الکترومیوگرافی به عنوان یک معیار سنجش از حجم کار اوج فعالیت ومجموعه ای ازمراقبت های حدواسط و ارتباط آن با آسیب های اسکلتی عضلانی: مطالعه اکتشافی ارگونومیک
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7352||2005||10 صفحه PDF||سفارش دهید||7009 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Applied Ergonomics, Volume 36, Issue 5, September 2005, Pages 609–618
Injury rates in Intermediate Care (IC) facilities are high and the factors related to these injuries are unclear. The objectives of this exploratory sub-study, which is part of a large multi-faceted study in 8 IC facilities are to: (1) evaluate EMG measured over a full-shift in the back and shoulders of 32 care aides (CAs) as an indicator of peak and cumulative workload (n=4×8n=4×8 facilities); investigate the relationship between EMG measures and injury indicators; and explore the relationship between EMG measures and other workload measurements. Lumbar EMG was converted to predicted cumulative spinal compression and ranged in CAs from 11.7 to 22.8 MN s with a mean of 16.4 MN s. Average compression was significantly different during different periods of the day (p<0.001)(p<0.001) with highest compression during pre-breakfast when CAs assist most with activities of daily living. Significant differences were found in average compression between low and high injury facilities for 3 of 5 periods of the day (p<0.010)(p<0.010). Peak compressions exceeding 3400 N occurred for very little of the workday (e.g. 11.25 s during the 75 min period pre-breakfast). Peak neck/shoulder muscle activity is low (99% APDF ranged from 8.33% to 28% MVC). Peak and cumulative spinal compression were significantly correlated with lost-time and musculoskeletal injury rates as well as with total tasks observed in the CAs (p<0.01)(p<0.01). Perceived exertion was only correlated with peak compressions (p<0.01)(p<0.01). Facilities with low injury rates provided significantly more CAs (p<0.01)(p<0.01) to meet resident needs, and subsequently CAs performed fewer tasks, resulting in less peak and cumulative spinal loading over the day.
According to the British Columbia Workers’ Compensation Board, injury rates for workers in health care are higher than those in any other industry in BC (Workers’ Compensation Board of British Columbia, 2000). Average injury rates among staff in Intermediate Care (IC) facilities in British Columbia are among the highest, ranging from 9.6 to 10.5 claims per 100 person years for the period of 1995–1999. This injury rate is approximately 50% higher than in BC's acute care sector and slightly higher than in long-term care as a whole (Workers’ Compensation Board of British Columbia, 2000). The majority of the injuries are musculoskeletal in nature, occurring especially to the back, shoulder and neck. IC facilities provide 24-h nursing care for individuals who can no longer live safely in their homes. Residents in IC are generally mobile, however they have varying degrees of intermittent dementia, resulting in high and changeable needs related to activities of daily living such as toileting, dressing, and eating (Cohen et al., 2003). Unlike Extended Care where Care Aide (CA) injuries are associated with frequent manual lifting, transferring and repositioning of residents, it is unclear in IC the factors contributing to such high injury rates. A large multi-method, multi-disciplinary study was conducted over 2.5 years in eight IC facilities to investigate the factors associated with injuries in order to determine strategies for prevention of such injuries. Four areas were investigated, including: organizational culture and climate; safety environment; physical environment; and workload. The main study design and effects of the organizational culture and climate on injury rates are presented elsewhere (Yassi et al., 2004). Results of various workload measures compared with injury rates are also presented elsewhere (Cohen et al., 2004). This study will present results of an exploratory ergonomic sub-study investigating the use of full shift electromyography (EMG) measures as an indicator of peak and cumulative workload. It will then compare the EMG measures with other measures of workload, as well as with rates of loss-time and musculoskeletal injury in IC. Workload may be thought of by CAs in several ways. The staffing level or number of residents per CA is an important workload construct and there is evidence that high staffing ratios are linked to improved resident outcomes, increased job satisfaction and higher retention rates (Feuerberg, 2000), as well as fewer injuries (Cohen et al., 2004). Yet, staffing levels do not describe fully the workload construct because workload also depends upon the acuity or demands of the residents. Those with higher levels of dementia require more time and assistance with activities of daily living, and thus more workload. To this end, Directors of Care will assign staff to units based not only on the number of residents, but also their acuity such that some designated dementia units have twice the staffing ratio, but not necessarily less workload. Workload can also be thought of in production terms, such as the number of tasks performed by CAs in the day. This is a function of how the facility organizes its workload among staff, for example whether CAs are required to also make beds, fold laundry, serve meals and bathe residents (some facilities have designated Bath Aides). Environmental factors can contribute to workload for CAs including the age and design of the facility, especially the size of resident rooms and bath rooms, and lengths of hallways. In some facilities, bathrooms are too small for mechanical lift equipment or 2-person lifting and all assistance is provided by single person manual lifts and transfers. It is expected that CAs who work in facilities with low staffing ratios and with residents of higher acuity, and who perform other tasks, often in tight spaces will have more awkward bending and lifting postures and therefore more peak and cumulative loading of the spine and shoulders. Few ergonomic studies in health care have investigated peak and cumulative spinal or shoulder loading, especially over an entire shift. Most studies measure very specific aspects of workload, such as the postures, loads and forces on the spine when performing patient lifts and transfers (Daynard et al., 2001; Engels et al., 1994; Winkelmolen et al., 1994). Often such studies report considerable peak loads on the lumbar spine of CAs while performing these tasks (Daynard et al., 2001). While there is ample evidence that peak loads contribute to low back pain and injury (Norman et al., 1998; Punnett et al., 1991; Marras et al., 1993), there is growing evidence that cumulative compressive load is also associated with back pain and disorders (Kumar, 1990; Norman et al., 1998; Seidler et al., 2001). Choosing methods for the measurement of workload in IC facilities is challenging. Observational techniques, supported by the use of videotaped recordings for further computer modeling analysis have been used extensively for peak and cumulative loading (Norman et al., 1998; Punnett et al., 1991; Daynard et al., 2001). However, in most of these studies the tasks were repetitive, or certain tasks were selected, and all occurred at a single workstation allowing for proper videotaping technique. In IC, the tasks are non-repetitive and varied and CAs move quickly from room to room making the set-up of videotape prohibitive. In addition, there are issues of privacy when residents are dressing and toileting that hinder observation, and difficulties obtaining informed consent with residents suffering dementia. Self-report measures of workload where workers respond to questions in self-administered questionnaires, diaries or interviews are also a popular technique (Burdolf and van der Beek, 1999; Wells et al., 1997; van der Beek and Frings-Fresen, 1998). While they have the advantage of being inexpensive to administer and allow for a wide variety of risk factors to be investigated, they often do not give reliable information on either the nature of the exposure, or the magnitude (Wiktorin et al., 1993). Direct measurement of tissue loads is generally preferred as it is thought to be objective, although it is more costly and time-consuming (Burdolf and van der Beek, 1999; Wells et al., 1997). Wells et al. (1997) advocate using lumbar compression as a common metric across measurement methods. They argue that it encompasses many risk factors including non-neutral trunk postures and heavy lifting, and is linearly related to trunk moment shown by Marras et al. (1993) to be a strong risk factor for back injury. Studies by Mientjes et al. (1999) and Wells et al. (1994) suggest an EMG-based method for continuous long-term monitoring of low back physical exposures and estimating cumulative compression. Potvin et al. (1990) showed that a linear normalization of erector spinae EMG to spine compressive force (called compression-normalized EMG or CNEMG) could be used to predict spinal compression in N while workers performed lifting tasks. CNEMG was presented as an amplitude probability distribution function allowing identification of peak compressions and percentage of time above specific levels of loading. The authors reported the advantages in this technique of not having subjects perform maximal voluntary back extension efforts, and the ability to compare loading with proposed load limits (Potvin et al., 1990). Mientjes et al. (1999) reported that the CNEMG method of estimating spinal compression compared favorably with biomechanical models (2D Watbak, Norman et al., 1998) of spinal compression utilizing videotaped posture and measured loads. In short-duration tasks, they found typical differences between techniques of 14% with CNEMG consistently higher when compression is greater than 1068 N. The CNEMG technique was not as accurate (30% differences) when axial twisting moments dominated the task. The authors concluded that the method is an accurate tool for assessing exposure to low back injury risk and is acceptable for field use since industrial tasks with pure axial twisting moments that contain no sagittal extensor moment are uncommon (Mientjes et al., 1999). The objectives of this exploratory sub-study in eight IC facilities are to evaluate EMG measured over a full-shift in the back and shoulders of CAs as an indicator of peak and cumulative workload and to investigate how the cumulative loading varies throughout the day. A second objective is to investigate the relationship between EMG measures and injury indicators. Thirdly, this study will explore the relationship between EMG measures and other workload measurements.
نتیجه گیری انگلیسی
EMG measures taken with a portable self-contained data collection unit are an effective method of obtaining direct indications of tissue loading in a complex environment characterized by high task variability, considerable movement of subjects, and where direct observation and video recording is prohibitive due to the subjects and tasks performed. The EMG measures can be normalized to spinal compression, which Wells et al. (1997) suggest as a common metric for investigating risk of back injury. Further, both peak and cumulative compression can be compared with data and guidelines in the literature. Levels of cumulative compression measured with EMG for a 7-h period among 32 CAs averaged 16.4 MN s, with individual CAs ranging up to 28.95 MN s. Norman et al. (1998) calculated cumulative compression on more than 250 workers in the automotive industry over a 2 year period with observations ranging from 2 to 8 h during normal work (104 cases and 130 controls) and representing more than 1175 assembly and assembly support (e.g. maintenance) tasks. All workers were videotaped and a trained observer identified all occurrences of “substantial” spinal load by estimating the instants of high spinal moments resulting from forward inclined trunk postures and/or high forces on the hands. These postures were then analyzed by a computerized biomechanical model to determine peak spinal loads. Cumulative load for each task was calculated based on the peak load for the task and the duration of exposure. Norman et al. (1998) developed a “low back pain index” suggesting from their data the percent of workers who are likely to report back pain at a given level of cumulative loading. From their data, a cumulative compression of 23 MN s corresponds with 50% of workers likely reporting low back pain. Comparing the low back pain index with cumulative compression collected for CAs in this study suggests their likelihood of reporting low back pain ranges from 26% to 63%, with a mean of 38%. This must be viewed with caution however as the data are from different populations of workers and cumulative compression is obtained with different methods. Kumar (1990) also estimated cumulative compression in a study of 161 institutional CAs (14 males, 147 females) with and without back pain using a structured questionnaire/interview in a retrospective study. Spinal loading estimates were obtained by using recall, line drawings and/or a manikin model to obtain estimates of working postures and then analyzing these postures with a two dimensional biomechanical model. Cumulative compressive and shear loads were then estimated based on estimates of task duration and frequency. The pain groups had significantly greater average estimates of cumulative spinal compression (males=15.6 MN s, females=14.5 MN s) than the no pain groups (males=6.6 MN s, females=9.3 MN s). Even though the recall approach is very different from EMG measures normalized to compression, the levels of cumulative compression over the day were quite similar to the average of 16.4 MN s in this study. Seidler et al. (2001) used a modification of the Kumar (1990) approach to evaluate cumulative occupational exposure of the lumbar spine to lifting, carrying and working postures with extreme forward bending. A case control study was conducted between 229 male patients with symptomatic osteochondrosis or spondylosis of the lumbar spine and 197 control subjects. Self-reported estimates of occupational lifting, flexion and duration were collected and a lifetime cumulative dose calculated. Seidler et al., found that working postures with extreme forward bending for up to 1500 h (calculated over all working years) was associated with the diagnosis of osteochondrosis or spondylosis (OR 2) and the odds ratio increased to 4.3 for more than 1500 h exposure. Combined exposures to lifting or carrying with working postures with extreme forward bending yielded odds ratios of 16:1. This is one of the first studies to use cumulative risk factor exposure as an independent variable. The authors suggest that the pathogenic concept of chronic increases in intervetebral pressure has long been considered an important cause of lumbar spinal disease, yet it has been difficult to quantify. All these studies have evaluated cumulative loading over occupational exposures. Since compressive loading does not end with the work day, the next goal in research may be to develop ways of measuring the non-occupational component of cumulative compression. Further, it would be useful to validate Kumar's and Seidler's interview-based methods with direct measurements to enable future investigators to use simpler, less expensive methods and thus collect data from larger numbers of workers than was possible in this study. EMG normalized to percent above standing compression was useful in this study for indicating differences in workload among different periods of the day. Mean compression in CAs averaged over 200% of standing compression during pre-breakfast and was not significantly different between facilities with high and low injury rates. CAs confirm that the morning period is the heaviest workload of the day and even facilities with low injury rates experience this heavy period. These results point to the importance of designing solutions to reduce workload during this period, such as overlapping shifts such that staffing is increased during this period, or reducing some of the tasks performed by allowing residents to breakfast at two sittings, or for some residents to breakfast in bed. The relationship between tasks performed and cumulative loading supports these recommendations. Few instances of peak compression above the 3400 N guidelines (Waters et al., 1994) were experienced by CAs in IC. During an average of 75 min pre-breakfast, compression exceeding 3400 N is experienced for an average of 11.5 s. Other periods of the day have even less peak compressions. Yet, peak compression was significantly correlated to injury rates, MSI rates, numbers of tasks performed in the day and perceived exertion in the day. It appears that even though the time spent in peak exertions is small, the perception of workload is highly influenced by these exertions. Norman et al. (1998) found strong correlations within the peak spinal loading variables and within the cumulative loading variables, but poor correlation between the two. They suggested that peak and cumulative loading are measuring different aspects of risk for these jobs. Peak and cumulative compression measured among CAs in this study were highly correlated with each other, but were independently correlated with different variables supporting Norman et al.'s assertion that both are important. Workload perceptions from the telephone survey, such as workload pressure, feeling you are working too hard and ratings of physical demands of the job did not correlate with any of the injury variables as reported by Cohen et al. (2004), nor did they correlate in this study with peak or cumulative lumbar EMG. However, Cohen et al. (2004) found these variables had some association with pain, burnout and self-reported health. In this study, peak neck/shoulder EMG had some association with workload pressure and feeling you are working too hard. Since none of these relationships can be thought of as causative, it is interesting to speculate about the connections between perceptions of burnout, pressure and poor health and tension experienced in the neck/shoulder. This relationship warrants further study. Cohen et al. (2004) compared the various workload variables and reported that most correlated with time-loss injury and MSI, including staffing ratio, resident-dependency to worker ratio and observed number of tasks performed. The average resident dependency was not significantly different between high and low injury rate facilities, but the staffing ratio and the resident-dependency to worker ratio were significantly different (p<0.01p<0.01, Cohen et al., 2004). It therefore appears that facilities with low injury rates have the same mixture of resident acuity, but they provide more staff to meet the resident demands. Observed tasks were also significantly correlated with staffing level and resident-dependency to worker ratio (Cohen et al., 2004). Facilities with low injury rates therefore require CAs to perform fewer tasks such as bed-making and bathing resulting in significantly less compressive loading during certain portions of the work day. The main limitation of this study is the small sample size for EMG measures within each of the eight facilities (n=4)(n=4) and the small number of facilities. Large standard deviations were found in measures such as cumulative compression and observed tasks between CAs within the same facility working with the same residents. It cannot be suggested that the four subjects are representative of the entire CA population for the facility. Yet, some of the variation between CAs was determined in interviews and focus groups to be due to lack of clear policies and philosophies of care regarding tasks performed such as manual transfers (Yassi et al., 2004). Correlations can result in overestimation of relationships (increased risk of type 1 errors), and this may be the case in this study. It is therefore being treated as an exploratory study designed to elicit potential interventions that can be tested in a more robust design. Significant differences were not seen in EMG measures between the four facilities with high injury rates compared with low injury rates, possibly due to the limited number of facilities (4 of each). Also, while there was a four-fold difference in injury rates between the highest and lowest injury-rate facility (A compared with H), there was little difference in rates between facility D and E (20.6 compared with 24.8 injuries per 100 person years). It would be beneficial to replicate this project with a larger number of facilities and CAs such that multi-variate analyses could be used to delineate the most important variables related to injury risk.