3
expressed interest, NIOSH researchers worked with the
mine management (e.g., mine manager or health and safety
professional) to identify potential study candidates.
The CDM participants included 21 employees from a
variety of surface mines of differing geographic regions, sizes,
and commodities throughout the United States including
one medium coal mine, one large coal mine, three small
stone, sand, and gravel (SSG) mines, one medium SSG
mine and one large metal mine. In this study, small was
defined as fewer than 25 employees, medium as between
26 and 100 employees, and large as over 100 employees
[12]. Each individual participant was currently employed
as a haul truck operator at one of the mines. As shown in
Table 1, the median mining experience was 20 years, and
the median haul truck operating experience was 15 years.
The protocol was reviewed and approved by the Centers for
Disease Control and Prevention as exempt human subjects
research* and reviewed for public burden and cleared by the
Office of Management and Budget.
Data Collection
When volunteers agreed to participate, a 1-hour meet-
ing was scheduled during their work hours and interviews
were conducted over Zoom for Government (Zoom Video
Communications, Inc.). Prior to the start of the interview,
all participants provided oral consent to participate in the
research. Each interview was conducted individually. There
were three or four researchers present for all interviews,
one serving as the interview lead, one building the timeline
using Lucidchart (Lucid Software Inc.) on a shared screen,
and the other(s) serving as notetaker(s). All interviews were
audio recorded and transcribed for data analysis.
DATA ANALYSIS AND EXAMPLE
The analysis plan used in the study is adapted from
Wong [18]. Wong outlines two complementary analysis
approaches for CDM data that allow for both structured
and emergent theme analyses. A combination of these
approaches is applied in this study as described below.
*.See 45 C.F.R. Part 46.104.
Step 1: Create a decision chart and summarize the
event.
Following the interview, the draft timeline was imported
into Visio (Microsoft, v2302). The event chronology
was verified by reviewing interview transcripts and audio
recordings. During this step, NIOSH researchers also cap-
tured additional relevant information to transform the
timeline into a decision chart. As illustrated in Figure 1,
the decision chart adds context to the decisions, such as
sensory cues and perceptions, cognitions, and actions, as
described by the haul truck operator when recounting the
incident. These decision charts are standalone summaries
which served as the foundation for the next step.
Step 2: Make a decision analysis table.
Next, for each interview, NIOSH researchers created a
decision analysis table. The objective of creating decision
analysis tables is to connect the data extracted from the
decision chart with corresponding justifications and objec-
tives gathered from probing questions during the interview.
These tables serve as a more elaborate resource for under-
standing the actions taken and decisions made in response
to the incident. First, NIOSH researchers took data from
the decision chart to populate columns for “sensory cues
/perceptions,” “situational assessment /cognitions,” and
“decisions /event.” Next, NIOSH researchers conducted
further review of the interview data to extract correspond-
ing information about “situational assessment,” “why was
the action /decision selected?” and “what for?”. An exam-
ple decision analysis table is provided in Table 2.
Step 3: Identify emergent themes.
Researchers next used the decision charts and deci-
sion analysis tables to identify emergent decision-related
themes. Using emergent thematic analysis [19], three
researchers independently reviewed the decision charts,
decision analysis tables, and interview transcripts in search
of initial themes. This phase of the data analysis allowed
for the discovery and development of as many themes
as required to capture the full depth and breadth of the
data. Next, NIOSH researchers held several meetings to
review the themes, identify commonalities, and rectify any
Table 1. Participant Experience Demographics (N=21)
Median
[years]
First Quartile
[years]
Third Quartile
[years]
Interquartile Range
[years]
Mining Experience 20 6.5 26 19.5
Mine Site Experience 5 3 20.5 17.5
Haul Truck Experience 15 3.75 21 17.25
Haul Truck Experience at Current Site 4.5 3 11.25 8.25
expressed interest, NIOSH researchers worked with the
mine management (e.g., mine manager or health and safety
professional) to identify potential study candidates.
The CDM participants included 21 employees from a
variety of surface mines of differing geographic regions, sizes,
and commodities throughout the United States including
one medium coal mine, one large coal mine, three small
stone, sand, and gravel (SSG) mines, one medium SSG
mine and one large metal mine. In this study, small was
defined as fewer than 25 employees, medium as between
26 and 100 employees, and large as over 100 employees
[12]. Each individual participant was currently employed
as a haul truck operator at one of the mines. As shown in
Table 1, the median mining experience was 20 years, and
the median haul truck operating experience was 15 years.
The protocol was reviewed and approved by the Centers for
Disease Control and Prevention as exempt human subjects
research* and reviewed for public burden and cleared by the
Office of Management and Budget.
Data Collection
When volunteers agreed to participate, a 1-hour meet-
ing was scheduled during their work hours and interviews
were conducted over Zoom for Government (Zoom Video
Communications, Inc.). Prior to the start of the interview,
all participants provided oral consent to participate in the
research. Each interview was conducted individually. There
were three or four researchers present for all interviews,
one serving as the interview lead, one building the timeline
using Lucidchart (Lucid Software Inc.) on a shared screen,
and the other(s) serving as notetaker(s). All interviews were
audio recorded and transcribed for data analysis.
DATA ANALYSIS AND EXAMPLE
The analysis plan used in the study is adapted from
Wong [18]. Wong outlines two complementary analysis
approaches for CDM data that allow for both structured
and emergent theme analyses. A combination of these
approaches is applied in this study as described below.
*.See 45 C.F.R. Part 46.104.
Step 1: Create a decision chart and summarize the
event.
Following the interview, the draft timeline was imported
into Visio (Microsoft, v2302). The event chronology
was verified by reviewing interview transcripts and audio
recordings. During this step, NIOSH researchers also cap-
tured additional relevant information to transform the
timeline into a decision chart. As illustrated in Figure 1,
the decision chart adds context to the decisions, such as
sensory cues and perceptions, cognitions, and actions, as
described by the haul truck operator when recounting the
incident. These decision charts are standalone summaries
which served as the foundation for the next step.
Step 2: Make a decision analysis table.
Next, for each interview, NIOSH researchers created a
decision analysis table. The objective of creating decision
analysis tables is to connect the data extracted from the
decision chart with corresponding justifications and objec-
tives gathered from probing questions during the interview.
These tables serve as a more elaborate resource for under-
standing the actions taken and decisions made in response
to the incident. First, NIOSH researchers took data from
the decision chart to populate columns for “sensory cues
/perceptions,” “situational assessment /cognitions,” and
“decisions /event.” Next, NIOSH researchers conducted
further review of the interview data to extract correspond-
ing information about “situational assessment,” “why was
the action /decision selected?” and “what for?”. An exam-
ple decision analysis table is provided in Table 2.
Step 3: Identify emergent themes.
Researchers next used the decision charts and deci-
sion analysis tables to identify emergent decision-related
themes. Using emergent thematic analysis [19], three
researchers independently reviewed the decision charts,
decision analysis tables, and interview transcripts in search
of initial themes. This phase of the data analysis allowed
for the discovery and development of as many themes
as required to capture the full depth and breadth of the
data. Next, NIOSH researchers held several meetings to
review the themes, identify commonalities, and rectify any
Table 1. Participant Experience Demographics (N=21)
Median
[years]
First Quartile
[years]
Third Quartile
[years]
Interquartile Range
[years]
Mining Experience 20 6.5 26 19.5
Mine Site Experience 5 3 20.5 17.5
Haul Truck Experience 15 3.75 21 17.25
Haul Truck Experience at Current Site 4.5 3 11.25 8.25