A portable ergonomic observation method (PEO) for computerized on-line recording of postures and manual handling

Applied ORTH EINEMANN

Ergonomics Vol26, No 2, pp. 9S100, 1995 Cowrieht 0 1995 Elsevier Science Ltd Printed’in &ea;Britain. All rights reserved ooO3-6870195 $10.00 + 0.00

A portable ergonomic observation method (PEO) for computerized on-line recording of postures and manual handling Charlotte Fransson-Hall, Robert Gloria, Asa Kilbom and Jgrgen Winkel Swedish National Institute of Occupational Health, Division of Applied Work Psychology, S-l 7184 Solna, Sweden

Lena Karlqvist and Christina Wiktorin Karolinska Hospital and Institute, Department of Occupational Medicine, S-104 04 Stockholm, Sweden

Stockholm Music 1 Study Group Occupational Health, Karolinska Hospital and Institute, Departments of EpidemiologylIMM, Orthopaedics, Rheumatology and Rehabilitation and Physical Medicine, Stockholm, Sweden; National Institute of Occupational Health, Divisions of Applied Work Physiology, Occupational Medicine, Psychophysiology and Work and Environmental Physiology, Solna, Sweden; National Institute of Psychosocial Factors and Health, Stockholm, Sweden

A new portable ergonomic observation method (PEO) is presented. It is applicable to most professions and work tasks and requires only moderate human resources for data collection and analysis. Observations are made in real time directly at the workplace using a portable personal or hand-held computer, and data are accessible for immediate analysis and presentation. Duration and number of events are calculated for postures at four body regions (arms, neck, trunk and knee) as well as for manual handling. An evaluation of the PEO method, assessing some important aspects of internal validity as well as intra- and inter-observer reliability, was carried out using video recordings. It showed acceptable validity for some types of physical exposure, and high intra- and inter-observer reliability. Practical experiences from using the PEO method in a field study and further improvements of the method are discussed. Keywords: observation method, computer, posture, manual handling, validity, reliability

technical measurements. However, this may be too expensive in studies comprising a large number of subjects. Thus, systematic observation applied by experienced ergonomists may offer a compromise. Several methods for observing posture and manual handling in the work environment have been developed. Two general methodologies can be distinguished:

With increasing awareness of the high prevalence and severe consequences of work-related musculoskeletal disorders, it has become obvious that successful prevention requires a better understanding of the causes and risk factors of the disorders. Moreover, actions taken in prevention should be thoroughly monitored to link a possible success to the specific preventive activity. For these reasons, more accurate and generally applicable quantitative methods of measuring exposures are needed. The most commonly used estimate of physical exposure has been obtained by job title (Burdorf et al, 1992; Winkel and Westgaard, 1992). Another instrument that has become more frequently used is quantifying specific risk factors by self-administered questionnaires. Unfortunately, the accuracy of this tool is low, according to recent studies (eg Burdorf and Laan, 1991; Wiktorin et al, 1993). The most accurate exposure data are presumably obtained by direct

(1) data collected as system states at prespecified times, ie time-sampled observations such as Posturegram (Priel, 1974), OWAS (Karhu et al, 1977), PWSI (Chen et al, 1989) and ARBAN (Holzmann, 1982); and (2) data registered in real time, ie events are recorded with their associated time as they occur. The ‘Posture and activity classification system’ (Foreman et al, 198S), ‘Postural analysis of the trunk and shoulders’ (Keyserling, 1986), ‘Ergonomic

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observation’ (Kilbom et al, 1984), the ‘Posturegram software’ (Clark et al, 1987), and VIRA (Kilbom et al, 1986) make use of the latter technique. ROTA (Ridd, 1988; Ridd et al, 1989) and TRAC (van der Beek et al, 1992) facilitate optional time sampling or continuous monitoring. Real-time observations provide information about the sequence, duration and frequency of the observed activities. Time-sampled observations only provide an estimate of this information: the higher the sampling frequency, the more accurate the time-based records obtained. The object of this study was to develop a systematic method for observation of musculoskeletal workload based on the following requirements:

(1) observations

made

in real time directly

at the

workplace; (2) data accessible for immediate analysis and presentation; (3) method applicable independently of the subject’s profession and work tasks; human resources required for data (4) moderate collection and analysis; of physical exposure (5) a compiled description obtained by combining several work tasks according to their prevalence. The PEO method is intended for collecting data on posture and manual handling in the field, and for subsequent data presentation including simple statistics and integration of data from several work tasks. In this study, the procedures of the method are reported and Table 1 Main and subcategories

its internal validity, intra- and inter-observer reliability will be described. The present investigation was carried out by a research group developing effective methods for physical load assessment in large populations. This group was part of the Stockholm MUSIC 1 Study group, which developed and evaluated methods to be recommended for large epidemiological studies. ‘MUSIC’, an acronym for ‘musculosketal intervention centre’, is a network of ten Stockholm departments, which aim at preventing musculoskeletal disorders (Hagberg et al, 1990; Hagberg and Hogstedt, 1991).

Material and methods With the PEO method, the observer continuously registers the posture and activities of a subject using a computer. The duration and number of events are calculated for four body regions as well as for manual handling. Definitions Main category denotes body region (eg neck) or activity (eg lift), and may be split into 2-5 subcategories. Main + subcategory jointly define an event. Table 1 and Figures I and 2 define the main and subcategories

of the PEO method. The PEO software computes the frequency (number of events during the recording period) for all events and duration (total time of the event) for all events except ‘Lift’ and ‘Extra event’.

included in the PEO method

Main category

Subcategory

Abbreviation

Specification

Comment

Hand (right, left)

Below shoulder level Above shoulder level Repetitive movements

RHbs, LHbs RHas, LHas RHrm. LHrm

Figure I Figure I

Right and left arms registered separately. RHas and RHbs (LHas and LHbs) mutually exclusive

Neck

Flexion >20 Rotation >45”

N20 Nr

Figure 1 Figure 2

Trunk

Flexion 20-60” Flexion >60” Rotation >45”

T20 T60 Tr

Figure 1 Figure I Figure 2

K

Kneeling or squatting

Knee

Pro-suoination. volar-dorsal wrist flexion’, radial-ulnar wrist deviation, finger flexionextension. Performed several times/min.

T20 and T60 mutually exclusive

Lift Lifting alone or together with others Subcategories mutually exclusive

l-5 kg 6-15 kg 16-45 kg >45 kg Unknown force Manual handling

Subsequently measured and entered Subcategories mutually exclusive

M l-5 kg 6-15 kg 16-45 kg >45 kg Unknown force

Subsequently measured and entered

Extra event

Ee

Observer defined

Extra time

Et

Observer defined

Complicated status

C

Above shoulder height, below knee height or with twisted back

Used together with ‘Lift’ and ‘Manual handling’

Portable ergonomic observation method

Neck flexion GO0

shoulder level

95

ing data collection with the Psion, data is transferred to a PC by using a program that also converts data to DOS format and stores it on a diskette. For both computer types, the internal clock is used to record observations in real time, to the nearest tenth of a second. Prior to observation, the magnitude of forces exerted by the subject during manual handling activities is measured by dynamometer (eg when pulling) or scales (eg when lifting). Software

shoulder level

Trunk flexion >600

Figure 1 Definition of hand position and neck and trunk flexion. The postures are used as subcategories in the PEO method (see Table 1)

Data collection. In order to facilitate operation and minimize input errors, continuous visual feedback is provided on the screen. Collection and storage of data are made directly at the workplace. Observations are made continuously in real time. When the subject turns into a posture or begins an activity according to Table 1, the observer hits the predefined keys and the software records the start time of the event. When the posture changes, or when the activity terminates, the observer again hits the same keys. This triggers the software to calculate and store the duration for this particular event. When using a PC, data entry is via a combination of the keys representing the main categories and five keys representing the subcategories. When using the Psion XP, each event is represented by a single key. Hence 15 keys are utilized with the PC, and 23 with the Psion. Several main and subcategories can be activated concurrently. The software ensures that mutually exclusive events are not active simultaneously. The data correction program is used to adjust start time, duration, weight specifications, or to delete erroneous observations. Data correction.

The data presentation program is used to view observations and derive simple descriptive statistics. Data can be presented both as text and in graphic form, and printouts can be made on any IBM graphics compatible printer. Data presentation.

Trunk/neck

rotation

>45”

Figure 2 Definition

of neck and trunk rotation. The postures are used as subcategories in the PEO method (see Table I)

Equipment

Observations can be registered on a personal computer (PC) equipped with two disk drives or a hard disk for sotfware and data storage and comparable to an IBM PC/XT/AT machine. In this study, an Olivetti Ml5 was used. It is a PC with a built-in screen, rechargeable batteries and a keyboard suitable for this application. In order to make the equipment portable, the hardware was separated and mounted on a modified rucksack. For work situations that are highly mobile or performed in limited space, a small hand-held computer may be used; the observers of the present study used a Psion Organizer II mod XP, weighing 286 g. After complet-

Weighted data presentation. Job exposure is obtained by weighting the observed task exposure data according to the duration of the tasks. The program compiles between two and eight PEO datafiles of one subject and presents an estimate of a ‘typical working week’, based on a subject interview regarding task occurrence and duration. The analyst defines the work tasks and links them with corresponding datafiles, specifying the proportion of time (percentage weekly working time) spent doing each task. Results may be presented as text and/or graphs, and printouts can be made on any IBM graphics compatible printer. System performance

In order to receive a comprehensive description of the work task including the temporal relationship between posture and activities, all categories are observed simultaneously. Alternatively, observations can be made for one main category at a time, which is assumed to increase the accuracy of the observation. The latter method was used to validate questionnaire information estimating manual handling, working postures, and

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movements in the Stockholm MUSIC I Study (Wiktorin et al, 1993). The procedure for using the PEO method is described in Table 2.

Table 3 Factors considered for evaluation inter-observer reliability Specification

Factor 5 observers 2 computer

types

Evaluation of the PEO method

Video recordings of four skilled professional workers (cook, secretary, mechanic and furniture mover) were made on location. A sagittal view with a camera-subject distance of 2-2.5 m was used, and recording of the whole body was made when possible. Each 20-30 min recording comprised several different work tasks. The cook prepared lunch, fetched food from storage and cleaned the kitchen; the secretary did VDU work, copied and filed paper; the mechanic drilled and ground material using different machines; and the furniture mover transported desks. Two scientists studied the videotapes at the laboratory and determined order and duration of events. Neck angles close to 20” and trunk angles close to 20” or 60” were measured by goniometer after pausing the video recorder. The scientists then viewed the videotapes and made PEO recordings, concentrating on one body region or activity at a time; these were subsequently used as ‘reference values’ for the observations made by five experienced physiotherapists (observers). When evaluating the PEO method, several factors were considered (Table 3). The five observers viewed the videotapes and made altogether four PEO registrations for each worker filmed, two using the Psion and the Olivetti computer after 10 h practice and another two after 100 h of practical use in the field. The observers had no previous knowledge of the work tasks recorded on the tapes. All main categories, except the left hand, were observed simultaneously. The following evaluations were then assessed: (1) internal validty, ie the observers’ observations compared with reference values; (2) inter-observer reliability, ie the observers’ registrations compared with each other; and (3) intra-observer reliability, ie registrations made by

of validity, intra- and

2 occasions 4 professions

Experienced physiotherapists Modified PC (Olivetti)/hand-held computer (Psion) 10 h training000 h practical use 4 professional workers were studied

the same observer on two occasions (separated between 2.5 and 6 months).

by

When evaluating ‘Lift’ and ‘Manual handling’, no distinction was made between the subcategories, as weight and force are not appraisable when watching a video recording. Statistical methods

Median value and range (minimum/maximum value) were used in statistical description of the internal validity of the method. Intra-observer reliability and differences between the two computer types used in the study were tested by the Wilcoxon signed ranks test, corrected for ties (Wilcoxon, 1945, 1947; Siegel and Castellan, 1988). The inter-observer reliablity was evaluated by use of the Kendall coefficient of concordance, W, corrected for ties (Siegel and Castellan, 1988; Kendall, 1970). Results Internal validity

Generally, the observers made no registrations without corresponding reference registration (Tables 4 and 5). This indicates a minimal number of errors due purely to accidental keystrokes. Observations of ‘Right hand above shoulder level’ showed the best agreement with the reference value. Durations of ‘Right hand below shoulder level’ were close to the reference values, while the frequency was underestimated for three of the four professions. ‘Right hand repetitive movements’ were

Table 2 Methodology of the PEO method. Note that all the software is gathered in one module Step 1 Interview

the subject

2 Plan the observation 3 Make priority list

4 Measure

forces

day(s)

exerted

5 Make PEO registrations 6 If a hand-held computer is used, data is transferred to a PC 7 View data after each work task observation 8 If necessary: correct erroneous data 9 (Optional) View/print data on each work task 10 Gather all files on a diskette or hard disk 11 Weighted data

Method and equipment

Outcome

Personal

Number and scope of work tasks, and their share of the work time Ensuring that all work tasks are observed Ensuring the main categories most indispensable according to the purpose of the investigation are registered correctly Permits observer to categorize subsequently observed manual handling and lift Obtaining data Data transferred to PC and converted to DOS format Data check

Obtain

contact permits

Dynamometer,

or telephone from supervisors

etc

scales

Data Data

collection software transfer software

Data

presentation

software

Data correction software Data presentation software

Weighted

data presentation

Data correction Simple statistics

software

Estimate week

of the data as text or graphics

of the physical

load during

a typical

Portable ergonomic observation method

The

generally underestimated. The observers tended to overestimate mild trunk flexion (20-60”). The results from the subjects who did deep trunk flexion (>60”) were not conclusive. As trunk rotation occurred only occasionally, no evaluation of its validity could be performed. Duration of neck flexion (>20“) was vastly overestimated, while the frequency was underestimated. Neck rotation occurred only rarely, but on the whole it seemed to be underestimated. In general, the frequency of events was underestimated. However, the frequency of lift was overestimated for all professions and the frequency of manual handling was overestimated for three out of four professions.

97

agreement

between

the observers was high was significant for both types, and on both occasions.

(Table 6)) and the concordance

computer

Discussion Selection ofparameters The categories included in the PEO method have been selected according to risk factors described in the literature. Based on real-time observations, the PEO method provides information about sequence, duration and frequency of exposure categories selected as important risk factors. Static work, characterized by long duration in the same posture, can be estimated via the PEO method. Quantification of static work is important, as it may cause chronic pain, especially when performed frequently and with long duration (Grandjean and Hunting, 1977). The main categories included represent selected regions of the human body, known for high prevalence and incidence of workrelated musculoskeletal disorders. Work including elevation of an arm more than 60” (approximately corresponding to ‘hand over shoulder

Reliability

Registrations of task duration did not differ significantly between the first and second occasion, but observations of task frequency were higher (for the Olivetti by 7% and for the Psion by 27%) on the first occasion than on the second. Observations registered with the Olivetti computer were slightly lower (about 3%) than the corresponding observations made with the Pison computer on the first, but not the second occasion.

Table 4 Frequency of events (= number of events) d&g the recording periods. Median value, range (min-max (maximum = 20) for the five observers compared with reference values (ref) Furniture

Cook Ref

Observers

mover

Ref

Observers

value) and number of observations

Secretary

Mechanic

Ref

Ref

Observers

Observers

Right hand Below shoulder height Above shoulder height Repetitive movements

31 7 33

15.5 (4-38); 20 5 (1-13); 20 1 (O-16); 20

23 7 0

10.5 (10-11); 4 4.5 (3-6); 4 0(@-0);4

7 3 4

10 (S-24); 20 4.5 (2-14); 20 6.5 (O-26); 20

32 20 10

24.5 (15~); 20 17.5 (W-33); 20 0 (&3); 20

Trunk Flexion 20-60” Flexion >60” Rotation

38 8 1

51.5 (2683); 20 14 (5-30); 20 0 (o-4); 20

15 13 0

21 (O-26); 9 13 (2-17); 9 O(O-1);9

0 0 0

6 (l-11); 19 0 (O-2); 19 0 (O-l); 19

12 0 0

6 (l-11); 19 0 (O-4); 20 0 (O-O); 20

Neck Flexion >20 Rotation

16 11

18.5 (8-23); 4 3 (l-10); 4

24 0

11.5 (4-24); 16 0 (O-2); 16

25 5

7.5 (l-16); 14 0 (O-l); 14

Lift

10

18 (3-29); 20

19

37 (S-47);

19

8

22 (l-28);

19

0

6 (5-8); 8

Manual handling

14

18.5 (8-36); 20

25

27 (16-47);

19

0

1 (l-7);

10

0

22 (3-37); 14

No obs. No obs.

Table 5 Duration (% observed time) of events during the recording periods. Median value, range (min-max (maximum = 20) for the five observers compared with reference values (ref) Cook

Furniture

remover

Secretary

Mechanic

Ref

Ref

Ref

Observers

Ref

Right hand Below shoulder height Above shoulder height Repetitive movements

82 1 34

93.5 (84-100); 20 1 (O-q;20 0 (O-18); 20

80 2 0

90.5 (85-92); 4 2 (14); 4 0(9-0);4

98 2;

93 (76-96); 19 4 (l-8); 20 22 (O-39); 20

71 18 4

69 (64-76); 20 20 (17-22); 20 0 (O-2); 20

Trunk Flexion 20-60” Flexion >60” Rotation

17 1 0

29 (21-38); 20 3 (l-13); 20 0 (O-S);20

13 13 0

17 (C25); 9 6 (O-15); 9 0(0-0);9

0 0 0

2 (O-7); 19 0 (O-l); 19 0 (O-O); 19

3 0 0

5 (3-27); 20 0 (O-2); 20 0 (&14); 20

43 0

84 (55-97); 16 0 (O-6); 16

49 0

94 (64-100); 14 0 (O-O); 14

Neck Flexion >20” Rotation Manual handling

7 7 27

75.5 (69-96); 4 O(O-2);4 11.5 (3-40); 20

2 0 28

Observers

value) and number of observations

No obs.

No obs. 28 (12-42);

19

0

Observers

0 (O-2); 9

0

Observers

17 (3-25);

14

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Fransson-Hall et al

Table 6 Agreement between observers, coefficient of concordance, W Computer

Olivetti Psion

type

calculated by Kendall

Occasion

Duration

Frequency

First Second First Second

0.765 0.897 0.902 0.865

0.750 0.671 0.790 0.858

height’) has been associated with acute shoulder pain (Bjelle et al, 1981). Accordingly, Herberts et al (1981) report work with elevated arms to be a risk factor. Repetitive hand movements have been associated with an increased risk of cumulative trauma disorders of the hand and arm (Armstrong et al, 1986; Silverstein et al, 1987). Laboratory studies and biomechanical simulations show that deviation from upright standing posture implies elevated loads on the lumbar spine (Lindh, 1989). Also, epidemiological studies have shown that non-neutral postures and movements are significantly related to the risk of low-back pain (Anderson, 1981; Keyserling et al, 1988; Riihimgki et al, 1989; Videman et al, 1989). Using four trunk-posture categories Punnett et al (1991) found an increased risk for back disorders according to both level and duration of exposure. Hunting et al (1981) reported work including neck flexion to be associated with an increased risk for injuries. Also, Kilbom et al (1986) found a strong positive relationship between disorders and VIRA registrations of forward neck flexion (>20”). Work including kneeling has been reported as a risk factor for knee trauma (Kivimaki et al, 1992; Thun et al, 1987). Force level, frequency and duration have all been identified as risk factors for overexertion injuries during manual handling (Chaffin and Park, 1973; Snook, 1978; Technical Contracts Reports NTIS, 1992). All observation methods involve two (usually contradictory) qualities: generality and accuracy. High generality in an observation method is usually compensated by lower accuracy. One example is OWAS (Karhu et al, 1977), a combination of four codenumbers representing back, arms, legs and weight load. OWAS can be used for all professions, but yields results low in detail. A method with high accuracy is, on the other hand, usually limited according to the number of observed postures or body regions, and often requires a restriction of the subject’s range of movement. An example is VIRA (Kilbom et al, 1986), which gives a detailed description of two body regions (neck and shoulder), but is restricted to stationary work. In order to resolve these contradictory demands, the PEO method can be used in two ways. To approximate the whole-body exposure to physical load, all main categories are observed simultaneously, but if higher accuracy is required only one category at a time is observed. This latter application has not yet been evaluated, but it can be expected that the internal validity is significantly higher compared with simultaneous observation of all categories. Evaluation of the PEO method When evaluating the PEO method, video recordings of authentic work situations were used. As the work was

not manipulated or pre-arranged, some categories rarely occurred, for instance neck and trunk rotation. Obviously, no conclusion can be drawn about validity and reliability of these categories. Internal validity. Generally, observations of duration showed higher internal validity than observations of frequency. Observations of work with hand above shoulder height had the highest internal validity. Also, observations of duration of work with hand below shoulder height could be done with minor errors. However, observations of repetitive hand movements generally showed large deviations from the reference values. This may be due to difficulties in creating a clear-cut definition of repetiveness. Generally, the duration of neck and trunk flexion was overestimated. As the accuracy of estimating neck and trunk flexion under optimal viewing conditions is about 5” (Ericson et al, 1991), a measurement error is introduced for movements in the critical range around the borderline of flexion (Burdorf et al, 1992). The same complex of problems has been described for observations of the shoulder (Keyserling, 1986). Our relatively low validity of trunk flexion observations, as compared with those reported by Burdorf et al (1992) and Nordin et al (1984), may be explained by different evaluation conditions. With the PEO method, several exposure categories are simultaneously observed and registered, while the observers in the other two studies could concentrate solely on observing the trunk angle. For the furniture mover, whose job included manual handling of heavy and large objects, registrations of manual handling were congruent with the reference value. The cook and the mechanic, however, handled small objects requiring less force. This may explain the low congruence with the reference value, as manual handling with a force below 10 N is not registered with the PEO method and it is impossible to estimate the applied force or weight of an object via videotape. This type of error is avoided when observations are made directly at the workplace, as the force may be measured using scales or a dynamometer. Reliability. Registrations of task duration made after 10 h training did not differ from registrations made after using the method in the field over several months. The higher number of task frequency registrations on the first occasion probably reflects an unfamiliarity among the observers with the position of the keys. If an erroneous key is hit, and the mistake is immediately corrected, the duration would be almost correct while the frequency (ie the number of keystrokes) would be too high. This type of error was, however, not found on the second occasion, indicating that data registration was improved by practice and experience. The registrations differed slightly between the computer types on the first, but not the second occasion. This indicates that any of the computer types may be used, according to the preference of the observer. The agreement between the five observers was high, which may be interpreted as meaning that the five observers were applying essentially the same standard. Generally, the concordance was slightly higher for registrations of duration than for frequency.

Portable ergonomic observation method

Evaluation methodology. Our evaluation method may be questioned. In an authentic situation, the observer obtains information about the work tasks before starting recording. During our evaluation, however, the observers were not allowed to look at the videotapes before observing, in order to avoid a training effect. This made registering more difficult. Foreman et al (1988) noted similar effects, and argue that observations made in the field overcome some of the problems associated with observations based on videotapes. The problem of observing threedimensional events via two-dimensional media has also been discussed by Keyserling (1986), who asserts that this influences the observers’ interpretation of posture. However, Ericson et al (1991) found no difference in accuracy between direct observations of trunk and neck angle compared with observations made from coresponding videotapes. Sources of error when using the PEO method

Thorough instruction and practice contribute to avoiding observer mistakes, eg hitting the wrong key or omitting deactivation when an activity stops. Estimation of neck and trunk flexion is easier when the subject wears tight-fitting clothes. A fast work rate may imply incorrect observations; van der Beek et al (1992) suggest that dynamic movements are an important source of disagreement between observers. This can be avoided through reducing the number of simultaneously observed categories, by (1) observing each work task several times, registering only a limited number of categories each time; (2) dividing the categories between two or more simultaneously registering observers; or (3) video filming the work for subsequent analysis, where the video is replayed several times and a limited number of categories is registered each time. The weighted data presentation is based on subject interviews. Determination of task occurrence and duration through questionnaire or interview may be easier to assess than direct exposure to body parts, eg duration of trunk inclination (Wiktorin et al, 1993, 1995). However, task occurrence and duration may vary between weeks or seasons (eg the work of a farmer). Practical experiences from using the PEO method in a field study The PEO method has been used to observe 97 subjects in 45 different occupations, and these results are presented separately (Karlqvist et al, 1994). Five experienced physiotherapists made PEO observations with the adjusted PC (80 subjects) and the hand-held computer (17 subjects). Findings from this field experience of the PEO are as follows.

(1) It

is crucial to interview the subject carefully to define and separate the work tasks. To obtain a true image of the work, each task has to be studied, preferably using several observations. (2) If the work pace is rapid and/or if several body regions are engaged simultaneously, only between

99

one and three main categories can be observed at the same time. Therefore, a priority list should be made, ensuring that the main categories most important for the purpose of the investigation are registered with a minimum of error. Alternatively, several observers, each registering different categories, may be used to affirm accurate observation of all categories. The maximal recommended time for PEO observa(3) tions in the field is 20-30 min at a time; it is our experience that the musculoskeletal workload of most work tasks can be captured within such a period. (4) It is difficult to register the right and left hands separately unless the observed work is slow and sedentary. (5) When used for several hours, the PC equipment was perceived as heavy and occasionally too large and bulky. The hand-held computer was considered to be sufficiently light in weight, easy to handle and to provide sufficient feedback; its disadvantage was that data had to be transferred to a PC after each data collection period. Further improvement

of the PEO method

The following areas would benefit from improvement:

(1) PEO

data available in ASCII format (event + start time + duration) for individualized data analysis (this feature is available now); (2) the main category ‘Lift’ is not necessary; instead only ‘Manual handling’ could be used. Often events starting out as a left subsequently turned into some other kind of manual handling, eg carrying; (3) software additions enabling the user to define the keys characterizing each main and subcategories; (4) software additions enabling the user to define current main categories (main categories not used will not distract the observer, and hitting a ‘deactivated key’ by mistake will not lead to any observation); (5) optional auditory feedback; (6) better definition of repetitive work.

Conclusions It is believed that the PEO method meets the requirements identified at the start of the paper; observations at the workplace give immediately accessible data for a wide range of professions and work tasks either individually or combined, and using only moderate resources. Additionally: The inter-observer reliability of the PEO method is high. Generally, observations of task duration showed higher internal validity than observations of task frequency. Within the same observer, no difference was seen between observations of task duration made on two separate occasions. This suggests that the PEO method is useful both for estimating differences (eg effects of intervention) and for comparing the exposure between subjects, provided the same observer makes all observations.

Fransson-Hall et al

loo l

l

Practical experience emphasizes the importance of a careful interview of the subject before observing the work. A priority list should be made, to ensure that the most important categories (according to the purpose of the investigation) are registered with a minimum of error even if the work tempo is fast.

Acknowledgements The authors would like to thank Agneta Willars, Elisabeth Melin and Kristina Selin for their skilful and devoted work with the PEO method, and Dr ClasHakan Nygird for valuable work with the evaluation of the PEO method. This work was partly supported by the Swedish Work Environment Fund.

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