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Psychological factors
Biological factors
Individual genetics and
medical history
Genetic vulnerability,
coping skills and
resilience
Social factors
Socioeconomics, health
care, technology,
compensation systems,
culture, society and
religion
Pain
Disability
Functional recovery
Health-related quality of life
Psychological outcomes
Social outcomes
Fig. 1. Conceptual framework for identifying factors impacting recovery
after a transport-related injury.
riences in their own way. This approach allowed clients to speak
freely, especially about negative experiences or behaviours.
Table I. Characteristics of 23 interviewed clients who sustained a
minor transport-related injury and made a claim at the Transport
Accident Commission (TAC)
Sociodemographic characteristics Mean
Age, years 49
Age groups
27–40 years 3 (13)
41–55 years 14 (63)
56–70 years 4 (16)
2 (8)
> 70 years
Sex
Male
8 (33)
Female
Injury type
15 (67)
15 (67)
Soft tissue
6 (25)
Contusion, abrasion, laceration
2 (8)
Other minor
Area
Metropolitan
16 (71)
Regional
Highest level of education
7 (29)
5 (21)
Year 10, 11 or 12
Data collection
11 (50)
TAFE/Trade
Recruitment was conducted in 3 phases to avoid recruiting more
clients than required to gain data saturation. Data saturation
defines the point at which no new themes are identified and it is
suggested that it is usually reached at around 12 interviews (22).
This phased approach also enabled the researcher to review the
interview questions at the conclusion of the first phase, to allow
adjustments to be made in subsequent interviews.
The first phase was conducted between March and May 2017.
Ten clients were interviewed during phase 1. After phase 1, pur-
posive sampling was employed to ensure adequate representation
of male clients and clients from regional areas. The second phase
was conducted between May and August 2017. Ten clients were
interviewed during phase 2. The final phase was conducted bet-
ween August and September 2017 during which 3 clients were
interviewed. In total, 12 clients were interviewed face-to-face and
the other 11 by phone based on the client’s personal preference.
n (%)
5 (21)
Undergraduate degree
2 (8)
Postgraduate degree
Health outcomes
Pain interference in last 4 weeks (NRS)
8 (33)
Mild
10 (42)
Moderate
5 (25)
Severe
EQ-5D-3L
4 (17)
0.80–1. 00 (High)
10 (46)
0.35 < 0.70 (Moderate)
9 (37)
< 0.35 (Low)
SF12 MCS 38.0
SF12 PCS 41.0
LBoT
LBoT score
1–4 (Not back on track)
5–6 (Intermediate)
7–10 (Back on track)
7.5
5 (21)
7 (33)
11 (46)
NRS: numeric rating scale; EQ-5D-3L: EuroQol Patient self-rated health
measure; SF12 PCS: Short Form Survey Physical Component Score: SF12
MCS: Short Form Survey Mental Component Score LBoT: Life Back on Track.
Qualitative data analysis
The interviews were audio-taped and typed verbatim by a
principal researcher who also conducted the interviews. A
thematic approach was taken to identify key issues. Thematic
analysis of transcripts was undertaken using NVivo, a qualita-
tive research software (QSR International). Deductive coding
was conducted with the conceptual framework used to guide
the analysis (Fig. 1). Inductive coding using open and axial
coding captured emerging concepts. The constant comparative
method was used by comparing concepts between individual
transcripts, and later comparing developed codes with emergent
themes. Regular meetings between the 4 authors allowed ac-
curate categorization and classification, and the development
of typologies and explanatory records to be pursued. In addi-
tion, to ensure rigour in data analysis, data were blindly coded
by a second qualitative researcher and developed themes were
reviewed and examined. After outlining connections between
concepts and categories, theoretical concepts and main themes
and sub-themes were developed.
RESULTS
Of the 41 patients contacted by phone to participate in
the study, 7 opted out, 11 were uncontactable and 23
www.medicaljournals.se/jrm
agreed to participate in the study. Their characterictics
are shown in Table I. Those who declined to participate
were more likely than those who agreed to participate
to have a higher life back on track (LBoT) score (mean
score of 7.5 vs 6.9), but other characteristics (age, sex,
injury type and education level were not significantly
different between the 2 groups.
More participants resided in metropolitan than re-
gional areas (71%); and were female (67%). There was
an over-representation of soft tissue injuries compared
with other types of minor injuries (67%). The mean
time since accident was 4 years with time from injury
ranging from 2 to 7 years. Twelve participants were
identified as not having their life back on track (LBoT
1–6) and 11 reported their life was back on track during
the initial survey (LBoT 7–10).
The majority of “poor recovery” clients (LBoT 1–6)
were aged between 41 and 55 years of age, married,
with moderate levels of pain and moderate to low