) Review the Milestone Three Guidelines and Rubric document, which is located in the Assignment Guidelines and Rubrics section of the course. It contains all requirements and detailed instructions for this paper.
- Helpful hint for additional information: Watch the five-minute Milestone Three video.
2) Locate a new article from a peer-reviewed journal. The new article must be in the same topic area as the three articles used in Milestones One and Two.
SCS 502 Final Project Milestone Three: Expanding Upon the Topic Guidelines and Rubric
Overview: For the final milestone for your final project, research and select an additional study which pertains to the topic area you selected in the earlier milestone assignments. You will also evaluate the three studies you selected for their contribution to their topic area. Finally, you will integrate the information presented in the published studies and the information learned in this class to draw your own conclusions about the topic area using appropriate evidence to support your claims. This assignment will use the same three articles as you used in Milestones One and Two.
Be sure that your submission addresses the following critical elements:
• Select an additional research article that aligns with the appropriate standards and guidelines of the field which would help inform future research into the topic area of the chosen studies. In other words, based on what the chosen studies have demonstrated about the topic area, what present research might help conduct future research in this area?
• Explain how the article you chose follows the appropriate standards and guidelines of the field. Some questions to consider: Is the article peer- reviewed? Is the article relevant to the topic? Is the article still currently relevant?
• Explain how the research article you located would help inform future research into the topic area of your chosen studies. Be sure to support your response with examples and support from the chosen studies.
• Describe how the evidence in the chosen studies (preselected and additional) contributes to the collective understanding of the topic. • Explain any new conclusions that you could reach about the topic area based on the evidence provided in your chosen studies. In other words, in your interpretation of
the evidence provided in the chosen studies, what conclusions can you reach that go beyond the research? • Predict what future research in the topic area of the chosen studies could explore.
In Milestone One you described the articles, and in Milestone Two you critiqued them. Now you will move on to a big-picture summary and future directions. See the following detailed instructions:
1. First you will need to conduct a literature search to find a new article in the same topic area as the other three papers. The “same topic area” has a small amount of room for interpretation. You have developed some expertise in the area so assume that you are introducing the topic to a new person—what additional article would you include that you believe would enhance their understanding of the topic as a logical next step? So long as you can justify this selection (a requirement of this milestone), then it should work. Make sure you have read and fully understand the article yourself before continuing.
2. Once you have found and are familiar with your new article, you are ready to start writing. Copy and paste the title page and reference list from Milestone Two into a new document. Hopefully the running head copies over as well, but if it does not, add that back in. Be sure to address any feedback from your instructor on these sections regarding proper APA style formatting so you have the best version moving forward.
3. Next, begin the new narrative by briefly describing the article you have chosen. This does not have to be indepth but must cover the following appropriate standards and guidelines:
• Hypothesis • Participants • Brief overview of methods
• Brief overview of results and discussion This should be more in depth than an abstract but does not need to be as detailed as what you have written for Milestone One. Basically, you want to provide enough information that readers can form an opinion on the claims you will make later in this assignment. Also, discuss why you have decided this particular article is credible. Why should a reader trust this article? In addition to the questions posed in the guidelines, consider a similar review as you did for the other three articles in Milestone Two. Make sure to discuss reliability and validity.
4. Then, discuss how this particular article is relevant to the topic at hand. What does it add to the discussion that you found particularly meaningful? How would it guide someone as they considered future directions for research in this topic area?
• Typically students choose articles that they consider credible, but if you have chosen an article that you do not feel is credible, discuss why you feel that it still has value in light of the concerns you outlined above. It is certainly possible that an article has value, even if the conclusions drawn are not credible.
5. Finally, reflect on the overall topic and the work done in all three milestones. • Discuss how this article contributes to the collective understanding of the topic. What is your current understanding of the topic? How did all four articles
contribute to this understanding? Can you integrate all four articles into a cohesive overview? Is there conflicting information? How have you attempted to deal with that information?
• Based on the evidence provided in your chosen articles, what new conclusion can be reached? What does it all mean? Be sure to consider your conclusions on the credibility of each article.
• Predict one new idea for a future direction of the research. Given everything you have learned, what would you recommend for somebody wanting to take the next step in this topic area?
PLEASE NOTE: You will have added at least one new references in this section so make sure to include the APA style reference in the reference list.
Guidelines for Submission: Your paper must be submitted as Microsoft Word document with double spacing, 12-point Times New Roman font, one-inch margins, running head, title page, and at least four sources cited in APA format. This submission should be approximately 2–3 pages (not counting title or reference page). It is anticipated that you will use the same title page and reference page as submitted in Milestone Two, with any feedback from your instructor incorporated and at least one additional source added to the reference page.
Critical Elements Exemplary Proficient Needs Improvement Not Evident Value Additional Research
Selects an additional research article that aligns with the appropriate standards and guidelines of the field which would help inform future research into the topic area of the chosen studies (100%)
Selects an additional research article which would help inform future research into the topic area of the chosen studies but fails to describe the article with enough information to justify claims of credibility (70%)
Does not select an additional research article which would help inform future research into the topic area of the chosen studies (0%)
Appropriate Standards and
Meets “Proficient” criteria and explanation demonstrates a sophisticated ability to determine how research follows the appropriate standards and guidelines of the field (100%)
Explains how the article chosen follows the appropriate standards and guidelines of the field (90%)
Explains how the article chosen follows the appropriate standards and guidelines of the field but explanation is cursory or contains inaccuracies (70%)
Does not explain how the article chosen follows the appropriate standards and guidelines of the field (0%)
Future Research Meets “Proficient” criteria and explanation demonstrates keen insight into what the future research in the topic area could explore (100%)
Explains how the research article you located would help inform future research into the topic area of your chosen studies (90%)
Explains how the research article you located would help inform future research into the topic area of your chosen studies but explanation is cursory or contains inaccuracies (70%)
Does not explain how the research article you located would help inform future research into the topic area of your chosen studies (0%)
Contributions to Collective
Meets “Proficient” criteria and description demonstrates keen insight into how the chosen studies collectively contribute to the shared understanding of the topic area (100%)
Describes how the evidence in the chosen studies contributes to the collective understanding of the topic supporting response with examples and support from the research (90%)
Describes how the evidence in the chosen studies contributes to the collective understanding of the topic but description is cursory, contains inaccuracies, or does not support response with examples and support from the research (70%)
Does not describe how the evidence in the chosen studies contributes to the collective understanding of the topic (0%)
Conclusions Meets “Proficient” criteria and explanation provides unique and insightful conclusions regarding the topic area that are appropriately supported by the research (100%)
Explains the new conclusions that could be reached about the topic area based on the evidence provided in your chosen studies, supporting response with examples and support from the research and personal claims (90%)
Explains the new conclusions that could be reached about the topic area based on the evidence provided in your chosen studies but explanation is cursory, contains inaccuracies, or does not support response with examples and support from the research and personal claims (70%)
Does not explain the new conclusions that could be reached about the topic area based on the evidence provided in your chosen studies (0%)
Predict Meets “Proficient” criteria and prediction demonstrates keen insight into what the future research in the topic area could explore (100%)
Predicts what could be explored by future research in the topic area of the chosen studies (90%)
Predicts what could be explored by future research but explanation is cursory or contains inaccuracies (70%)
Does not explain the new conclusions that could be reached about the topic area based on the evidence provided in your chosen studies (0%)
Response Submission is free of errors related to citations, grammar, spelling, syntax, and organization and is presented in a professional and easy-to-read format (100%)
Submission has no major errors related to citations, grammar, spelling, syntax, or organization (90%)
Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas (70%)
Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas (0%)
Association Between Childhood Residential Mobility and Non-medical Use of Prescription Drugs Among American Youth
Meagan E. Stabler1 • Kelly K. Gurka2 • Laura R. Lander3
Published online: 9 July 2015
� Springer Science+Business Media New York 2015
Introduction Prescription drug abuse is a public health
epidemic, resulting in 15,000 deaths annually. Disruption
of childhood residence has been shown to increase drug-
seeking behavior among adolescents; however, little
research has explored its association specifically with non-
medical use of prescription drugs (NMUPD). The objective
of the study was to measure the association between resi-
dential mobility and NMUPD.
Methods The 2010 National Survey on Drug Use and
Health data were analyzed for 15,745 participants aged
12–17 years. NMUPD was defined as self-report of any
non-medical use (i.e., taking a prescription drug that was
not prescribed to them or consumption for recreational
purposes) of tranquilizers, pain relievers, sedatives, or
stimulants. Logistic regression for survey data was used to
estimate the association between residential mobility and
NMUPD, adjusting for potential confounders.
Results After controlling for demographic, intrapersonal,
interpersonal, and community factors, adolescents with low
mobility (1–2 moves in the past 5 years) and residential
instability (C3 moves) were 16 % (OR 1.16, 95 % CI 1.01,
1.33) and 25 % (OR 1.25, 95 % CI 1.00, 1.56) more likely
to report NMUPD compared to non-mobile adolescents (0
moves). Low-mobile adolescents were 18 % (OR 1.18,
95 % CI 1.01, 1.38) more likely to abuse pain relievers,
specifically. No relationship was found between moving
and tranquilizer, stimulant, or sedative use.
Discussion Increasing childhood residential mobility is
associated with NMUPD; therefore, efforts to prevent
NMUPD should target mobile adolescents. Further exam-
ination of the psychological effects of moving and its
association with pain reliever abuse is indicated.
Keywords Residential mobility � Adolescents � Health behavior � Prescription drug misuse � Opioids
What is already known on this subject? Among adoles-
cents, childhood residential instability is linked to devel-
opmental and social-emotional issues, including substance
use. However, the relationship between residential mobility
and non-medical use of prescription drugs (NMUPD) in
particular is unknown.
What this study adds? Residentially mobile adolescents
are more likely to use prescription drugs non-medically
than non-mobile adolescents. Drug-specific associations
indicate a relationship between low-mobile adolescents
and pain reliever abuse. This suggests that increasing
childhood residential mobility is associated with increased
& Meagan E. Stabler [email protected]
1 Department of Epidemiology, Robert C. Byrd Health
Sciences Center, West Virginia University School of Public
Health, P.O. Box 9190, Morgantown, WV 26506-9190, USA
2 Department of Epidemiology, Injury Control Research
Center, West Virginia University School of Public Health,
Research Ridge, 3606 Collins Ferry Road, Suite 201,
Morgantown, WV 26505, USA
3 Department of Behavioral Medicine and Psychiatry, Chestnut
Ridge Center, West Virginia University School of Medicine,
930 Chestnut Ridge Road, Morgantown, WV 26505, USA
Matern Child Health J (2015) 19:2646–2653
Prescription drug abuse is a public health epidemic .
One in every 20 Americans take prescription drugs for non-
medical use, resulting in 15,000 deaths annually .
American youth have also felt the impact of this epidemic.
One in every three people aged 12 years or older who ini-
tiated drug use in 2009 did so with non-medical use of
prescription drugs (NMUPD) . Prescription medications
are second to cannabis as the most commonly abused illicit
drugs among youth aged 12–17, with an estimated 759,000
individuals who reported current NMUPD [13, 30].
In addition to high rates of NMUPD, the US has con-
sistently high residential mobility rates. In 2012, about 36.5
million Americans, 1 year of age or older, moved .
Adverse developmental-, behavioral-, social-, emotional-,
and health-related outcomes are attributed to childhood
residential mobility. Long-term effects that continue into
adulthood include depression, lack of continuity of health
care, poorer well-being, psychosocial stress, exhaustion,
and lack of consistency in personality characteristics [3,
18–20, 25]. Childhood residential mobility is a risk factor
for late-adolescent substance use disorders, particularly
alcohol, marijuana, and nicotine-dependence [3, 17, 31].
An increased number of residential moves in childhood and
adolescence is also associated with early initiation of illicit
drugs . However, it is not known specifically how resi-
dential mobility influences adolescent NMUPD. Thus, the
purpose of this study was to explore the association
between childhood residential mobility and NMUPD
among American adolescents.
The National Survey on Drug Use and Health (NSDUH) is
a nationally-representative survey that provides country
and state-level information on the distribution and deter-
minants of tobacco, alcohol, and illicit drug use (including
NMUPD) among non-active-duty Americans aged
12 years and older. NSDUH utilizes a complex, multi-level
sampling strategy described in detail elsewhere [22, 30,
33]. The survey includes a 1-h interview that is conducted
in each participant’s home using a laptop computer into
which most responses are entered by the participant.
Audio, computer-assisted, self-interviewing is utilized for
sensitive questions. Participants are provided $30 for
completing the interview.
For the current study, publicly-available, de-identified
data from the 2010 survey were analyzed. Thus, ethics
approval was not required as this research was not considered
human subjects research. A total of 68,487 participants
completed interviews. Of those, 18,614, were aged
12–17 years and completed the youth experiences ques-
tionnaire. Topics in this questionnaire include participant
physical and social environments; legal and illegal activities
and behaviors; accessibility of substances and substance
prevention programs; and personal attitudes, perceived
norms, and risk related to drug use.
Residential mobility was assessed during the interview by
asking the question ‘‘How many times have you moved in
the past 5 years’’. In the NSDUH dataset, this categorical
variable has eight response options ranging from ‘‘none’’ to
‘‘six or more times’’, including ‘‘I don’t know’’. From this
question, the independent variable was created where
respondents were classified as ‘residentially immobile’ if
they reported zero moves, ‘low mobility’ if they reported
one or two moves, and ‘residentially unstable’ if they
reported three or more moves. This coding is consistent
with other research [1, 10, 28] in which residential insta-
bility is defined as three or more childhood or adolescent
moves [1, 2, 15, 18, 35].
The primary outcome of interest for this study was
NMUPD. During the NSDUH interview, participants were
asked if they had ever used tranquilizers, pain relievers,
sedatives, and/or stimulants non-medically. Participants
were instructed to only report NMUPD if the drug was not
prescribed to them or if they ‘‘took the drug for the expe-
rience or feeling it caused’’ . They were asked to only
report on drugs that require a doctor’s prescription, not
over-the-counter drugs. A picture and name of each pill/
brand was shown to the participant to improve participant
recall. For example, non-medical use of prescription pain
relievers is ascertained from the following question:
‘‘[Have you] ever used pain reliever non-medically?’’ The
outcome variable was created from responses to questions
regarding NMUPD that were asked throughout the survey.
Participants were classified as ‘yes’ for NMUPD if they
endorsed ever using a prescription drug non-medically at
least once during the interview or ‘no’ for NMUPD if they
never endorsed using a prescription drug non-medically.
In addition to the overall NMUPD variable (any pre-
scription drug, regardless of class), individual variables
were created for each of the four NSDUH categories of
prescription drugs, i.e. tranquilizers, pain relievers, seda-
tives, and stimulants. Participants were classified as ‘yes’
for drug-specific NMUPD if they endorsed ever using any
of the drugs in the specific category non-medically at least
Matern Child Health J (2015) 19:2646–2653 2647
once during the interview and ‘no’ for drug-specific
NMUPD if they never endorsed using any drugs in that
category non-medically during the interview.
To calculate the least-biased estimate of the effect of
NMUPD on childhood residential mobility, confounding
by a number of factors was explored. Socio-demographic,
intrapersonal, interpersonal, and community factors likely
to influence adolescent prescription drug misuse were
identified utilizing the social-ecological model as a theo-
retical framework. This model conceptualizes the interplay
between intrapersonal-, interpersonal-, and community-
level factors and their effect on health outcomes . The
current study utilized a three-level, modified social-eco-
logical framework to select potential confounders a priori.
Socio-demographic factors used in the analysis included
race/ethnicity, sex, age, and financial assistance. Race/
ethnicity was categorized as ‘non-Hispanic white’; ‘non-
Hispanic black’; ‘Native American, Alaskan, Hawaiian, or
other Pacific Islander’; ‘non-Hispanic Asian’; ‘non-His-
panic, mixed race’; or ‘Hispanic, any race’. Participants
were classified ‘yes’ for financial assistance if they
endorsed participating in one or more government assis-
tance programs, including supplemental security income,
food stamps, cash assistance, and/or non-cash assistance.
Intrapersonal-level factors included in the analysis were
perception of health, perceived risk of drug use, sensation
seeking behavior, bonding to school, average grades,
delinquent behavior, and other drug use. Using a 5-point
scale ranging from ‘‘excellent’’ to ‘‘poor’’, participants
were asked to rate their current health. Responses of ‘‘ex-
cellent’’, ‘‘very good’’, and ‘‘good’’ were classified as
positive perceived health. Responses of ‘‘fair’’ and ‘‘poor’’
were classified as negative perceived health. Perceived risk
of drug use was classified as ‘present’ if respondents
answered ‘‘great risk’’ to eleven drug related activities
(e.g., ‘‘smoke 1? packs of cigarettes per day’’). Sensation-
seeking behavior was classified as ‘present’ if the partici-
pant endorsed that they agree with the following statements
‘‘sometimes’’ or ‘‘always’’: ‘‘I get a real kick out of doing
dangerous things’’ and ‘‘I like to test myself by doing risky
things’’. School bonding was classified as ‘high’ if
respondents reported participating in more than one
school/community-based youth activity within the previous
school year or if they positively responded to questions
regarding attitudes and feelings towards school. Partici-
pants were also classified based on their average grades as
passing (C or above) or failing (below a C). Delinquent
behavior was considered ‘present’ if the participant
reported activity in six antisocial scenarios (e.g., ‘‘had a
serious fight at school/work’’). Use of other substances was
classified as ‘present’ if the participant reported ‘‘yes’’ to
smoking part or all of a cigarette in the past 30 days,
having ever had a drink of alcohol (excluding sips or a
couple of drinks from someone else’s alcoholic drink), and
having ever used crack, heroin, LSD, PCP, mescaline,
psilocybin (i.e., mushrooms), ecstasy, or any other
Interpersonal-level covariates include parental monitor-
ing, parental disapproval of drug use, perceived peer drug
use, and peer disapproval of drug use. Parental monitoring
was classified as ‘present’ if the participant responded
‘‘always’’ or ‘‘sometimes’’ for six example scenarios
reflecting parental monitoring in the previous year (e.g.,
‘‘my parents check if homework is done’’). Parental dis-
approval of drug use was classified as ‘present’ when
participants perceived their parents to ‘‘strongly disap-
prove’’ of four drug-related activities (e.g., ‘‘smoking a
pack of cigarettes per day’’). Peer disapproval of drug use
was classified as ‘present’ if participants reported one of
their close friends ‘‘strongly’’ or ‘‘somewhat’’ disapproving
of four drug-related activities (e.g., ‘‘have one to two
alcoholic drinks per day’’). Peer drug use was classified as
‘yes’ if the participant reported that ‘‘most’’ or ‘‘all’’ stu-
dents in their grade smoke cigarettes, use marijuana, drink
alcoholic drinks, or get drunk at least once a week.
Community-level factors were availability of drugs,
school norms against drug use, and community norms
against drug use. Availability of drugs was classified as
‘yes’ if participants reported being approached by someone
selling drugs or if they perceived their ability to obtain
marijuana, cocaine, crack, heroin, or LSD as ‘‘fairly easy’’
or ‘‘very easy’’. School and community norms against drug
use were classified as ‘yes’ if participants reported ‘‘yes’’ to
having had any drug education in school or if they saw
drug prevention messages outside of school.
Descriptive statistics and Chi square tests were utilized to
describe the sample and compute population estimates of
predetermined variables by drug use. To measure the
association between residential mobility and NMUPD,
multivariable logistic regression models were fit, account-
ing for the complex survey design. Due to oversampling in
the survey design, weights were utilized during the anal-
ysis. A sensitivity analysis was conducted to explore
missing data among the covariates for participants with
complete data and participants with incomplete data; there
were no significant differences in the exposure variable,
outcome variable, or exposure-outcome association
between the complete and incomplete cases. Then a com-
plete-case, multivariable analysis was performed, during
which only participants without missing data (n = 15,745)
2648 Matern Child Health J (2015) 19:2646–2653
for all of the factors under study were included in all of the
descriptive and multivariable analyses. When assessing for
confounding, conducting a complete-case analysis enables
attributing changes in the effect estimates to confounding
rather than differences in the participants included in the
Four models were fit to estimate the association between
residential mobility and NMUPD for all prescription drug
types, while adjusting for the different groups of social-
ecological covariates. The first model included the expo-
sure and outcome variables of interest, adjusting for only
demographic variables. In the second model, the intraper-
sonal-level variables were added to the model with the
demographic variables. In the third model, the interper-
sonal-level variables were added to the model with the
demographic and intrapersonal-level variables. In the final
model, all of the variables, including the community-level
variables were incorporated. All analyses were conducted
using SAS� 9.3.
Of the 15,745 participants aged 12–17 years included in
this study, 54 % (n = 8594) were non-mobile, 33 %
(n = 5081) were low-mobile, and 13 % (n = 2070) were
residentially instable (Table 1). Among the 10 %
(n = 1642) of adolescents who reported using drugs for
non-medical purposes, most moved, were female, older,
relied on financial assistance, and were Native American,
Alaskan, Hawaiian or other Pacific Islander or non-His-
panic white, compared to adolescents who did not report
NMUPD. Adolescents who reported NMUPD were sig-
nificantly more likely to perceive their health to be fair or
poor, engage in sensation seeking behaviors, report low
school bonding, have lower grades on average, exhibit
delinquent behavior, use other drugs, lack parental moni-
toring, perceive parents and peers to not disapprove of drug
use, have friends who use drugs, have access to drugs, and
do not perceive school norms to be against drug use,
compared to adolescents who did not report NMUPD.
Adolescents with low mobility were 26 % (unadjusted
OR 1.26, 95 % CI 1.20, 1.41) and adolescents with resi-
dential instability were 81 % (unadjusted OR 1.81, 95 %
CI 1.49, 2.21) more likely to use prescription drugs for
non-medical purposes than their non-mobile counterparts
(Table 2). This association persists after controlling for
socio-demographic and social-ecological factors. When
controlling for socio-demographic factors only, the odds of
NMUPD among low-mobile and residentially unstable
adolescents were 32 and 94 % greater, respectively, than
the odds of NMUPD among non-mobile adolescents. When
controlling for social-ecological factors via a four step
Table 1 Individual-, intrapersonal-, interpersonal-, and school-level characteristics of study sample, NSDUH, 2010 (n = 15,745)
Total Drug use No drug use
N (%) N (%) N (%)
Number of moves*
0 8594 (54) 747 (46) 7847 (55)
1–2 5081 (33) 582 (35) 4499 (33)
C3 2070 (13) 313 (19) 1757 (13)
Non-Hispanic 9767 (60) 1007 (61) 8760 (60)
Non-Hispanic 1964 (14) 182 (12) 1782 (14)
Native American 271 (1) 43 (1) 228 (1)
Non-Hispanic 487 (4) 23 (2) 464 (4)
Non-Hispanic 653 (2) 90 (3) 563 (2)
Hispanic 2603 (19) 297 (21) 2306 (19)
Male 7949 (51) 744 (47) 7205 (52)
Female 7796 (49) 898 (53) 6898 (48)
12 2133 (14) 78 (5) 2055 (15)
13 2439 (16) 114 (7) 2325 (17)
14 2558 (16) 204 (12) 2354 (17)
15 2772 (18) 345 (21) 2427 (17)
16 2901 (18) 411 (23) 2490 (18)
17 2942 (19) 490 (32) 2452 (17)
Yes 3550 (23) 492 (29) 3058 (22)
No 12,195 (77) 1150 (71) 11,045 (78)
Perception of overall health*
Fair/poor 547 (3) 101 (6) 446 (3)
Good/excellent 15,198 (97) 1541 (94) 13,657 (97)
Perceived risk of drug use
Present 15,202 (97) 1586 (97) 13,616 (97)
Absent 516 (3) 55 (3) 461 (3)
Sensation seeking behavior*
Present 4121 (26) 790 (47) 3331 (23)
Absent 11,624 (75) 852 (53) 10,772 (77)
Bonding to school*
High 15,645 (100) 1608 (99) 14,037 (100)
Low 100 (1) 34 (1) 66 (0)
A, B or C 14,915 (95) 1445 (89) 13,470 (96)
D or F 830 (5) 197 (11) 633 (4)
Present 4806 (30) 967 (58) 3839 (27)
Absent 10,939 (70) 675 (42) 10,264 (73)
Other drug use*
Yes 6440 (40) 1377 (84) 5063 (35)
No 9305 (60) 265 (16) 9040 (65)
Matern Child Health J (2015) 19:2646–2653 2649
modeling process, the association again persists but is
attenuated with odds ratios ranging from 1.32 (controlling
for socio-demographic and intrapersonal-level factors) to
1.16 (controlling for socio-demographic, intrapersonal-,
interpersonal-, and community-level factors) for adoles-
cents with low mobility; in contrast, residentially unstable
adolescents had attenuated odds ratios ranging from 1.94 to
1.25. After controlling for all social-ecological factors,
low-mobile adolescents were 16 % (OR 1.16, 95 % CI
1.01, 1.33) and residentially unstable adolescents were
25 % (OR 1.25, 95 % CI 1.00, 1.56) more likely to use
prescription drugs for non-medical purposes than their non-
With regard to specific categories of prescription drugs,
low-mobile adolescents were 18 % (OR 1.18, 95 % CI
1.01, 1.38) more likely to abuse pain relievers than their
non-mobile counterparts; this association was not signifi-
cant for residentially unstable adolescents. The association
between moving and NMUPD was not significant for
tranquilizers, stimulants, or sedatives alone (Table 3).
In a nationally-representative sample of US adolescents,
low-mobile and residentially unstable adolescents were
more likely to use prescription drugs for non-medical
purposes than non-mobile adolescents. The magnitude of
the association increased with more moves and persisted
even after controlling for traditional confounders [5, 34],
which were selected and organized using the social-eco-
logical model. Pain relievers were the only specific cate-
gory of prescription drugs that low mobility adolescents
were significantly more likely to abuse than non-mobile
These results are congruent with existing literature. The
current study, along with previous studies [8, 14], found
adolescents who are female, white, have depressed socioe-
conomic status, poor perceived health, poor academic
Table 1 continued
Total Drug use No drug use
N (%) N (%) N (%)
Present 14,499 (92) 1447 (88) 13,052 (92)
Absent 1246 (8) 195 (12) 1051 (8)
Parental disapproval of drug use*
Present 15,271 (97) 1468 (91) 13,803 (98)
Absent 474 (3) 174 (9) 300 (2)
Perceived peer drug use*
Yes 7705 (49) 1277 (78) 6428 (46)
No 8040 (51) 365 (22) 7675 (54)
Peer disapproval of drug use*
Present 14,503 (92) 1290 (79) 13,213 (94)
Absent 1242 (8) 352 (21) 890 (6)
Availability of drugs*
Yes 8779 (56) 1387 (84) 7392 (52)
No 6966 (44) 255 (16) 6711 (48)
School norms against drug use*
Yes 11,902 (76) 1135 (68) 10,767 (76)
No 3843 (24) 507 (32) 3336 (24)
Community norm against drug use
Yes 12,193 (77) 1232 (76) 10,961 (77)
No 3497 (23) 408 (24) 3089 (23)
n, number of participants; %, weighted percent (takes into account
NSDUH’s complex survey design and does not include missing
* Significant (p\ 0.05) Rao–Scott Chi Square value
Table 2 Association between childhood residential mobility and non-medical use of prescription drugs, NSDUH 2010 (n = 15,745)
OR (95 % CI) Model 1b Model 2c Model 3d Model 4e
aOR (95 % CI) aOR (95 % CI) aOR (95 % CI) aOR (95 % CI)
Moves in previous 5 yearsa
1–2 versus 0 1.26 (1.20, 1.41) 1.32 (1.17, 1.50) 1.18 (1.04, 1.35) 1.16 (1.01, 1.34) 1.16 (1.01, 1.33)
C3 versus 0 1.81 (1.49, 2.21) 1.94 (1.57, 2.39) 1.35 (1.09, 1.68) 1.27 (1.02, 1.60) 1.25 (1.00, 1.56)
NSDUH National Study on Drug Use and Health, n number of participants, OR unadjusted odds ratio, aOR adjusted odds ratio, CI confidence
interval a Respondents were classified based on 0 moves (non-mobile), 1–2 moves (low mobility), and C3 moves (residential instability) b Model 1 adjusts for race, sex, age, and financial assistance c Model 2 adjusts for Model 1 covariates ? perceived overall health, bonding to school, sensation seeking behavior, average grades, delinquent
behavior, and other drug use d Model 3 adjusts for Model 2 covariates ? parental monitoring, parental disproval of drug use, peer drug use, and peer disapproval of drug use e Model 4 adjusts for Model 3 covariates ? availability of drugs and school norms against drug use
2650 Matern Child Health J (2015) 19:2646–2653
performance, delinquent behavior, use other drugs, lack peer
and parental disapproval of drug use, and have drugs
available to them are more likely to use prescription drugs
non-medically. Also, the increasing magnitude of the asso-
ciation between residential mobility and NMUPD with
increased instability is similar to those observed of other
illicit drug use .
Short- and long-term effects of childhood residential
mobility have been linked to adolescent alcohol, marijuana,
and nicotine use [3, 7, 17, 31]. Additionally, increased
numbers of moves before 16 years of age have been shown
to be associated with early initiation of illicit drugs,
including marijuana, hallucinogens, crack/cocaine, and illi-
cit use of prescribed drugs . Yet in previous research,
prescription drug misuse was not broken down into drug
types and illicit use of prescription drugs was only signifi-
cantly associated with moving four or more times before the
age of 16 years. The current study, however, showed an
association between different levels of residential mobility
and NMUPD via drug-specific categories; i.e., low-mobile
adolescents were at increased odds of prescription pain
reliever abuse compared to their non-mobile counterparts.
After controlling for potential confounders, this relationship
was not significant for other drug-specific categories nor for
residentially unstable adolescents. This study may have been
underpowered to detect small differences in the other drug
types due to the lower prevalence of abuse of these classes
of drugs, compared to pain relievers, and the lower preva-
lence of frequent residential moves within our sample.
The influence of moving on adolescent drug use could
have numerous explanations. Usually children have little
control over the decision to move. This lack of control over
a major life event could result in adolescents feeling pow-
erless, frustrated, and lonely . Loneliness resulting from
moving is common and can have serious implications for
adolescents who need supportive social and normative
structures . Close social structures aid in adolescent self-
esteem and social competence [6, 16]. Absence of support to
deal with stress and anxiety could make these adolescents
more vulnerable to deviant behavior, such as drug use ini-
tiation . Many changes at once (e.g., schools, friends,
neighborhood, neighborhood surroundings) could be stress-
ful. These adolescents are forced to adjust quickly. Many
studies have shown that youth who transfer to a new school
are more likely to exhibit academic and behavioral problems
[11, 26, 27]. Another reason relocating is associated with
adolescent drug use could be the time and energy demands
placed on the parents associated with moving. DeWit 
purport that parental distraction, resulting from moving,
could result in less parental supervision, which could prompt
children to seek acceptance from peers. Peer delinquency
and best-friend delinquency are strong risk factors for ado-
lescent substance abuse .
These findings suggest that social-ecological factors
confound the association between residential mobility and
NMUPD. There was a substantial increase in the odds ratio
between models 1 and 2, which is evidence of confounding
by intra-personal factors. Future studies, therefore, should
further establish the association between intra-personal
factors and NMUPD.
This study has several strengths and limitations. This
analysis utilizes a large, nationally-representative sample
of US adolescents. The interviewing methodology has been
tested and utilized over several years. Because participants
are asked to report their own historic drug use, their
responses are dependent upon accurate recall and honest
answers. Though these data were obtained through self-
report, which has the above-mentioned limitations, these
data are not available from an alternative source. Further-
more, the manner in which sensitive data are collected, by
way of direct entry into a study computer and the different,
repeated ways in which questions are asked about the same
topic, ensure that the data are as accurate as possible. This
study is the first to examine the association between resi-
dential mobility and different categories of prescription
drugs. In addition, the participants were only asked to
Table 3 Association between childhood residential mobility and NMUPD by drug class, NSDUH, 2010 (n = 15,745)
NMUPDb Pain relieversb Tranquilizersb Stimulantsb Sedativesb
OR (95 % CI) aOR (95 % CI) aOR (95 % CI) aOR (95 % CI) aOR (95 % CI)
Moves in previous 5 yearsa
1–2 versus 0 1.16 (1.01, 1.33) 1.18 (1.01, 1.38) 1.07 (0.79, 1.45) 1.08 (0.75, 1.55) 1.33 (0.71, 2.50)
C3 versus 0 1.25 (1.00, 1.56) 1.12 (0.89, 1.42) 1.28 (0.92, 1.79) 1.35 (0.85, 2.13) 1.03 (0.54, 1.96)
NMUPD non-medical use of prescription drugs, NSDUH National Study on Drug Use and Health, n number of participants, aOR adjusted odds
ratio, CI confidence interval a Respondents were classified based on 0 moves (non-mobile), 1–2 moves (low mobility), and C3 moves (residential instability) b Model is adjusted for race, sex, age, financial assistance, perceived overall health, bonding to school, sensation seeking behavior, average
grades, delinquent behavior, other drug use, parental monitoring, parental disproval of drug use, peer drug use, peer disapproval of drug use,
availability of drugs, and school norms against drug use
Matern Child Health J (2015) 19:2646–2653 2651
recall residential mobility that took place within the past
5 years, thus potentially reducing errors in reporting of
residential mobility. A limitation of using secondary data
to answer this research question, however, is that the def-
inition of residential mobility employed was dependent on
the questions asked during the survey, preventing the
consideration of the effect of the distance between moves
on the outcome. Furthermore, because the data are cross-
sectional in nature, the temporal relationship between
moving in the last 5 year and lifetime use of NMUPD is
unclear. Given the age range of the participants, however,
the likelihood of initiation of drug use prior to any moving
in the previous 5 years is less likely than in an older
In addition, we were unable to control for adverse
childhood experiences (ACE), which could confound the
association between frequency of moves and NMUPD.
Potentially important ACE factors (e.g., parental divorce,
abuse, and family dysfunction) were not included in the
NSDUH interview. ACE have been studied with regard to
their influence on child health, their continued impact on
adult health, alcohol initiation, drug addiction, and lifetime
drug use [8, 9]. Though the influence of ACE on the
relationship between frequent childhood and adolescent
moves and NMUPD has not been studied, the current study
did explore numerous variables under the application of the
social-ecological model. Variables exploring financial sta-
bility, perceived health and risk of drug use, parent moni-
toring, delinquent behaviors, and parental/peer use and
disapproval of drugs may serve as proxy measures for
certain ACE factors, for which the current study was
unable to control.
Based on these findings, childhood residential mobility is
associated with adolescent NMUPD, with the magnitude of
the association increasing with more moving. Future
research should further examine the association between
moving and NMUPD, particularly with regard to the
direction of the association and the types of drugs involved.
In addition, interventions to prevent prescription drug
misuse and abuse among adolescents should be developed
for and targeted towards mobile adolescents and the par-
ticular challenges faced by this group. Given that pre-
scription drugs are most commonly obtained from family
and friends, and the influence that parents have on ado-
lescent initiation of drug use, future interventions should
also target parents of residentially mobile adolescents.
Acknowledgments Kelly Gurka was partially supported by the Centers for Disease Control and Prevention, National Center for
Injury Prevention and Control, Grant R49CE002109. The content is
solely the responsibility of the authors and does not necessarily rep-
resent the official views of the CDC.
Conflict of interest The authors declare no conflict of interest.
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- Association Between Childhood Residential Mobility and Non-medical Use of Prescription Drugs Among American Youth
- Data Source
- Independent Variable
- Dependent Variables
- Statistical Analysis