Reducing Hypoglycemia Fear in Parents of Young Kids Via Video-based Telemedicine
Phase: NA
Conditions: Parents
Sponsor: University of Kansas Medical Center

Protocol Title: Reducing hypoglycemia fear in parents of young kids with video-based telemedicine 
ClinicalTrials.gov #: NCT03879642 
Document Approval: Oct 12, 2017 
 

Current Research Design. The proposed study timeline is shown in Figure 1. We will recruit 48 parents of 
young children with T1DM (ages 1-6 years) from the Pediatric Diabetes Clinic at the Children’s Mercy Hospital 
(CMH). Inclusion criteria are: age between 1-6 years, diagnosis ≥6 months, treatment with intensive insulin 
regimen (pump or MDI). Exclusion criteria are: parents of children on a conventional regimen and parents who 
do not speak English. If successful, a future trial of a Spanish version of RED CHiP would be developed. As of 
05/2014, there are 138 families of young children with T1DM who receive care at CMH. Since 2010, there has 
been a consistent rate of new diagnoses in this age group of 25-30 children per year. The PI has averaged a 
75% recruitment rate from the CMH clinic for projects recruiting families of young children. Thus, if she is able 
to maintain this rate, she would have about 120 families interested in participating in this project, of which only 
48/120 are needed, suggesting successful recruitment if at least 40% of likely interested families enroll.  
Procedure. The study will use a randomized wait-list controlled design. The parent (mother or father) primarily 
involved in their child’s daily T1DM management will be invited to participate with their child. We will plan to 
recruit 24 families to each of the immediate treatment and wait-list control groups (we will target at least 20 
families per group to complete the study; 20% attrition rate). A member of the research team will identify 
families eligible to participate. Parents will undergo randomization after they provide written informed consent. 
We will stratify parents based on their child’s gender and conduct random assignment to the two groups using 
blocks of four. We intend to recruit three family cohorts each consisting of 16 families (8, immediate treatment, 
8 wait-list). We will instruct parents randomized to the wait-list control group to follow their physician’s 
recommendations for their child’s T1DM. Then, after the 14 week wait-list control period, we will invite parents 
in the control group to participate in RED CHiP. We will instruct parents randomized to the immediate 
treatment group to follow their physician’s recommendations for their child’s T1DM. In addition, they will 
receive 14 weeks of RED CHiP. Parents randomized to the immediate treatment group will also complete a 
follow up assessment, corresponding with the time when parents in the wait-list control group have finished the 
RED CHiP program (see Figure 2). Because we plan to use a mixed-method approach to evaluate the 
feasibility and acceptability of RED CHiP, we will also randomly sample 5 parents from both the immediate 
treatment and wait-list control groups (n=10 total) to complete a semi-structured qualitative interview. Parents 
will complete the interview at the time of their last assessment visit (e.g., followup, for parents in the immediate 
treatment group; post-treatment for parents in the wait-list control group). Parents will be able to complete all of 
the surveys online either with their own computer or an iPad 2 loaned to them by the study. A research 
assistant will work with parents to complete the online surveys, download children’s glucometers and insulin 
pump, and collect a finger stick blood sample to measure children’s Hemoglobin A1c (HbA1c) at each time 
point. 
RED CHiP Treatment. The 
RED CHiP (Reducing 
Emotional Distress for 
Childhood Hypoglycemia in 
Parents) treatment is based 
on the PI’s previous 
research17, 25, 27 and the 
seven core concerns 
identified in a recent 
systematic review of 
parental FH16. We propose 
a treatment format that will 
alternate between group 
and individual telemedicine 
sessions. We will teach core 
intervention material during 
the group sessions, while 
we will use the individual 
sessions to tailor strategies 
for each family. Some 
examples of tailoring include using each child’s personal accelerometer data to help parents identify behavioral 
patterns that may increase/decrease risk of hypoglycemia and reviewing each child’s glycemic pattern to help 
parents see how over or under-treating for hypoglycemia may relate to daily glycemic control. The intervention 
will use a three-pronged approach to reduce parents’ FH. It will leverage diabetes education and problem-
solving to enhance parents’ knowledge and skills. It will use behavioral parent training (BPT) to promote 
parents’ skills and confidence in managing disruptive child behaviors and reducing their reliance on other 
hypoglycemia avoidance behaviors. Finally, it will apply cognitive-behavioral therapy (CBT) strategies drawn 

from the anxiety literature to promote parental coping and self-efficacy and reduce parental fear and stress. 
Sessions will last about 60 minutes each. The primary interventionist will be a psychology postdoctoral fellow 
whom we will hire for the current project. He/she will use the RED CHiP treatment manual for sessions (see 
Appendix C) and will receive ~20 hours of training with the PI prior to the start of the intervention. The PI will 
also assume primary responsibility for on-going clinical supervision of the treatment sessions. We will measure 
fidelity to the treatment manual by comparing a digital video recording of the sessions to a check list of content 
items for each session. The video recording will be captured and stored via the videoconference bridge. A 
research assistant who is not involved in treatment delivery will complete the fidelity check for 33% of sessions. 
We will conduct the telemedicine sessions using the Polycom RealPresence m500 app. We selected this 
software system because it is reliable and viewable on multiple televideo devices (e.g., mobile devices and 
computers). The software is also uniquely geared toward group sessions because it can simultaneously 
display up to 10 different sites (i.e., parents) or a powerpoint presentation on a mobile device or computer 
screen (e.g., like the tiled opening credits of the 1970’s Brady Bunch TV show). Families will use the Polycom 
software to access KUMC via one of our existing videoconference bridges. These bridges provide a secure 
and confidential connection to KUMC and are fully HIPAA compliant. Although the Polycom software is 
viewable on a computer or mobile device (i.e., iPod Touch, iPad, smart phone), we will, as needed, loan 
families an iPad2 tablet with data plan (16GB, WiFi and 3-G-enabled; Apple, Inc.) to use for the duration of the 
study. All of the iPad2 tablets used in this study will include tracking software to discourage theft. Parents 
receiving a loaned iPad2 will need to sign the standard KUMC iPad loan agreement for research (see 
Appendix D). In the past, colleagues who have used these procedures when loaning out devices (e.g., 
computer, tablet) have reported a high recovery rate (95% total recovery rate; ~80% if we exclude damaged 
iPads). At the end of the study all iPad2 tablets will be returned to the research staff. Of note, families owning 
their own camera-enabled iPad/computer and with internet access may be able to participate using their own 
devices. Based on the PI’s research, 95% (136/143 families) of parents of young children with T1DM report 
access to a computer with an internet connection. If we estimate that 80% of these families will also have an 
internet-enabled device with a camera, then it is possible that our actual rate of iPad2 loaning may be low (we 
estimate 12 families). 
Orientation. A trained research assistant will conduct orientation visits following randomization for families in 
the immediate treatment group and the wait-list period for families in the wait-list control group. These visits will 
include training on how to use the iPad and Real Presence m500 app. 
Accelerometer. During RED CHiP, children will wear an accelerometer (Actigraph GT3X) for at least 5 days to 
measure their typical daily physical activity (PA). In young children, the link between glycemic response and 
PA remains unclear. Accelerometer data will provide an accurate measure of children’s PA, since research 
shows that parents often underreport their child’s engagement in unstructured PA.41 Children’s total daily PA 
(total movement counts/total measurement time in minutes) will be calculated as well as a diagram of their 
typical daily PA patterns. We will use these data to educate parents regarding the relationship between their 
child’s activity patterns and blood glucose levels. We expect that giving parents specific strategies for insulin 
dosing and carbohydrate intake in the context of their child’s typical PA routine will improve parents’ T1DM 
management and children’s glycemic control. 
Wait-list Control. After randomization, families assigned to the wait-list control condition will receive a copy of 
the clinics’ standard flow sheet for the treatment of hypoglycemia. Families will cross over to the treatment arm 
at the end of the 14-week wait-list period.  
Outcome Measures. Primary outcome measures will be: parents’ FH, parenting stress, children’s glycemic 
levels (measured using mean daily blood glucose levels and HbA1c), and children’s glycemic variability 
(measured using the average daily risk range and the low blood glucose index). Secondary outcome measures 
will be the Feasibility and Acceptability of RED CHiP. Covariates for these pilot analyses will be parents’ 
depressive symptoms and child age (see Table 3). If more than one parent participates in RED CHiP, we will 
use the data from the parent who self-identifies as the most responsible for their child’s T1DM management in 
the study analyses. If parents indicate equal responsibility, we will collect data from both parents for each time 
point and we will average both parents’ data for the analyses. 
Data Management and Statistical Analyses. Parents will input their data into a RedCap database accessible 
via the internet. Missing data for continuous variables that cannot be recovered from parents will be imputed 
using either subscale or total scale mean score substitutions (e.g., HFS-PYC, PIP, CES-D). Again, covariates 
for Hypotheses 2a-b and 3a-b will be parents’ depressive symptoms (DS), and child age (AGE). 
Hypotheses. 
Hypothesis 1: RED CHiP will be feasible and acceptable to families of young children with T1DM. 

Hypothesis 2a and b: Parents who receive RED CHiP will have a reduction in fear of hypoglycemia (HFS-PYC) 
and parenting stress (PIP) as compared to the wait-list group (Hyp 2a) and pre-RED ChiP measures (Hyp 2b). 
Hypothesis 3: Children whose parents receive RED CHiP will experience an improvement in mean glycemic 
levels (MDBG & HbA1c) and variability (ADRR & LBGI) as compared to the wait-list group (Hyp 3a) and pre-
RED ChiP measures (Hyp 3b). 
Power analysis. This is a pilot and feasibility study with the purpose of generating data to support a full, 
randomized controlled trial. Power analysis of a test of the difference between pre- and post-HFS-PYC with a 
10% decline in survey scores (i.e., from M=78.6+ 18.417 to M=71) yielded a power of 84%, while a 15% decline 
in PIP-F scores (i.e., from a M=107.2+32.627 to M=91) yielded a power of 92% when n=40, α=0.05 for both 
tests. Repeated measures ANCOVA (RM-ANCOVA via GLM) yielded a power of 92% and 82%, respectively, 
for 10% declines in parents’ HFS-PYC and PIP-F scores. When using RM-ANCOVA and assuming a 10% 
decline in children’s HbA1c, tests yielded 95% power when n=40 and α=0.05 (M=8.8+1.5% to 8.0%). 
Assuming an attrition rate of 20%, we will need to recruit 48 parents (24 per group) to ensure we have >40 
parents with post-treatment data. This sample size is also sufficient to estimate effect sizes for the study 
outcomes. 
Data Analysis. We will first run descriptive statistics and statistical distributions for all measured variables at 
baseline (B), weeks 15-16 (w15-16), and weeks 32-33 (w32-33). We will conduct sensitivity analyses for all 
primary outcomes to evaluate any effects due to attrition. We will also use an intent-to-treat analysis strategy, 
wherein we will use an imputation model to examine participant data even if they are lost to attrition. 
Hypothesis 1: (Quantitative 
data): We will assume 
feasibility if families’ mean 
group session attendance is 
>70% and participant 
attrition is <20. We will 
assume acceptability if 
parents’ mean scores on the 
Treatment Satisfaction 
Questionnaire are >65. 
(Qualitative data): We will 
use Framework Matrix 
Analysis (FMA) initially. 
FMA is an efficient 
approach to qualitative data 
analysis where data are 
analyzed using themes 
derived a priori instead of de 
novo.52 A priori themes will 
be based upon the interview 
agenda (viz., strengths, 
weaknesses, ways to 
improve RED CHiP and 
overall study feasibility). 
Thus, use of FMA will allow 
refinement of RED CHiP 
within the limited timeframe 
of the R21 mechanism. We 
will apply a grounded theory 
approach to analyze transcripts upon completion of all interviews. This more comprehensive approach will 
allow for identification of de novo themes, which will be integrated into RED CHiP protocols and submitted for 
publication.53, 54 
Hypotheses 2a and b: We will score outcome measures as continuous variables with within-group 
standardized effect sizes (in SD units) and within-group changes for FH (HFS-PYC) and parenting stress (PIP-
F and PIP-D) calculated based on parents’ B, w15-16, and w32-33 scores. To test for between-group 
differences on parents' FH and stress at B, w15-16, and w32-33, we will use both repeated measures 
ANCOVA (RM-ANCOVA) and a 2x2 factorial (condition x time) MANCOVA. We will also use these to test for 
within-group x time differences. Our covariates will be AGE and DS. 

Hypotheses 3a and b: We will calculate within-group standardized effect sizes (in SD units) and within-group 
changes for children’s glycemic levels and variability based on children’s B, w15-16, and w32-33 values. As in 
Hypothesis 2, we will employ General Linear Models (GLMs) such as RM-ANCOVA and a 2x2 factorial 
(condition x time) MANCOVA to test for between-group differences on children’s glycemic levels (MDBG & 
HbA1c) and variability (ADRR & LBGI) at B, w15-16, and w32-33 and for within-group x time differences. Our 
covariates will be AGE and DS. 
.