|Year : 2021 | Volume
| Issue : 4 | Page : 149-155
Using occupational therapy process addressing sleep-related problems in neurorehabilitation: A cross-sectional modeling study
Chia-Wei Fan, Kathryn Drumheller
Department of Occupational Therapy, Advent Health University, Orlando, Florida, USA
|Date of Submission||16-Jun-2021|
|Date of Decision||01-Sep-2021|
|Date of Acceptance||09-Sep-2021|
|Date of Web Publication||29-Sep-2021|
PhD, OTR/L. AdventHealth University, 671 Winyah Drive, Orlando, FL, 32803
Source of Support: None, Conflict of Interest: None
Introduction: Sleep is one of the main occupations defined in the occupational therapy (OT) Practice Framework-4. Methods: A survey link was sent to registered OT practitioners in Florida (N = 14,978) in September 2019 through E-mail addresses obtained from the Florida Department of Health website. A convenience sample of 213 OT practitioners responded; the majority were female (87%), with 56% reporting over 10 years of experience treating patients with neurological disorders. The person-environment-occupation-performance (PEOP) OT process provided the guiding framework for the proposed model. Spearman's rho correlation coefficients determined the correlations between the variables of interest. Regression coefficients attained through hierarchical ordinal logistic regression estimated the log odds between the variables. Results: Therapists who wrote more sleep-oriented goals were predicted to use a greater variety of sleep-related assessments (odds ratio [OR] = 1.256; 95% confidence interval [CI] = 1.171–1.347). Furthermore, a greater repertoire of sleep interventions was predicted when more types of sleep assessments were utilized (OR = 2.134 (95% CI = 1.750–2.602); more clients expressed sleep-related concerns to the OT practitioners (OR = 1.207; 95% CI = 1.044–1.395); and when the OT practitioners worked in a greater number of clinical settings (OR = 1.308; 95% CI = 1.113–1.539). Conclusion: The findings confirmed that the PEOP model might guide the OT service process when addressing sleep-related problems in neurorehabilitation. However, variations between settings and environmental facilitators/barriers may also play a role in sleep-related interventions.
Keywords: Model application, neurorehabilitation, occupation, sleep
|How to cite this article:|
Fan CW, Drumheller K. Using occupational therapy process addressing sleep-related problems in neurorehabilitation: A cross-sectional modeling study. Asian J Soc Health Behav 2021;4:149-55
|How to cite this URL:|
Fan CW, Drumheller K. Using occupational therapy process addressing sleep-related problems in neurorehabilitation: A cross-sectional modeling study. Asian J Soc Health Behav [serial online] 2021 [cited 2023 Dec 3];4:149-55. Available from: http://www.healthandbehavior.com/text.asp?2021/4/4/149/326959
| Introduction|| |
Sleep is vital to health and overall well-being., Sleep deficits and disorders can impact individuals' occupational performance,,,, which may have dire consequences for public safety, in addition to personal health., The occupational therapy practice framework (OTPF), 2nd edition first classified sleep as an occupation due to its significant role in day-to-day life. Therefore, sleep falls into occupational therapy's (OTs) service scope. Practitioners must consider sleep in clinical practice and follow the process established within the updated OTPF to treat patients' sleep concerns using evaluation, intervention, and outcomes to achieve sleep-related goals.
The American OT Association stated that all OT practitioners should assess and treat sleep. Although the literature validates the importance of OT addressing sleep and urging incorporating evidence into clinical practice,,, there is a disparity because some OT practitioners are unaware of their professional role in addressing sleep. Many OT patients have sleep difficulties. Sleep problems are especially common in individuals with neurological diagnoses. Therefore, occupational therapists are called upon to incorporate sleep assessment and treatment as an area of potential growth for the profession.,
| The Importance of Incorporating Theory into Clinical Practice|| |
Evidence-based practice models are integral to the OT process because they provide an organized structure for clinicians to follow that strengthens the practical application, and their use is vital to the growth and development of the profession. However, Ho and Siu found that current sleep intervention research in the OT literature rarely addresses the underlying theoretical framework used to organize and guide clinical practice. Therefore, they proposed that the person-environment-occupation-performance (PEOP) model could guide OT sleep interventions because it is one of the OT practice models that considers the influence of sleep on occupation and ways to address it in the clinical practice.
The PEOP model emphasizes that a dynamic interaction occurs between the person (i.e., intrinsic factors) and the environment (i.e., extrinsic factors), which influences occupation through barriers and/or enabling factors. This interaction affects one's competence to complete the desired occupation as well as the final occupational performance. When occupational performance is constrained, the client's ability to participate in coveted occupations is hindered, and well-being may be negatively affected. Ho and Siu ascertained that OT practitioners might use the PEOP model to address clients' sleep needs because it provides an evidence-based approach to guide sleep interventions. The PEOP model describes a four staged OT process: (1) narrative, (2) assessment and evaluation, (3) intervention, and (4) outcome. During the narrative stage, OT practitioners assess their clients' perceived strengths and problems on personal/environmental/occupational factors and then establish goals. Then, the assessment and evaluation components identify intrinsic and extrinsic barriers and facilitators that impact the person's ability to achieve the expressed goal. Next, based on the assessment and evaluation results, interventions are created to enable clients to reach their desired outcomes (e.g., sleep performance).
Therefore, the current study aims to explore the factors that predict the use of sleep interventions in current OT practice, particularly for OT clinicians who treat clients with neurological diagnoses, using the PEOP model as a guiding framework. In addition, barriers that impact the PEOP OT process will be identified, and implications for clinical practice and application will be discussed.
Specifically, here are our assumptions [Figure 1]:
|Figure 1: Proposed model in explaining sleep-related intervention based on the person-environment-occupation-performance model|
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- Hypothesis 1: How frequently OT practitioners write sleep-related goals will be an explanatory factor for the number of different sleep-related assessments they use in clinical neurorehabilitation practice
- Hypothesis 2: The number of different sleep-related assessments utilized by OT practitioners will be an explanatory factor for the number of different sleep-related treatments used by OT practitioners in neurorehabilitation practice.
| Methods|| |
This project was approved by AdventHealth University IRB (#OT27118) and complies with the declaration of Helsinki (2000 revision). All participants signed the informed consent before completing the web-based questionnaire.
This exploratory study used a web-based questionnaire to query registered occupational therapists (OTRs) and certified OT assistants (COTAs) in the state of Florida about how they address sleep-related problems in clinical practice. E-mail addresses of all the current OTRs and COTAs were obtained through the Florida Department of Health website. Participants must have provided direct OT services to clients with neurological disorders within the past 4 weeks to qualify for the study.
A link introducing this research study and the study questionnaire was E-mailed to 14,978 current Florida OT practitioners (including 9,149 OTRs and 5,829 COTAs) in September 2019. After reviewing and signing the informed consent, participants were directed to the study questionnaire. Participants were asked to complete the survey based upon their last 7 days of practice. Two E-mail reminders were sent 7 and 14 days after the initial E-mail to increase the response rate.
The research study team developed a questionnaire consisting of two parts, with a total of 12 questions. The first part collected the participants' demographic information [Table 1]. The second part investigated the OT practitioners' current practice in addressing sleep-related problems in neurorehabilitation units, including the assessments they used to evaluate their clients' sleep-related problems and the treatment they provided for clients with sleep-related problems [Table 2]. A sample question from the second part is: “Based upon the last seven days of practice, what were the assessments you used to evaluate sleep-related problems among clients (select all that apply).” Among the 12 questions, six were multiple-choice items, five were multi-response items, and one question was open-ended (i.e., List any limitations/barriers you've encountered in your current practice on addressing sleep-related problems). Three questions at the second part of the survey were based on the PEOP OT process; these questions had acceptable internal consistency (Cronbach's alpha = 0.628).
|Table 2: Clinical practice with sleep-related problems in neurorehabilitation|
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Statistical analyses were conducted using the SPSS software version 27 (New York, United States). The participants' characteristics were analyzed through the descriptive statistics (e.g. mean, standard deviation [SD], and percentage). Three items were initially collected as multi-response items (i.e., “Select all the clinical practice setting (s) where you currently work,” “Indicate the assessments you use to evaluate sleep-related problems among your clients,” and “Indicate the intervention techniques you use to treat sleep-related problems among your clients”) and were converted to dichotomous coding for analysis.
For the proposed model based on the PEOP OT Process, Spearman's rho correlation coefficients first determined the existence of zero-order correlations between the variables of interest. Ordinal logistic regression was then applied to examine the extent to which the independent variable contributed to the dependent variable. The Wald Chi-square test was then used to analyze the null hypothesis and ensure the estimate equaled 0, with an α level set at 0.05. The regression coefficient was used to estimate the increase in the log odds of the dependent variable per unit increase in the value of the independent variables.
While conducting the analyses, we found that two extra variables (i.e., works at more clinical settings, and more clients expressed sleep-related problems) also significantly predicted the dependent variable (i.e., sleep-related interventions used). Therefore, these two additional variables were added to the final model [Figure 2]. Specifically, this study examined whether writing sleep-related goals more often impacted the total variety of sleep-related assessments OT practitioners use in clinical practice (H1) when all other variables in the model are held constant. Furthermore, we explored whether OT practitioners implement a wider selection of sleep-related interventions into their clinical practice when they use a larger variety of sleep-related assessments (H2); currently work in a greater number of clinical settings (H3); and if a greater percentage of their clients express sleep-related concerns (H4) when all the other variables in the model are held constant. The odds ratio (OR), or exponential function of the regression coefficient, will be reported at the 95% confidence interval (CI).
|Figure 2: Model of sleep-related intervention performed by the occupational therapy practitioners|
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The survey contained one open-ended item that allowed clinicians to express limitations they have experienced when addressing their clients' sleep-related problems. The responses were categorized as different themes and examined relative to the proposed model and the survey findings.
| Results|| |
Although we sent E-mails to all the current OT practitioners in Florida, we did not know the exact number of practitioners who had provided OT service to clients with neurological disorders in the past 4 weeks. Therefore, the response rate cannot be calculated. Of the 219 OT practitioners who signed the study's informed consent, 216 completed the questionnaire, and three submitted their questionnaires with missing answers and were excluded from the final analysis. Therefore, the final analysis consisted of 213 OT practitioners. The missing rate is 2.7%. The participants' average age was 44.78 years old (SD = 11.37), and the majority were female (87.3%).
In addition, 48.4% of the sample held a Master's degree in OT, with 64.3% of the overall sample having ten or more years of experience as an OT practitioner. Furthermore, 56.3% had ten or more years of experience working with clients who have neurological diagnoses. [Table 1] and [Table 2] for additional participant demographic details.
Sleep-related occupational therapy goals and total number of assessments used
[Figure 3] depicts the results of the proposed model in explaining sleep-related interventions used by OT practitioners in neurorehabilitation. The rate that practitioners write sleep-related goals was correlated with the total number of sleep assessments used by the practitioners (r = 0.327; P < 0.001), thereby supporting the hypothesis (H1) that writing sleep-related goals more often (e.g., ×2 per week vs. never) was positively related to the practitioners using more assessment options to evaluate their clients' sleep difficulties. The Wald Chi-square test for the relationship between the frequency in which the practitioner writes sleep-related goals and the total number of assessment options selected was 14.24 (P < 0.001). The regression coefficient for the frequency of sleep-related goal writing was significantly different from zero for approximating the total number of assessment options the practitioner has used to evaluate for sleep problems. The OR = 1.256 (95% CI = 1.171–1.347). Thus, practitioners that wrote sleep-related treatment goals more often were also likely to use a greater variety of sleep assessments with their clients. The regression results are shown in [Table 3].
|Table 3: Regression results: Sleep-related assessments used as the outcome|
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|Figure 3: Results of the proposed model in explaining sleep-related intervention used by occupational therapy practitioners in neurorehabilitation|
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Explanatory factors for sleep-related intervention used
The results of the current study demonstrated significant correlations between the dependent variable in the model (i.e., sleep-related interventions used) and the total number of sleep assessments used (r = 0.531; P < 0.001); the total number of selected clinical practice settings (r = 0.211; P = 0.002); and the percentage of clients that have expressed sleep concerns to the practitioner (r = 0.208; P = 0.002). The Wald Chi-square test for the total number of sleep-related assessments used is 55.619 (P < 0.001) with the OR = 2.134 (95% CI = 1.750–2.602) (H2). The Wald Chi-square test for the total number of current clinical practice settings is 10.632 (P = 0.001) with the OR = 1.308 (95% CI = 1.113–1.539) (H3). Last, the Wald Chi-square test for the percentage of clients that have expressed sleep concerns is 6.594 (P = 0.010), with the OR = 1.207 (95% CI = 1.044-1.395) (H4). Therefore, the results of the proposed model demonstrate that OT practitioners are likely to use a larger variety of sleep-related interventions in clinical practice when they also use a greater variety of sleep-related assessments to investigate sleep concerns; currently work in a greater number of clinical settings; and if a larger percentage of clients express sleep concerns to them. The regression results are shown in [Table 4].
|Table 4: Regression results: Sleep-related intervention used as the outcome|
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| Discussion|| |
The current study results revealed several factors that predicted the use of more sleep interventions in clinical practice. First, writing more sleep-oriented goals predicted a greater number of sleep assessments used (H1), which also projected more types of sleep interventions used (H2). However, using more types of sleep interventions was also more likely when the OT practitioner worked in a greater number of clinical settings (H3) and when OT practitioners had a larger percentage of clients expressing sleep concerns (H4) in the past 7 days of practice.
The results of the study show multiple factors increase the likelihood that OT practitioners will use a greater array of sleep interventions. However, writing sleep-associated goals more frequently, which increased the variety of assessments used to evaluate for sleep difficulties (e.g., Pittsburgh sleep quality index, Epworth sleepiness scale, interview, etc.), had the greatest impact on the number of sleep interventions (e.g., routine modification, environmental modification, etc.) a clinician used. This sequence appears to support the assertion that the PEOP model may offer an effective framework for sleep interventions. Furthermore, this route aligns with the progression of the PEOP OT process, particularly the narrative (i.e., provide information to write sleep goals), assessment and evaluation, and intervention stages. The last stage of the PEOP OT process (i.e., outcome) was not included in the current study. Follow-up information regarding the efficacy of interventions was not collected due to the cross-sectional design of the study.
Research studies that assessed environmental barriers to sleep within the hospital setting and intervened accordingly also offer similar support for the utility of the PEOP model in sleep interventions., However, an identified framework is essential to truly understand the person-environment-occupation interaction leading to the overall action and outcome. Therefore, therapists must incorporate occupation-based models, such as the PEOP model, into their clinical practice.
OT practitioners who had more clients expressing sleep concerns were also likely to incorporate more types of sleep interventions into practice. In our study, however, these OT practitioners bypassed the narrative and assessment stage of the PEOP OT Process. The limitations and barriers identified by OT practitioners may explain this alternate route in the proposed model. For example, reimbursement criteria and productivity demands created common obstacles and were also expressed in the current study's open-ended question as factors that limited the OT practitioners' ability to address sleep.
“…Insurance reimbursement wants to focus on Activity of Daily Living (ADLs) and improving the amount of assistance required by a helper. Because sleep is not an activity measured by a helper, it is not as applicable as a goal in Inpatient Rehabilitation Facility (IRF). However, I often focus on sleep as a part of either patient or family education depending on their cognitive level and understanding.”
“My company has strict forms and checklists that need to be used and addressed because of reimbursement. So, I cover it in therapy as a side issue, not an actual focus of treatment.”
“Point of care system for documentation does not provide an opportunity to address [sleep].”
When researchers used the PEOP model to identify the facilitators and barriers OT practitioners experienced in a skilled nursing facility, they encountered similar issues. Emphasis was placed upon productivity, which stressed bathing and dressing goals, and medications were used instead to treat sleep concerns. In addition, administrators feared reimbursement would be denied for sleep-related OT services. Furthermore, sleep challenges tend to be conceptualized as less important,, and there have been no standardized OT sleep assessments,, which may also explain why goals and assessments did not apply in this route. Responses to the open-ended question in the current study echo this assumption.
“Although sleep-related problems are important, and good rest is promoted, often patients/caregivers have several priorities when in an acute care setting (strengthening, improving cognition/communication, basic ADLs, functional mobility).”
“School-based practice limits goal writing for sleep. Parents often report this as a primary problem, so I offer solutions on the side to support school performance.”
The challenges that certain clinical settings created may explain another route of the proposed model. For instance, clinicians who work in more clinical settings are more apt to use a greater variety of sleep interventions than those working in fewer settings. OT practitioners who work in a larger array of clinical settings may have a greater chance of working in locations without these barriers.
Furthermore, OT practitioners have repeatedly voiced that their lack of sleep management training made them feel inept at forming treatment plans to address it, thus creating an intrinsic barrier, exacerbated by a lack of resources, and limited research regarding OT sleep-related interventions.,,, Consequently, clinicians rarely treated the sleep concerns their clients expressed. The OT practitioners queried in the current study commented similarly.
“Lack of education, lack of outcome tools for adequate measurement.”
“Not trained enough to address those issues.”
“1) A Standard assessment is not available, and 2) Not enough training was provided in school.”
The implications for practice are substantial due to the relationship between sleep, well-being, and occupational performance. When people experience occupational performance problems with sleep, they may no longer feel safe participating in other valued occupations, severely impacting well-being. Therefore, OT practitioners must address sleep in clinical practice with all clients and advocate that it is within the OT scope of practice, as determined by the OTPF-4. Furthermore, OT practitioners must remain informed of current research to increase evidence-based practice usage and close the gap between the OT literature and clinical practice.
Limitations and future research suggestions
Some potential limitations should be noted in this study. First, the limited sample size, in which the majority of respondents were female and all participants located in Florida, may hinder the generalization of results. Future studies should consider increasing the male sample size and investigating OT practitioners across the United States to understand the current practice regarding sleep better. In addition, the data collected were based upon the last 7 days of the participants' clinical practice, which may have limited their responses and impeded a comprehensive view of the sleep-related problems they encountered. In addition, the sample included both OTRs and COTAs. Due to their differing roles and responsibilities, participants may not have been equally involved in evaluating and treating sleep-related problems. The current study did not further explore differences between them. Therefore, future research could expand upon the current study and assess OTRs and COTAs separately to understand better the impact of role delineation on this topic.
| Conclusion|| |
Sleep is an occupation that is essential to all, and addressing sleep is within the OT scope of practice. Translating OT practice models into clinical practice is integral to the OT process. The current study demonstrated that several different routes predicted the use of sleep interventions. The strongest route aligned with the PEOP OT process. However, OT practitioners face multiple barriers to treating the occupation of sleep, which can potentially impact clients' occupational performance across occupations. Therefore, there is a critical need for more research and advocacy in this area to increase the available resources to clinicians and expand their awareness that the occupation of sleep is within the OT scope.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3], [Table 4]