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2 0 1 6 - 2 0 1 7 A N N U A L R E P O R T
UPLOADSU N D E R S T A N D I N G A N D P R E V E N T I N G
L E D O U T D O O R A C C I D E N T S D A T A S Y S T E M
T H I S P R O J E C T I S S U P P O R T E D BY F U N D I N G F R O M T H E AU S T R A L I A N R E S E A R C H CO U N C I L ( A R C ;
L P 150100287 ) I N PA R T N E R S H I P W I T H AU S T R A L I A N C A M P S A S S O C I AT I O N , O U T D O O R CO U N C I L
O F AU S T R A L I A , T H E O U T D O O R E D U C AT I O N G R O U P, S P O R T A N D R E C R E AT I O N V I C TO R I A , V I C TO -
R I A N Y M C A ACCO M M O DAT I O N S E R V I C E S P T Y LT D, O U T D O O R S V I C TO R I A , O U T D O O R S N S W, O U T -
D O O R S WA , O U T D O O R S S O U T H AU S T R A L I A , Q U E E N S L A N D O U T D O O R R E C R E AT I O N F E D E R AT I O N ,
W I L D E R N E S S E S C A P E O U T D O O R A D V E N T U R E S , V E N T U R E CO R P O R AT E R E C H A R G E , A N D C H R I S T I A N
V E N U E S A S S O C I AT I O N . C A R O L I N E F I N C H WA S S U P P O R T E D BY A N H M R C P R I N C I PA L R E S E A R C H F E L -
LO W S H I P ( I D : 565900 ) . T H E AU S T R A L I A N C E N T R E F O R R E S E A R C H I N TO I N J U R Y I N S P O R T A N D I T S
P R E V E N T I O N ( AC R I S P ) I S O N E O F T H E I N T E R N AT I O N A L R E S E A R C H C E N T R E S F O R P R E V E N T I O N O F I N J U -
R Y A N D P R OT E C T I O N O F AT H L E T E H E A LT H S U P P O R T E D BY T H E I N T E R N AT I O N A L O LY M P I C CO M M I T T E E
( I O C ) . PAU L S A L M O N’S CO N T R I B U T I O N WA S F U N D E D T H R O U G H H I S C U R R E N T AU S T R A L I A N R E S E A R C H
CO U N C I L F U T U R E F E L LO W S H I P ( F T 140100681 ) . N ATA S S I A G O O D E ’S CO N T R I B U T I O N WA S F U N D E D
T H R O U G H T H E U N I V E R S I T Y O F T H E S U N S H I N E CO A S T A N D T H E S TAT E O F Q U E E N S L A N D T H R O U G H T H E
D E PA R T M E N T O F S C I E N C E , I N F O R M AT I O N T E C H N O LO G Y A N D I N F O R M AT I O N , A D VA N C E Q U E E N S L A N D
R E S E A R C H F E L LO W S H I P.
T H E U P LO A D S R E S E A R C H T E A M
Professor Paul Salmon 1
Dr Natass ia Goode 1
Prof essor Carol ine F inch 2
Dr Amanda Clacy 1
1Cen tre for Hu man Factors and Sociotechnical Systems, Univers i ty of the Sunshine Co as t
2Austr a l ian Centre for Research into In jury in Sport and i ts Prevent ion, Federat ion Univ ers i ty
ii iii
U P LOA D S
UPLOADS2 0 1 6 - 2 0 1 7 A N N U A L R E P O R T
iv
1
U P LOA D S
The UPLOADS Project has been growing and evolving since inception 8 years ago, when industry stakeholders recognised a need to tackle issues around incident reporting and injury causation in the led outdoor activity (LOA) sector in Australia.
The UPLOADS incident reporting system that was developed allows LOA providers to collect essential incident details which go beyond standard reports. Using a systems-theory model of accident causation (Rasmussen, 1997), the UPLOADS method provides a contributing factor classification scheme and a mapping framework. This method provides the tools necessary to identify the factors contributing to incidents in LOAs, as well as the systemic relationships between them.
Through the analysis of this aggregate data, the UPLOADS National Incident Dataset can be used to identify sector-wide patterns and trends in the incidence rates and contributory factors of activities. Prior to the UPLOADS Project, this information was not available in the LOA sector in Australia. It is important to note that although the reports are analysed by the research team,
all the contributing factors and relationships that are identified come directly from the deidentified incident reports provided by Australian LOA organisations. Therefore, the analyses of contributing factors presented in this report represent the issues that are considered important by those who reported the incidents.
The aim of this report is to present a detailed overview of the data collected during the third year of data collection for the National Incident Dataset (1st June 2016 – 31st May 2017).
Copies of the first and second annual reports can be found on our website at
www.uploadsproject.org
Together, the annual reports generated by the UPLOADS National Incident Dataset contribute to an improved understanding of the incidents that occur during LOAs in Australia. These findings can be used to support the development of data-driven, targetted incident prevention strategies.
IntroductionCONTENTS
1 INTRODUCTION
2 IN THIS REPORT...
5 INJURY INCIDENTS
11 SYSTEMS ANALYSIS OF INJURIES
21 ILLNESS INCIDENTS
26 SYSTEMS ANALYSIS OF ILLNESSES
34 NEAR MISS INCIDENTS
38 SYSTEMS ANALYSIS OF NEAR MISS INCIDENTS
48 LEARNING WITH UPLOADS
50 AFTERWORD
13 O R G A N I S AT I O N S F R O M AC R O S S AU S T R A L I A CO N T R I B U T E D DATA D U R I N G T H E 2016 - 2017 R E P O R T I N G P E R I O D
SA 2WA 1
QLD 3
NSW 1ACT 1
VIC 5
6 c a m p s 4 commercial enterprises 2 schools 1 training organisation (e.g., tafe, university)
509 I N C I D E N T S W E R E U P LOA D E D I N TO T H E N AT I O N A L I N C I D E N T DATA S E T
0 50 100 150 200 250 300 350
Social/Psychological Outcomes
Near Misses
Illness
Injuries 340
145
23
19
I N T H I S R E P O R T. . .
2
The following report is presented in three separate sections for illnesses, injuries, and near miss incidents.
In this report...
O U TCO M E D E F I N I T I O N W I T H I N U P LOA D S
Incident Any event that results in an adverse outcome or a near miss.
Adverse outcomeAny event resulting in a negative impact, including: missing/overdue people; equipment or environmental damage; injury; illness; fatality; or social or psychological impacts.
Near miss
Any serious mishap that has the potential to cause an adverse event but fails to do so. For example, during a rock climbing activity an instructor notices that a participant’s carabineer was not locked. If the student had fallen, this may have led to a serious injury.
INCIDENT STATISTICS Each section of this report starts with an overview of the data collected for each outcome and a summary of the characteristics of the incidents. Incident rates for LOAs are calculated per 1000 participants ((number of incidents/number of participants) x 1000)) for each activity. As there are over 80 different types of activities captured in the UPLOADS data, activities are clustered into 20 broad categories which group activities with similar characteristics. For example, the category “walking/running outdoors” includes bush walking, orienteering and adventure races. The category ‘river activities’ includes canoing, rafting and kayaking. Other incident statistics presented in this report include incident severity ratings and demographic information.
SYSTEMS ANALYSIS Also included in each section of this report is the analysis of the contributing factors involved in each incident. The UPLOADS accident analysis method was used to classify the contributing factors and relationships that reporting practitioners identify in the incident report. These factors are then represented as AcciMaps, which show the network of contributing factors that were identified in the incident reports, and the relationships between them.
METHOD For a full description of the method used by the UPLOADS project for the collection of data for the National Incident Dataset, please refer to our website. Details regarding the design, recruitment, and data inclusion and analysis can also be found in our earlier annual reports.
U P LOA D S
3
2.2 I N J U R Y I N C I D E N T S W E R E R E P O R T E D P E R 1000 PA R T I C I PA N T S
340 I N J U R Y I N C I D E N T S R E P O R T E D I N T H E U P LOA D S N AT I O N A L I N C I D E N T DATA S E T
1Finch, C . F. , Cassel l , E . , & Stathak is , V. (1999) . The epidemiology of spor t and ac t ive recreat ion injur y in the La Trobe Val ley : Monash Univers i t y
Accident Research Centre.4
I N T H I S R E P O R T. . . U P LOA D S
Injury incidents
INJURIES IN THE WILDIn Australia, the rates of injury per 1000 participants in LOAs are substantially lower than some organised sports, such as cricket (242/1000), horse-riding (122/1000), and soccer (107/1000)1.
U P LOA D S
0
50
100
150
200
250
300
SevereSeriousModerateMinor
267
60
109
Num
ber o
f inj
ury
inci
dent
s
Severity Rating
79% O F I N J U R Y I N C I D E N T S W E R E R AT E D A S M I N O R
6 7
U P LOA D SI N J U R Y I N C I D E N T S
Free-time in the outdoors had the highest recorded number of injuries in the data set with 15.7 incidents per 1000 participants. Residential camps and campcraft (i.e., cooking, camp fires) were also amongst the activities with the highest incidence rates (7.4 and 6.2 incidents per 1000 participants, respectively).
0
5
10
15
20
Arch
ery
Arts
& C
rafts
Hors
e/Ca
mel
ridi
ngSn
owsp
orts
Cavi
ngHa
rnes
s: ou
tdoo
rsTr
avel
ling
Oce
an a
ctiv
ities
Team
build
ing
gam
esRi
ver a
ctiv
ities
Beac
h ac
tiviti
esHa
rnes
s: in
door
sW
heel
spor
tsW
alki
ng/r
unni
ng o
utdo
ors
Curri
culu
m-b
ased
act
iviti
es
Cam
ping
tent
sCa
mp
craf
t Re
siden
tial c
amps
Free
tim
e ou
tdoo
rs
47% of all activities had an injury incident rate of ≤1 per 1000 participants.
INJURY RATES BY AC TIVIT Y
Reported injury rate per 1000 participants (No. injury incidents/No. of participants)
INJURIES IN THE WILDThe injury incidence rate and the severity of the injuries that occur during Australian LOAs has remained relatively stable since the UPLOADS Project began collecting data in 2014.
R AT I N G D E F I N I T I O N
No impact Requires no treatment (near miss).
Minor Requires localised care (non-evacuation) with short term effects.
Moderate Requires ongoing care (localised or external; i.e., evacuation or not) with short to medium term effects.
Serious Requires timely external care (evacuation) with medium to long term effects.
Severe Requires urgent emergency assistance with long term effects.
Critical Requires urgent emergency assistance with serious ongoing long term effects.
Fatality Fatality.
O F I N J U R E D P E O P L E R E Q U I R E D E VAC UAT I O N
4.4%
2.4%
O F I N J U R E D P E O P L E R E Q U I R E D H O S P I TA L I S AT I O N
O F I N J U R Y I N C I D E N T S R E Q U I R E D E M E R G E N C Y S E R V I C E S
9.7%
The figure below presents the three most frequently reported injury types for each body region. The body regions that were injured most frequently are indicated by red triangles.
T YPES AND BODY LOCATIONS OF REPOR TED INJURIES
8
I N J U R Y I N C I D E N T S U P LOA D S
The majority of the evacuations that were required for injuries were undertaken by vehicle 75.7%. In 15.2% of evacuations the injured persons were walked out, and in 9.1% of cases a stretcher was required.
9
U P LOA D S
2 CO N T R I B U T I N G FAC TO R S I D E N T I F I E D O N AV E R AG EP E R I N J U R Y R E P O R T
649 FAC TO R S CO N T R I B U T I N G TO I N J U R Y I N C I D E N T S W E R EI D E N T I F I E D BY R E P O R T E R S
10
I N J U R Y I N C I D E N T S
DEMOGRAPHICS
The majority of the people injured were activity participants (84.4%), with an average age of 15 years.
52% 47%
0
50
100
150
200
250
300
Missing
Not applicable
Yes
Serious+ModerateMinor
80.1%
17.2%
23.3%
42.1%
76.7%31.6%
Proportions of incidents in severity rating categories partitioned by whether the leader was reported to have relevant quali�cations
Num
ber o
f inj
ury
inci
dent
s
26.3%
GROUP PROFILE
The average number of participants involved in activities associated with injury incidents was 15. There was a ratio of 2 activity leaders for every 15 participants in these activities.
QUALIFICATIONS
In 79% of incidents, the activity leader was reported to have relevant qualifications. In 21% of incidents qualifications were reported to be “not applicable” and predominantly involved:
• free time activities (42%) • campcraft (15%)• walking/running outdoors (10%)
This graph shows the proportion of injury incidents by severity ratings, partitioned according to leader qualifications.
11
U P LOA D S
S Y S T E M S A N A LY S I S O F I N J U R I E S I N T H E L E D O U T D O O R S
The contributing factors that were identified by reporters were in the lower four levels of the UPLOADS Accident Analysis Scheme (see table below). The relationships between these factors, and the frequencies with which they were reported, are presented in the AcciMap on the following page.
LEGENDGOVERNMENT DEPARTMENT
DECISIONS AND ACTIONS
REGULATORY BODIES AND ASSOCIATIONS
LOCAL AREA GOVERNMENT, SCHOOLS, PARENTS &
CARERS, AND HIGHER LEVEL MANAGEMENT
SUPERVISORY AND MANAGEMENT DECISIONS AND
ACTIONS
DECISIONS AND ACTIONS OF LEADERS, PARTICIPANTS AND OTHER ACTORS AT THE SCENE
OF THE INCIDENT
EQUIPMENT, ENVIRONMENT AND METEOROLOGICAL
CONDITIONS
Supervisor / Field Manager:
Activity or Program Design
Equipment, Clothing & Personal Protective
Equipment
Infrastructure & Terrain
Activity Leader:
Communication, Instruction /
Demonstration
Higher Level Management:
Risk Assessment & Management
Parents / Carers:
Communication
Documentation Animal & Insect Hazards Weather Conditions
Activity Leader:
Judgement & Decision-making
Activity Leader:
Mental & Physical Condition
Activity Leader:
Situation Awareness
Activity Leader:
Supervision & Leadership of Activity
Activity Participant:
Communication & Following Instructions
Activity Participant:
Compliance with Procedures / Violations /
Unsafe Acts
Activity Participant:
Experience & Competence
Activity Participant:
Judgement & Decision-making
Activity Participant:
Mental & Physical Condition
Activity Participant:
Planning & Preparation for Activity or Trip
Activity Participant:
Situation Awareness
Activity Group Factors:
Group Dynamics
Food & Drink Trees & Vegetation Water Conditions
Others in Group:
Situation Awareness
Activity Group Factors:
Time Pressure
Activity Leader:
Planning & Preparation for Activity or Trip
Activity Group Factors:
Group Composition
Others in Environment:
Situation Awareness
Relationships identified in less than 1% of reportsRelationships identified in 1-4% of reportsRelationships identified in more than 5% of reports
Factors identified in more than 20% of reports
Factors identified in more than 5% of reports
There were no factors or relationships reported at these levels of the system
The most frequently reported factor relationships were between Activity Equipment, Clothing & PPE and Infrastructure & Terrain at the bottom level of the system and Activity Participant Situation Awareness and Experience & Competence at the second level of the system.
Only relationships that were identified in more than one incident reported have been illustrated on this AcciMap.
14
I N J U R Y I N C I D E N T S
Relationships refer to the interactions between contributory factors. In the following figures, the most frequently identified factor relationships are presented. Relationships that were most frequently identified by reporters are highlighted in red text.
RELATIONSHIPS WERE IDENTIFIED BETWEEN INJURY CONTRIBUTING FACTORS 300
“Example”
15
LOCAL AREA GOVERNMENT, SCHOOLS, PARENTS & CARERS, AND HIGHER LEVEL MANAGEMENT There were 17 factors reported at Local Area Government, Schools, Parents & Carers, and Higher Level Management levels of the LOA system framework. Fourteen (14) relationships were identified between these factors and lower level factors.
U P LOA D S
“The location that the activity was being run in made it difficult for the activity leader to
maintain supervision.”
“The repetition of the activities (bushwalking and mountain biking)
while carrying a hiking pack combined with the participants
inexperience contributed to this injury.”
“Towards the end of camp, the participant
was exhausted and not concentrating on the
task.”
“Campsite was not properly maintained.”
“Program management team were not aware that the tension on the flying
fox had been lost.”
“Precautionary measures were unable to be taken
as participant’s pre-existing condition was
not listed on the medical form.”
“Parents knew of child’s sleepwalking, but
decided to withhold this information.”
16
I N J U R Y I N C I D E N T S
ACTIVITY LEADERS
In 34 incident reports, contributing factors related to the decsions and actions of Activity Leaders were identified by reporters. Thirty-two (32) relationships were identified between these factors and lower level factors.
“Activity leader did not bring appropriate
footwear or PPE.”
“The participant had a lack of hazard awareness while
running around on the grass and the instructor did not give proper instruction
about appropriate footwear.”
“Participant inexperience was not mitigated by
correct and proper instructions.”
“Instructors were not supervising
participants while they were washing the
cooking equipment and knives.”
“Leader was not diligent about
ensuring participants are put into
appropriate skill-level groups.”
“Activity leader was not properly supervising
students who rode out of bounds.”
ACTIVITY PARTICIPANTS
Contributing factors related to the decsions and actions of Activity Participants were identified in 299 incident reports. Between these factors and lower level factors, there were 236 factor relationships identified.
U P LOA D S
17
“Novice walker underestimated the
terrain.”
“Participant lacked experience and
panicked when faced with the challenging
terrain.”“Exceeding ability and technique caused the participant to hit the
guard rail.”
“Participant did not have the experience
at bushwalking to properly prepare her
equipment for the trip.”
“The waves were quite sporadic. The participant had no
prior experience with surfing.”
“The participant’s ability was not up to
the task of swimming that distance in fresh
water.”
“The participant’s inexperience with bushwalking was
exacerbated by the wet conditions.”
“Participant was sitting too close to the fire trying to warm up. No
previous experience with open fires.”
“Participant was fatigued and tripped when
walking up the boat ramp.”
“Participant had poor coordination and slipped
on the loose gravel.”
“Strop lengths were inappropriate for the weight of the
participant.”
“Participant was sleep walking and fell from the
top bunk.”
18
I N J U R Y I N C I D E N T S
“The sharp knives in use were not being given
suitable attention by the participant.”
“The participant wasn’t watching where they were
going and ran into a pump.” “Participant stumbled on a log and fell heavily onto their
wrist.”
“Poor decision making to remove hot pan in unsafe
manner.”
“Participant decided to leap through the spider
web (superman style) and landed on his shoulder.”
“Participant decided to ride away from the group and
onto loose gravel.”
“The participant was running backwards in the
sand being silly.”
U P LOA D S
“The participant was turning their back to the waves and so
was unaware of where their fellow surfers were.”
“Participant was not paying attention to their surroundings and sat in a
jumping jack ant nest.”
“Fainting caused by low fluid intake in hot weather
showed a lack of awareness by participant.”
“The participant cut themselves when opening a tin can of sweet corn for
lunch.”
19
“Despite being told to get off the trampoline, the
participant attempted a back flip and kneed himself
in the nose.”
“Participant used her hands instead of the safety tools that were instructed
causing a burn.”
“Participant disregarded instructions to stick to paths and not go through gardens or
roped off areas.”
“Ants got into the tent causing several insect bites. Participants did not zip up
the tent as instructed.”
I L L N E S S I N C I D E N T S
1 I L L N E S S I N C I D E N T WA S R E P O R T E D P E R 1000 PA R T I C I PA N T S
I L L N E S S I N C I D E N T S W E R ER E P O R T E D I N T H E U P LOA D S N AT I O N A L I N C I D E N T DATA S E T145
LE
SS
TH
AN
P E R C E N T O F I L L N E S S I N C I D E N T S W E R E R AT E D A S M I N O R73%
O F I L L P E O P L E R E Q U I R E D E VAC UAT I O N
I L L N E S S I N C I D E N T S R E Q U I R E D E M E R G E N C Y S E R V I C E S2
22%
U P LOA D S
0
20
40
60
80
100
120
SevereSeriousModerateMinor
106
37
20
Num
ber o
f illn
ess i
ncid
ents
Severity Rating
Illness incidents
The majority of ill people were evacuated by vehicle (16.6%, average severity = 2, range: 1-3) or walked out (4.8%, all with a severity rating of 2). Only 1.4% of ill people required emergency services, all for asthma-related conditions (severity ratings of 1 and 2) and 2.1% of ill people required hospitalisation following evacuation (average severity = 3).
21
22
I L L N E S S I N C I D E N T S
0
1
2
3
4
5
6
7
8
Arch
ery
Cavi
ng
Beac
h ac
tiviti
es
Harn
ess:
indo
ors
Curr
icul
um-b
ased
act
iviti
es
Arts
& C
rafts
Snow
spor
ts
Hors
e/Ca
mel
ridi
ng
Harn
ess:
outd
oors
Team
build
ing
gam
esW
heel
spor
tsO
cean
act
iviti
esTr
avel
ling
Rive
r act
iviti
esCa
mp
craf
tFr
ee ti
me
outd
oors
Wal
king
/run
ning
out
door
sRe
siden
tial c
amps
Cam
ping
tent
s
42% of all activities had an illness incident rate of ≤1 per 1000 participants.
Camping in tents had the highest illness incidence rate (7.4 incidents per 1000 participants), followed by residential camps (4.2 incidents per 1000 participants) and walking/running in the outdoors (1.9 incidents per 1000 participants).
ILLNESS IN THE OUTDOORS
Camping in tents has been the activity associated with the highest rates of LOA illness in the Australia since the UPLOADS National Incident Dataset began collecting data in 2014.
ILLNESS RATES BY AC TIVIT Y
Reported illness incident rate per 1000 participants (No. illness incidents/No. of participants)
ILLNESS T YPE
17.2% A B D O M I N A L P R O B L E M S13.1% H E AT - R E L AT E D I L L N E S S
7.6% N O N - S P E C I F I C F E V E R6.9% ALLERGIC REACTION
6.9% DIARRHEA6.2% ASTHMA
6.2% MENSTRUAL
1 CO N T R I B U T I N G FAC TO R WA S I D E N T I F I E D O N AV E R AG EP E R I L L N E S S R E P O R T
204 CO N T R I B U T I N G FAC TO R S TO I L L N E S S I N C I D E N T S W E R EI D E N T I F I E D BY R E P O R T E R S
24 25
U P LOA D SI L L N E S S I N C I D E N T S
DEMOGRAPHICS
The majority (91%) of ill people were identified as activity participants. The average age of ill activity participants was 15 years.
0
20
40
60
80
100
120
Serious+ModerateMinor
Missing
Not applicable
Yes
Proportions of incidents in severity rating categories partitioned by whether the leader was reported to have relevant quali�cations
Num
ber o
f illn
ess
inci
dent
s
65.1%
67.6%
32.4%
5.7%
29.2%
50%50%
GROUP PROFILE
The average number of participants involved in activities associated with illnesses was 12. The average number of activity leaders was 1. There was an average ratio of 1 activity leader for every 12 participants in these activities.
QUALIFICATIONS
In 65.5% of incidents, the activity leader was reported to have relevant qualifications and in 8.6% of incidents qualifications were reported to be “not applicable”.
The graph below shows the proportion of illness incidents by severity ratings, partitioned according to leader qualifications.
46.2% 42.4%
S Y S T E M S A N A LY S I S O F I L L N E S S I N T H E L E D O U T D O O R S
The contributing factors that were identified by reporters were at three of the lower four levels of the UPLOADS Accident Analysis Scheme (see table below). The relationships between these factors, and the frequencies with which they were reported, are presented in the AcciMap on the following page.
The most frequently reported factor relationships were between Activity Participant Situation Awareness and Experience & Competence and Weather Conditions and Food & Drink.
Only relationships that were identified in more than one incident reported have been illustrated on this AcciMap.
28
In the following figures, the most frequently identified relationships are presented. Relationships that were most frequently identified by reporters are highlighted in red text.
RELATIONSHIPS WERE IDENTIFIED BETWEEN ILLNESS CONTRIBUTING FACTORS 88
“Example”
LOCAL AREA GOVERNMENT, SCHOOLS, PARENTS & CARERS, AND HIGHER LEVEL MANAGEMENT
Contributing factors at the Local Area Government, Schools, Parents & Carers, and Higher Level Management levels of the LOA system framework were identified in 10 incident reports. The same number (10) of relationships were identified between these factors and lower level factors.
U P LOA D S
ILLNESS IN THE OUTDOORS
The factors and relationships identified in the bottom two levels of the LOA system describe the flow of events leading up to and during an incident, including the decisions and actions made by leaders, participants, and other members of the activity group. These levels of the system are referred to as the ‘sharp end’.
“Participant had been experiencing symptoms of tonsillitis before camp. This was not communicated on
the medical form.”
“Parents made poor decision to sent child to camp when they were feeling unwell.”
“Parents should have ensured that their child’s medication was full and
packed before sending them on camp.”
29
30
ACTIVITY LEADERS
I L L N E S S I N C I D E N T S
“The participants were bushwalking on a hot day.
Activity leader did not remind them to drink extra
water.”
Contributing factors related to the decsions and actions of Activity Leaders were identified in 7 incident reports. Six (6) relationships were identified between these factors and lower level factors.
ACTIVITY PARTICIPANTS
In 117 incident reports, contributing factors related to the decsions and actions of Activity Participants were identified by reporters. Between these factors and lower level factors, there were 70 factor relationships identified.
U P LOA D S
“Participant was exhausted/headaches from being
exposed to higher levels of exercise than they were used
to, especially on a hot day.”
“Inexperience at camp and excitement led the
participant to overeat and throw up.”
31
“Participant failed to be aware or pay attention
to consumption of food that would cause them
problems.”
“Participant had poor situation awareness in
hot weather and did not consume adequate water.”
“Participant was unaware her water bottle was
leaking causing her to have inadequate water
throughout the day.”
I L L N E S S I N C I D E N T S
“Walking in the rain all day and having an extremely small frame led to mild
hypothermia.” “Preexisting low heart rate caused the
participant to faint. No previous condition or
treatment was listed on the medical form.”
“Pollen from the flowering trees caused the participant
to experience severe hayfever.”
U P LOA D S
“Participant had sensitivities to a number
of foods.”
“Participant was travel sick.”
“Participant forgot her iron tablets and
felt ‘run down’.”
“Participant was bitten multiple times by insects
and had an allergic reaction.”
N E A R M I S S I N C I D E N T S W E R ER E CO R D E D I N T H E U P LO A D S N AT I O N A L I N C I D E N T DATA S E T23
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Arch
ery
Oce
an a
ctiv
ities
Cavi
ngBe
ach
activ
ities
Curr
icul
um-b
ased
act
iviti
esAr
ts &
Cra
fts
Snow
spor
tsH
orse
/Cam
el ri
ding
Har
ness
: out
door
sTe
ambu
ildin
g ga
mes
Rive
r act
iviti
esW
heel
spor
ts
Wal
king
/run
ning
out
door
sCa
mp
craf
tTr
avel
ling
Free
tim
e ou
tdoo
rsCa
mpi
ng te
nts
Har
ness
: ind
oors
Resi
dent
ial c
amps
42% of all activities were not associated with any near miss incidents.
U P LOA D S
Near miss incidents
Residential (i.e., hard top) camps had the highest near miss incidence rate (1.1 incidents per 1000 participants), followed by harness: indoors (0.9 incidents per 1000 participants), and camping in tents (0.8 incidents per 1000 participants).
Reported near miss incident rate per 1000 participants (No. near miss incidents/No. of participants)
61% O F N E A R M I S S I N C I D E N T S H A D A S E R I O U S TO FATA L P OT E N T I A L S E V E R I T Y
36
N E A R M I S S I N C I D E N T S
0
2
4
6
8
10
UnsurvivableCriticalSevereSeriousModerateMinor
1
2
6
10
1
3
Potential Severity Rating
Num
ber o
f nea
r miss
inci
dent
s
NEAR MISS INCIDENT SE VERIT Y
THE NATURE OF NEAR MISS
The importance of reporting and analysing near miss incidents in the LOA sector is emphasised by the con-sistent finding that the majority of these types of incidents are reported to be potentially serious or fatal.
Near miss incidents are rated in terms of potential severity, and refer to any serious mishap that has the potential to cause an adverse event but fails to do so because of chance or because it is intercepted.
37
U P LOA D S
0
2
4
6
8
10
UnsurvivableCriticalSevereSeriousModerateMinor
Not applicable
Yes
100%100%
83.3%
16.7%
20%
80%
100%
100%
Proportions of near miss incidents in potential severity rating categories partitioned by whether the leader was reported to have relevant quali�cations
Num
ber o
f nea
r miss
inci
dent
s
GROUP PROFILE
The average number of partici-pants involved in activities asso-ciated with near miss incidents was 14. Respectively, the aver-age number of activity leaders and supervisors was 2 and 1. There was an activity ratio of 1 activity leader for every 7 partic-ipants when near miss incidents occurred.
DEMOGRAPHICS
The majority of people in-volved in near miss incidents were identified as activity par-ticipants (82.6%). Insufficient data was reported for the cal-culation of sex and average age.
QUALIFICATIONS
In majority of the near miss incidents (82.6%), the activity leader was reported to have relevant qualifications. In four incidents leader qualifications were reported as “not applicable”.
The graph below shows the proportion of near miss incidents by potential severity ratings, partitioned according to leader qualifications.• activities (42%) • campcraft (15%)• walking/running outdoors
(10%)
2 CO N T R I B U T I N G FAC TO R S W E R E I D E N T I F I E D O N AV E R AG EP E R N E A R M I S S R E P O R T
53 CO N T R I B U T I N G FAC TO R S TO N E A R M I S S I N C I D E N T S W E R EI D E N T I F I E D BY R E P O R T E R S
S Y S T E M S A N A LY S I S O F N E A R M I S S I N C I D E N T S I N T H E L E D O U T D O O R S
N E A R M I S S I N C I D E N T S
Near miss incident reporters identified contributing factors at four of the five levels of the UPLOADS Accident Analysis Scheme (see table below). The relationships between these factors, and the frequencies with which they were reported, are presented in the AcciMap on the following page.
39
U P LOA D S
38
THE NATURE OF NEAR MISS
Analysing near miss reports offers a unique opportunity to learn from incidents before they eventuate into serious events. The factors that underpin these incidents are comparable to the contributory factors identified in adverse incidents.
The most frequently reported factor relationships were between Activity Participant Judgment & Decision Making and Activity Equipment, Clothing & PPE, and Activity Leader Communication and Activity Participant factors.
42
In the following figures, the most frequently identified relationships are presented. Relationships that were most frequently identified by reporters are highlighted in red text.
RELATIONSHIPS WERE IDENTIFIED BETWEEN NEAR MISS-RELATED CONTRIBUTING FACTORS 23
“Example”
43
LOCAL AREA GOVERNMENT, SCHOOLS, PARENTS & CARERS, AND HIGHER LEVEL MANAGEMENT
Risk Assessment and Management was identified in two reports as a contributing factor. Two (2) relationships were identified between this factor and lower levels of the system.
U P LOA D S
“Old, breaking beds had not been checked
recently and may not meet regulatory standards for
accommodation.”
“Guidance on wearing shoes while swimming did not
take into consideration the different water conditions.”
44
N E A R M I S S I N C I D E N T S
ACTIVITY GROUP FACTORS
SUPERVISORY AND MANAGEMENT DECISIONS AND ACTIONS
Contributing factors at the Supervisory & Management Decision level were identified in 2 incident reports. Two (2) relationships were identified between these factors and lower levels of the UPLOADS framework.
In 2 reports, contributing factors at the Activity Group Factor level of the system were identified. One relationship was identified between Activity Group Composition and Participant Mental & Physical Condition.
“The activity leader was unsure whether
participants were required to wear shoes while swimming within the canoeing activity.”
“The activity program required the instructor
to drive to the ferry early in the morning at a dangerous time for wildlife on the road.”
“Participant had autism and became frustrated
with the group who were ignoring his acting
out behaviours.”
U P LOA D S
45
Eleven (11) incident reports identified contributing factors from the Activity Leader level of the UPLOADS framework. Eight (8) relationships were identified between these factors and lower level factors.
ACTIVITY LEADERS
“The instructor was brief with students’ ability and
did not slow down the group to account for all
skill levels.”
“The activity leader did not have enough control over the participant who
then walked off on the group.”
“There was not enough communication between
the instructor and the students at the other end
of the flying fox.”
“Activity leader was not aware the wood splitter had a loose end until it flew into the bushes.”
“Activity leader didn’t notice the large number
of ants at the location chosen for lunch.”
45
ACTIVITY PARTICIPANTS
Twenty-one (21) reports identified contributing factors at the Activity Participant level of the framework. Between these factors and lower level factors, there were 6 factor relationships identified.
“Participant deliberately poured metho over the ground and lit it during
cooking activities.”
“Participant failed to communicate to the activity leader that a
pulley was still on the cable.”
“Participant became agitated with concerns
about a leech down his pants. No leech was
found.”
“Two participants were walking to their tents and did not see the snake and
they stepped on it.”
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L E A R N I N G W I T H U P LO A D S
Learning with UPLOADSThere are a number of important lessons pertaining to incident causation in Australian LOAs that can be drawn from the analysis of the UPLOADS National Incident Dataset.
INCIDENCE RATES
The incidence rate for injuries, illnesses and near misses is considered very low (2.2, 0.9, and 1.1 per 1000 participants respectively). When compared to other sports such as cricket (242 injuries per 1000 participants), horse-riding (122/1000), soccer (107/1000) and netball (51/1000; Finch, Cassell, & Stathakis, 1999), the injury rate for LOAs is relatively low. These incidence rates have also remained relatively stable over the three years in which UPLOADS has been in operation.
The analysis of the National Incident Dataset also shows which activities have the greater incidence of injuries, illnesses and near miss incidents.
For injury incidents, free-time outdoors, residential camps and campcraft (i.e., cooking and camp fires) had the highest recorded number of injuries (15.7, 7.4, and 6.2 incidents per 1000 participants, respectively). Camping in tents had the highest illness-related
incidence rate (7.4 incidents per 1000 participants), followed by residential camps (4.2 incidents per 1000 participants) and walking/running in the outdoors (1.9 incidents per 1000 participants). Notably, these findings are again consistent across the previous UPLOADS dataset analyses (Clacy et al., 2016; van Mulken et al., 2015).
The consistency of the incident rates for these activities suggests that further attention should be given to safety management during these types of activities, which are less overtly risky (compared to harness or water based activities, for example).
CONTRIBUTORY FACTORS
Perhaps the most important contribution of the National Incident Dataset is the collection of information regarding the systemic factors that contribute to injury, illness and near miss incidents during LOAs.
The most frequently identified contributing factors were Activity Participant Mental & Physical Condition, Activity Participant Situation Awareness, Activity Equipment, Clothing & PPE, and Infrastructure & Terrain.
49
U P LOA D S
Whilst these are important, the key to preventing future adverse events lies in understanding why actions made sense at the time. Accordingly, various other contributory factors were identified including organisations risk assessment and management processes, communications between schools, parents and activity providers, and activity or program design.
The relationships identified between the contributory factors reported in the National Incident Dataset also offer detailed insight into LOA incidents. The most frequently reported contributing factor relationships were between Activity Equipment, Clothing & PPE and Infrastructure & Terrain, and Activity Participant Situation Awareness and their Experience & Competence.
Relationships were also found between higher and lower level factors, as seen between Parent & Carer Communication and Documentation; Higher Level Management Risk Assessment & Management and Infrastructure & Terrain; and Activity & Program Design and Activity Participant Experience & Competence.
Examining these networks of contributing factors and their relationships reveals the prominent contributing factors from across the LOA system, from the immediate environment to the influence of the parents and carers of activity participants. By considering the complexities of safety in the Australian LOA sector, future incident
prevention strategies may better focus on the broad network of contributing factors driving adverse events, as opposed to focusing on the issues associated with instructors, participants, equipment and the activity environment in isolation.
CONCLUSION
The findings once again demonstrate that injury, illness and near miss incidents represent systems issues in that they are underpinned by a network of contributory factors that reside across the overall LOA system. A range of contributory factors and relationships were identified across the incidents reported in the National Incident Dataset. There remains work to do to ensure that the full range of contributory factors are being reported; however, the contributingorganisations should be commended for the rich dataset that they have provided.
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AFTERWORD
We would like to acknowledge the sector’s critical role in producing the UPLOADS National Incident Dataset. This dataset represents a huge contribution of time and effort from the organisations involved, both in terms of data collection and maintaining the quality of the reports. We would like to thank those organisations and our funding partners. We would also like to urge others to contribute data in future. The future of UPLOADS is dependent upon the provision of data from participating organisations across Australia. Whilst we acknowledge that practitioners are working under significant pressures and time constraints, we urge the sector to continue contributing data. Without data, it is not possible to generate meaningful analyses or for the UPLOADS National Incident Dataset to survive. The UPLOADS team are currently working towards developing a new reporting system which will reduce the administrative burden of contributing data.
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