This study therefore will focus on determine the factors affecting the appropriateness of MDs’ use in ICU from nurses’ perception Appropriateness of medical devices’ use is a growing concern to health professionals due to the fact that medical devices become unseparated part of the healthcare providing cycle [1- 4]. New technology of medical devices (MDs) are described as complex and sophisticated [5- 8]; [4].MDs are used in a complex sophisticated environment such as intensive care unit (ICU) [9]. They need a special and concentrated observations to assure the proper uses of such devices in order to provide safe, effective, and high quality healthcare services [10]; [6]. MDs are responsible of a huge portion of medical errors mainly caused by the interaction between the user and the MDs, which has been identify in the literature as human factors related MDs errors [5] [11; 12]. A medical device can be used safely and effectively only if the interaction between the operating environment, user capabilities, stress level and device design [13]. Assessment of the medical device in the healthcare context especially from nurses’ point of view could help to support and guide decisions regarding MDs’ appropriate of use, safety, regulations, procurements, etc [1]; [14- 15]. Several studies have indicated the importance of on-going assessment as an integral part of the MDs development process [15 -19]. Furthermore, nurses’ perception in assessing the appropriateness of MDs use is essential since they are considered the primary users of MDs in direct patient care [10]; [20- 22]. Several studies that focus on the users especially in ICU, have concluded that adequate competent, knowledge, skill, and training on device management and use are essential to foster safe and appropriate use of MDs [1]; [23-27];[8]; [28- 30]. Other studies highlighted the medical errors related devices design which includes poor equipment design, confusing, poorly written, or disregarded warning labels, and complex and long equipment manuals (WHO, 2010; [31] They also include size, misleading indicators, confusing software features; and physical layout of equipment [32]; [7]. However, when it comes to the effect of the environment on MDs operations, a number of studies found that physical environment; noise, light, space, etc, impedes ICU nurses performance contributing to medical errors and impact bedside care giving which may lead to occupational stress to nurses and in turn promote higher levels of burnout among them [1]; [33-36]; [22]; [37- 41]. At Riyadh General Hospitals. It aims to answer the main question: What is the appropriate usage of MDs in ICU based on nurses’ perception? This general study question broke down into two specific study questions:

RQ1: What are the factors that may influence appropriate of MDs’ use?

RQ2: Highlight human factors related to MDs errors?

Inappropriate use or error related to MDs can cause serious problems to patients and public health in general, including incorrect or delayed diagnosis and treatment or patient injuries [42-44]. When an inappropriate use or errors involving MDs happen repeatedly, people usually put the blame on the users, mostly healthcare professionals, overlooking the MDs involvement, which can be the main reason due to the effects of human factors related to MDs [5]; [11; 12]. In health care, the objective of human factors is to improve human performance with medical products, including MDs [45- 48], and to reduce the likelihood of inappropriate use or errors, thus improving patient and workplace safety. Assessment of the medical device in the healthcare context especially from nurses’ point of view could help to support and guide decisions regarding MDs’ appropriate of use, safety, regulations, procurements, etc [1; 14; 15].

A descriptive quantitative study design was used to conduct this study to identify the ICU nurses’ perception regarding the appropriate use of MDs. The study will cover four general hospitals in Riyadh City including King Fahad Medical City, King Khaled University Hospital, Security Forces Hospital, and Riyadh National Hospital. Ethical approval has been obtained from institutional Review Board, Security Forces Hospital Program, Riyadh, in 3 February 2019, NO. 19-344-42. Convenient sampling will be applied to ICU departments in the mentioned hospitals by using a structured questionnaire for data collection. It was carried out during the period of January – April 2016. The questionnaire was provided to ICU Nurses during their work shifts (day/night). The questionnaire, consisting of 29 questions, was developed and pilot tested with 15 ICU nurses. The structure of the questionnaire aimed to provide information on (1) ICU Nurses’ socio-demographic characteristics, (2) their perception to MDs appropriate use in regard of user, devices, and environment perspectives. The researcher calculated Pearson Correlation for recognizing internal consistency validity of the questionnaire, Face Validity was confirmed after the field application of the study tool was applied on the sample data, in terms that Correlation Coefficient among study axes and study tool total degree is calculated; Pearson Correlation was (0.872) for the first axe, (0882) for the second axe and (0.813) for the third axe. it appears that these coefficients has significant at level of (0.01), indicating the high rates of internal consistency coefficient and the high level of validity and reliability enough to apply the current study. The reliability was test using Cronbach's alpha reliability coefficient. Total value of Reliability coefficient (Alpha) was (0.909) indicating the high reliability degree, as study tool reliability coefficient was as follows (0.789 ? 0.908 ? 0.789), indicating the high level of Reliability Coefficients enough to apply the current study. Furthermore, to achieve the aim of this study and analyze collected data, the researcher used several related statistical methods using Statistical Package for Social Sciences (SPSS) version (21). Statistical measurements includes; Frequencies, Percentages, Pearson Correlation, Cronbach's Alpha, Means, Standard Deviation and Independent Sample T-Test.

It appears very clearly as shown in table 1 that the majority of study individuals are females by an average of (69.1%), meanwhile (30.9%) of the study sample individuals are males. In terms of Age variable, the majority of study individuals aged (30 years old or more) by an average of (60.0%). According to academic qualification variable, the majority has bachelor degree or less by an average of (89.1%), while (10%) of study individuals have postgraduate qualification. In addition to the above, and with respect to the years of experience, there are (65.5%) of the study members their experience are (less than 10 years), while there are (34.5%) their experience is (10years and more), and there are (27.3%) their experience ranges from (5-9 years), As for the usual periods of work variable, the largest percentage of the study members (80.0%) are working at day period, while there are (20.0%) are working at night period. Regarding to the training on of medical devices usage, the bulk of the study members (90.0%) have received training to use those devices, while there are (10.0%) of the study members did not receive any training to use those devices.

Table 1: Shows demographic characteristics of Study Individuals.

The results relating to the study questionnaire

First question: what are the factors that may influence appropriate of MDs errors? To recognize the factors which influence on the standard deviation for answers of the study members have been done. These dimensions were ranged according to its arithmetic average.

Table 2: The influential factors in the appropriate usage of MD.

Factors Related to the Device

The above table illustrates that the general arithmetic average of the axis is (3.40 ± 0.38), and this shows that there are neutral between approval and rejection among the study members on the influential factors in the appropriate usage of medical devices related to the device, and the most prominent of these factors: (Each MDs Has Its Unique Alarm Of Notification With A Mean Of (3.65 ± 0.64), In ICU, MDs Are Located Where They Are Supposed To Be With A Mean Of (3.60 ± 0.74), I understand all the steps required for device setup With A Mean Of (3.56 ± 0.71), It is easy to move MDs from one place to another when needed With A Mean Of (3.53 ± 0.60).

Table 3: The Arithmetic average and standard deviation of the study members’ responses about the influential factors in the appropriate usage of medical devices.

Factors Related To The user

Table 4: The Arithmetic average and standard deviation of the study members’ responses about the influential factors in the appropriate usage of medical devices related to the user.

The above table illustrates that the general arithmetic average of the axis is (3.43 ± 0.56), and this shows that there are neutral between approval and rejection among the study members on the influential factors in the appropriate usage of medical devices related to the user, and the most prominent of these factors: (I Know How To Fix (Plug/Unplug) MDs Accessories With A Mean Of (3.69 ± 0.63), I Use My Previous Experience On Handling MDs With A Mean Of (3.51 ± 0.69), I Am Aware Of Medical Errors That May Result From MDs With A Mean Of (3.49 ± 0.63), I Have Enough Knowledge In Interpreting MDs Results With A Mean Of (3.44 ± 0.71). 

Factors Related To The work environment

Table 5: The Arithmetic average and standard deviation of the study members’ responses about the influential factors in the appropriate usage of medical devices related to the work environment.

The above table illustrates that the general arithmetic average of the axis is (3.45 ± 0.50), and this shows that there are neutral between approval and rejection among the study members on the influential factors in the appropriate usage of medical devices related to the work environment, and the most prominent of these factors: (I Work Longer Than My Usual Schedule With A Mean Of (3.65 ± 0.95), Too Many Types Of Alarms Of MDs Influence My Work Performance With A Mean Of (3.60 ± 0.74), Relationship With Supervisors In ICU Influence My Ability To  Manage MDs With A Mean Of (3.55 ± 0.79), There Is A Shortage Of Staff In My ICU With A Mean Of (3.44 ± 0.92), Relationship With Colleges In ICU Influence My Ability To Manage MDs With A Mean Of (3.42 ± 0.79).

Second Question: Are there statistically significant differences in the study members’ responses about the influential factors in the appropriate usage of medical devices by the variety of the study variables?

To identify if there are statistically significant differences in the study members responses about the influential factors in the appropriate usage of medical devices by the variety of the study variables (Gender, Age, Academic Qualification, Experience, Work period, Training), (T) test was used on to Independent Sample) as the on the following table No (6).

Table 6: Differences in the study member’s responses about the influential factors in the appropriate usage of medical devices by the variety of the study variables.

The above table illustrates that there is no statistically significant differences in the study members responses about the influential factors in the appropriate usage of medical devices by the variety of the study variables (Gender, Age and Work shift), Where the value of the significance level of these variables respectively (0.715, 0.713, 0.954), and all of it are values more than (0.05) of any non-statistically significant values. However, the results show that there is a statistically significant difference among the other variables (Qualification, Experience, and Training) for those who have Graduate Studies, 10 years and more, and have previous training, Where the value of the significance level of these variables respectively (0.036, 0.041, 0.036). These results reflect the effects of qualification, experience, and training on the ICU nurses’ perceptions toward the appropriateness of medical devices use in ICU.

The results showed that there is an agreement among the study members on the influential factors in the appropriate use of medical devices with an overall average (3.43 ± 0.38), where factors related to the work environment comes in the first place with an overall average (3.45 ± 0.50), followed by factors related to the user with an overall average (3.43 ± 0.56), and in the latter factors comes the factors related to the device with an overall average (3.40 ± 0.38), Perhaps the reason that the relating factors are from the most important factors affecting the appropriate use of the devices to the great importance of the availability of appropriate physical conditions for the use of devices within the intensive care unit (such as light - space - calm), As well as the shortage of staff within the care unit or adequacy affects heavily on the use of such devices, in addition to that the good cooperation between nurses and supervisors contributes significantly in the good use of nurses to those devices. In addition to the above, the results may also stressed the importance of factors related to the user in the optimal use of medical devices within the intensive care unit, and the reason for this is that the training of nurses on the use of such devices and teaching them about the characteristics of these devices and how to handle it and how to read the results that may appear on the those devices screens; all of these factors significantly affect the ability of the nurses on the use of such devices. In the latter comes the factors relating to the device as less factors affecting the optimal use of nurses to the medical devices and related to each the good location of the device and the ease of movement from one place to another if needed, in addition to the possibility of using the device whenever the need arises.

Healthcare systems are complex systems that need to be examined carefully to avoid errors and improve their quality standards. MDs represent a huge part of the healthcare services’ cycle through which most of healthcare management practices are done. Inappropriate use of MDs can cause serious problems to patients and public health in general, including incorrect or delayed diagnosis and treatment or patient injuries. This study has defined three factors that could have an effect on inappropriate use of MDs. These factors include the device itself, the user of the device, or the environment where the device operates. The environment factor is the most influencer on the appropriate usage of MDs, followed by factors related to the user and the last factors related to the device. Manufacturers should pay more attention to set a distinguished notification alarm for each MD, a clear setup and operating instructions, and an easy mechanism to move MD arounds. Hospital decision maker and administrators should focus on creating teamwork environment between colleagues and their supervisors to reduce undesirable influence while managing MDs. They also should implement an effective staffing plan to avoid shortage of staff, and long working hours. It is very important to enhance the knowledge of nursing staff especially in ICU about managing MDs through proper training.

1. De Cremer D, Nguyen B and Simkin L. The integrity challenge of the Internet-of-Things (IOT): On understanding its dark side. Journal of Marketing Management 2016; 33: 1-2.
2. Marganski A, Melander L. Intimate Partner Violence Victimization in the Cyber and Real World: Examining the Extent of Cyber Aggression Experiences and Its Association With In-Person Dating Violence. Journal of Interpersonal Violence. 2018; 33: 1071-1095.
3. Woodlock M. The Abuse of Technology in Domestic Violence and Stalking. Violence against Women, 2016; 23: 584-602.
4. Stark E. Coercive control: How men entrap women in personal life. 1st edition. Oxford: Oxford University Press. 2007.
5. Stark E. From domestic violence to coercive control in the United Kingdom. Domestic Violence Report, 2016; 21: 23-26.
6. Burman M and Brooks-Hay O. Aligning policy and law? The creation of a domestic abuse offence incorporating coercive control. Criminology & Criminal Justice 2018; 18: 67-84.
7. Douglas H. Do we need a specific domestic violence offence? Melbourne University Law Review 2015; 39: 434-471.
8. Toussaint W and Ding A. Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge Intelligence. Proceedings of the Second International Conference on Cognitive Machine Intelligence. 2020.
9. Gaslight 1944 film. 2020.
10. Bentham J. The Panopticon Writings. First edition. New York: Verso. 2010.
11. Foucault M. Discipline and Punish. 1st ed. Pantheon Books. 1977.
12. United Nations Development Programme and UN Women. Combatting Online Violence against Women & Girls: A Worldwide Wake Up Call: Highlights. 2015.
13. Gillespie T. The Politics of Platforms. New Media & Society, 2010; 12: 347-364.
14. Suzor N. Digital Constitutionalism: Using the Rule of Law to Evaluate the Legitimacy of Governance by Platforms. Social Media + Society, 2017; 4: 1-11.
15. Stilgoe J, Richard O, Phil M. Developing a framework for responsible innovation. Research Policy. 2013; 42: 1568-1580.
16. Templeton A. Biological Races in Humans. Stud Hist Philos Biol Biomed Sci. 2013; 44:262-271.
17. Jenkins R. Social anthropological models of inter-ethnic relations. In: Theories of Race and Ethnic Relations. 1st edition. Cambridge: Cambridge University Press. 1986; 170-186.
18. Vanden Berghe P. Ethnicity and the sociobiology debate. In Theories of Race and Ethnic Relations. Cambridge: Cambridge University Press. 1986; 246-263.
19. Wilkinson D and King G. Conceptual and Methodological Issues in the Use of Race as a Variable: Policy Implications. The Milbank Quarterly, 1987; 65: 56-71.
20. Anderson B. Imagined Communities. Third edition. New York: Verso. 1983.
21. Baker J. Race. First edition Oxford: Oxford University Press. 1974.
22. Stark E and Hester M. Coercive Control: Update and Review. Violence against Women, 2019; 25: 81-104.
23. Van der Molen F. How knowledge enables governance. The coproduction of environmental governance capacity. Environmental Science and Policy. 2018; 87: 18-25.