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10-Year Incident Monitoring Trends in Outdoor Behavioral Healthcare: Lessons learned and future directions

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JTSP  •  99
10-Year Incident Monitoring Trends in
Outdoor Behavioral Healthcare: Lessons
learned and future directions.
Stephen E. Javorski, MA
Research Assistant
Outdoor Behavioral Healthcare Research Cooperative
University of New Hampshire
Michael A. Gass, PhD, LMFT
Director
Outdoor Behavioral Healthcare Research Cooperative
University of New Hampshire
Risk in Outdoor Programming
Risk is an inherent and requisite element of wilderness and adventure-
based programming, intentionally used by skilled facilitators and therapists
to create a state of eustress in clients to support positive development
(Russell & Harper, 2006). Providers of adventure programming strive
to minimize inappropriate risks in client experiences while maintaining
appropriate levels of actual and perceived risks sufcient to create the 
adaptive dissonance necessary to support positive change (Gass, Gillis, &
Russell, 2012; Priest & Gass, 2005). In addition to physical risks, Outdoor
Behavioral Healthcare (OBH) programs provide clients opportunities to
confront social, emotional, and behavioral risks through Adventure Therapy
(AT) interventions. This involves the prescriptive use of adventure activities
by mental health professionals to kinesthetically engage clients on affective,
behavioral, and cognitive levels (Gass et al, 2012). The key to this process
is to manage risks so that clients are engaged in these experiences enough
to foster functional change while limiting their exposure to inappropriate
dangers.
One important method professionals use to manage such risks is to
track incidents occurring while clients are in the eld so they may better 
understand the factors that lead to accidents and other negative incidents.
This is done to enable OBH professionals to adapt programming to
reduce the likelihood of similar incidents in the future. There have been
considerable efforts to assess injury and illness rates in outdoor programs
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100  •  JTSP
over the past 20 years (Boulware, Forgey, & Martin, 2003;Auerbach, 1992).
One of the most comprehensive analyses of incidents in adventure
activities comes from data developed through the WRMC/AEE Incident
reporting project conducted from 1992 – 2008.  This project provided 
insight into the types and severities of incidents commonly occurring in
guided adventure activities, and established industry-wide injury and illness
rates by activity (Leemon, 2008).While this information can serve as a 
benchmark to compare OBH incident rates, several differentiating factors
must be considered. OBH clients differ from most clients in other forms
of adventure programming in two signicant ways: (1) OBH clients are 
primarily drawn from at-risk adolescent populations and can be placed
in program against their will and (2) training in high –risk adventure 
activities is not the primary focus of OBH programs (Russell and Harper,
2006). It is possible that these differences in client and program level
characteristics may be related to higher or lower incident rates, therefore
direct comparisons of OBHIC to WRMC/AEE or other expeditionary
education providers such as the National Outdoor Leadership School
(NOLS) are not ideal. In addition, the WRMC data does not track incident
data regarding physical restraints, a practice that is often associated with
behavioral healthcare programs.
Physical Restraints
The use of physical restraints is a frequent intervention in inpatient
mental health settings (Prinsen & van Delden, 2009).A review of the 
literature prior to 2000 reports prevalence rates of 28% -60% in 
psychiatric facilities serving children and youth (De Hert, Dirix, Demunter,
& Correll, 2011). There is some evidence that physical restraint is an
acceptable practice with children and adolescents when they in in danger
of causing harm to themselves and others (Dean, Duke, George, & Scott,
2007; Delaney, 2006). However, the majority of evidence supports the
contrary, showing restraints to be physically and emotionally harmful to
both staff and clients (De Hert, et al., 2011; Masters et al., 2002; Miller, Hunt,
& Georges, 2006). Nunno, Holden, and Tollar (2006) reported 45 fatalities
related to restraints in child and adolescent mental health facilities between
1993 and 2003, and there is signicant ethical concern from the national 
and international community about these practices (Steinert et al., 2010).
In 2003, the Substance Abuse and Mental Health Services
Administration (SAMHSA) published a National Action Plan for reducing
the use of restraints in mental health services. The plan suggested changes
in policy to empower staff to use treatment approaches that discouraged
the need for restraints, and called for improved monitoring of restraint
interventions in the mental health industry (SAMHSA, 2003). Several
programs have been developed to address these goals, and evidence found
signicant decreases in restraint rates in child and adolescent mental 
health facilities following their implementation (LeBel et al., 2004; Martin,
Krieg, Esposito, Stubbe, & Cardona, 2008; McCue, Urcuyo, Lilu, Tobias,
& Chambers, 2004; Miller, et al., 2006). Despite signicant reductions in 
restraint rates in such programs, the National Association of State Mental
Health Program Directors Research Institute (NRI) reported the national
restraint rate for youth ages 13-17 in inpatient mental health care was
8.4 hours of restraint per 1000 client days, with 10.8% of all clients being 
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JTSP  •  101
restrained during treatment as of December 2009 (NRI, 2010). Given the 
Miller Bill’s (Stop Child Abuse in Residential Programs for Teens Act, 2008) 
claims that wilderness therapy programs were excessively dangerous and
frequently overused physical restraints, it became extremely important
for OBH programs to examine the validity of these claims and accurately
document restraint rates while working to reduce them as much as
possible.
OBHIC Risk Incident Tracking
The Outdoor Behavioral Healthcare Industry Council’s (OBHIC) risk
management database specically examines incidents, illnesses, and restraint 
rates in residential Outdoor Behavioral Healthcare (OBH) programs,
and has contributed to this knowledge base since its inception in 2001
(Outdoor Behavioral Healthcare Research Cooperative (OBHRC), 2011;
Russell & Harper, 2006). Previous analyses of OBHIC data have shown
promising trends in OBH program incident, illness, and restraint rates
(OBHRC, 2011). The OBHIC injury rate has been relatively stable since
2001, the illness rates have shown a consistent decreasing trend (OBHRC
2011), and the OBHIC restraint rate in 2010 was more than four times
smaller than that found in inpatient mental health facilities serving youth
in the United States (Gass, et al., 2012). Although the OBHIC data has
clearly described incident types and frequencies, information about the
circumstances surrounding each incident has not been included in the
database to this point.
A deeper understanding of the factors related to incidents and
actual incident rates in Outdoor Behavioral Healthcare programs is
essential to practitioners seeking to improve their own risk management
practices. Such ndings may have substantial practical application for OBH 
practitioners, for once patterns in incident rates are established for OBH
programs, practitioners can make informed decisions about when to
increase staff to client ratios, alter programming to provide appropriate
levels of physical and emotional challenges, and change timing for meals,
technical skill lessons, therapeutic processing, and reection in order to 
more effectively manage or reduce exposure to actual risk in the eld.
The purpose of this study was to: (1) identify trending in OBHIC 
incident rates since data collection began in 2001; (2) explore the
relationships between injury, illness, restraint, and runaway rates in OBHIC
programs and time of day, current activity, and percentage of the program
completed at the time of the incident; and (3) evaluate these results in the
context of injury and illness data from the WRMC/AEE incident tracking
project (Leemon, 2008), traditional expeditionary programming for youth,  
and national restraint and injury rate estimates for adolescent in inpatient
treatment centers.
Methods
The following criteria were established for incidents to be included in
the annual report to the risk management database . Level one injuries and
illnesses were dened as any such incident requiring a client to spend more 
than 12 hours out of regular programming (including time spent at rest in
the eld). Injuries and illnesses were categorized as Level two if the incident 
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102  •  JTSP
required the client be removed from regular programming for more
than 24 hours. Runaways were similarly divided, with Level one runaways
referring to clients who were away from regular programming for 12 hours
or more, and Level two runaways referring to incidents when clients were
away from their group from 24 hours or more. Restraints were dened as 
any action that restricted a client’s freedom of movement against their will,
even in the absence of physical or chemical restraint devices. While OBHIC
has historically categorized such actions into three categories based on
duration of the hold, they were collapsed this year to allow for easier
comparison to restraint rates in other programs.
All injuries and illnesses (guides and clients), as well as runaways and
restraints (clients only) meeting these criteria were recorded by OBHIC
member programs for 2011 (n = 12) and submitted to the OBHIC incident
database at the University of New Hampshire. Note that data was not
collected in 2005. Starting in 2011, the activity the client/guide was engaged
in, weather, number of client days in program, time of day, and date at the
time of each reportable incident, as well as total client and staff eld days,
average length of stay, total clients enrolled, and total clients completing
treatment were reported. In 2011, 181 client incidents were reported over 
70,028 client eld days, with an additional 28 guide incidents over 30,001 
guide eld days, for a total of 209 incidents over 100,029 user days.
Client and staff injury and illness rates, as well as client restraint and
runaway rates, were calculated in terms of incidents per 1000 client/
guide eld days, where one eld day was dened as a 24 hour period in a 
program for one client. In addition, total OBHIC incident and illness rates
were calculated by aggregating client and guide incident data. Incident rates
were calculated by combing Level one and Level two data in all categories.
OLS regression analyses were conducted on all incident rates by year to
identify trends in incident rates over time. Data was further disaggregated
by activity, time of day, and percentage of program completed (based on
average length of stay) at the time of incident. Data about activity duration
was not collected in 2011, and therefore incident rates by activity could not
be calculated. Frequency data was further explored through histograms.
Results
Injuries
The total client injury rate in OBHIC member programs for both
Level 1 and 2 injuries was 0.51 per 1,000 client eld days in 2011, or one 
client injury for every 1,961 client days of programming. When only Level 
2 injuries were calculated, including both those that were eld manageable 
and those that required evacuation for medical attention, the injury rate fell
to 0.11 per 1000 client eld days, or one injury every 9,091 client days.The 
average client injury rate for programs contributing to the OBHIC database
since 2001 was 0.52 injuries per 1000 client eld days, or 1 injury for every 
1,923 days of client programming. Figure 1 illustrates OBHIC incident rates 
by year since 2001. Regression analysis indicated a slight positive trend in
the incident rate since 2001, estimating a negligible increase of 1 additional
client injury every 58,824 client eld days per year. Note however that the 
regression coefcient of this increase was not signicant (β = .018,p = .34).
This suggests that with the currently available data time was not a signicant 
LESSONS LEARNED AND FUTURE DIRECTIONS
JTSP  •  103
prediction of client injury rate.
The guide injury rate on OBHIC ranged from a high of 0.83 injuries 
per 1000 eld days in 2011 to a low of 0.32 injuries per 1000 guide eld 
days in 2001 (see Figure 1). The 10-year average guide injury rate was
0.55 injuries per 1000 guide eld days, or one guide injury for every 1,827 
guide eld days. Regression analysis indicated a slightly positive, but again 
insignicant trend in guide injury rate since 2001 (β = .023,p = .107).
Total OBHIC annual injury rates are displayed in Figure 2. The average
total injury rate in OBHIC programs since 2001 was 0.53 injuries per
thousand eld days, or about one injury for every 1,887 eld days. The total 
injury rate ranged from a low of 0.36 per thousand eld days in 2003 to a 
high of 0.75 injuries per thousand eld days in 2007.
Illnesses
Client illness rates (see Figure 3) have ranged from 0.26 per 1000
client eld days in 2003 and 2011 to 0.69 illnesses per 1000 client eld 
days in 2006. Practically speaking, this range indicates at the highest point
in 2006 there was one client illness for every 1449 client eld days, while 
at the lowest illness rate in 2003 and 2011 there was on client illness every
4348 client eld days. The average illness rate in OBHIC programs since 
2001 was 0.40 illnesses per 1000 client eld days or one client illness for 
every 2,529 day of client programming. Regression analysis indicated a 
slight negative trend in illness rates since 2001, estimating a decrease of
one illness for every 71,429 client eld days per year.As with the injury 
analysis, the regression coefcient was not signicant (β = -.014,p = .287), 
indicating that time is not a signicant predictor of illness rate with the 
available data.
Guide illness rates are displayed by year in Figure 3. The 10 year average
guide illness rate in OBHIC programs was 0.22 illnesses per 1000 guide eld 
days, or one guide illness every 4,632 days. The guide illness rate reached
its lowest historical level in 2011, when there was one guide illness every
10,000 guide eld days. Regression analysis indicated a slightly negative, but 
statistically insignicant trend in guide illness rates (β = -.017,p = .189).
Client Restraints
As illustrated in Figure 4, OBHIC restraint rates have been decreasing
since 2006. It is of note that when OBHIC reported their highest restraint
rate in 2006, one program reported 42% of all restraints. Since 2001, the 
OBHIC programs have reported an average restraint rate of 1.95 restraints 
per 1000 client eld days, or one restraint for every 513 client days. In 
2011, OBHIC reported the lowest restraint rate since 2001, with one
restraint occurring every 763 days. Regression analysis suggested a slightly
positive but statistically insignicant trend in restraint rate since 2001 (β = 
.010, p = .828).
Runaways
The OBHIC runaway rate has ranged from a low of 0.32 per one
thousand client days in 2004 to a high of 1.54 runaways per thousand
client days in 2010. This translates to one runaway for every 3,125 client
days in 2004 and one runaway every 649 client days in 2010.The increased 
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104  •  JTSP
runaway rate in 2010 can be largely attributed to one program reporting
82% of the runaways that year.The average OBHIC runaway rate since 
2001 was 0.73 per thousand client days, or one runaway every 1,368 days.
Excluding data from 2010, this rate fell to 0.63 runaways per thousand
client eld days or one runaway every 1,599 client days. Regression analysis 
indicated a relatively stable trend in the OBHIC runaway rate since 2001,
though the relationship was statistically insignicant (β = .005,p = .886).
Incident Frequency and Time of Day
Figure 5 illustrates the frequency of restraints, runaways, injuries, and
illnesses for both clients and staff by time of day. Client injuries did not
occur before 9:00am, and they reached their greatest frequency between 
9:00-10:00am.There were additional increases in injury frequency between 
3:00-4:00pm and 5:00-6:00pm. Frequency of staff injuries also peaked early 
in the day between 7:00am and 8:00am, with a second increase between 
3:00-5:00pm.  
While there were insufcient staff illnesses data to identify any trends,
the most frequent time of onset for client illness was 8:00-10:00 am, with 
additional increases in frequency around lunch and dinner time. Restraint
frequency was very low before 9:00am, and most frequent between 12:30-
1:30pm and 4:00-6:00pm. Runaway frequency was also highest between 
12:30-1:30pm, and exhibited secondary increases from 9:00-10:00 am and 
4:00-6:00pm.
Incident Frequency and Percentage of Program Completed
Figure 6 illustrates incident frequency by the percentage of the
program the client had completed at the time of the incident for 2011.
Incidents that occurred when the client had been in the program for
longer than that program’s average length of stay at the time of the incident
were coded as 105% of the program completed. Data regarding staff days 
in program were not collected, and so the results refer only to client
incidents for 2011.
Injury frequency was also greatest earlier in the program for clients,
but unlike restraint and runaway frequencies, peaked between 6% and 20% 
of average treatment time. Injury frequency increased again slightly at 50% 
of average treatment time, then tapered off, with the exception of a small
increase in injury frequency for clients who had been in treatment longer
than the average length of stay for their respective program.
Illness frequency peaked early in the program, and tapered down over
the rst 20% of average time in treatment.There was a slight increase in 
illness frequency at the 40% program completion mark, followed by very 
few illnesses until the nal 20% of time in treatment. There was a slight 
increase in illnesses reported for clients who had been in treatment longer
than the average length of stay at their respective program.
Restraints most frequently occurred at the very beginning of
treatment, with about 41% of all restraints reported during the rst 6% 
of average treatment time and 64% of all restraints reported during the 
rst 20% of average treatment time. There was a small increase in restraint 
frequency for clients who had been in treatment longer than the average
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JTSP  •  105
length of stay for their respective program.
Runaways were also most frequent at the beginning of the program,
with about 31% of all runaways reported during the rst 6% of average 
treatment time and 57% of all runaways reported during the rst 20% 
of average treatment time. As with injury, illness, and restraint frequency,
there was a slight increase in runaway frequency for clients who had been
in treatment longer than the average length of stay for their respective
program.
Incident Frequency and Activity
Activity data were available for 166 of 182 client incidents and all 28 
staff incidents in 2011.About 56% of all client incidents and 54% of all staff 
incidents (see Table 1) on OBHIC programs in 2011 occurred during times
of transition or while hiking. No comparative analyses can be made about
the relative safety of individual activities, as the number of participant days
devoted to each activity listed was not reported in 2011.
In 2011, client injuries most frequently occurred while clients were
hiking (51.5%), in transition from one activity to another (24.2%), and 
while breaking camp and obtaining water (3.1%). Staff injuries were most 
common while staff were hiking (36%), in transition from one activity to 
another (16%), or were caused by a client (8%). Client Illnesses were most 
commonly reported while clients were hiking (29.4%), during meal time 
(23.5%), and while clients were sleeping (17.6%). Staff illnesses were most 
frequently reported while hiking (67%) and while hiking (33%), however,
only three staff illnesses were reported in 2011. More data are needed
before a denitive pattern in staff illnesses by activity can be established.
Restraints were most frequent while clients were in transition from
one activity to another (37%), hiking (14.8%), and during the intake process 
(9.9%). Runaways were most frequent while clients were hiking (34.3%, in 
transition from one activity to the next (20%), and while sleeping (11.4%).
Discussion
The purpose of this study was to address the following research questions:
1. What were the trends in OBHIC annual incident rates since 2001?
2. What were the relationships between OBHIC client and staff incident
frequencies and time of day, percentage of program completed, and
activity at the time of an incident?
3. How does the OBHIC incident data compare to data established
through the AEE/WRMC incident monitoring project (Leemon, 2008), 
traditional expeditionary education courses for youth (NOLS, 2011),
and national restraint/injury data for youth in inpatient mental health
services?
10-Year OBHIC Incident Trends
While regression analyses of OBHIC incident rates over time did not
show any signicant relationships between incident rate and time, they did 
indicate that injury, illness, restraint, and runaway rates appear relatively
stable over the 10 year history of the OBHIC incident tracking project.
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106  •  JTSP
Despite this, there are some variations in the data that warrant attention.
First, in 2007, when the peak client injury rate was reported, OBHIC
programs also experienced record high enrollment. It is possible that in
order to accommodate this, there were more new staff than usual in the
eld, or that staff experienced less down time between shifts than in other 
years, leading to an elevated injury rate. Further exploration of the impact
of guides’ level of experience and duty cycles are warranted in future
analyses.
Second, when OBHIC reported their highest restraint rate in 2006,
it was the only year where a program that worked exclusively with
adjudicated youth participated in the incident reporting project. This
program reported 40% of restraints lasting 30 minutes or longer, while 
another program reported 45.6% of all restraints lasting less than 30 
minutes. It is possible that different standards of practice in the adjudicated
youth program, and inconsistencies in restraint reporting from the other
outlier program, signicantly impacted the restraint rate for 2006. Future 
research should include analysis of client and program level characteristics
to better understand their relationship to incident trends.
OBHIC Incident Frequencies and Time of Day, Percentage of
Program Completion, and Activity
The incident trends by time of day displayed in Figure 5 reect anecdotal 
trends commonly reported by eld staff. Injury and illness frequency increase 
signicantly early in the day, or about the time when OBHIC groups break 
camp and begin the day’s travel. While restraint and runaway frequencies also
increase at this time, they are highest around lunch time, when clients were
often transitioning from a meal at rest back to travel. Restraint, runaway, and
injury frequencies all increased again in the late afternoon, when clients are
often coming to the end of a long day of travel, or in transition before the
evening meal. This data suggests that programs may benet from exploring 
ways to help clients better manage transitions from states of relative rest to
travel.
The majority of OBHIC incidents occurred early in a client’s stay in
program ; 56.9% of all restraints, 54.3% of all runaways, and 40% of all injuries 
occurred during the rst 20% of clients’ time in treatment. There also was a 
signicant increase in incidents for those clients who had been in treatment 
longer than the average length of stay for their program. This suggests that
programs could benet from developing strategies to better help clients 
transition into program. It is possible that increased staff to client ratios,
contact time with clinical staff, and reduced intensity of travel early in the
program might help to further decrease incident rates early in treatment, and
should be further explored.
Although the present results do not allow for the calculation of incident
rates by activity, and no statements about the relative risks of each activity
type can be made, there are some clear trends. That the majority of injuries
occur while groups are hiking is not surprising; the WRMC/AEE Incident
Reporting Project showed that the most common type of injury during
wilderness-based programming with youth were athletic injuries such as
sprains and strains (Leemon, 2008).That incident rates are also elevated 
during transition times on OBHIC programs suggests that it would be
LESSONS LEARNED AND FUTURE DIRECTIONS
JTSP  •  107
benecial for programs to explore strategies to help clients better cope with 
these times of change. Further research into factors related to incidents
occurring during these times is warranted.
OBHIC Incident Data in Relation to Comparative Injury Rates
The U.S. Center for Disease Control and Prevention estimated the
national average rate of injuries for adolescents treated in U.S. hospital
emergency rooms was 0.38 per 1000 days in 2010 (WISQARS, 2011). The 
rate of injuries in Outdoor Behavioral Healthcare programs in 2011was
0.51 injuries per 1000 days, only increasing the actual risk of injury to
an adolescent by 0.13 incidents per 1000 days (or 1 additional incident
every 7692 participant days). Given that most clients who participate in 
Outdoor Behavioral Healthcare programs are generally involved in higher
risk behaviors than the general population statistic reported above (e.g.,
substance use, reckless driving, self-abusive behaviors), it is quite plausible to
state that given the high risk behaviors of these clients, and the current state
of risk management practices in Outdoor Behavioral Healthcare, there is
less actual risk for these youth while on OBHIC programs than while in the
general population (Gass, Gillis, & Russell, 2012).
Note this conservative Figure used by OBHIC includes injuries that
were treatable in the eld, and did not require additional medical attention.  
When only those injuries that required OBHIC participants be removed
from regular programming for 24 hours or more were counted (including
some treated in the eld, and some who were evacuated to emergency 
rooms/medical attention), the OBHIC injury rate fell to 0.11 in 2011, or one
injury requiring medical attention every 9,091 client days. The U.S. Center 
for Disease Control and Prevention estimated the national average rate
of injuries for adolescents treated in U.S. hospital emergency rooms was
0.38 per 1000 days in 2010 (WISQARS, 2011). Therefore, in 2011, OBHIC 
program clients were about three times more likely to go to the emergency
room for an injury at home as they were while on program.
The National Outdoor Leadership School (NOLS) offers wilderness-
based expeditionary education experiences to youth and adults, with a
focus on technical and leadership skill development. While OBHIC injury
rates cannot be directly compared to NOLS because of differences in
client characteristics, purpose of programming and denitions for medical 
incidents, NOLS is viewed as a leader in wilderness risk management; until
more longitudinal incident data is compiled by OBHIC, NOLS can serve as a
benchmark to quality.The NOLS incident denitions are more inclusive than 
OBHIC’s, so Figure 7 compares the NOLS medical evacuation rate (injuries
and illness) to the total medical incident rate of OBHIC programs (all injuries
and illnesses, including those managed in the eld) for 2011, ve year average,
and 10 year average values. The comparison suggests that OBHIC injury and
illness rates are slightly below those of traditional educational expeditionary
programs for youth.
This analysis clearly supported OBHIC programs, contrary to claims
made against wilderness therapy programs in the Miller Bill (Stop Child Abuse
in Residential Care Act, 2008). OBHIC program members have been able to 
provide quality wilderness-based interventions to clients without exposing
them to undo levels of risk. Further support for the ability of OBHIC programs
LESSONS LEARNED AND FUTURE DIRECTIONS
108  •  JTSP
to effectively manage risk to clients was apparent when comparing OBHIC
incident rates to those of more common activities and guided outdoor pursuits
(see Figure 8). Participants on guided backing, mountain biking, downhill skiing,
and snowboarding courses are about 1.5, 5.5, 10, and 33 times as likely to be
injured as OBHIC clients respectively (Leemon, 2008). When compared to 
traditional team sports, high school football players are 30 times more likely to
be injured during a practice, and 141 times as likely to be injured during a game
as an OBHIC client in treatment.
A further charge against wilderness therapy providers in the Miller
Bill is the overuse of physical restraints in the treatment process. When
compared to existing national data on restraint rates in inpatient treatment
facilities youth (assuming the average length of restraint in these facilities
was 60 minutes), OBHIC clients were more six times less likely to be
restrained in treatment than youth in inpatient mental health care in the
US (NRI, 2010). While it is necessary to consider the population served
by inpatient facilities likely presented with higher levels of symptom acuity
than clients of OBHIC programs, this comparison provides compelling
evidence against the claims in the Miller Bill.
Limitations
While the study results are promising, there are several limitations
that need to be considered. First, the programs participating in the OBHIC
Risk Incident Monitoring Project have not been consistent throughout the
history of data collection. Additionally, some contributing programs are much
larger than others. Both of these variables may have led to inconsistencies
in the results, and also limit the extent to which study conclusions can be
generalized across programs. As stated earlier, programmatic differences may
have a signicant impact on incident rates, and such differences were not 
accounted for in this analysis.
Second, although data collection was based on a common set of incident
denitions, reporting was generally done at the end of the year and it is 
possible that staff across different organization had different interpretations
of the incident denitions.This may have led to some inconsistencies in the 
data. OBHIC will be transitioning to live online incident reporting starting in
2013, which may help to address this concern.
Data collection did not include any identifying information, and as such, it
was impossible to identify clients involved in more than one incident. Future
research should include some method for tracking this, and potentially linking
incident data to individual level demographic and outcome assessments.
Third, this data was only collected for those programs participating in
the OBHIC research database. Generalization of the ndings needs to be 
restricted to those programs participating in the study and those following
the risk management procedures of OBHIC programs.
Finally, this study did not allow for comparisons of the relative risk
associated with participating in different activities while on OBHIC programs.
Future studies should include information about the time spent in each
activity to improve the understanding of the risks associated with different
activities and methods of travel for OBHIC clients and guides.
LESSONS LEARNED AND FUTURE DIRECTIONS
JTSP  •  109
Conclusions
The OBHIC Risk Incident Project is the longest-operating active risk
management database tracking incidents across multiple programs for any
outdoor pursuits, including wilderness therapy. Despite the limitations of
this study, results indicated OBHIC programs provide wilderness-based
treatment programs to clients without exposing them to relatively low
levels of physical risk. Continued expansion of the data collected through
this project will continue to expand understanding of the factors related to
incidents in OBH programs. OBH service providers can greatly benet from 
participating in this project, and from sharing their methods for addressing
risk in the back country, especially in those situations shown to be related to
higher incident frequencies. Continuing risk-related incident research in OBH
programs is essential, and may help inform programmatic changes to further
reduce clients’ exposure to inappropriate risks in the future.
LESSONS LEARNED AND FUTURE DIRECTIONS
110  •  JTSP
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Stop Child Abuse in Residential Programs for Teens Act, HR 5876 (2008).
WISQARS. (2011). Overall all injury causes nonfatal injuries and rates 
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Center for Injury Prevention and Control, CDC.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
2001 2002 2003 2004 2006 2007 2008 2009 2010 2011
ClientInjuryRate GuideInjuryRate
Figure 1. Client and guide injury rates per thousand client/guide eld days between
2001 and 2011
LESSONS LEARNED AND FUTURE DIRECTIONS
JTSP  •  113
Figure 2. OBHIC total injury and illness rates per thousand participant days (clients
& sta)
Figure 3. Client and guide illness rates per thousand client/guide eld days from
2001-2011
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
2001 2002 2003 2004 2006 2007 2008 2009 2010 2011
TotalInjuryRate TotalIllnessRate
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
2001 2002 2003 2004 2006 2007 2008 2009 2010 2011
ClientIllnessRate GuideIllnessRate
LESSONS LEARNED AND FUTURE DIRECTIONS
114  •  JTSP
Figure 4. Client restraint and runaway rates per thousand client eld days between
2001 and 2011
0
0.5
1
1.5
2
2.5
3
2001 2002 2003 2004 2006 2007 2008 2009 2010 2011
OBHICRestraintRate OBHICrunawayRate
Figure 5. OBHIC incidents by type, person, and time of day for 2011
LESSONS LEARNED AND FUTURE DIRECTIONS
JTSP  •  115
Figure 6. Client incidents by incident type and %age of program completed at time of
incident for 2011
Figure 7. OBHIC medical incident rates vs NOLS medical evacuation rates in 2011,
5-year and 10-year averages
0
0.2
0.4
0.6
0.8
1
1.2
1.4
2011 5yearaverage 10yearaverage
NOLSMedialEvacuationRate
OBHICMedicalIncidentRate
LESSONS LEARNED AND FUTURE DIRECTIONS
116  •  JTSP
Figure 8. OBHIC 2011 client injury rates compared to incident rates in organized
outdoor activities
72.24
16.77 15.36
5.15
2.92
0.77 0.51
0
10
20
30
40
50
60
70
80
HighschoolFootballGames(Shankaretal,2007)
Snowboarding(Leemon,2008)
HighschoolFootballPractice(AJSM,2007)
DownhillSkiing(resort)(Leemon,2008)
MountainBikingInjury(Leemon,2008)
Backpacking(Leemon,2008)
OBHRC(2011)
Table 1: Client incident frequencies by incident type and activity*
Client  Staff Total
RestraintRunawayInjuryIllnessClient
Sub-Total
Injury Illness Staff Sub-
Total
All
Incidents
Activity at
time of
incident
Hiking12(14.8%)12(34.3%)17(51.5%)5(29.4%)46(27.6%)9(36.0%)2(66.7%)11(39.3%)57(29.4%)
Solo01(2.9%)0 01(.06%)0001(0.5%)
Group 1(1.2%)1(2.9%)01(5.9%)3(1.8%)0003(1.5%)
Latrine02(5.7%)002(1.2%)0002(1.0%)
BreakingCamp01(2.9%)1(3.1%)02(1.2%)1(4.0%)01(3.6%)3(1.5%)
Transition/InCamp30(37.0%)7(20.0%)8(24.2%)2(11.8%)47(28.3%)4(16.0%)04(14.3%)51(26.2%)
MealTime5(6.2%)004(23.5%)9(5.4%)1(4.0%)01(3.6%)10(5.2%)
GettingWater6(7.4%)1(2.9%)1(3.1%)08(4.8%)1(4.0%)01(3.6%)9(4.6%)
Intake8(9.9%)0008(4.8%)0008(4.1%)
MedicalProcedure3(3.8%)01(3.1%)04(2.4%)0004(2.1%)
Sleeping04(11.4%)03(17.6%)7(4.2%)0007(3.6%)
CampSetUp1(1.2%)1(2.9%)1(3.0%)03(1.8%)0003(1.5%)
MedRun02(5.7%)002(1.2%)0002(1.0%)
Other7(8.6%)0 1(3.0%)2(11.8%)10(6.0%)2(4.0%)1(33.3%)3(10.7%)13(6.7%)
Group/StaffChange1(1.2%)0001(0.6%)0001(0.5%)
Transport3(3.8%)0003(1.8%)0003(1.5%)
Therapy(Indiv)2(2.5%)0002(1.2%)0002(1.0%)
Bedtime1(1.2%)0001(0.6%)0001(0.5%)
Cooking001(3.0%)01(0.6%)0001(0.5%)
UsingTool/Knife001(3.0%)01(0.6%)3(12%)03(10.7%)4(2.1%)
Horses01(2.9%)001(0.6%)1(4.0%)01(3.6%)2(1.0%)
Surfing01(2.9%)001(0.6%)0001(0.5%)
Canoeing1(1.2%)1(2.9%)002(1.2%)0002(1.0%)
XCSkiing001(3.0%)01(0.6%)1(4.0%)01(3.5%)1(0.5%)
CausedbyClient000002(8.0%)02(7.1%)2(1.0%)
Total 81 35 3317 16625328194
(…) =%age of incidents during activity for that incident type
* is chart was generated using all incident entries that included activity data (n = 166 of 182 total client
incidents)
LESSONS LEARNED AND FUTURE DIRECTIONS
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This study aims to provide an overview of the scientific literature on the benefits of wood lands on people’s health, well-being, and quality of life. Its intention is to high light the advantages of the forest as a place for leisure activities, restoration, recovery from stress and further social and therapeutic interventions. Its aim is to take stock of the current state of the scientific knowledge and provide a knowledge base for projects re lating to Green Care in wood - lands and Green Public Health. Both scientific and practical pro - jects have been taken into account. We conducted a comprehensive review of the literature in order to collate and synthesise the findings of studies investigating the benefits of woodlands on human health and well-being. In the process, we surveyed the research published in scientific journals between 1993 and 2013. Reports in books and grey literature supplement the results of our systematic search. Overall, the study includes 149 peer-reviewed articles as well as 31 landmark publications, originating mainly from Western countries and East Asia, specifically from Korea and Japan. Shinrin-yoku, which translates as “forest bathing”, is currently considered apreeminent and hot topic in restoration research. Shinrin-yoku strives at connecting the positive effects of forests for physical and mental well-being. Generally, the findings of the scientific work we reviewed suggest that the time spent in woodlands can have positive effects on physical, psychological and social health and on well-being. These effects may come about due to the promotion of physical activity or simply on account of enjoying the atmosphere in the woods. More specifically, spending time in forests increases positive emotions, decreases negative emotions and helps in coping with subjectively experienced stressors. This is how woodlands contribute to mental health. With respect to physiological stress indicators, most of the studies reported positive effects and prevention of stressrelated diseases. Social forestry projects make use of the forest’s inclusive potential for the benefit of the socially vulnerable. Wilderness therapy programmes as well as therapeutic activities in a healing forest are cited as practical examples that make use of the forest’s healing powers. In scientific literature, Nacadia in Denmark serves as the bestdocumented example for a healing forest garden. Further best-practice examples can be found in a number of different countries in Europe, Australia and Asia. In woodlands, well-being can be affected by the duration of the stay, the activities undertaken and the physical exercise performed as well as the social context. Even short visits can have recreational effects. Sports activities and exercises can enhance these positive effects. Especially for mental health, woodlands seem to provide more benefits than other environments and settings. A sense of safety, supported way-finding, accessibility, easy legibility of the terrain and walk - ability, but also a certain degree of natural diversity and alter - nation are important aspects of the beneficial effects. Both crowding and the complete absence of other people are considered negative, with perceived safety being an important aspect of well-being. A well-kept but natural-looking impression, open tree stands and lots of light at the site as well as the absence of noise are further advantages that get people to feel at ease in woodlands. There are numerous studies on how the monetary value of the benefits provided to the population by recreational forests is calculated. Woodlands furnish precious non-tradable goods such as recreation and health effects. The positive influence of (computer- generated) virtual forests was likewise demonstrated in the medical context, albeit with less intensity. Evaluation studies clearly underscore the impor - tance of collaboration between the woodland sector, health professionals, the government and local structures. We found there to be an ongoing social trend towards visiting wooded areas more frequently. This trend is reflected in the growing number of scientific publications worldwide. Empirical evidence for the positive effects of natural landscapes in general on health and well-being appears to be better researched than that for woodlands in specific. Similarly, em pi - rical evidence for the restorative power and health benefits of woods appears to be better evaluated than therapeutic interventions. As a special natural area, woodland can have numerous positive effects on physical, psychological and social health as well as human well-being. Projects in practice could benefit from the reported findings in three ways. Firstly, from the theoretical and empirical background. Secondly, from the detailed information relating to the planning, development and evaluation of an intervention. Thirdly, from the special layout requirements that wooded areas need to meet in order to satisfy the needs of the respective user group. This report does not include any cost-benefit calculations and does not cover any issues relating to the legal framework. These should be taken into account in future work, however. Future research should further strive to undertake systematic reviews as well as meta-analyses and be committed to evidence-based practice. Common standards and guidelines on how to evaluate forest-based programmes and interventions are needed to ensure comparability of the results and warrant the quality of the programmes.
... There was no significant correlation between intake BMI and length of stay, suggesting that clients' length of stay was determined by clinical progress rather than physical fitness at the time of intake. In addition, these findings support previous research that, although OBH is seen as putting participants at risk due to the nature of the intervention, it can be in fact less risky than keeping youth in their home environments ( Javorski & Gass, 2013). ...
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This study examined the body composition changes of adolescents participating in an outdoor behavioral healthcare program. The sample was grouped by body mass index (BMI) categories of underweight, normal weight, overweight, and obese to discern the physiological changes across these categories as a result of participation. In addition, this study tested for gender differences and differences based on season of enrollment (summer vs. winter). Paired samples t tests revealed that, on average, adolescent participants moved toward healthier body compositions from intake to discharge. Specifically, underweight participants gained a significant amount of weight, predominantly composed of lean mass. Normal-weight participants stayed at approximately the same weight but gained lean mass and lost fat mass. Overweight and obese participants lost significant amounts of weight. Two-way ANOVA analyses revealed gender differences in terms of weight loss within BMI categories, yet no differences by season or between the genders across seasons were found.
... injuries) in such programmes have hitherto been given only little attention in systematic research and evaluations (Annerstedt & Währborg, 2011). Javorski and Gass (2013) showed that the incidence of injuries among (young) clients is slightly higher than in the remainder of the population. The explanation they provide is that, compared to the general population, most of the clients in the studied programme had an above-average risk of injury. ...
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Objective The primary aim of the present work was to gather scientific literature on the health effects of forest landscapes. While the forest is considered only a marginal aspect in terms of nature and health research priorities, this work focuses on the forest as a special place for leisure and recreation, to reduce stress and as a place for social work and therapeutic interventions. The main aim of the literature review was to identify the current state of the art in order to provide a basis for Green Care and Green Care projects. Method A comprehensive literature review on forest and health was made and supplemented by fundamental knowledge from nature and recreational research. The systematic research considered literature that has been published in scientific journals between 1993 and 2013. These studies were extended to other scientific papers and reports in books and to gray literature. Results Every stay in the forest and forest landscapes has a positive effect on the physical, psychological and social health. Thus, physical activity can be promoted and movement associated diseases be prevented. In addition, a forest stay improves mood and contributes to the overall well-being and mental health. Social forestry projects show the socially integrative function of forest landscapes, which have the goal to strengthen the condition of underprivileged people through guided interventions in the forest with regard to health factors. Research studies are available both for the forest as a therapeutic agent and a setting for therapeutic interventions. These include in particular the Wilderness Therapy Program and Nacadia. Especially in England cooperation between forestry, the health sector and local structures is carefully evaluated and researched. The length of stay, activities and exercises, as well as the social context are the main factors that affect the health effects of the forest. So, already short forest stays have recreational effects. Sporting activities may also enhance these positive effects. Especially for the mental health, the forest seems to be positive and superior to other environments and settings. Both over-crowding and the complete absence of any other person during the stay in the forest are considered potentially negative, with perceived safety being an important aspect. Factors that make a forest stay particularly pleasant, in addition to sufficient orientation ability and clarity, is easy accessibility. A maintained impression, loose stand density and brightness as well as the absence of noise are advantageous to feel good in the forest. Best-practice examples can be found in Europe, Australia and Asia. Especially Shinrin - Yoku ( " bathing in the forest ") is an interesting research topic in Asia. It is about the desire to investigate the positive influences of forests on the physical and mental well-being. In the medical context, positive influences of ( computer-generated ) virtual forests could be demonstrated , albeit with less intensity. Discussion and Outlook Based on the positive effects of natural environments, the physical, psychological and social effects of forests as a special natural landscape have been studied and the many positive effects described. There are numerous studies available on the monetary valuation of the benefits of recreation forests for the population. The forest provides non-tradable goods such as recreation and health effects, which have a high value and benefit to man. Although a number of health-related studies on forests exist, an empirical validation in key areas is still missing and therefore desirable. We observe a current social trend to more frequent stays in the forest, which is also reflected in an increase in scientific publications worldwide. The empirical evidence in the field of nature seems to be more secure compared to the forest. Future research should strive towards evidence-based practice, with systematic reviews and meta-analyses with a focus on forest health as a next step. " ... More and more, research tells us that, the time people spend with forests may help them to stay emotionally well, cognitively effective , connected with others , and physically healthy . " Terry Hartig ( ForHealth , 2008)
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This paper is a direct response to a recent article in this journal by Gass et al. (JAMA 39: 291–302) in which the authors describe an “ethical” model for the involuntary transport of youth into Outdoor Behavioral Healthcare programs, often synonymously referred to as wilderness therapy in the literature. These authors suggest that international law supports involuntary transport and that their approach is research-based, trauma-informed, ethical, and does not interfere with client outcomes. We believe each of these claims to be in error: The international laws cited include strict rules about involuntary transport, professional codes of ethics forbid all but exceptional uses of force, and there is a large literature on the harms of involuntary transport and admission that appears to be ignored. We suggest that involuntary transport is almost always contraindicated for wilderness therapy and this practice is a symptom of what has been called the “troubled teen industry.”
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Österreichs Wälder tragen auf vielfältige Weise zur Gesundheit und zum sozialen Wohlbefinden bei. In diesem Zusammenhang ist auf die vier Funktionen von Waldlandschaften hin­zuweisen: Nutzfunktion, Schutzfunktion, Wohlfahrtsfunktion und Er­holungsfunktion. Vor allem die Erholungsfunktion ist in Bezug auf Green Care und Public Health wesentlich. Das primäre Ziel der vorliegenden Arbeit war es, die wissenschaftliche Literatur zur Wirkung von Waldlandschaften auf Gesundheit, Wohlbefinden und Lebensqualität zu sammeln. Die Studie sollte die Vorteile von Wäldern als spezielle Naturräume zum Aufenthalt in der Freizeit, zur Erholung, zum Abbau von Stress und als Ort für soziale und therapeutische Interventionen aufzeigen. Der Schwerpunkt der Literaturrecherche lag darin, den gegenwärtigen wissen­schaftlichen Erkenntnisstand aufzu­zeigen, um grundlegendes Wissen für Projekte in den Bereichen Green Care und Green Public Health bereitzustellen. Dies gilt sowohl für wissen­schaftliche als auch praktische Projekte. Eine umfassende Literaturrecherche wurde durchgeführt, die Er­gebnisse kategorisiert und zusammengefasst. Die Recherche berück­sichtigte Literatur, die zwischen 1993 und 2013 in wissenschaftlichen Fachzeitschriften veröffentlicht wurde. Eine Erweiterung boten zusätzliche wissenschaftliche Arbeiten und Berichte in Büchern. Insgesamt wurden 149 wissenschaftlich geprüfte Artikel und 31 themenrelevante Publikationen inkludiert. Die bearbeitete Literatur stammt größtenteils aus westlichen Ländern und Ostasien. Vor allem in Korea und Japan stellt Shinrin-yoku einen prominenten und interessanten Gegenstand in der Erholungsforschung dar. Shinrin-yoku, übersetzt als „Baden im Wald“, beschreibt das in Japan traditionelle Bestreben, die positiven Einflüsse von Wäldern auf das körperliche und seelische Wohlergehen zu nutzen.Im Allgemeinen wirken sich Aufenthalte im Wald positiv auf die physische, psychische und soziale Gesundheit aus. Dies kann auf die Förderung körperlicher Aktivitäten oder einen simplen Genuss der Bedingungen im Wald zurückgeführt werden. Im Detail verbessert ein Waldaufenthalt die Stimmung, beugt stressassoziierten Krankheiten vor und trägt sowohl zum allgemeinen Wohlbefinden als auch zur mentalen Gesundheit bei.
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The aim of this study was to identify quantitative data on the use of seclusion and restraint in different countries and on initiatives to reduce these interventions. Combined literature review on initiatives to reduce seclusion and restraint, and epidemiological data on the frequency and means of use in the 21st century in different countries. Unpublished study was detected by contacting authors of conference presentations. Minimum requirements for the inclusion of data were reporting the incidence of coercive measures in complete hospital populations for defined periods and related to defined catchment areas. There are initiatives to gather data and to develop new clinical practice in several countries. However, data on the use of seclusion and restraint are scarcely available so far. Data fulfilling the inclusion criteria could be detected from 12 different countries, covering single or multiple hospitals in most counties and complete national figures for two countries (Norway, Finland). Both mechanical restraint and seclusion are forbidden in some countries for ethical reasons. Available data suggest that there are huge differences in the percentage of patients subject to and the duration of coercive interventions between countries. Databases on the use of seclusion and restraint should be established using comparable key indicators. Comparisons between countries and different practices can help to overcome prejudice and improve clinical practice.
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This parameter reviews the current state of the prevention and management of child and adolescent aggressive behavior in psychiatric institutions, with particular reference to the indications and use of seclusion and restraint. It also presents guidelines that have been developed in response to professional, regulatory, and public concern about the use of restrictive interventions with aggressive patients with regard to personal safety and patient rights. The literature on the use of seclusion, physical restraint, mechanical restraint, and chemical restraint is reviewed, and procedures for carrying out each of these interventions are described. Clinical and regulatory agency perspectives on these interventions are presented. Effectiveness, indications, contraindications, complications, and adverse effects of seclusion and restraint procedures are addressed. Interventions are presented to provide more opportunities to promote patient independence and satisfaction with treatment while diminishing the necessity of using restrictive procedures.
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Children and adolescents with severe emotional and behavioral problems in residential settings can become so aggressive that physical restraints are utilized to keep them and others safe. Recently, the use of physical restraints in residential treatment facilities for school-aged children has come under increased scrutiny, and there have been legislative mandates that the use of physical restraints be reduced. This article describes a quasi-experimental field study conducted to examine the effectiveness of a 2-phase (organizational and milieu) physical restraint reduction intervention in a multisite residential treatment center. Results provide support for the effectiveness of organizational-level and milieu interventions for restraint reduction. Overall, restraint rates were reduced by 59% using these interventions.
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The evolution and history of adventure therapy, as chronicled in the second chapter of this book, well demonstrates how far this field has evolved from a “divergent therapy” into an efficacious form of therapy that engages clients on cognitive, affective, and behavioral levels. Adventure Therapy is written by three professionals who have been at the forefront of the field since its infancy. The theory, techniques, research, and case studies they present are the cutting edge of this field. The authors focus on: • the theory substantiating adventure therapy • illustrations that exemplify best practices • the research validating the immediate as well as long-term effects of adventure therapy, when properly conducted. This book is the leading academic text, professional reference, and training resource for adventure therapy practices in the field of mental health. It is appropriate for a wide range of audiences, including beginner and experienced therapists, as well as graduate students.
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Seclusion and restraint are frequent procedures to intervene in aggressive and potentially dangerous patients in psychiatric settings. However, little is known about their utilization and effectiveness in pediatric populations. We aimed to examine the prevalence and determinants of seclusion and restraint utilization in children and adolescents in psychiatric settings. Using PubMed, PsychInfo and Cinahl, we performed a systematic literature review of studies published in the last 10 years reporting on the prevalence of seclusion and restraint use in psychiatrically ill youth (<21 years old) treated in psychiatric settings. Only seven publications addressed the topic. Primary outcomes were prevalence rates, reported either as the proportion of patients restrained/secluded or as the number of restraints/seclusions per number of patient days. All studies found relatively high baseline rates of seclusion (26% of patients; 67/1,000 patient days), and restraints (29% of patients; 42.7/1,000 patient days). In four studies, an intervention, implemented to reduce seclusion and restraints, resulted in a dramatic weighted mean reduction in the more restrictive use of restraints by 93.2%, with a 54.2% shorter duration. There was a small, weighted mean reduction in the use of less restrictive seclusions (-0.6%), but results were heterogeneous (-97.2 to +71.0%), with the only increase in seclusions being reported in one study in which the intervention-based padded seclusion room was utilized more frequently instead of more restrictive measures. Otherwise, seclusion episodes reduced by 74.7%, including a 32.4% shorter duration. Few studies reported on risk-factors and predictors, consisting of past or current aggression and/or violence, suicidal behavior, more severe psychopathology, non-White ethnicity, emergency admissions, out-of-home placement, and poorer family functioning, while findings regarding age were inconsistent Except for duration, data about the effectiveness of seclusion and restraints were missing, although there is some indication that seclusion and restraints can lead to severe psychological and physical consequences. Future research should focus on indications, predictors, preventive and alternative strategies, as well as on clinical outcomes of seclusion and restraints in psychiatrically ill youth. In addition, there is a clear need for transparent policies and guidelines.
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The practice of coercive measures in psychiatry is controversial. Although some have suggested that it may be acceptable if patients are a danger to others or to themselves, others committed themselves to eliminate it. Ethical, legal and clinical considerations become more complex when the mental incapacity is temporary and when the coercive measures serve to restore autonomy. We discuss these issues, addressing the conflict between autonomy and beneficence/non-maleficence, human dignity, the experiences of patients and the effects of coercive measures. We argue that an appeal to respect autonomy and/or human dignity cannot be a sufficient reason to reject coercive measures. All together, these ethical aspects can be used both to support and to reject a non-seclusion approach. The total lack of controlled trials about the beneficial effects of coercive measures in different populations however, argues against the use of coercive measures.
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This study examined usage patterns of restraint and seclusion before and after the implementation of collaborative problem solving (CPS), a manualized therapeutic program for working with aggressive children and adolescents. The clinical setting was a 15-bed psychiatric inpatient unit for school-age children. A total of 755 children were hospitalized for a total of 998 admissions from fiscal years 2003 to 2007 (median age=11 years; 64% boys). Data were collected for three years before and 1.5 years after the six-month implementation of the CPS model of care. There were 559 restraint and 1,671 seclusion events during the study period. After implementation of the CPS model there was a reduction in the use of restraints (from 263 events to seven events per year, representing a 37.6-fold reduction, slope [beta]=-.696) and seclusion (from 432 to 133 events per year, representing a 3.2-fold reduction, beta=-.423). The mean duration of restraints decreased from 41+/-8 to 18+/-20 minutes per episode, yielding cumulative unitwide restraint use that dropped from 16+/-10 to .3+/-.5 hours per month (a 45.5-fold reduction, beta=-.674). The mean duration of seclusion decreased from 27+/-5 to 21+/-5 minutes per episode, yielding cumulative unitwide seclusion use that dropped from 15+/-6 to 7+/-6 hours per month (a 2.2-fold reduction; p for trend .01 or better for all slopes). During the early phases of implementation there was a transient increase in staff injuries through patient assaults. CPS is a promising approach to reduce seclusion and restraint use in a child psychiatric inpatient setting. Future research and replication efforts are warranted to test its effectiveness in other restrictive settings.