The level of serum IL-21 in renal allograft patients. Note that there was no statistic difference in the IL-21 level between the CR and NC groups

No changes in circulating B cells, PDL-1 and ICOSL in the CR patients

Since B cells are key players in the graft rejection [19], we further determined the frequency of total B cells and compared their change with that of Tfh cells. The ratio of B lymphocytes was not significantly different between CR and NC groups (Fig. 4), unlike Tfh cells. Because PDL-1-expressing B cells interact with PD-1+ Tfh cells to regulate the maturation and survival of B cells [20], we next detected the expression of PDL-1 in B cells. Unlike the change in the PD-1 of Tfh cells, PDL-1 did not decrease in B cells at all in the CR group (Fig. 5a). Also, ICOSL had no significant change in the CR patients (Fig. 5b).

thumbnailFig. 4. The frequency of B cells. Note that there was no significant difference between two groups

thumbnailFig. 5. The expression of PDL-1 and ICOSL in B cells. Note that there were no appreciable differences in both PDL-1 (a) and ICOSL (b) between two groups

All these results suggest that the increase in circulating Tfh cells with PD-1 down-regulation is a specific and characteristic change in the CR patients.


We have made a novel finding in this work, i.e., a major increase in circulating Tfh cells with a significant decrease in PD-1 in the patients with chronic renal allograft rejection. In sharp contrast, B cells and the alloimmune-regulating molecules such as CXCR5, ICOS, ICOSL, PDL-1 and IL-21 did not show any appreciable change in parallel.

Tfh cells display multiple features for their helper functions in secondary lymphoid organs or tissues with inflammation [21]. They migrate into B cell follicles of germinal centers [22] and thereby help B cells generate antibodies for humoral immunity [3], [6], [23]. In fact, Tfh cells, as an immune regulator, are critically involved in the pathological processes of many immune diseases [8]. In renal allograft rejection, the germinal center reactions are dependent on Tfh, while B cells are indispensable for the immune attack to the newly transplanted kidney [24].

Tfh cells express PD-1 [6], while B cells produce PDL-1, an endogenous ligand of PD-1 [19]. The PD-1/PDL-1 signaling has been shown to play an important role in regulating immune functions and affecting the activation of regulatory T cells, cytotoxic T cells and Dendritic cells [25]. Such signaling also influences the generation and differentiation of Tfh and B cells themselves [26]. Recent evidence suggests that blocking the PD-1 signaling induces an up-regulation of Tfh generation and differentiation, which may directly lead to autoimmune encephalomyelitis [27]. In contrast, stimulating this pathway can prolong the survival of the patients after cardiac allograft transplantation [28]. More recently, PD-1 ligands are found to protect the kidneys from ischemia reperfusion injury [29]. In fact, PDL-1, the endogenous ligand of PD-1, has been demonstrated as a required factor for peripheral transplantation tolerance and protection aganist chronic allograft rejection [30].

Taken together, PD-1 signaling is a key regulator for attenuating the Tfh cells and down-regulating the overreaction of humoral immunity against the transplanted kidneys. Therefore, the novel finding of the present study strongly suggests that the deficiency of PD-1 expression causes the increase in Tfh cells, thereby leading to an overreaction of humoral immunity against the allergenic organ, which may be a major reason for chronic allograft rejection.

Tfh and B cells also express many other immune-regulating molecules such as CXCR5, ICOS, ICOSL, and IL-21 [6], [19], [26]. All these molecules are actively involved in the regulation of immune function [26]. For example, an increase in the expression of CXCR5 can enable Tfh cells to migrate into germinal centers [21]. On the other hand, ICOS, another surface receptor like PD-1, also mediate the generation, development and function of Tfh cells by activating ICOS/ICOSL signaling [31], [32]. Moreover, IL-21,a pro-inflammatory cytokine secreted by Tfh cells,has an important role in Tfh cell differentiation, B cell proliferation [33], and the expression of PD-1 [34] and CXCR5 [26]. However, all of these immune regulators did not shown any change in the patients with chronic allograft rejection. We are therefore confident that the deficient PD-1 expression with increased circulating Tfh cells is a specific and characteristic change in chronic allograft rejection.

In the lymph nodes, CD4+ CXCR5+ Tfh cells are more effective in helping B cells than their peripheral counterparts [7]. Humoral response in the lymph nodes can be suppressed by anti-CD40 mAb via regulating Tfh cells [23]. In the transplanted kidneys with acute rejection, infiltrated Tfh cells have been found to participate in the antibody-mediated rejection [14]. However, little is known about the role of these special Tfh cells in the transplanted kidneys with chronic rejection. We speculate that the increase in circulating Tfh cells with a decrease in PD-1 expression might, at least partially, contributes to the genesis of the renal chronic rejection by migrating and infiltrating into germinal centers of renal allografts and lymphoid organs. We will further clarify this issue in our future work.

In addition, pre-existent DSA storing before renal transplantation and de-novo DSA developing after renal transplantation are associated with antibody-mediated rejection and allograft failure [35]. However, recent studies have shown that despite the numbers of circulating Tfh cells were higher in the patients with pre-existent DSA than those without pre-existent DSA, the levels of circulating Tfh cells were not different among the patients with or without de-novo DSA [35], [36]. Therefore, the relationship between the frequency of circulating Tfh cells and the level of DSA in renal allograft rejection is not clear yet and needs more investigations.


Our first data show that decreased PD-1 expression may contribute to the increase in circulating Tfh cells in the patients with chronic renal allograft rejection. This finding provides a potential hint for a new target for the treatment of chronic rejection. Moreover, a dynamic change in the expression of PD-1 and the number of circulating Tfh cells may be used as an index for monitoring chronic allograft rejection after kidney transplantation as.


Tfh: Follicular helper T cells

CXCR5: Chemokine receptor type 5

ICOS: Inducible T cell co-stimulator

PD-1: Programmed death-1

ICOSL: Inducible T cell co-stimulator ligand

PDL-1: Programmed death-1 ligand

IL-21: Interleukin-21

Bcl-6: Transcription factor B-cell lymphoma 6

CR: Chronic rejection

NC: Normal control

ELISA: Enzyme-linked immunosorbent assay

sCr: Serum creatinine

BUN: Blood urea nitrogen

DSA: Donor-specific antibodies.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

JS, XX, XH and YX conceived and designed the experiments. JS, FL and QS performed the experiments. JS analyzed the data. XH provided research reagents. JS and YX wrote the paper. All authors read and approved the final manuscript.


This work was supported by the National Natural Science Foundation of China (Grant No.81273267) . YX was partially supported by NIH (AT-004422).


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Quantitative analysis of a Māori and Pacific admission process on first-year health study

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Quantitative analysis of a Māori and Pacific admission process on first-year health study

Elana Curtis1*, Erena Wikaire1, Yannan Jiang2, Louise McMillan2, Robert Loto1, Airini3 and Papaarangi Reid1

Author Affiliations

1 Te Kupenga Hauora Māori, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92015, Auckland, New Zealand

2 Department of Statistics, Faculty of Science, University of Auckland, Private Bag 92015, Auckland, New Zealand

3 Faculty of Human, Social and Educational Development, Thompson Rivers University, Thompson, BC, Canada

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BMC Medical Education 2015, 15:196  doi:10.1186/s12909-015-0470-7

The electronic version of this article is the complete one and can be found online at:

Received: 15 December 2014
Accepted: 20 October 2015
Published: 3 November 2015

© 2015 Curtis et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Universities should provide flexible and inclusive selection and admission policies to increase equity in access and outcomes for indigenous and ethnic minority students. This study investigates an equity-targeted admissions process, involving a Multiple Mini Interview and objective testing, advising Māori and Pacific students on their best starting point for academic success towards a career in medicine, nursing, health sciences and pharmacy.


All Māori and Pacific Admission Scheme (MAPAS) interviewees enrolled in bridging/foundation or degree-level programmes at the University of Auckland were identified (2009 to 2012). Generalised linear regression models estimated the predicted effects of admission variables (e.g. MAPAS Maths Test; National Certificate in Educational Achievement (NCEA) Rank Score; Any 2 Sciences; Followed MAPAS Advice) on first year academic outcomes (i.e. Grade Point Average (GPA) and Passes All Courses) adjusting for MAPAS interview year, gender, ancestry and school decile.


368 First Year Tertiary (bridging/foundation or degree-level) and 242 First Year Bachelor (degree-level only) students were investigated. NCEA Rank Score (estimate 0.26, CI: 0.18-0.34, p< 0.0001); MAPAS Advice Followed (1.26, CI: 0.18-1.34, p = 0.0002); Exposure to Any 2 Sciences (0.651, CI: 0.15-1.15, p = 0.012); and MAPAS Mathematics Test (0.14, CI: 0.02-0.26, p = 0.0186) variables were strongly associated with an increase in First Year Tertiary GPA. The odds of passing all courses in First Year Tertiary study was 5.4 times higher for students who Followed MAPAS Advice (CI: 2.35-12.39; p< 0.0001) and 2.3 times higher with Exposure to Any Two Sciences (CI: 1.15-4.60; p = 0.0186). First Year Bachelor students who Followed MAPAS Advice had an average GPA that was 1.1 points higher for all eight (CI: 0.45-1.73; p = 0.0009) and Core 4 courses (CI: 0.60-2.04; p = 0.0004).


The MAPAS admissions process was strongly associated with positive academic outcomes in the first year of tertiary study. Universities should invest in a comprehensive admissions process that includes alternative entry pathways for indigenous and ethnic minority applicants.


Admission; Selection; Indigenous; Ethnic minority; Health professional; Higher education; Widening participation; Workforce development; Māori; Pacific


Worldwide, tertiary institutions are attempting to widen participation to historically underserved populations including indigenous and ethnic minority students [1] Often driven by social inclusion and social accountability policies, universities have devised a number of strategies to increase diversity. Within an indigenous and ethnic minority health workforce context, a pipeline approach is recommended to address well-known barriers to accessing and succeeding in university-level studies. A pipeline approach often includes early exposure interventions aimed at raising aspirations and academic preparation for a career in health [2]–[4]; addressing educational disadvantage via the provision of bridging/foundation programmes [5], [6] and improving student performance by providing comprehensive support programmes [7]–[9]. Given the highly competitive context of health professional programme selection, it is also recommended that universities provide more flexible and inclusive selection and admission policies for students from underserved populations [1], [10].

Universities have a choice of selection tools that can be used to inform student admission including prior academic performance, interview scores and results from aptitude tests. Both cognitive and non-cognitive tools are used by universities when selecting students; however it is arguable that prior academic performance remains a dominant tool for medical selection in many universities [11]. Given this reality, indigenous and ethnic minority students are required to aim to achieve a high level of academic performance within the pathways used for future selection into medical or health professional programmes of study [12]. Unfortunately, students from underserved populations are less likely to receive access to science-rich subjects and are more likely to leave high school with lower qualifications than their peers [5], [10], [13]. Providing an admissions process that can determine whether indigenous and ethnic minority applicants are academically (and socially) ready to achieve success in pre-medical degree pathways and the provision of alternative entry pathways is recommended for tertiary institutions committed to widening participation [14], [15].

An extensive body of research identifies the tertiary conditions and factors that impact on academic success within the first year of study at university [16]–[20]. Indicators of prior academic performance such as: secondary school grade point averages [21]; secondary school factors including markers of socio-geographic status (e.g. school decile) [22]; and student characteristics (e.g. autonomy, confidence, motivation, control) [17], [23] have been identified as important factors impacting on academic performance in the first year of study. In addition, factors associated with the environment of the tertiary institution also impact on student engagement; such factors include: opportunities for teachers and students to engage with each other [18]; levels of institutional support to provide environments conducive to learning [20]; and the provision of academic, social and personal support [16].

To date, few studies have explored the effect of equity-targeted admission processes on the academic performance of indigenous and ethnic minority students in their first year of tertiary study. As a result, tertiary institutions have little empirical evidence to understand the effect of equity-targeted selection processes and whether such initiatives are likely to support a widening participation agenda.

This article explores the predictive effect of admission variables associated with an equity-targeted admission process on academic outcomes for Māori (the indigenous peoples of Aotearoa New Zealand) and Pacific (a heterogeneous composite of peoples with Pacific nation ancestry born and/or living in New Zealand) applicants applying under the Māori and Pacific Admission Scheme (MAPAS) to the Faculty of Medical and Health Sciences (FMHS) at the University of Auckland (UoA).


FMHS entry pathways

Admission into FMHS health professional programmes is generally via direct entry into First Year Bachelor level undergraduate study for those applicants who meet the necessary entry requirements [24]. The FMHS also offers a one-year, MAPAS-specific bridging/foundation programme, the Certificate in Health Sciences (CertHSc) through which Māori and Pacific students who achieve a CertHSc GPA above B+ can gain alternative entry into First Year Bachelor undergraduate study. Hence, Māori and Pacific First Year Tertiary students within FMHS could either be enrolled in the CertHSc bridging foundation programme, or, the first year of bachelor level study (Table 1). The first year of bachelor level study also acts as a ‘pre-medical’ year prior to admission into the FMHS Medical programme in year 2. Table 1 provides definitions of the Certificate in Health Sciences, First Year Tertiary, and First Year Bachelor terms used within this study (Table 1).

Table 1. Definition of terms used within the FMHS context

Māori and Pacific Admission Scheme (MAPAS)

MAPAS operates an equity-targeted admissions process for applicants with indigenous Māori and Pacific ancestry. The process aims to gather a broad range of information about Māori and Pacific applicant preparation for tertiary health study. The December interview process involves a Multiple Mini Interview (MMI), an English test and a mathematics test.

The MMI is an alternative form of admission interview that aims to reduce interviewer bias by consisting of a number of short interview stations with multiple interviewers. The MMI has been shown to be reliable, acceptable and feasible in a variety of tertiary health study contexts [25]. In building on the original pilot of the MMI [26], other studies have taken advantage of the intended benefit of the flexibility of station development in their own contexts [27], [28]. Whilst the original authors aimed to assess suitability of applicants as health professionals, the MAPAS MMI aims to assess Māori and Pacific applicant preparation for and potential to succeed in FMHS programmes. In the MAPAS context, the MMI has been redeveloped to include four 8-min stations assessing career aspirations; academic preparation; family support and student information. The MAPAS mathematics and English testing are used in addition to the MAPAS MMI to objectively assess academic numeracy and literacy skills. Using MMI and testing information, two assessments are made about: 1) potential to succeed within the CertHSc, and 2) potential to succeed within the Bachelor of: Health Sciences; Science (Biomedicine)1 ; Nursing; or Pharmacy. Potential to succeed is assessed as: pass, borderline or fail (objective testing) for the English and mathematics testing and few, some, or major concerns (subjective testing) for each MMI station. A MAPAS Recommendations Team reviews the combination of results and provides a provisional MAPAS recommendation (advice regarding the applicant’s recommended best starting point given their intended health career) for applicants (and families) on the day of their interview. Recommended starting points are reflected within three categories: (1) Bachelor i.e. start at degree-level; (2) CertHSc i.e. start at bridging/foundation; or (3) Not FMHS i.e. start in a pathway not provided by FMHS (likely to need further academic preparation not offered by the FMHS). Following the release of secondary school results in January, all information is re-reviewed and a final MAPAS recommendation is provided. MAPAS recommendations are not binding if an applicant has met guaranteed entry criteria for any FMHS programme. In this context, the applicant can choose to follow MAPAS advice (or not)2 .


This study used a Kaupapa Māori Research (KMR) approach, broadly defined and responsive to Pacific research methodologies [29], [30]. This approach recognises that issues associated with power, privilege and agency within society are hypothesised to act similarly on both Māori and Pacific students [31], [32]. In this instance KMR aims to: ensure research outputs are positive for Māori and Pacific students; explicitly challenge ‘victim blame’ or ‘cultural deficit’ analyses that may blame Māori or Pacific students for educational failure; and provide a structural analysis to promote institutional change targeting Māori and Pacific student success [14], [33]. This research was led by senior Māori and Pacific researchers with input from a FMHS advisory group.

Study design

The predictive effect of MAPAS admission process variables on academic outcomes in the first year of tertiary study was explored. Applicant data were obtained from the MAPAS admissions database and the university’s centralised student data management system for all MAPAS interviewees (2008 – 2011) who subsequently enrolled in relevant tertiary health programmes (2009 – 2012) within the FMHS at the UoA. Approval to complete this research was granted by the University of Auckland Human Participant Ethics Committee (Ref 8110). As per ethics protocols, written informed consent was not required for this research project due to the use of secondary administrative data sources. All secondary data obtained from these datasets were de-identified by an independent research member with no student contact or teaching responsibilities and data analysis occurred via a coding system. Two student cohorts are identified: First Year Tertiary Students i.e. students enrolled in either the CertHSc or the first year of a bachelor programme in the year following their MAPAS interview; and First Year Bachelor Students i.e. students enrolled in a bachelor programme in either the first or second year following their MAPAS interview (may include CertHSc graduates).


Demographic variables include: Year of Admission (2009–2012); Gender (Female, Male); Ancestry (Māori, Pacific, Both) and School Decile (High, Medium and Low). Secondary schools with a mid-low decile rating have been linked to higher levels of deprivation associated with reduced access to, and outcomes from, tertiary education [34] (Table 2).

Table 2. Descriptive summary of first year tertiary and first year bachelor student demographic and outcome variables

Admission predictor variables include: MAPAS Testing results (%); MMI Station results (Some or Major Concerns (SMC) versus Few Concerns (FC)); Provisional December Recommendation (CertHSc, Bachelor, Not FMHS); secondary school results including New Zealand’s NCEA Rank Score3 (out of 320); Level 3 NCEA Subject Credits (number of credits achieved in English, biology, chemistry, physics, mathematics); Exposure to Any 2 Sciences of senior biology, chemistry or physics (yes, no)4 ; Followed MAPAS Advice (yes, no); and Final January Recommendation made in January (CertHSc, Bachelor, Not FMHS).

Academic outcome variables include: Grade Point Average (GPA) Eight Courses, 09 (i.e. GPA achieved across a total of eight courses over the year); GPA Core 4 Courses, 09 (i.e. GPA achieved across four core courses5 taken in the first year of bachelor study that are specifically assessed for selection into second year medicine at the UoA); Passes All Courses, yes/no (i.e. across total of eight courses); Passes All Core 4 Courses, yes/no (i.e. across the four core courses).

Statistical analysis

All downloaded data were recorded in Microsoft Office Excel spread sheets. Statistical analyses were performed using SAS version 9.3 (SAS Institute, Cary, NC, USA). Continuous variables were presented as mean and standard deviation (SD); categorical variables as frequencies (n) and percentages (%) (Tables 2 and 3). Generalised linear and logistic regression models were used to estimate the predicted effects of individual admission variables on academic outcomes (i.e. GPA and Passes All); adjusting for pre-defined demographic variables (i.e. MAPAS interview year, gender, ancestry and school decile) (Tables 4, 5, 6 and 7). Admission variables that showed significant single predictive effect (i.e. MAPAS Maths Test, NCEA Rank Score, Any 2 Sciences and Followed MAPAS Advice) were included in the multiple regression analyses to determine their joint effects on the academic outcomes of interest (Tables 8 and 9). All statistical tests were two-sided at 5 % significance level.

Table 3. Descriptive summary of first year tertiary and first year bachelor student predictor variables

Table 4. Univariate regression analysis results – GPA eight courses

Table 5. Univariate regression analysis results – GPA core 4 courses

Table 6. Univariate regression analysis results – passes all eight courses

Table 7. Univariate regression analysis results: passes all core 4 courses

Table 8. Multiple regression analysis results – linear regression a

Table 9. Multiple regression analysis results – logistic regression a


Descriptive variables

A total of 368 students were identified in the First Year Tertiary cohort. Of these, 37 % were Māori, 57 % Pacific and 6 % had Both Māori and Pacific ancestry. Two thirds were female (67 %), the mean age was 19.2 years (SD 4.2 %) and 70 % or more came from a secondary school with a medium or low school decile (representing more deprived communities). The First Year Bachelor cohort had a total of 242 students with a similar demographic profile to First Year Tertiary students (Table 2).

Predictor variables

Mathematics and english testing

The First Year Tertiary cohort had a mean percentage mark for the mathematics test of 79.0 % (SD 18.3 %) and 68.4 % (SD 13.6 %) for the English test. This represents a borderline-fail result for bachelor-level study and a pass result for CertHSc-level study as the best starting point of entry across both assessments. The First Year Bachelor cohort had a slightly higher mean mark for both the mathematics (80.4 %, SD 18.3 %) and English tests (70.6 %, SD 12.8 %) (Table 3).


Over 80 % of all students from both cohorts were assessed as having few concerns for CertHSc-level entry across the four MMI stations. Forty-four percent of all First Year Tertiary students were assessed as having some or major concerns for bachelor-level entry at the Academic Preparation and Student Information MMI stations. For First Year Bachelor students, the stations with the highest proportion of some or major concerns for bachelor-level entry were Career Aspirations (48 %) and Student Information (39 %) (Table 3).

School results

The average NCEA rank score (out of a total of 320) was 190.5 (SD 51.3) for First Year Tertiary and 201.8 (SD 52.7) for First Year Bachelor students. Both averages fall below requirements for guaranteed entry within FMHS (set at a rank score between 210 – 250 depending on the programme). The average number of subject credits for both cohorts were 0.3–3.4 credits below requirements for guaranteed entry (i.e. 16 – 18 subject credits depending on programme) (Table 3). At least two thirds of all students admitted into either the CertHSc or bachelor programmes had taken two or more science subjects in their final year of secondary school (Table 3).

MAPAS recommendations

For First Year Tertiary students, MAPAS recommended CertHSc to 72 % of all students, followed by Bachelor (26 %) and Not FMHS (2 %). For First Year Bachelor students, 58 % were recommended to start at the CertHSc level, followed by 39 % Bachelor and 3 % Not FMHS (Table 3).

Followed MAPAS advice

Over 83 % of all students followed MAPAS advice regarding the best starting point for success with only 12 – 17 % of students from each cohort not following their final MAPAS recommendation (Table 3).

Outcome variables

GPA All eight courses and core 4 courses

The average GPA for all eight courses (out of a total of 9) was 4.3 (SD 2.0) for First Year Tertiary and 4.1 (SD 2.1) for First Year Bachelor students. The average GPA achieved for the Core 4 Courses was 3.8 (SD 2.4) for First Year Bachelor students.

Passes All eight courses and passes All core 4 courses

Seventy-five percent of First Year Tertiary students and 60 % of First Year Bachelor students passed all eight courses. Sixty-four percent of First Year Bachelor students passed all Core 4 Courses (Table 2).

Multiple regression analysis

First year tertiary – GPA

As shown in Table 8, all predictors had a statistically significant effect on First Year Tertiary GPA, with the most significant predictor being NCEA Rank Score, then MAPAS Advice Followed, Any 2 Sciences and MAPAS Mathematics Test results. First year Tertiary GPA increased by an average of 0.3 (out of a total 9) for every 20 point increase in NCEA Rank Score (CI: 0.18-0.34; p < 0.0001). Students who followed MAPAS advice had on average a GPA that was 1.2 points higher (out of a total 9) than students who did not (CI: 0.57-1.78; p = 0.0002).

First year tertiary – passes All courses

The odds of passing all eight courses was 5.4 times higher for those students who followed MAPAS advice versus those students who did not (CI: 2.36-12.39; p < 0.0001) (Table 8). The odds of passing all eight courses was 2.3 times higher for those students who had exposure to Any 2 Sciences versus those students who did not (CI: 1.15-4.61; p = 0.019) (Table 8).

First year bachelor – GPA

For every 20 point increase in NCEA Rank Score, the GPA achieved by First Year Bachelor students increased by an average of 0.4 for all 8 courses (CI: 0.30-0.50; p < 0.0001) and for Core 4 courses (CI: 0.26-0.50; p < 0.0001) (Table 7). Students who followed MAPAS advice had on average a GPA that was 1.1 points higher than students who did not follow MAPAS advice for all eight courses (CI: 0.45-1.73; p = 0.0009) and Core 4 courses (CI: 0.60-2.04; p = 0.0004) (Table 8).

First year bachelor – passes All courses

A 20 point increase in NCEA Rank Score increased the odds of passing all first year bachelor courses by a factor of 1.5 (CI: 1.24-1.74; p < 0.0001), with similar results for passing all Core 4 courses (Table 8). The odds of passing all first year bachelor courses (CI: 1.45-7.69; p = 0.005) and all Core 4 courses (CI: 1.39-7.69; p = 0.007) was 3.3 times higher for those students who followed MAPAS advice versus those students who did not (Table 9).


Our findings confirm that the MAPAS admissions process is strongly associated with positive academic outcomes in the first year of tertiary study. Our results reinforce the evidence-base showing a strong association between secondary school performance via NCEA rank score (a marker of the quality of grades achieved) and positive tertiary academic outcomes [35]. The existing literature base has also been extended, given our identification of a strong association between exposure to two or more senior science subjects (a marker of breadth of knowledge) and first year academic outcomes. Similar to other studies, our findings show that the number of credits achieved within NCEA subjects appear to be less strongly correlated with tertiary outcomes [35].

Overall, our findings suggest that there is value in providing a comprehensive admissions process for indigenous and ethnic minority students applying under equity targeted admission programmes. Students admitted into tertiary institutions under targeted admission programmes have been shown to experience peer/educator stigma and ‘everyday racism’. Demonstrating the effectiveness of targeted admission programmes may assist some indigenous and ethnic minority students to override this societal (and potentially internalised) stigma to receive the benefits that targeted admission programmes have to offer.

Increasing the odds of passing all first year courses has relevance for all students. This is important for applicants pursuing medicine as even small increments in first year bachelor GPA, particularly within the Core 4 courses used for medical selection, may have a profound impact on potential selection [12], [19]. A student’s progress towards completion of total point requirements within their degree has been shown to improve student retention and increase the likelihood of degree completion [36]. Aligning MAPAS admission to a comprehensive process focussed on achieving equity in access and performance is likely to have contributed to the recent increase in numbers and improved performance observed for Māori and Pacific students within the FMHS [5], [37].

Our data suggests secondary schooling is yet to demonstrate the ability to prepare Māori and Pacific students adequately for tertiary health professional study. Both teaching and subject selection are critical factors. Māori and Pacific students and their families are not to blame for the observed inequities in secondary education. Rather, Māori and Pacific students and their families should receive greater support to navigate NCEA subject selection and ensure that students achieve the right number and quality of credits [38]. This is consistent with international evidence showing that indigenous and ethnic minority students are less likely to receive high-quality careers or university advice [38], [39] and in some instances may be actively discouraged from pursuing a health professional career [2].

Based on our findings, it appears that the secondary education sector is failing to ensure that indigenous and ethnic minority students are ‘university-ready’ for health-professional study. Unfortunately, this is not a new issue [5], [14], [40], [41] and nor is it unique to New Zealand [3], [42]. Action by secondary schools and educators to address their own role in the creation and maintenance of ethnic inequities in academic outcomes is recommended [43]. Likewise, tertiary institutions are expected to be part of the solution [44]. Pechenkina & Anderson (2011) call for “more effective institutional response to the lack of adequate preparation of indigenous students…via greater investment in the pipeline and provision of transitioning programmes” (p. 5-6). Our findings further support the delivery of bridging/foundation programmes targeting indigenous and ethnic minority students.


This study explores a unique application of the MMI within an equity-targeted context [14], [26]. Although we identified varied associations between individual MMI stations and academic outcomes, we believe that our overall findings support maintaining the MMI within the MAPAS admissions process. This reflects the strong association observed between following MAPAS advice (a predictor variable that is determined by the combined assessment of all results) and higher academic outcomes.

Using both cognitive (e.g. NCEA school results, MAPAS Maths and English test) and non-cognitive (e.g. MMI results) tools for student selection within the total MAPAS admission process supports a widening participation agenda and is consistent with recommendations to use more inclusive selection tools [10], [45]-[47]. This is particularly important when assessing the potential of alternative admission or older applicants who may possess maturity shown to be positively associated with tertiary programme completion [36], [48].


This study has a number of limitations. The analysis relied on secondary data and is therefore limited by the quality of data sources. However, combining central university and MAPAS datasets has reduced the potential for data misclassification by using verified ancestry and increased the admission variables available for analysis [49], [50]. Our research was limited to first-year outcomes due to resource and time constraints. Ideally, the effect of predictor variables on long-term outcomes across all FMHS programmes should be examined. Comparing academic outcomes across all ethnic groups may also highlight issues of disadvantage and privilege [51]. This research is in progress and is drawing on the methods developed within this study. We acknowledge that combining Māori and Pacific data is not ideal from an indigenous rights or Pacific-centric perspective. However, this is consistent with our methodological approach as it maximises statistical power (to aid student success) and supports a structural critique of the effect of ‘society’ on ‘ancestry’ [14]. As the quantum of Māori and Pacific data increases, further research should investigate Māori-specific and Pacific-specific predictors of academic success.


Tertiary institutions committed to widening participation should prioritise the funding and delivery of a comprehensive, flexible and inclusive admissions process that includes alternative entry pathways for indigenous and ethnic minority applicants [10], [52], [53].

Ethical approval

This project was approved by the University of Auckland Human Participants Ethics Committee, Ref 8110.


CertHSc: Certificate in Health Sciences (Hikitia Te Ora)

CIE: Cambridge International Exam

FMHS: Faculty of Medical and Health Sciences

GPA: Grade Point Average

IB: International Baccalaureate

KMR: Kaupapa Māori Research

MAPAS: Māori and Pacific Admission Scheme

NCEA: National Certificate of Educational Achievement

UoA: University of Auckland

Competing interest

The authors declare that they have no competing interest.

Authors’ contributions

EC led the study design, methodological approach, interpretation of the data analysis, and drafted the manuscript. EW contributed to study design and provided research assistance to obtain and clean data variables. She contributed to drafting and revising the manuscript and was responsible for producing the data tables. YJ provided senior statistical expertise for data analysis. She contributed to drafting and revising the manuscript. LM provided junior statistical expertise and contributed to drafting and revising the manuscript. RL contributed to the study design and provided Pacific research methodological expertise in the drafting and revising of the manuscript. A provided senior Pacific educational and research expertise and contributed to drafting and revising the manuscript. PR provided senior Māori educational, institutional and KMR expertise and contributed to drafting and revising the manuscript. All authors read and approved the final manuscript for submission. All authors agreed to be accountable for all aspects of the work

Authors’ information

EC (Te Arawa, FNZCPHM, MPH (Distinc), MBChB) is a specialist in public health medicine who has experience in research and policy concerned with eliminating ethnic and indigenous inequalities in health. Elana is a Senior Lecturer and the Director Vision 20:20 at Te Kupenga Hauora Māori, The University of Auckland. She is a postgraduate Doctor of Medicine (MD) candidate (exploring indigenous and ethnic minority health workforce development) and has ongoing research interests in ethnic inequities in service utilisation and health outcomes.

EW (Ngāti Hine, PGDipPH (Distinc), BHSc) is a Māori Physiotherapist who has experience in research concerned with Māori and Indigenous health workforce development, cultural competence, and psycho-oncology in Māori and Indigenous populations. Erena is currently completing a Masters in Public Health whilst working as Researcher at Te Kupenga Hauora Māori, University of Auckland. Ongoing research interests include Māori health workforce development and addressing ethnic inequalities in health.

YJ (Chinese, PhD) is a Senior Research Fellow at the Department of Statistics and Senior Statistical Consultant at the Statistical Consulting Centre (SCC), Faculty of Science, University of Auckland, New Zealand. Ongoing research interests include: randomised controlled trial design and analysis, national surveys, longitudinal and case-control studies with response-selective sampling and missing data problems.

LM (Pākehā, MSc, MMath) is an Assistant Analyst at the Statistical Consulting Centre (SCC), Faculty of Science, The University of Auckland, New Zealand. She is a PhD candidate in the Department of Mathematics and Statistics.

RL (Samoa, PGDipPsych-Community, MSocS-Hons) proudly hails from the villages of Fagamalo and Avao (Savai’i) where he was raised as a young child. Rob is a Professional Teaching Fellow within Hikitia Te Ora – Certificate in Health Sciences programme at Te Kupenga Hauora Māori, FMHS, UoA. Rob is a Registered Community Psychologist and his aspirations are firmly rooted in the wellbeing and development of Māori and Pacific communities in regards to identity and health.

A (PhD, MEd (Distinc), MBA, BA, DipTchg, CertARM) specialises in higher education research, with a particular focus on Pasifika, indigenous and under-served students. Airini has Samoan ancestry, has a national and international record in Pasifika education research and recognised expertise in Pasifika methodologies. Airini is Dean, Faculty of Human, Social and Educational Development, Thompson Rivers University, BC, Canada. With a view to informing further education system reform in New Zealand and internationally, as a Fulbright Scholar based in Washington DC Airini investigated how to convert education policy into better results for under-served students.

PR (Te Rarawa, DipComH, BSc, MBChB, DipObst, FNZCPHM) is Tumuaki and Head of Department of Māori Health at the Faculty of Medical and Health Sciences, University of Auckland, New Zealand. She is a specialist in public health medicine and her research interests include analysing disparities between indigenous and non-indigenous citizens as a means of monitoring government commitment to indigenous rights.


The authors would like to thank members of the Te Hā Advisory Group: Dr Teuila Percival; Dr Vili Nosa; Dr Malakai Ofanoa; Associate Professor Mark Barrow; Lynley Pritchard; James Clark and Carolyn (Shaoxun) Huang. Andrew Sporle and Joanna Stewart are acknowledged for providing input into the early stages of project design from a statistical perspective. Dr Elana Curtis was supported by Te Kete Hauora, Ministry of Health (New Zealand) to conduct this research via the provision of a Research Fellowship (Contract 414953/337535/00). We also thank Ngā Pae o Te Māramatanga for their support for Erena Wikaire to attend and present these research findings at the Leaders in Indigenous Medical Education (LIME) Connection V conference in Darwin, Australia 2013.

End notes

    1. Completion of the first year of study within either the Bachelor of Health Sciences or the Bachelor of Science (Biomedicine) programme is required for an undergraduate application to the medical programme at the UoA

    1. For additional information, see previous publications 5. Curtis E, Reid P. Indigenous health workforce development: Challenges and successes of the Vision 20: 20 programme. Australian & New Zealand Journal of Surgery. 2013;83(2013):49-54, 13. Curtis E, Reid P, Jones R. Decolonising the Academy: The process of re-presenting indigenous health in tertiary teaching and learning. In: Cram F, Phillips H, Sauni P, Tuagalu C, editors. Māori and Pasifika Higher Education Horizons. Bingley, U.K.: Emerald Group Publishing Limited; 2014. p. 147-66, 14. Curtis, E., Wikaire, E., Jiang, Y., McMillan, L., Loto, R., Airini, & Reid, P. (2015). A tertiary approach to improving equity in health: Quantitative analysis of the Māori and Pacific admission scheme (MAPAS) process, 2008-2012. International Journal for Equity in Health, 14(7). 10.1186/s12939-015-0133-7. or

    1. The National Certificate of Educational Achievement (NCEA) is the major assessment method used in New Zealand secondary schools. The NCEA Rank Score reflects the best 80 credits at Level 3 or higher, over a maximum of five approved subjects. It reflects a system of Grade Point Average and is used by the UoA to assist with admission to limited entry programmes 23. Shulruf B, Hattie J, Tumen S. New Zealand’s standard-based assessment for secondary schools (NCEA): implications for policy makers. Asia Pacific Journal of Education. 2010;30(2).

    1. Exposure to a minimum of two final year secondary school science subjects is recommended for success within the CertHSc (alongside English and mathematics rich subjects). This variable includes secondary school results from NCEA, International Baccalaureate (IB) and Cambridge International Examinations (CIE).

  1. The Core 4 courses include: CHEM110 (Chemistry of the living world), POPLHLTH 111 (Population Health), MEDSCI 142 (Biology for Biomedicine Science: Organ Systems) and BIOSCI 107 (Biology for Biomedicine Science: Cellular Processes and Development).


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