The Conditions in Ocational Therapy: Effect on Ocational Performance

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Assesses and treats patients within the CA Licensing Board and AOTA American Occupational Therapy Association scope of practice including but not limited to ADL's Activities of Daily Living , cognitive and perceptual status, swallow evaluation and treatment, splinting, wheelchair fitting and seating, and functional mobility.

May serve as a clinician in both the inpatient and outpatient settings.

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Observes actual performance of activities and tasks to identify specifically what supports or hinders performance including motor skills e. Analyzes findings to determine therapy diagnosis and prognosis and designs a program to maximize outcomes and alleviate impairment and functional limitations; identifies the frequency and duration required to meet goals. Selects and administers appropriate assessment and treatment techniques.

Performs age appropriate competency skills in area of practice and with respect to individual patient's problems. Evaluates the need for, recommends, and trains in use of complex durable medical equipment, orthotics, prosthetics, and adaptive devices; Fabricates orthotic and adaptive devices.

Performs all necessary patient care documentation, including assessment, plan of care, progress notes, discharge summaries, and charges for evaluation and treatment. Documentation reflects patient status, progress or change, participation by patient and family in goal setting and delivery of care. Discharges patient from treatment when appropriate with adequate discharge planning including equipment procurement and family training, and communicates this appropriately to patient, family and health care team.

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Organizes and maintains a patient caseload consistent with department productivity standards. Schedules patients and informs supervisor if problems arise related to the delivery of patient care or caseload volume. Ensures documentation and billing are timely, accurate and complete, including precautions, monthly and discharge summaries. Participates in clinical teaching, including the clinical instruction of occupational therapy interns and other staff.

Prepares and presents an in-service at least one per year at a department meeting. Provides input regarding the educational needs of the staff and serves as a resource in meeting those needs.

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As students are highly interested in their program of choice, such programs should display a low interest diversity. Other programs could be more attractive to students who have ulterior motives like pleasing their parents and should display a higher interest diversity. As students are less intrinsically interested in their program of choice, these programs display more variance in student vocational interest, resulting in a higher interest diversity.

On an individual level this find indicates that in general, the PE fit between students and their programs is quite high: RIASEC profiles between student and program correlate. Indeed, students predominantly seem to choose a higher education study program that fits their interests quite well when given the opportunity, as is the case in an open access environment. Results also showed that the variance in program interest diversity is related to motivation.

Study programs with low interest diversity were linked to students with relatively higher autonomous motivation, while programs with a higher interest diversity were linked to students with a higher controlled motivation. This relation between student motivation and interest diversity indicates that some programs do attract more students with a higher controlled motivation.

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For our second research question, we explored the direct effect of the program interest diversity on average study results. As different programs could reward different interest patterns, we took a conservative approach and pitted three hypotheses against each other on how program interest diversity would influence average program study results. The curvilinear relation between program interest diversity and average study results provided evidence for our mixed effects hypothesis. Different programs indeed rewarded different interest patterns [ 29 ].

To provide an explanation for this curvilinear effect, we performed a post-hoc analysis. Results of this analysis showed that in general, larger program interest diversity was linked to better average study results. In other words, programs with more interest diversity in their student population showed better average results. However, some study programs with very specific interest patterns that scored high on the Social dimension and low on the Realistic dimension showed an opposite relation: lower program interest diversity in student populations in such environments was associated with better study results.

To improve general study results, these findings suggest policy makers and institutions in open access higher education should allow for interest diversity in the student population of study programs. At the same time, policy should also ensure a sufficiently high individual student PE interest fit, as literature already suggested [ 21 , 1 , 24 , 22 , 26 , 23 , 9 , 25 ].

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However, to ensure better study results for very specific programs high on the social dimension and low on the practical dimension like Educational Sciences, the fit between student and program should indeed be as high as possible, resulting in a very low program interest diversity and a very high individual PE interest fit. As such, our continuous approach of interest diversity represents a valuable addition to the measurement of internal similarity of environments usually determined through dichotomous test statistics [ 30 — 32 ]. For our final research question we compared the effect of program interest diversity on study results to the effect of individual PE fit.

We hypothesized that due to the low interest program diversity or high internal similarity the effect of PE fit would be low. We also tested the cross-level interaction of individual program fit and environmental program diversity. Analyses indicated that the effects at the individual level on study results were very modest at best: student PE fit only explained up to 0. Hence, in an open access higher education environment, the variance in PE fit between students and their program barely has a meaningful impact on individual study results. Moreover, program interest diversity of different study programs did not only influence average study results, we also obtained partial evidence that this diversity explained more study result variance in the total multilevel models than the individual indicators of PE fit.

These findings are analogous to those found in our second question and provide additional evidence that higher education institutions should indeed consider program interest diversity when making policy decisions towards student orientation and admission. As a possible explanation, most students in this open system showed a high PE fit with their program of choice. In systems were choice is restricted on the basis of exams or GPA requirements , students may have to choose for programs that match their interests less well, and then this larger variety in PE fit has a bigger impact on individual study results.

Indeed, earlier research that examined PE fit effects on study results in constrained access systems typically observed more explained variance [ 22 , 10 , 26 , 23 , 24 , 9 , 25 ]. This discussion on the consequences of open access policy illustrates the importance of studying PE fit effects in a variety of study contexts. As Nauta already indicated, study environments remain understudied [ 2 ]. Entry exams or GPA requirements yield a selection bias in student intake that will influence the internal similarity in student populations, and therefore also the effects of the observed PE fit variance.

Such contextual effect are likely partly responsible for the mixed results regarding the influence of PE fit on study results. As theory predicted, the influence of the environment on outcomes in this open access set up becomes quite influential, while the individual level almost has no explanative power at all regarding study results. In other words, the open access environment causes study program interest diversity to have a profound influence on study results, while severely diminishing the influence of individual student PE fit.

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To close the discussion on our third question, the variance in program interest diversity and student PE fit was limited to the extent the cross level interaction between individual and environment was not significant. In other words, program interest diversity did not influence the student PE fit-study results relation: effects of individual PE fit remained low, regardless of the interest diversity of study programs.

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These findings in our open access study environment are at odds with results from internal similarity research from Tracey and colleagues [ 9 ]. They showed that the effects of PE fit on individual study success was indeed constrained by the study environment. As an explanation, we speculate the open access system leads to such low interest variance that prevents a cross-level interaction between study program interest diversity and student PE fit. The present study is unique in its assessment of PE fit effects in an open access system.

It would be interesting in the future to directly compare study environments with more constrained entry restrictions on the exact same measurements, using the exact same analyses.

We speculate that such an approach would show enlarged PE fit effects in more restricted study programs, while the influence of interest diversity will diminish. The access restrictions could thus be a crucial factor in explaining the mixed findings in literature regarding PE fit, while elaborating literature with interest diversity research. Our conceptualization of interest diversity and its motivational connection could also be used in organizational and occupational research.

We predict that not all work environments will show the same amount of interest diversity. As access to the work environment works quite differently in comparison to access to higher education, we can also expect different effects.

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For instance, open access to certain jobs low degree requirements could result in higher interest diversity. Indeed, a student in an open access environment picks a certain program because that program is of particular interest to him or because his parents wants him to study that specific program.

An employee could have other motives to pick a job. Employees who have no or a low degree can decide to work out of financial motives exclusively. Though highly speculative, we think that the different motivation in work and study contexts will lead to different patterns of interest diversity for both contexts and could ultimately end up explaining why the strength of the PE fit—study results relation is so underwhelming in comparison to the theoretical predictions. In the present study, we have assessed program interest diversity of student populations in study programs. In an open access environment, interest diversity of student populations in study programs is low.