DIY Power Tools Injuries

Public Health Project 2010-2011

Power Tools that don’t lend a Helping Hand

Amit Anand, Nicholas Campion, James Cheshire, Thomas Haigh, James LeckenbyThird Year Medical Students

University of Birmingham

Word Count: 5317

Power Tools that don’t lend a Helping Hand 2011

Abstract

Objectives: To identify demographic and behavioural trends associated with hand injuries sustained

by power tool use, and to conduct a relevant treatment outcome analysis. We hope that our findings

will motivate further investigation into preventative measures that are specific to the identified “at

risk” groups.

Design: A cross-sectional data analysis of the Home and Leisure Accident (HASS/LASS) database

between 2000 and 2002, specifically looking at domestically sustained power tool injuries to the

hand.

Setting: The Department of Trade and Industry (DTI) selected 16 hospital A&E departments widely

representative of the UK demographic population.

Population: The data provided by DTI sampled 4131 cases of power tool injuries sustained in the

domestic setting serious enough to warrant A&E admission. This dataset was refined to only include

cases specifically looking at power tool injury to the hand, producing the final study sample of 1806

cases.

Measurements: Specially-trained HASS/LASS interviewers identified newly-admitted A&E patients

suffering from domestically sustained accidents and interviewed them using a standardised

questionnaire documenting the following details: patient age and sex, year of Injury, history of the

accident and location, body part injured and injury sustained, behaviour preceding the incident,

injury sustained and outcome following assessment at A&E.

Results:

Demographic analysis: Men sustained 89.5% of all hand related DIY power tool injuries. Most

injuries (75.4%) occurred in the 30-69 year age group. The elderly age bracket (70+ years) showed

the lowest frequency of hand injuries admitted to A&E (11.2%), but the highest proportion of injuries

requiring follow up in secondary care (44.8%, p=0.002). Altogether, 37% (p=0.002) of hand injuries

sustained across all age groups resulted in hospital care, with a further 22.8% (p=0.002) requiring

care in the community. The power tools most commonly causing injury were found to be circular

saws (28.6%) and hedge trimmers (27.4%), cumulatively accounting for the majority (56%) of hand

injuries studied. Hedge trimmers, were accountable for the majority of injuries amongst females

(56.6%) whilst circular saw accounted for the majority (30.9%) amongst males.

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Injury Analysis: Circular saws and hedge trimmers accounted for 66.7% (p=0.002) of specialist care

review, and 87.7% (p=0.002) of immediate specialist attention.

Behavioural Analysis: Atypical positioning was the commonest behavioural cause (20.4%) of injury

followed by complacency (16.4%) and distraction/inattention (10.1%). Males were found to be more

complacent (16.1% in men vs. 13.3% in women), while women suffered more injuries due to

distraction and inattention (20% in women vs. 7.9% in men). Females showed better adherence to

safety measures as 0% of injuries sustained in women were due to lack of safety measures.

Complacency accounted for 17% of injuries sustained in the younger age group (p=0.015). Despite

this they were better at adhering to safety measures than their elder counterparts (0.4% in young vs

2.5% in middle aged).

Conclusion: In an economic climate lending itself to increased DIY activity, this research should be a

focus in emergency medicine. This is the only study that identifies demographic and behavioural

trends leading to hand injuries from such a broad spectrum of power tools. Injuries in the elderly

population most commonly require secondary care; a significant finding considering the healthcare

burden from an ageing population. A majority (51.4%) of hand injuries are avoidable in that they

have a behavioural root cause. Thus, implementing appropriate preventative measures will not only

significantly reduce the number of injuries presenting to A/E, but also the overall demand placed

upon the NHS.

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Introduction

The great columns of Rome, the finishing touch to the Mona Lisa, the cups of tea a mother makes for

her family first thing in the morning. We might queue to take photographs, gaze in amazement or

simply smile a gentle curve of appreciation. Yet never is this directed to the miracle of normally

functioning hands, never do we recall the essential ingredient in the recipe of such marvels. Human

hands are at the core of all our accomplishments, whether they shape history or just the mood of a

single individuals day. They are indispensable to our creativity and achievements. The monuments we

build, the discoveries we make, the relationships we establish, all act as demonstrations of their

understated ability.

Twenty percent of patients attending A&E have hand injuries, equating to more than 1.36

million attendances in the UK per year [1]. The hands prove to be greatly vulnerable to injury during

Do-it-Yourself (DIY) activities due to their necessity in most tasks and their close proximity to the

hazardous components of the power tools. UK studies show that hand trauma is a consequence in

approximately a quarter of all DIY activities [2] equating to upwards of 200,000 hospital visits each

year; of which, 87,000 are specifically due to power tools [3]. These figures are likely to remain high

according to The Royal Society for the Prevention of Accidents (RoSPA), who state that the current

economic climate has led to an increase in people choosing to undertake DIY activities rather than

hiring a professional labourer.

An audit of hand injuries [4] identified serious shortcomings in service provision; stating that

treatment was often delayed by over 24 hours due to lack of available theatres (62%) and shortage

of staff (13%). The predicted increase in hand injuries and current lack of services available highlights

the importance of devising preventative measures. This is particularly relevant as a UK economic

analysis showed that costs of this kind of injury tripled between 1990 and 2000, amounting to a over

£100 million in healthcare costs in 2000 [5].

Hand trauma can have a major impact on an individual’s life. Frank et al. states that the

socioeconomic impact of these injuries is immense, explaining that patients can suffer from

significant losses in wages and potential earnings [6]. Additionally, patients are vulnerable to

psychosocial implications as the human hand is so instrumental in independence and care giving [7,

8].

It is evident that the prevention of hand injuries sustained domestically can not only have

significant benefits to an individual’s life but also to the healthcare system as a whole. For this

reason, such injury prevention should be a focus in emergency medicine. Previous preventative

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strategies have already shown to be effective; however, there is a distinct lack of understanding

surrounding the behaviours leading to injury. The behavioural and demographic analysis our study

conducts establishes which specific behaviours lead to injury and the ‘at risk’ population groups. This

understanding provides another facet from which specific preventative measure can be developed.

Overview of Existing Research

Our literature review served to gain insight into current and already-documented trends in patterns

and behaviour associated with non-work related power tool hand injuries.

To achieve our objective, a PubMed search with MeSH headings ‘hand injury’ AND

‘accidents, home’ identified several American papers that demonstrated consistent views in sex and

age distributions in those acquiring domestically sustained hand injuries. Frank et al, conducted two

retrospective studies using the same patient group affected by circular-saw related injuries [6, 9].

This patient group showed an overwhelming male dominance (93%) in which the majority of cases

were in older age groups. Conn et al. also showed a male dominance (75%) in their cross-sectional

study population of finger amputation patients that presented to A&E [10]. The highest rates of

injuries in their study group had occurred between the fourth to the six decade of life (11.2-14.9

amputations per 100 000 population).

Our review showed no established pattern with regards to which hand is more commonly

injured. While Frank et al. and Bonte and Goldberg show almost uniform distribution of injuries

between the dominant and non-dominant hands [9, 11], Hoxie et al. and Hussey report higher

incidence of injuries in the non-dominant hand. [12] The pattern of digit involvement is documented

in the work of Frank et al., which is depicted in the diagram below.

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The studies discussed are limited in that they only assess the pattern of injury specific to a

single power tool. To develop an understanding of trends in hand injury from a broader sample of

power tools, the terms ‘DIY,’ ‘power tools’ and ‘hand injury’ were inserted into an advanced

scholarly search engine. A British, cross sectional study by Williams and Power [13] was recovered

and cited circular saws (21%), hedge trimmers (21%) and electric drills (17%) as the power tools most

commonly associated with such injury. Although their study suggests that power tools only account

for 25% of domestically sustained hand injuries, 94.6% of these cases went on to require specialist

care, indicating the high level of healthcare provision attributed to these injuries.

There are evident limitations in the studies reviewed. Conn et al’s surveillance database, for

instance, demonstrated so much insufficiency in patient records that in a quarter of cases (25.2%)

the digits involved were not specified [10]. As their surveillance system only gathered data for finger

amputations treated in A&E, those treated in outpatient clinics were not included. Likewise, it is

difficult to have complete confidence in the results from Frank et al’s study as circular saws, in

America, have been attributed to self-inflicted harm in cases of insurance fraud [14]. Since they

included subjects with “insufficient medical documentation” and there was “negligent accident

analysis”, this limitation cannot be completely ruled out [9].

In all of these studies, there is a lack of clear insight into the behavioural components that

lead to injury. Conn et al. notes: “Studies are needed to assess how human factors… increase the

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Figure 1: a) Distribution of injuries to one finger only; b) distribution of simultaneous injuries to two fingers; c) distribution of simultaneous injuries to three fingers


likelihood of injury to fingers when power tools are used.” [10] Speed attempts to address this gap in

knowledge by proposing several psychosocial factors that play a role in the way people approach DIY

tasks, including complacency and price.

Speed reports that those who lack DIY experience are more cautious in carrying out tasks,

while those with more DIY-experience tend to underestimate the difficulty of the procedure, and

show more complacency towards the recommended safety measures. Frank et al. supports this

notion, highlighting that 75% of his injured study population had more than 10 years of experience

of power tool use; 64% admitting to using their circular saws on a regular basis [6]. Only one of the

patients injured in their study group was a first-time user. In 13 cases (11%), the subject was so

complacent, that they removed the safety devices (e.g. blade guards) prior to conducting the task

[6].

Speed subsequently states that one of the triggers to engage in DIY tasks is to save on costs

involved in hiring professional labour. Frank et al. notes that this is particularly true in today’s

economic climate, where ‘circular saws, particularly the smaller and cheaper “consumer models,”

enjoy an upsurge of sales.’ In fact, 22 (19%) of the cases in their study reported that the ‘saws were

self-constructed.’ [9] Speed explains that while cheaper equipment is favoured, it is less likely to

meet the required safety standards, and thus more likely to lead to avoidable hand injury [15].

Additionally, our literature review also identified “inattention and distraction,”

“intoxication,” “and “lack of peer supervision” as other significant behavioural factors causing hand

injuries. Frank et al. described four patients (4%) that admitted that distraction may have led to

their injury, eight cases (7%) had consumed alcohol, and there was a lack of supervision in 75% of

cases [9].

While the literature shows a degree of behavioural analysis related to DIY hand injury, it is

often limited in content, and typically specific to a single power tool. We hope to address this gap in

knowledge and develop a thorough understanding of the behaviours that lead to hand injury on a

backdrop of a broad spectrum of power tools.

This research will serve to motivate further investigation into preventative measures to reduce

the occurrence of this kind of injury. A review of relevant literature assessing the effectiveness of

preventative measures shows optimistic findings. A PubMed search of the following MeSH headings:

“Accident Prevention” AND “Hand Injuries,” returned with a cohort study by Lipscomb et al. which

highlighted the importance of education, showing a 31% reduction in the incidence of hand injuries

after the subjects attended an apprenticeship education programme [16]. Frank and Ekkernkamp

highlight the effectiveness of improved engineering, reporting no reoccurrence of injury following

the modification of a faulty safety feature in a vole captive bolt device [17]. Finally, a case-crossover

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study by Sorock et al demonstrates the effectiveness of appropriate enforcement of safety

equipment, reporting a 60-70% reduction in risk of laceration and puncture injury after using gloves

in an industrial setting [18].

By developing an understanding of the demographics and behaviours related to such injury,

we hope that our work will aid in developing specific preventative measures. The evident benefits in

previous prevention strategies, discussed above, justify the importance of our research.

Aims and Objectives

We hope to determine:

Demographic trends of hand injuries related to power tool use in the domestic setting.

Trends in treatment outcome related to specific power tool use.

Behavioural patterns that lead to power tool-related DIY injury

We hope that our research will motivate further investigation into preventative measures specific to

the identified ‘at risk’ groups, and their behavioural patterns.

Null Hypotheses

There is no difference in age or gender distribution of hand injuries.

No one tool is responsible for the majority of incidents.

There is no relationship between injury from a specific tool and age or gender.

There is no relationship between injury from a specific power tool and the resultant treatment

outcome.

There is not one specific behavioural pattern responsible for DIY related hand injuries.

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Methods

The raw data analysed in this study was originally collected for the Department of Trade and

Industry’s (DTI) 24th Report of the Home and Leisure Accident Surveillance System (HASS/LASS), a

nationwide database recording domestically sustained injuries serious enough to warrant hospital

visitation between 2000 and 2002. This information, provided by RoSPA, is the most up-to-date data

of its kind, as the DTI ceased data collection by HASS/LASS in 2003.

The HASS/LASS Database

The dataset sampled 16 hospitals across the UK (appendix, table 1), selected on the basis

that they tended to more than 10,000 A&E cases/year, operated a 24-hour service, and took

ambulance cases. To ensure that the hospitals were widely representative, they were based in

different geographical regions (urban and rural), served different population volumes, and consisted

of different-sized A&E units.

Specially-trained HASS/LASS interviewers were allocated to the A&E units of the

participating hospitals. They identified newly-admitted patients suffering from domestically

sustained accidents and interviewed them using a standardised questionnaire (appendix,

questionnaire 1). The data was immediately entered onto a dedicated HASS/LASS computer in the

hospital, and transferred onto a central DTI database.

Each patient account on the database remained confidential, and was organised in tabular

form to include the following details:

- Patient age and sex

- Year of Injury

- History of the accident and location

- Body part injured and injury sustained

- Behaviour preceding the incident

- Mechanism of injury

- Outcome following assessment at A&E

Manipulation of Dataset

The data was first refined to only include the cases specific to our project. To do this, ‘Power Tools in

Domestic Setting’ was entered into the database search engine, allowing the exclusion of any injuries

not sustained by power tool use and occurring in non-domestic settings (appendix, table 2). This

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search produced a sample of 4131 cases, which was further narrowed to a final set of 1806 cases

when refined to only include injuries specific to the hand (appendix, table 3).

To investigate the specific behaviours and power tools most commonly involved in injury, we

closely analysed the histories that were provided in the database. From this information, we were

able to add two further columns to our data set: a) the power tool involved; and b) patient

behaviour that preceded the incident. These columns were then codified (appendix, table 4) and

entered into ‘Statistical Package for the Social Sciences (SPSS)’ for statistical processing.

Similarly the treatment outcomes for each injury were codified after being categorised into

broader outcome groups for the ease of statistical analysis. Five broad categories were established

from the numerous original categories (appendix, table 5): 1) community care, 2) no treatment after

A&E visit, 3) hospital care, 4) immediate specialist attention required, and 5) unspecified. This kind of

broad categorisation was also done to make age groups: young (0-29), middle-aged (30-69), and

elderly (70+).

In some of the data analyses, we combined cases that fell into the categories ‘hospital care’

and ‘immediate specialist attention required’ into a single ‘specialist care’ group, to draw

comparisons between those cases that required secondary follow-up care, and those that did not.

Once the data was fully coded and entered into SPSS, descriptive statistics functions were

used to produce frequency tables and cross table comparisons. The chi squared test function was

used to obtain p values for our comparative data.

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Results

Demographic Results

A demographic analysis revealed that men sustain 89.5% [appendix, table 6] of all hand related DIY

power tool injuries, and that most injuries (75.4%) occurred in the 30-69 year age group [appendix,

table 7]. A detailed analysis showed that, specifically, the 50-59 year age bracket [appendix, table 8]

were the most susceptible to hand injuries, accounting for 20% of all injuries sustained. The elderly

age bracket (70+ years) showed the lowest frequency of hand injuries admitted to A&E (11.2%)

[appendix, table 9], but the highest proportion of injuries requiring hospital care (38.4%, compared

to 37.3% amongst middle-aged injuries, and 34.0% amongst injuries in the young, p=0.002) , and

immediate specialist care (6.4%, compared to 2.6% and 0.4%, p=0.002) [see figure 2 below;

appendix, table 9]. Altogether, 37% (p=0.002) of hand injuries sustained across all age groups

resulted in hospital care, with a further 22.8% (p=0.002) requiring care in the community [appendix,

table 9].

0-29 30-69 70+0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

UNSPECIFIEDNO TREATMENT REQUIRED AFTER A+E VISITIMMEDIATE SPECIALIST ATTENTION REQUIREDHOSPITAL CARECOMMUNITY CARE

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 24.050a 8 p = 0.002

Likelihood Ratio 23.677 8 .003

N of Valid Cases 1806

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Figure 2: Histogram showing Healthcare Outcome in relation to Patient Age


The power tools most commonly causing injury were found to be circular saws (28.6%) and

hedge trimmers (27.4%), cumulatively accounting for the majority (56%) of hand injuries studied

[appendix, table 10]. These tools accounted for the highest incidence of injury amongst the middle-

aged population (29.4% and 27.2% of injuries, respectively) and the elderly population (42.9%, and

29.1%) [appendix, table 10]. In the youngest age group, however, hedge trimmers accounted for the

largest proportion of injuries (26.6%) followed by drill-related injury (25.3%), which otherwise

accounted for 19% of all injuries [appendix, table 10].

Hedge trimmers, which evidently account for a substantial proportion of hand injuries across all

age groups, were shown to be responsible for the majority of injuries amongst females (56.6%)

[appendix, table 6]. Amongst males, however, circular saws were the commonest power tools

associated with injury (30.9%) [appendix, table 11].

Injury Results

An outcome analysis showed that circular saws and hedge trimmers accounted for 66.7% (p=0.002)

of specialist care review, and 87.7% (p=0.002) of immediate specialist attention [see figure 3 below;

appendix, table 12].

In 2002 there was an increase in the proportion of injuries sustained that required specialist

review, and a reduced proportion of injuries managed at the community level, compared to 2000 (p

= 0.105) [Appendix, table 13].

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Chi-Square Tests

Value df P value

Pearson Chi-Square 22.671a 7 .002

Behavioural Results

The aim of our behavioural analysis was to broadly determine whether the majority of the injuries

sustained resulted from a fault in the patient’s conduct; or due to a fault in the tool’s mechanism

whilst in use. The former cause of injury was classified as ‘behavioural,’ and the latter was termed

‘mechanical.’ Finally, a third category termed ‘unspecified’ contained accounts that were difficult or

too vague to classify with confidence.

The group that was responsible for the highest proportion of injuries was the ‘behavioural’

group, accounting for the majority (51.4%) of injuries sustained [see figure 4 below; appendix, table

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Figure 3: A histogram depicting number of cases and treatment outcome by power tool.


14]. It is important to note, however, that with the limitations in our dataset, it was impossible to

attribute a specific cause to all injuries studied; hence our ‘unspecified’ category accounted for

34.2% of our data [appendix, table 14].

Amongst those cases with an attributable cause to injury, a detailed analysis showed that

atypical positioning was the commonest behavioural cause (20.4%) [appendix, table 15], and the

leading cause of injury amongst middle-aged individuals (20.2%, p=0.015) [appendix, table 16]. The

tools that most commonly associated atypical positioning injury included hedge trimmers (32%),

drills (25%), and circular saws (20.6%) [appendix, table 15]. Cases acquiring injuries from these tools

collectively accounted for 79.8% of injury requiring secondary care follow-up (p=0.002) [appendix,

table 17]. Thus, atypical positioning accounted for the greatest proportion of healthcare provision,

responsible for 30.2% of cases with an attributable cause requiring follow-up specialist attention

(appendix, table 12).

Complacency (16.4%) and distraction/inattention (10.1%) were the most common

behavioural causes leading to injury after atypical positioning [appendix, table 15]. Both were shown

to be most commonly associated with injury from hedge trimmers, accounting for 30.9% and 23.3%

(respectively) of cases with attributable cause [appendix, table 15]. These behaviours showed

marked gender differences: amongst those injuries serious enough to warrant specialist attention,

males were more complacent relative to their female counterparts (cause of 16.1% of injuries in

men compared to 13.3% in women, p=0.081) [appendix, table 20], while women suffered more from

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Figure 4: Bar Chart showing Relative Causes of Hand Injury


injury by distraction and inattention (20% compared to 7.9%, p=0.081). Interestingly females showed

better adherence to safety measures as 0% of injuries sustained in women were due to lack of safety

measures [appendix, table 20, p=0.081].

Complacency was significantly marked amongst the youngest population studied, accounting

for 17% of injuries sustained in this age group (p=0.015) [appendix, table 21]. Whilst the young were

more complacent, they were better at adhering to safety measures than their elder counterparts.

Only 0.4% of injuries occurred due to lack of safety measures in the young, while a lack of safety

measures accounted for 2.5% of cases in the middle aged group and 3% of cases in the elderly

(p=0.015) [appendix, table 21].

Malfunction made up 3.3% of all injuries sustained to the hand, the highest occurrence being

in drills (12.2%) accounting for more than twice as many injuries proportionately compared to other

power tool malfunction [appendix, table 21]. This would suggest that stricter regimes in quality

assurance at the manufacturing level of these drills may need to be implemented.

Discussion

From a database of 4131 cases we determined that 1806 were relevant to this study. On the basis of

these cases we conducted our demographic analysis, severity analysis and behaviour analysis.

Demographic Analysis

An overwhelming majority of injuries resulting from power tool use were found to occur in men

(89.5%) between the ages of 30-69 (75.4%), suggesting that high-risk domestic DIY tasks are

performed chiefly by this population. The injuries sustained in this study group were most

commonly caused by circular saws and hedge trimmers (54.8%). A relevant outcome analysis

identified that this age group accounted for the highest volume of cases (860) requiring secondary

care after A/E admission. While this may be true, a greater proportion of the elderly population (of

70+) required secondary care (44.8%, p = 0.002); again, mostly due to circular saws (42.9%) and

hedge trimmers (29.1%). These results have a significant implication to healthcare provision when

considering an ageing population.

According to current literature, an increasing trend of DIY tool use is predicted by most

authors in accordance with the current economic climate. The UK National Estimates of power tool

related injuries between 2000 and 2002 (provided by RoSPA, n = 4131) back up these predictions by

showing increasing national estimates of such injuries: 24,605 in 2000 rising to 28,270 in 2002. When

we investigated the frequency of power tool injury specific to the hands in our study population (n =

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1806) over this time period, a statistically insignificant (p = 0.267) decreasing trend was described,

contradicting current literature.

Severity Analysis

Our demographic tables show that circular saws and hedge trimmers accounted for the majority of

hand injuries acquired (cumulatively, 56%); on further analysis, these power tool injuries also

accounted for the highest proportion of secondary care attention required (66.7%, p=0.002). These

results illustrate the burden these tools have upon the healthcare system, not just in the shear load

of cases requiring attention, but also the high level of healthcare provision which they demand. This

is further exemplified in that these tools accounted for 87.7% (p=0.002) of the most severe hand

injuries sustained (those requiring immediate specialist attention).

A trend analysis in the outcomes of these injuries over the years shows that this burden is

likely to increase in the future. Between 2000 and 2002, there was seen to be a statistically

significant increase in the cases requiring immediate specialist attention: a rise from 19 cases in 2000

to 22 in 2002 (p=0.044).

Behaviour Analysis

When the causes of injuries were grouped into their broader categories (behavioural, mechanical,

and unspecified), the majority of hand injuries (51.4%) could be attributed to a behavioural cause.

As behavioural causes to injury can be modified, our data would suggest that the majority of

hand injuries sustained using power tools at home are avoidable. The specific behaviours most

responsible for injury were: atypical positioning (20.4% of all injuries), complacency (16.4%), and

distraction/inattention (10.1%). This information provides a basis from which safety and

preventative measures can be suggested; for example, preventing injuries from atypical positioning

and distraction/inattention can be reduced by promoting supervision or peer support when

conducting DIY. Likewise, complacency can be reduced with the provision of sufficient training and

education.

Our data goes on to suggest that such preventative measures can greatly reduce the burden

of such injury to our healthcare system. Of those injuries requiring follow-up after initial

presentation, it can be seen that, most of the time, community-level management is not sufficient

for those with a behavioural cause. A degree of specialist attention is required for the greater part

of these injuries; a cost which we have already shown to be avoidable provided that safer power-

tool behaviour is promoted and improved.

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Limitations

As we were not personally able to validate each of the cases, our results carry the same

limitations as those in the HASS/LASS dataset. There were considerable limitations observed; for

instance, a number of accounts showed discrepancy in gender description in the provided history

and what was written under the gender subheading. When this occurred we used the information

provided in the gender column. Additionally, we also noted a number of duplicate accounts. To

avoid bias, we included all accounts in our results.

A lack of sufficient detail in some of the accounts introduced other drawbacks in our study.

On occasion, the information was so limited that the power tool used was not clear. For instance

“electric saw” was often recorded; when this occurred, we reclassified the power tool as “circular

saw,” potentially leading to an overrepresentation of circular saw incidents. Assumptions also played

a role whilst categorising each case into the various behaviour categories. Histories would often have

little information on the circumstances leading to injury, only including terms such as “caught” when

describing causative events. It was agreed that the term “caught” meant that an individual was being

complacent, as the patient could have taken more care. This, of course, may have not been the

interpretation intended. Where these inferences could not be made, the lack of sufficient detail led

to the creation of an unspecified category in our behaviour analysis. This subjected the data to

additional bias as it may have led to an underestimate of the relevant categories.

Finally, insufficient detail under “outcome following admission to A&E” occasionally made it

difficult to definitively state each patient’s treatment outcome. This shortcoming could have been

improved using the OPCS-4 coding system which documents all operations, procedures and

interventions carried out on a patients during a hospital admission; translating each entry into an

alphanumeric code. Its Incorporation would have allowed for more accurate and efficient analyses.

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Recommendations (for future research)

While our study investigates several key research areas related to domestically sustained

hand injuries, our literature review revealed several other areas worthy of investigation. A key at-risk

population identified by Conn et al. were children younger than 5-years old who accounted for the

highest rate of finger amputations in American emergency departments annually. More research

focused at developing preventive measures is especially important in such a young age group as

these injuries can carry significant life-long functional restrictions. Additionally, Williams and Power

showed that an overwhelming majority of domestically sustained hand injuries are from manual

tools, not power tools. The study showed that a Stanley Knife, on its own, caused as many hand

injuries leading to A&E admission as all power tool combined. Thus, it can be easily inferred that the

healthcare burden from manual tools is still extraordinary and worthy of further investigation.

Our research provides a basis to several areas of further investigation. As alluded to in our

introduction, the economic impact of these types of injuries is significant. Our data not only suggests

that these injuries contribute to a significant financial burden to the NHS currently, but that this

burden is likely to increase with an ageing population. Investigation directed at the current and

expected costs surrounding these injuries would complete our understanding of their burden.

Additionally, we found that the malfunctioning of the power tool accounted for 3.3% of all injuries

sustained to the hand, namely in activity involving drills. This finding lends itself to further

investigation into the quality assurance criteria involved in tool engineering.

As a continuation to this project, we are currently undertaking a study looking to identify

measures to prevent the occurrence of power tool related hand injuries in the domestic setting.

From the trends that we have described in the mechanisms and behaviours leading to injury, a

questionnaire has been developed and distributed amongst healthcare personnel who deal with

hand injuries on a regular basis. The aim of this questionnaire is to gather expert opinions regarding

the commonest causes of injury, and their suggestions of how to prevent such injury from occurring.

The study will be conducted using the Delphi technique, where the questionnaire will circulate

amongst the expert panel for a number of cycles, each time being refined and narrowed to only

include opinions and suggestions that are widely accepted by the group. The end result will be a

common consensus as to what the most common root-cause to injury is, and the important

preventative measures that are needed to prevent this from occurring.

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Conclusion

In an economic climate lending itself to increased DIY activity, it is important to develop an

understanding of the demographic and behavioural trends in hand injuries caused by power tools.

This is the only study that has been able to identify such trends leading to hand injuries from such

a broad spectrum of power tools. Our study has shown that while men between the ages of 30-69

account for the highest volume of such cases, it is the elderly population (70+) that are most

burdensome to our healthcare service; a key finding considering an ageing population. Likewise,

circular saws and hedge trimmers have been shown to cause the most healthcare burden, both in

volume of cases and secondary care required. The majority (51.4%) of hand injuries are avoidable

due to their behavioural root cause. The commonest modifiable behaviours leading to injury are

atypical positioning (20.4%) and complacency (16.4%). Implementing specific prevention strategies,

such as education and training, can reduce the incidence of these injuries and the subsequent

demand placed upon the healthcare system

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Bibliography:

1. Brennen M, Burge P, Burke F, et al. Hand Surgery in the UK. Manpower, resources, standards and training. The British Society for Surgery of the Hand, 2007.

2. Ashby K. Injuries Associated with Do-it-Yourself Maintenance Activities. Victorian Health Promotion Foundation. Edition No. 41. 1999.

3. The Royal Society for the Prevention of Accidents. What are the most common DIY injuries? http://www.rospa.com/faqs/detail.aspx?faq=221 (accessed 19/04/11) .

4. Dias J. Helping the Hand; A report on the provision of surgical care for acute hand disorders in the United Kingdom. British Society for Surgery of the Hand, Royal College of Surgeons, London 1999.

5. Burke F, Dias J. Providing care for hand disorders: a reappraisal of need. Journal of Hand Surgery (British) 2004; 29(6):575-9.

6. Frank M, Hecht J, Napp M et al. Mind your hand during the energy crunch: Functional Outcome of Circular Saw Hand Injuries. Journal of Trauma Management & Outcomes 2010; 4:11.

7. Bylund S, Burström L, Knutsson A. A descriptive study of women injured by hand-arm vibration. The Annals of Occupational Hygiene 2002; 46(3):299-307.

8. Aghazadeh F, Mital A. Injuries due to hand tools; Results of a questionnaire. Applied Ergonomics 1987; 18(4):273-8.

9. Frank M, Lange J, Napp M et al. Accidental circular saw injuries: Trauma mechanisms, injury paterns, and accident insurance. Forensic Science International. 2010; 198(1-3):74-8.

10. Conn J, Annest J, Ryan G et al. Non-Work-Related Finger Amputations in the United States, 2001-2002. Annals of Emergency Medicine 2005; 45(6):630-5.

11. Bonte W , Goldberg R. Accidental circular saw injuries. Journal of Legal medicine 1982; 89(3):173-80.

12. Hoxie S, Capo J, Dennison D, Shin A. The Economic Impact of Electric Saw Injuries to the Hand. Journal of Hand Surgery. 2009; 34(5): 886-889.

13. Williams S, Power D. Hand injuries from tools in domestic and leisure settings: relative incidence and patterns of initial management. Journal of Hand Surgery (European Volume) 2011

20

http://www.jhandsurg.org/article/S0363-5023(09)00111-7/abstract




http://www.ncbi.nlm.nih.gov/pubmed?term=%22Goldberg%20R%22%5BAuthor%5D

http://www.ncbi.nlm.nih.gov/pubmed?term=%22Bonte%20W%22%5BAuthor%5D


14. Bonte W . Self-mutilation and private accident insurance. Journal of Forensic Science 1983; 28(1):70-82.

15. Speed M. Consumer Knowledge of Tool and DIY Safety. UK Department of Trade and Industry. 2002

16. Lipscomb H, Nolan J, Patterson D et al. Prevention of traumatic nail gun injuries in apprentice carpenters: use of population-based measures to monitor intervention effectiveness. American Journal of Industrial Medicine 2008; 51(10):719-27.

17. Frank M , Ekkernkamp A. Small change, big impact: prevention of vole captive bolt device hand injuries. Journal of Trauma 2010; 69(2):478.

18. Sorock G, Lombardi D, Peng D et al. Glove Use and the Relative Rick of Acute Hand Injury: A Case Crossover Study. Journal of Occupational and Environmental Hygiene 2004; 1(3):182-190

21

http://www.ncbi.nlm.nih.gov/pubmed?term=%22Ekkernkamp%20A%22%5BAuthor%5D

http://www.ncbi.nlm.nih.gov/pubmed?term=%22Frank%20M%22%5BAuthor%5D

http://www.ncbi.nlm.nih.gov/pubmed?term=%22Bonte%20W%22%5BAuthor%5D


Appendices

Table 1 - The hospital Accident and Emergency departments participating in the surveillance system between 2000 and 2002.

Hospitals SampledAiredale, Keighley

Blackburn Royal Infirmary, Lancs

Daisy Hill, Newry

George Elliot, Nuneaton

Hereford City General, Hereford

Kings College, Denmark Hill

Luton & Dunstable, Beds

Macclesfield General, Cheshire

Monklands General, Airdrie

Norfolk & Norwich, Norwich

North Devon, Barnstaple

North Tees General, Stockton

Prince Charles, Merthyr Tydfil

Royal Berkshire, Reading

Selly Oak, Birmingham

Skegness and District, Lincs

St. Helier, Carshalton

Worthing

N.b Two hospitals left the sample during the 2000-2002 reporting period without being replaced. Monklands provided data until the end of June 2001, and Royal Berkshire left the sample at the end of 2001.

22


Table 2 - The exclusion criteria for location of injury.

Table 2: Exclusion Criteria filtering location of Injury- Air Museum- Airport- Backlane- Boat Yard- Business/Public Building/ Bank- Car park, Bus Station, Service Station- Education Area- Factory, Warehouse, Workshop, Plant- Field- Filling Station- Holiday Play Scheme- IED- In Sea, Lake, River, Canal, Marsh, Water- Inside School, University, College- Leisure, Public Building, Library, Church- Boat, Ship, Draft, Airbed- Other Industrial Production Area- Other Leisure Facility- Other Location- Other Natural Area- Other Road Area- Other Trade/ Service Area- Parkland/ Cemetery Gardens- Public Playground- Riding School- Rural Road, Pavement, Grass- School Grounds- Shopping Area- Sport Field/ Hall- Swimming Pool- Ulcultivated Fiels/ Woods- Unknown- Unspecified- Waterside/ Beach- Woods- Workshop

23


Table 3 - Inclusion criteria for classifying hand injuries

Table 3: Inclusion Criteria for Classifying Hand Injuries- Both Hands- Fingers, Thumb, Digit, Phalange- Wrists- Nail

Table 4 - Behaviour coding legend

Code Behaviour1.1 Unspecified (patient does not know how the

injury occurred or the history provided by the data was insufficient to ascertain how the injury came about)

1.2 OtherPatient Behaviour2.1 Inexperience (drill bit coming out, drill getting

stuck in material, igniting self, not realising being burnt by power tool)

2.2 Complacency (hand behind drill, fingers too close to saw, poor lighting, patient intoxicated, holding object being cut)

2.3 Distraction/Inattention (includes not realising machine was on, loss of concentration, patient missing material, not paying attention, multitasking)

2.4 Lack of Safety Implementations (hand being dragged into saw by gloves or wood)

2.5 Atypical Hand Position (includes slip/slipping, fell, lost balance, loss of grip, machine not stabilised, catching falling tool)

Mechanical3.1 Indirect Mechanical injury (being hurt by

material, by power tool when not being used, indirect, hurt from hot surface)

3.2 Direct Mechanical Injury (Vibration injury, kick back, injured while cleaning, steam from power tool, hot water)

3.3 Malfunction (tool snapping, electric shock)

24


Table 5 - Categorising of Treatment OutcomeReferral Categories

Immediate Specialist Attention Required

- Admitted to Specialist Hospital- Referred to Orthopaedics- Referred to Plastic Surgery- Referred to Brighton Plastics- Referred to St Georges Plastics Dept- To be admitted to Specialist Hospital

Hospital Care

- Discharged IP, Referred Outpatient Clinic- Inpatient- Unspec Outcome- Inpatient, then transf to other hosp- IP for less than one day- Referred to any outpatient clinic- Other outcome – Newark hospital- Referred to other hospital- Review at a & e 3 days- Review 3 days- Review a & e 4 days- See in 6 days- To be admitted to ward next day- Treated in triage- Admit to coombes- Admitted to other hospital- Discharged IP-No more treatment required

Community Care

- Discharged IP- Referred to GP- Occupational health- Referred to GP

No treatment required after a/e visit

- Examined but no treatment given- Treated; no more treatment required- Review a & e- Review a & e- Review a&e- Review in a/e- Review in a and e

Unspecified

- Patient did not wait- Other Outcome- Unknown Outcome

25


Table 6 - Frequency of injuries sustained by men and women

Frequency Percent Valid Percent

Cumulative

Percent

FEMALE 189 10.5 10.5 10.5

MALE 1617 89.5 89.5 100.0

Total 1806 100.0 100.0

Table 7 - Frequency of injuries sustained by age group

Age group Frequency Percent

0-29 241 13.3

30-69 1362 75.4

70+ 203 11.2

Total 1806 100.0

Table 8 - Frequency of injuries sustained by age group

Frequency Percent

Valid 0-9 23 1.3

10-19 53 2.9

20-29 165 9.1

30-39 356 19.7

40-49 334 18.5

50-59 362 20.0

60-69 310 17.2

70-79 159 8.8

80-89 37 2.0

90+ 7 .4

Total 1806 100.0

26


Table 9 - Frequency of patient outcome with respect to age

OUTCOME

AgeSmall

Total0-29 (Young)

30-69

(Middle

Aged)

70+

(Elderly)

IMMEDIATE SPECIALIST

ATTENTION REQUIRED

Count 1 35 13 49

% within

AgeSmall

.4% 2.6% 6.4% 2.7%

HOSPITAL CARE Count 82 508 78 668

% within

AgeSmall

34.0% 37.3% 38.4% 37.0%

COMMUNITY CARE Count 47 317 48 412

% within

AgeSmall

19.5% 23.3% 23.6% 22.8%

NO TREATMENT

REQUIRED AFTER A+E

VISIT

Count 101 451 58 610

% within

AgeSmall

41.9% 33.1% 28.6% 33.8%

UNSPECIFIED Count 10 51 6 67

% within

AgeSmall

4.1% 3.7% 3.0% 3.7%

Total Count 241 1362 203 1806

% within

AgeSmall

100.0% 100.0% 100.0% 100.0%

Chi-Square Tests

Value df P value


27


Table 10 - Frequency of tool type used with respect to age group

TOOL TYPE

AgeSmall

Total

0-29

(Young)

30-69

(Middle

Aged)

70+

(Elderly)

CHAINSAW Count 16 63 9 88

% within AgeSmall 6.6% 4.6% 4.4% 4.9%

CIRCULAR SAW Count 28 401 87 516

% within AgeSmall 11.6% 29.4% 42.9% 28.6%

DRILL Count 61 261 22 344

% within AgeSmall 25.3% 19.2% 10.8% 19.0%

GRINDER Count 33 187 16 236

% within AgeSmall 13.7% 13.7% 7.9% 13.1%

HEDGE TRIMMER Count 64 371 59 494

% within AgeSmall 26.6% 27.2% 29.1% 27.4%

MISCELLANEOUS Count 16 26 6 48

% within AgeSmall 6.6% 1.9% 3.0% 2.7%

WALLPAPER STRIPPER Count 20 35 4 59

% within AgeSmall 8.3% 2.6% 2.0% 3.3%

WELDER Count 3 18 0 21

% within AgeSmall 1.2% 1.3% .0% 1.2%

Total Count 241 1362 203 1806

% within AgeSmall 100.0% 100.0% 100.0% 100.0%

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Table 11 - Frequency of injuries sustained by particular tools in males and females

SEX

TotalFEMALE MALE

TOOL TYPE CHAINSAW Count 9 79 88

% within SEX 4.8% 4.9% 4.9%

CIRCULAR SAW Count 16 500 516

% within SEX 8.5% 30.9% 28.6%

DRILL Count 17 327 344

% within SEX 9.0% 20.2% 19.0%

GRINDER Count 9 227 236

% within SEX 4.8% 14.0% 13.1%

HEDGE TRIMMER Count 107 387 494

% within SEX 56.6% 23.9% 27.4%

MISCELLANEOUS Count 16 32 48

% within SEX 8.5% 2.0% 2.7%

WALLPAPER STRIPPER Count 14 45 59

% within SEX 7.4% 2.8% 3.3%

WELDER Count 1 20 21

% within SEX .5% 1.2% 1.2%

Total Count 189 1617 1806

% within SEX 100.0% 100.0% 100.0%

29


Table 12 - Frequency of injuries sustained from specific tools with respect to outcome of the patient

OUTCOME

SPECIALIST

CARE

HOSPITAL

CARE

IMMEDIATE

SPECIALIST

ATTENTION

REQUIRED


% within OUTCOME 4.6% 8.2% 4.9%


% within OUTCOME 42.2% 71.4% 44.2%

DRILL Count 93 1 94

% within OUTCOME 13.9% 2.0% 13.1%


% within OUTCOME 10.3% .0% 9.6%


% within OUTCOME 22.9% 16.3% 22.5%








% within OUTCOME 100.0% 100.0% 100.0%

30


Chi-Square Tests

Value df P value


Table 13 - Frequency of outcomes within each year

YEAR

Total2000 2001 2002

OUTCOME COMMUNITY CARE Count 159 130 123 412

% within YEAR 24.9% 22.1% 21.2% 22.8%

HOSPITAL CARE Count 227 221 220 668

% within YEAR 35.5% 37.6% 38.0% 37.0%

IMMEDIATE SPECIALIST

ATTENTION REQUIRED

Count 19 8 22 49

% within YEAR 3.0% 1.4% 3.8% 2.7%

NO TREATMENT

REQUIRED AFTER A+E

VISIT

Count 217 206 187 610

% within YEAR 34.0% 35.0% 32.3% 33.8%


% within YEAR 2.7% 3.9% 4.7% 3.7%

Total Count 639 588 579 1806

% within YEAR 100.0% 100.0% 100.0% 100.0%

Chi-Square Tests

Value df P value


Table 14 - Behaviour frequency

31


Frequency Percent

UNSPECIFIED 629 34.8

BEHAVIOURAL 928 51.4

MECHANICAL 249 13.8

Total 1806 100.0

32


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Table 15 - Behaviour type frequency with respect to particular tool used

BEHAVIOUR

TOOL TYPE

TotalCHAINSAWCIRCULAR SAW DRILL GRINDER

HEDGE TRIMMER MISCELLANEOUS

WALLPAPER STRIPPER WELDER

UNSPECIFIED Count 36 260 63 87 138 10 20 3 617

% within TOOL TYPE 40.9% 50.4% 18.3% 36.9% 27.9% 20.8% 33.9% 14.3% 34.2%

OTHER Count 0 0 4 1 4 3 0 0 12

% within TOOL TYPE .0% .0% 1.2% .4% .8% 6.3% .0% .0% .7%

INEXPERIENCE Count 1 9 14 2 5 3 1 6 41

% within TOOL TYPE 1.1% 1.7% 4.1% .8% 1.0% 6.3% 1.7% 28.6% 2.3%

COMPLACENCY Count 13 60 60 40 110 4 4 5 296

% within TOOL TYPE 14.8% 11.6% 17.4% 16.9% 22.3% 8.3% 6.8% 23.8% 16.4%

DISTRACTION/INATTENTION

Count 5 45 28 12 83 5 3 1 182

% within TOOL TYPE 5.7% 8.7% 8.1% 5.1% 16.8% 10.4% 5.1% 4.8% 10.1%

LACK OF ADEQUATESAFETY MEASURES

Count 3 20 2 5 10 0 0 1 41

% within TOOL TYPE 3.4% 3.9% .6% 2.1% 2.0% .0% .0% 4.8% 2.3%

AYTPICAL POSTIONING Count 16 76 92 51 118 5 10 0 368

% within TOOL TYPE 18.2% 14.7% 26.7% 21.6% 23.9% 10.4% 16.9% .0% 20.4%

INDIRECTMECHANICAL INJURY

Count 6 16 15 5 11 11 10 4 78

% within TOOL TYPE 6.8% 3.1% 4.4% 2.1% 2.2% 22.9% 16.9% 19.0% 4.3%

DIRECT MECHANICAL INJURY

Count 6 30 24 20 14 6 11 1 112

% within TOOL TYPE 6.8% 5.8% 7.0% 8.5% 2.8% 12.5% 18.6% 4.8% 6.2%

MALFUNCTION Count 2 0 42 13 1 1 0 0 59

% within TOOL TYPE 2.3% .0% 12.2% 5.5% .2% 2.1% .0% .0% 3.3%

Total Count 88 516 344 236 494 48 59 21 1806

% within TOOL TYPE 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


34


Table 16 - Behaviour frequency causing injury with respect to age

BEHAVIOURAgeSmall

Total0-29 (Young) 30-69 (Middle Aged) 70+ (Elderly)


% within AgeSmall 33.2% 33.6% 39.4% 34.2%

OTHER Count 1 10 1 12

% within AgeSmall .4% .7% .5% .7%

INEXPERIENCE Count 9 32 0 41

% within AgeSmall 3.7% 2.3% .0% 2.3%

COMPLACENCY Count 41 222 33 296

% within AgeSmall 17.0% 16.3% 16.3% 16.4%

DISTRACTION/

INATTENTION

Count 32 126 24 182

% within AgeSmall 13.3% 9.3% 11.8% 10.1%

LACK OF ADEQUATE

SAFETY MEASURES

Count 1 34 6 41

% within AgeSmall .4% 2.5% 3.0% 2.3%

AYTPICAL

POSTIONING

Count 39 293 36 368

% within AgeSmall 16.2% 21.5% 17.7% 20.4%

INDIRECT

MECHANICAL

INJURY

Count 19 55 4 78

% within AgeSmall 7.9% 4.0% 2.0% 4.3%

DIRECT MECHANICAL

INJURY

Count 14 84 14 112

% within AgeSmall 5.8% 6.2% 6.9% 6.2%

MALFUNCTION Count 5 49 5 59

% within AgeSmall 2.1% 3.6% 2.5% 3.3%

Total Count 241 1362 203 1806

% within AgeSmall 100.0% 100.0% 100.0% 100.0%

Chi-Square Tests

Value df P value


35


Table 17 - Frequency of specific tools with respect to outcome of the patient

OUTCOME

SPECIALIST

CARE

HOSPITAL

CARE

IMMEDIATE

SPECIALIST

ATTENTION

REQUIRED




% within OUTCOME 42.2% 71.4% 44.2%

DRILL Count 93 1 94

% within OUTCOME 13.9% 2.0% 13.1%




% within OUTCOME 22.9% 16.3% 22.5%








% within OUTCOME 100.0% 100.0% 100.0%

Chi-Square Tests

Value df P value


36


Table 18 - Frequency and type of care received with respect to behaviour causing injury

BEHAVIOUR

HIC2

Total

COMMUNITY

CARE

NO TREATMENT

AFTER A+E VISIT

SPECIALIST

CARE UNSPECIFIED

UNSPECIFIED Count 131 156 297 33 617

% within BEHAVIOUR 21.2% 25.3% 48.1% 5.3% 100.0%

OTHER Count 3 7 2 0 12

% within BEHAVIOUR 25.0% 58.3% 16.7% .0% 100.0%

INEXPERIENCE Count 8 16 13 4 41


COMPLACENCY Count 76 97 114 9 296


DISTRACTION/

INATTENTION

Count 48 65 64 5 182


LACK OF ADEQUATE

SAFETY MEASURES

Count 7 17 14 3 41


AYTPICAL

POSTIONING

Count 89 147 127 5 368


INDIRECT

MECHANICAL INJURY

Count 19 35 24 0 78

% within BEHAVIOUR 24.4% 44.9% 30.8% .0% 100.0%

DIRECT MECHANICAL

INJURY

Count 21 44 43 4 112


MALFUNCTION Count 10 26 19 4 59


Total Count 412 610 717 67 1806


37


Table 19-Frequency of outcome of the patient with respect to sex

SEX

TotalFEMALE MALE

OUTCOME IMMEDIATE SPECIALIST

ATTENTION REQUIRED

Count 2 47 49

% within SEX 1.1% 2.9% 2.7%

HOSPITAL CARE Count 58 610 668

% within SEX 30.7% 37.7% 37.0%

COMMUNITY CARE Count 38 374 412

% within SEX 20.1% 23.1% 22.8%

NO TREATMENT

REQUIRED AFTER A+E

VISIT

Count 88 522 610

% within SEX 46.6% 32.3% 33.8%

UNSPECIFIED Count 3 64 67

% within SEX 1.6% 4.0% 3.7%


% within SEX 100.0% 100.0% 100.0%

Chi-Square Tests

Value df P value


38


Table 20 - Frequency of type of behaviours causing injury occurring in men and women

SEX

TotalFEMALE MALE

BEHAVIOUR UNSPECIFIED Count 24 273 297

% within SEX 40.0% 41.6% 41.4%

OTHER Count 0 2 2

% within SEX .0% .3% .3%

INEXPERIENCE Count 0 13 13

% within SEX .0% 2.0% 1.8%

COMPLACENCY Count 8 106 114

% within SEX 13.3% 16.1% 15.9%

DISTRACTION/

INATTENTION

Count 12 52 64

% within SEX 20.0% 7.9% 8.9%

LACK OF ADEQUATE

SAFETY MEASURES

Count 0 14 14

% within SEX .0% 2.1% 2.0%

AYTPICAL POSTIONING Count 10 117 127

% within SEX 16.7% 17.8% 17.7%

INDIRECT MECHANICAL

INJURY

Count 2 22 24

% within SEX 3.3% 3.3% 3.3%

DIRECT MECHANICAL

INJURY

Count 1 42 43

% within SEX 1.7% 6.4% 6.0%

MALFUNCTION Count 3 16 19

% within SEX 5.0% 2.4% 2.6%


% within SEX 100.0% 100.0% 100.0%

Chi-Square Tests

Value df P value


39


Table 21 - Frequency of behaviour causing injury with respect to age

BEHAVIOURAgeSmall

Total0-29 (Young) 30-69 (Middle Aged) 70+ (Elderly)


% within AgeSmall 33.2% 33.6% 39.4% 34.2%

OTHER Count 1 10 1 12

% within AgeSmall .4% .7% .5% .7%

INEXPERIENCE Count 9 32 0 41

% within AgeSmall 3.7% 2.3% .0% 2.3%

COMPLACENCY Count 41 222 33 296

% within AgeSmall 17.0% 16.3% 16.3% 16.4%

DISTRACTION/

INATTENTION

Count 32 126 24 182

% within AgeSmall 13.3% 9.3% 11.8% 10.1%

LACK OF ADEQUATE

SAFETY MEASURES

Count 1 34 6 41

% within AgeSmall .4% 2.5% 3.0% 2.3%

AYTPICAL

POSTIONING

Count 39 293 36 368

% within AgeSmall 16.2% 21.5% 17.7% 20.4%

INDIRECT

MECHANICAL

INJURY

Count 19 55 4 78

% within AgeSmall 7.9% 4.0% 2.0% 4.3%

DIRECT MECHANICAL

INJURY

Count 14 84 14 112

% within AgeSmall 5.8% 6.2% 6.9% 6.2%

MALFUNCTION Count 5 49 5 59

% within AgeSmall 2.1% 3.6% 2.5% 3.3%

Total Count 241 1362 203 1806

% within AgeSmall 100.0% 100.0% 100.0% 100.0%

Chi-Square Tests

Value df P value


40


Authors ContributionsEvery member of this group contributed in their only particular way towards each section of this project. It was a group effort.

Author ContributionAmit Anand - Discussion

- Introduction- Conclusion- Shortcomings- Appendices- Methods

Nicholas Campion - Discussion- Data Analysis and Results- Appendices- Communication with Supervisor- Literature Review

James Cheshire - Discussion- Introduction- Shortcomings- Conclusion- Appendices- Methods

Thomas Haigh - Literature Review- Abstract- Aims and Objectives- Recommendations for Future Research- Appendices- Methods

James Leckenby - Literature review- Data Analysis and Results- Appendices- Communication with Supervisor

Project design, data gathering, and all other sections were done by all of us.

Every member of the group has both read and agreed the final version.

Signatures:

Amit Anand Nicholas Campion James Cheshire

Thomas Haigh James Leckenby

41

DIY Power Tools Injuries

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