Hospital homebound students and K-12 online schooling.

The flexibility afforded by online education may provide opportunities for learners with disability who require absence from traditional learning environments. This study sought to describe how a subset of learners with disability, those with hospital-homebound designation, perform in K-12 online classes, particularly as compared to non-hospital homebound counterparts. A cross-sectional analysis was performed of all Florida Virtual School course enrollments from August 1, 2012 to July 31, 2018. Researchers analyzed 2,534 course enrollments associated with K-12 students who, at the time of their course enrollment, had hospital-homebound designation, and a comparison group of 5,470,591 enrollments from K-12 students without hospital-homebound status. Data analysis showed three important outcomes. First, hospital-homebound designated student academic performance was equivalent to their non-hospital homebound counterparts. Second, however, hospital-homebound course enrollments were 26% more likely to result in a withdrawal prior to grade generation. Third, these withdrawals were potentially mitigated when H/H designated students were enrolled in five or more classes or in classes with five or more students. The results of this study provided evidence that when they can remain enrolled, hospital-homebound learners experience equivalent academic outcomes in online learning environments. These findings suggest that healthcare professionals should be made aware of the potentially equivalent outcomes for their patients. Moreover, virtual schools should seek to identify and create supports for these students.

Introduction

Given advances in healthcare, more children are surviving illness and disability than in years past [1]. These children represent considerable diversity racially, ethnically, and in the heterogeneity of their health-related needs [2]. Promising research suggests that while chronic illness represents a challenge, it does not prevent children from living fulfilling lives. For example, Blackwell et al. examined data from three cohort studies and determined life satisfaction was comparable between those with and without chronic illness. The authors concluded that: “chronic illnesses…do not preclude children from leading happy and satisfying lives” [1(p6)].

Nevertheless, growing up with a chronic illness or disability not only requires high levels of medical care, it also places children at increased risk of poor educational outcomes. For example, they are at a higher risk for missed school days, low educational attainment, repeating a grade, and poor mental health outcomes than the typical child [3, 4]. These educational risks also translate to poor occupational outcomes such as difficulties in obtaining or maintaining employment, potentially negatively impacting psychosocial well-being and quality of life [3, 5]. Meeting the educational needs of these children to provide a foundation for their fulfillment and independence requires a robust support system, dedicated resources, and interprofessional collaboration [6].

The dominant paradigm in the United States (US) for educating students with chronic disability and illness encourages inclusion, integrating learners with different needs in the same classroom [7]. However, a small but significant number of students with chronic illnesses or disabilities may not be healthy enough to attend school in a traditional environment. In these cases, hospital/homebound (H/H) instruction may be an appropriate option [8, 9].

H/H instruction is not a new phenomenon; evidence of homebound instructional services for pregnant teens in the US dates to the 1930s [10]. H/H programs provide educational instruction in non-school settings for children who are living with short-term and chronic disabilities H/H programs are publicly funded and supported; this differs significantly from homeschooling where a child’s parent or guardian traditionally assumes responsibility for the delivery of educational services. H/H is administered in several different formats, varying between localities and states. Examples include home-based instruction (in which a certified teacher physically visits students in their home) or phone-based instruction. Most recently, following a similar trend in homeschooling, there has been increasing enrollment in one or more online courses [11]. Online instruction can also take many different formats, but most instruction typically involves electronic engagement between a teacher, student, and course materials (e.g., audio, video, text, or other course materials located in a learning management system; see Davis & Ferdig) [12].

H/H environments are considered highly-restrictive; as such, learners wishing to participate in an H/H program must meet qualification standards on a case-by-case basis related to their health impairment [13, 14]. For instance, in the state of Florida, obtaining H/H designation and services requires confirmation from a physician, nurse practitioner, or physician assistant with Florida licensure that the student meets the following criteria:

That the student is expected to be absent from school for at least 15 consecutive school days (or the equivalent on a block schedule) due to a physical or psychiatric condition, or for at least 15 school days (or the equivalent on a block schedule), which need not run consecutively, due to a chronic condition.

That the student is confined to the home or hospital.

That the student will be able to participate in and benefit from an instructional program.

That the student is under medical care for illness or injury, which is acute, catastrophic, or chronic in nature.

That the student can receive instructional services without endangering the health and safety of the instructor or other students with whom the instructor may come in contact.

(Exceptional Student Education Eligibility for Students Who Are Homebound or Hospitalized § 6A-6.03020, 2006, p.1).

There is very little published research about H/H programs or the children they serve; this is due, in part, to the relatively small number of learners who receive H/H services during their academic career as well as the varied nature of the programs themselves [15]. Data are also challenging to obtain due to inconsistency in state laws related to reporting; moreover, federal datasets do not report on disability or illness and its impact on children’s learning and school attendance (e.g., National Center for Educational Statistics or National Institute of Health) [10]. The limited research that does exist describes H/H programs as frequently substandard, characterized by instructors who may lack the qualifications to teach critical core subject matters, and teachers with limited instructional time [10, 14, 16].

Kindergarten to 12th grade (K-12) online education (also frequently referred to as virtual or online K-12 schooling), constitutes an internet-facilitated means for children to maintain or further their education. Originating in the United States in 1995, online schooling now exists in all 50 states in a variety of different models (public, private, and charter). In 2019, more than 300,000 U.S. K-12 students received all their instruction online, with another 4.7 million participating in hybrid instruction where students engage in online learning in addition to traditional school-based instruction [17, 18].

Given the flexibility offered by online education, multiple researchers have hypothesized that it may provide affordances for students who qualify for H/H status and other critical populations [19-21]. High-quality online schooling can effectively establish a sense of community and promote differentiated instruction with personalized learning, qualities that may be lacking in traditional H/H services [22]. Several research studies have explored online schooling for children with disabilities, all of which describe poorer outcomes when compared to children without disability [19, 23–25]. However, these studies often rely on parent-reported data, small sample-sizes, and a range of outcome variables (i.e., course level grade to high school graduation) that limit their generalizability. Finally, to date, published research has mainly focused on the broad and diverse population of students who receive special education accommodations rather than their outcomes.

The goal of this study was to respond to this dearth of existing research [26, 27]. The present study uses a robust dataset to analyze how students with H/H designation performed in K-12 online classes, particularly as compared to non-H/H counterparts. We analyzed six years of academic data from one large, online K-12 school in the United States, identifying those middle and high school students (typically between the ages of 11 and 19) with H/H designation and those without such designation. Our analysis was primarily descriptive, with some comparisons between groups. The remainder of the paper addresses the methods and results of the analyses, concluding with implications for practitioners and educators.

Methods

This Institutional Review Board (UF IRB#201802520) exempt study explored de-identified data comprising all Florida Virtual School (FLVS) students who registered for at least one online course between August 1, 2012 and July 31, 2018. FLVS is a fully accredited, statewide public school district offering more than 190 courses to students from kindergarten through 12th grade (FLVS, n.d.) in Florida and globally. The state of Florida is one of at least five US states that require students to complete at least one online course prior to graduation; FLVS is just one of several providers with which students may complete this requirement [28]. (Exemptions to this requirement are made for learners enrolled in special education programs with individual education plans that indicate online learning is inappropriate [29]).

As a not-for-profit organization, FLVS reinvests revenues into the development of new educational technologies and course development. The FLVS curriculum team designs state and national standards-aligned courses, incorporating best practices in educational technology and online learning [30]. Certified teachers draw on these courses to offer both synchronous (live) and asynchronous instruction (e.g., pre-recorded lessons) as well as individualized discussion-based assessments and support.

FLVS students have a variety of flexible and full-time enrollment options and can register for one or multiple courses. These courses include the core academic courses, electives, career and technical education courses, and Advanced Placement (college-level curricula) courses. Course content for middle and high school level courses is designed to cover 18 weeks of week (aligning with a standard semester). Importantly, while students may progress at their own pace through a course, students enrolled in ‘core’ courses (Algebra 1, Geometry, Biology, US History, Middle School Civics) must complete a statewide, standardized end-of-course examination. These examinations are offered over two-week periods five different times through a calendar year. FLVS designs its courses to interactive and incorporate games, videos, and multiple tools that aid learners in mastering course objectives [31]. Lessons begin with an overview of the content to be addressed (Fig 1 contains an example Algebra 1). Lessons also include activities and assignments to be completed individually or with peer feedback (see Figs 2 and 3 for examples from Algebra 2 and English 3).

Fig 1

FLVS Algebra 1, lesson overview.

Fig 2

FLVS Algebra 1, interactive guided practice.

Fig 3

Screenshot, FLVS English 3, lesson overview.

Students have round-the-clock access to their courses allowing them to study anytime and anywhere. They master course objectives to complete the course and receive course credit Additionally, FLVS courses include accommodations, when and where applicable, such as extended time and as-needed opportunities for shortened assignments [32]. FLVS curricula, their online learning tools, and FLVS teachers have repeatedly received state, national and international accolades for online teaching and learning excellence [33].

Data and inclusion criteria

Prior to receiving the dataset, identifiers include name, address, email, phone number were removed by FLVS staff unassociated with the study. Given the study’s IRB designation at exempt, the requirement for consent/assent was waived. The resultant dataset consisted of course instance data from two cohorts. Cohort one was comprised of all FLVS students with H/H status from August 1, 2012 to July 31, 2018. Cohort two contained all non-H/H students enrolled during that same time frame. Non-H/H students included those individuals who were either full or part-time enrolled in one or more FLVS courses (see Table 1 for a listing of courses included in this dataset). This group included students who were designated as homeschooled students at the time of their enrollment. FLVS provided deidentified aggregate course outcomes data for both cohorts for the timeframe in question. To protect student privacy, FLVS does not collect student health information (i.e. medical condition(s) necessitating H/H designation) only those students who had received H/H designation by a designated healthcare professional and provided appropriate documentation were able to receive H/H designation at FLVS.

Table 1

FLVS courses included in dataset.

Adv Alg. w/ Financial Applications

AP Art History

AP Biology

AP Calculus AB

AP Calculus BC

AP Computer Science A

AP English Lit. and Composition

AP Environmental Science

AP Human Geography

AP Macroeconomics

AP Microeconomics

AP Psychology

AP Statistics

AP US Government and Politics

AP United States History

Algebra 1

Algebra 2

Algebra 2 (CR)

Anatomy and Physiology

Art History 1 Honors

Art in World Cultures

Biology 1

Calculus Honors

Career Research/Decision Making

Careers in Fashion/Interior Design

Chemistry 1

Chemistry 1 (CR)

Chinese 1

Chinese 2

Chinese 3 Honors

Computing for College and Careers

Creative Photography 1

Criminal Justice Operations 1/Level 2

Critical Thinking/Study Skills

Information Technology/Level 2

Driver Education/Traffic Safety

Earth/Space Science

Economics with Financial Literacy

Econ. w/ Financial Literacy (CR)

English 1

English 1 (CR)

English 2

English 2 (CR)

English 3

English 3 (CR)

English 4

English 4 (CR)

English 4: Florida College Prep

Fitness Lifestyle Design

Forensic Science 1

Foundations of Web Design/Level 3

French 1

French 2

Geometry

Guitar 1

Health 1 –Life Management Skills

HOPE–Physical Education

Intensive Reading

Intro. To Educational Technology

Journalism 1

Latin 1

Latin 2

Law Studies

Leadership Skills Development

Liberal Arts Mathematics 1

Liberal Arts Mathematics 2

M/J Business Keyboarding

M/J Career Research/Decision

M/J Civics

M/J Comprehensive Science– 6/7

M/J Comprehensive Science– 7/8

M/J Comprehensive Science 1

M/J Comprehensive Science 2

M/J Comprehensive Science 3

M/J Creative Photography 1

M/J Critical Thinking & Learning

M/J Fitness–Grade 6

M/J Grade 6 Mathematics

M/J Grade 7 Mathematics

M/J Grade 8 Pre-Algebra

M/J Guitar 1

M/J Language Arts 1

M/J Language Arts 2

M/J Language Arts 3

M/J Pre-Algebra

M/J Reading I

M/J Spanish, Beginning

M/J Spanish, Intermediate

M/J United States History

M/J World History

Marine Science 1

Mathematics for College Readiness

Music of the World

Outdoor Education

Parenting Skills/Level 2

Peer Counseling 1

Peer Counseling 2

Personal & Family Finance/Level 2

Personal Fitness

Physical Science

Physics 1

Pre-Calculus Honors

Psychology 1

Reading for College Success

Social Media 1

Sociology

Spanish 1

Spanish 2

Spanish 3 Honors

Spanish 4 Honors

Spanish 3

Theatre & Film Production

United States Government

United States Government (CR)

United States History

User Interface Design

User Interface Design/Level 3

World History

World History (CR)

AP: Advanced Placement, CR: Credit Recovery, M/J: Middle/Junior High School Level.

Data analysis

Given the paucity of quantitative information about children with special healthcare needs and K-12 online learning, this study focused on two key areas. First, we set out to explore enrollment information of H/H students enrolled in FLVS courses. This included the number of students enrolled, the courses that they enrolled in, and their performance in these courses. After determining the size of the H/H cohort (n = 375), we limited the exploration of demographic data to avoid indirect student identification (in several cases only three or fewer H/H students were associated with a particular Florida county, age or age group in a specific year) and adhere with Federal Law (Family Educational Rights and Privacy Act, 20 U.S.C. § 1232g; 34 CFR Part 99). The second area of study was to examine H/H performance against traditional online students enrolled during the same time frame and in the same types of courses as H/H students.

Prior to analysis, the data were reviewed for outliers, resulting in one H/H student’s elimination from the dataset (this student was associated with more than 300 course instances in one semester, all of which resulted in withdrawals). During our analysis we defined characteristics of the data using specific terminology described by Cavanaugh et al. and Black et al. [34, 35], commonly used in the study of K-12 online learning, including:

: course name, year and semester/segment, and the frequency of grade and non-grade outcomes

: a course instance where an A-F grade was generated;

: a single course registration and associated de-identified information (course name, year and semester/segment of intended enrollment, and outcome);

: a course instance with a non-grade outcome (e.g. withdrawing from a course).

: a proportion of Course Completion to Course Non-Completion

Chi-square tests were used to explore dichotomous student outcomes (grade generating versus non-grade generating) by dichotomous status (H/H versus non-H/H status) drawn from the entire FLVS population. That is, we compared whether the categorical variables were independent of each other. Z-tests of proportion were explored to test whether two populations or groups differed significantly [36]. During instances where multiple statistics were run on the same dataset, we employed the Benjamini and Hochberg procedure to control for familywise Type I error [37]. We used descriptive statistics to describe non-categorical data. Data was analyzed using R and RStudio, and the tidyverse, and psych packages [38-40].

Results

A total of 375 unique students (44.0% female, 56.0% male) were enrolled in the FLVS hospital-homebound (H/H) program between August, 2012 and July, 2018. The comparison group, comprised of non-H/H students enrolled in one or more FLVS courses during the same time period totaled 1,191,508 unique students (57.0% female, 43% male). We did not explore race and ethnic data from the H/H cohort, but in 2019–2020 FLVS reported that 70.2% of part-time enrollees identified as White, 16.1% as Black of African American, 6% as Multi-Racial, and 4.5% as Asian. The H/H cohort was comprised of learners from 25 different Florida counties, two university-associated lab schools, and homeschooled students. Whereas the comparison group represented students from all 67 Florida school districts. Among both cohorts the majority of learners lived in more populous counties (e.g. Miami-Dade, Broward, Orange, Hillsborough).

There were a total of 2,534 H/H course enrollments; each student was associated with a mean of 5.8 course instances (SD = 6.8, median = 3, mode = 2). Among these 375 students, 26.6% (n = 100) had only one semester of enrollment or attempted enrollment in an FLVS course. Non-H/H students were enrolled in an average of 4.6 courses (SD = 5.8. median = 3, mode = 1).

Finding #1: Students designated as H/H performed similarly to non-H/H designated counterparts across core content areas

Courses in which A-F grades were generated (n = 922 for H/H; n = 2,381,607 for non-H/H) were evaluated to compare student outcomes across all course enrollment. Overall, students designated as H/H received grades that did not significantly differ from non-H/H students. In other words, while non-significance cannot be interpreted as support for no difference between groups, H/H students in this sample performed similarly, even given challenges associated with chronic illness or disabilities, see Table 2.

Table 2

Graded performance by course instance (H/H vs Non-H/H designated students, 2012–2018).

H/H Students			Non-H/H Students
Outcome	Frequency	Percent	Outcome	Frequency	Percent	Z	p	adj p (Benjimini and Hochberg)**
A	481	52.17%	A	1,284,619	53.94%	1.16	.28	.28
B	266	28.85%	B	733,520	30.80%	1.64	.19	.28
C	125	13.56%	C	279,801	11.75%	2.90	.08	.14
D	31	3.36%	D	52,899	2.22%	5.52	.01	.05
F	19	2.06%	F	30,768	1.29%	4.27	.03	.08

** Critical p values adjusted to address family-wise error.s

This finding needs to be contextualized within a broader understanding of the types and rigor of courses being taken by H/H students. Table 3 presents course completion data for the 10 most frequent course registrations by H/H students as well as comparative data for non-H/H students. Two outcomes are apparent. First, H/H students enrolled in similar core courses as their non-H/H counterparts. Standard diploma requirements in Florida include English/Language Arts, Math, Science, Social Studies (including government and economics), Physical Education (e.g., HOPE in the table below), and Fine Arts. H/H students demonstrate similar levels of course completion compared to non-H/H students in most core topics. The second evident result from this table relates to course selection and functionality of H/H students. In addition to core courses, H/H students take and complete life-skills courses like Drivers Education in relatively the same manner as their non-H/H peers. In sum, H/H students took the same types and rigor of courses and still performed similarly to their non-H/H counterparts in this study.

Table 3

Performance by course instance for the 10 most frequent course registrations by H/H students (with comparison to Non-H/H designated students) 2012–2018.

Course	H/H Instances	H/H Completion	H/H Non-Completion	Proportion Complete	Non-H/H Instances	Non-H/H Completion	Non-H/H Non-Completion	Proportion Complete	Pa	adj p (Benjimini and Hochberg)b
Driver Education/Traffic Safety–Classroom	145	80	65	55%	459,070	280,672	178,398	61%	0.142	NA
Algebra 1	108	39	69	36%	191,866	49,916	141,950	26%	0.016	0.14
English 1	105	21	84	20%	150,789	39,894	110,895	26%	0.134	NA
Biology 1	99	21	78	21%	135,004	35,488	99,516	26%	0.25	NA
Spanish 1	95	33	62	35%	278,820	122,388	156,432	44%	0.072	NA
World History	92	25	67	27%	175,048	56,821	118,227	32%	0.27	NA
Economics with Financial Literacy	86	47	39	55%	67,722	33,926	33,796	50%	0.39	NA
Algebra 2	81	29	52	36%	177,607	61,948	115,659	35%	0.86	NA
United States Government	80	22	58	28%	77,858	35,205	42,653	45%	0.002	0.02
HOPE—Physical Education (Core)	78	49	29	63%	326,285	181,749	144,536	56%	0.2	NA

a: All comparisons were conducted using a Z-test of proportion.

b: Critical p values adjusted to address family-wise error.

Finding #2: Student course enrollments resulting in a grade were significantly different between H/H students and non-H/H students

Of the 2,534 H/H course enrollments, 36.4% (n = 922) resulted in a final grade ranging between “A” and “F” (Table 4). Comparatively, 43.5% of non-H/H student enrollments (n = 2,281,607) resulted in a grade. When analyzed, these data suggest that courses taken by H/H designated students were 25.9% (95% CI: 2.5–97.5%) less likely to result in grade generation as compared to courses taken by non-H/H students (p < .01; Table 4).

Table 4

Non-grade outcomes by course instance (H/H v non-H/H designated enrollments, 2012–2018).

H/H Designated Course Instances			Non-H/H Course Instances
Outcome	Frequency	Percent	Outcome	Frequency	Percent	|z|	p	adj p (Benjimini and Hochberg)a
NAb	578	35.86%	NA	1,635,820	53.0%	13.75	< .001	< .001
NAcc	3	0.19%	NAc	10,760	0.3%	1.1	0.27	0.27
Wd	472	29.28%	W	363,249	11.8%	21.84	< .001	< .001
WNGe	50	3.10%	WNG	177,898	5.8%	4.58	< .001	< .001
WFf	131	8.13%	WF	133,810	4.3%	7.5	< .001	< .001
WPg	248	15.38%	WP	416,121	13.5%	2.25	0.001	0.048
NULLh	130	8.06%	NULL	351,326	11.4%	4.18	< .001	< .001

a: Critical p values adjusted to address family-wise error.

b: NA: Student had verification from guidance but was never assigned to a teacher. This status occurs when student does not reply to course request message. FLVS subsequently removes the course request. Student will need to re-register.

c: NAc: Student was assigned an instructor, but was removed from course (may be initiated by teacher or student). Please note: This often occurs when students do not respond to welcome call attempts by their teacher.

d: Withdrawn (W/WNG): Student has been withdrawn during the 14-day drop/add period with no penalty. No credit is awarded.

e: WF: Student withdrew from course with a grade of less than 60% after the 14-day drop/add period expired. No credit is awarded.

f: WP: Student withdrew from course with a 60% or higher grade after the 14-day drop/add period expired. No credit is awarded.

g: NULL: No data provided.

Student completion rates in online courses may be low for a variety of reasons [41]. For H/H designated students, course instances resulting in non-graded outcomes were most frequently due to failure on the part of the student or family to complete their enrollment (despite having authorization from the school of record; 35.9%) or withdrawal from the course during the 14-day drop/add period (29.3%). A complete list of non-grade outcomes by course instance between H/H and non-H/H students is presented in Table 5.

Table 5

H/H vs. non-H/H designated outcomes by course instance (grade generation vs. non-grade generation).

H/H Enrollments/Instances		Non-H/H Enrollments/Instances
n (%)		n (%)		P
Grade	922 (36.4%)	Grade	2,381,607 (43.53%)	<0.01
Non-Grade	1,612 (64.00%)	Non-Grade	3,088,984 (56.47%)

Finding #3: H/H student completion rates were positively correlated with two important aspects of enrollment

On average, course completion rate for H/H students was 0.36 for all courses. That number climbs to 0.56 when examining courses where five or more students were enrolled suggesting that the more courses taken by the H/H student translates to a higher likelihood of completion. This translates to a statistically significant, positive correlation between student enrollments and completion ratios (r = .79, p < .01) suggesting that the presence of peers in an online classroom is associated a higher likelihood of completion. Similar analyses were conducted on course completion by student. These data provide evidence that, on average, the average rate of course completion on a per H/H student is .49 (sd = .37), but when reviewing the completion ration of H/H students with five or more course instances (n = 140), that number climbs to .62 (sd = .29). This translates to a statistically significant, positive correlation between student enrollments and completion ratios (r = .75, p < .01), suggesting that the more courses taken by the H/H student translates to a higher likelihood of completion.

Discussion

K-12 online schooling continues to expand, evolve, and become a mainstay in education around the world. It saw significant growth during the COVID-19 pandemic, which impacted parent, teacher, and student perspectives of online learning. For instance, COVID has encouraged many parents to consider alternatives to traditional means of education, particularly the care-givers of students who may have health concerns such as those with respiratory disease or who are immunocompromised [42-46].

However, even with the increased recent focus, since the inception of K-12 online education, there has been little attention paid to supporting the needs of students with chronic illnesses or disabilities [47]. There are few studies of students who have been afforded school accommodations specific to their healthcare needs [24]. This is due to myriad barriers to research including different data systems, different definitions of health care needs compared to educational needs, and a lack of grade standardization across educational institutions. Specific to virtual schools, prior research related to students with disabilities frequently relied on convenience sampling, qualitative data, or parents’ willingness and ability to communicate their child’s health status and learning outcomes [19]. The studies that do exist provide evidence that learners with special healthcare needs comprise a significant subset of the population of students attending K-12 online schools in the United States [25].

The present study used a rigorous inclusion criterion (hospital/homebound status) to identify an extremely vulnerable, high risk population. These criteria allowed the research team to reduce concerns for self/parent-selection bias, convenience sampling, and survivorship bias. In doing so, this study represents the first, systematic study of a large virtual schooling population that compares traditional (non-H/H designation) students to those with legally documented health care needs.

Each of the three outcomes of this study lends important insight into the study of H/H students taking online courses for their educational continuity. First, H/H students were as successful in online schooling as their non-H/H counterparts in this study. This included both functional (e.g., driver’s education) classes and nearly all core courses (e.g., Algebra and Economics). These results support prior, descriptive, research that provided evidence that FLVS H/H students achieved similar grade associated outcomes [19, 23–25, 48]. This means that practitioners and parents should consider K-12 online schooling as a valid opportunity for students who are unable to attend in person.

It is worth noting that not every H/H student will be successful, just like not every non-H/H student is successful in either face-to-face or online schooling. In this study, H/H students had a significantly different course-to-completion percentage (36.4%) than their non-H/H counterparts (43.53%). However, H/H students taking online classes in this study were more successful when taking multiple courses. Parents, practitioners, and advisors should consider this when enrolling H/H students in online courses.

Broader implications and future research

H/H students accounted for less than 0.1% of total FLVS course instances during the six years associated with this analysis. The reality is that H/H students represent a population underserved by many education systems, including online education. The low enrollments here may point to a lack of awareness of the opportunity that online schooling can provide. Data findings suggest that practicing pediatric healthcare professionals should be made aware of the positive potential outcomes for their patients.

There are several areas for future and related research. First, the data analyses provided evidence that H/H students who participated in five or more courses were more likely to complete a course. Similarly, those courses that had more than five H/H student enrollments during the study period were also more likely to result in H/H student completions. It is not enough to determine this happened; researchers need to further explore why this happened. Such outcomes would then impact policy recommendations for course enrollment of H/H students (e.g., many states have a requirement that all students participate in at least one online course prior to high school graduation).

A second area for future investigation relates to differences in registrations, enrollments, and de-enrollments of courses. H/H designated students were significantly more likely to withdraw from a course than non-H/H designated students (p < .01). This was true regardless of whether the student withdrew before or after the 14-day drop/add period and irrespective of whether they had a passing or failing grade at the time of withdrawal. The data presented in this study are not able to explain this discrepancy. Possible causes include improvement in the students’ health allowing for a return to their traditional schooling environment, academic challenges unrelated to health, or a decline in student health. Future research should include interviews of H/H students—both those who have completed courses and those who were unable to complete courses—to better understand learner experiences.

Conversely, among non-H/H designated students, 53% of course instances without grades are associated with incomplete registration processes; that is, the student had verification from their guidance office, but was never assigned to a teacher. This status occurs when the student or parent does not reply to course request message. The online school (in this case, FLVS) subsequently removes the course request. It is noteworthy that the rate associated with incomplete registrations was significantly lower within the H/H population (p < .001), which, again, reflects an area for future investigation. Recent research provides evidence that the odds of student disengagement and subsequent non-completion in an online learning environment drop by 50% during first 25–50 minutes of use [49]. Future research could examine specific practices to support H/H students during this timeframe.

A final area for subsequent research relates to pediatric investigations of H/H online students in terms of both disease/disability management and overall mental health. Child health professionals need to understand the educational outcomes of their patients as they do health outcomes; and, at a minimum, they need to understand intended goals for their patients when they document their medical necessity. Certainly, educational outcomes will be less prioritized than medical outcomes and procedures that are lifesaving, yet child health providers cannot lose sight of this important goal at a time when children are surviving (and surviving well) many of the conditions they might not have survived even a decade or two earlier.

Having acknowledged these educational interests, literature surrounding medical outcomes and clinical trials may not necessarily overlap with online schooling research. Yet there are promising opportunities for increased collaboration. For instance, clinical research has provided evidence that innovative technologies like virtual reality can significantly support pain management, and a further outcome could be educational attainment (e.g., Malloy & Milling) [50]. Public health research has also provided evidence that social network communities (like those presented in online learning management systems) can provide significant support for mental health, a common reason for choosing virtual schooling [51]. Yet there is scarce interprofessional research to date that takes the next step and examines the impact of virtual schooling and online education for adolescent mental health and positive medical outcomes like pain or disease management.

Limitations

It is important to acknowledge limitations associated with this study. This study explored data from one virtual school, thus limiting generalizability. FLVS does not collect private health information about its students; therefore, the analysis presented here did not include information about morbidities or acuity. Analyses also excluded demographic information, which could have resulted in inadvertent identification. It also did not include behavioral variables related to student use of online learning materials (i.e., time on task and task repetition). These exclusions limited our understanding of the H/H population. Finally, our comparison population may have included children living with disabilities and special healthcare needs who do not qualify or have not received hospital/homebound designation.

To further address these limitations, future research should include a more granular analysis of students, student wellness, and learning outcomes. Future research should also incorporate methods such as survival analysis, commonly employed in sociology and epidemiology, but increasingly found in educational studies to explore and better predict learning attrition and the efficacy of interventions to address it [44, 52, 53]. Importantly, there is likely a selection bias associated with students, both those qualified for H/H and ‘typical’ students who enroll in K-12 online schools, resulting in less racial and ethnic diversity and more affluence than students in traditional learning environments. Finally, it is critical to note that this analysis did not incorporate the varied nature of course curricula as an independent variable. Curricula, even same subject matter curricula, can vary significantly over time and between instructors.

Implications for policy

The H/H student population represents a vulnerable, underserviced, and understudied population and a unique opportunity for research into the intersection of health and education. Fundamental questions about the impact of learning on health and quality of life outcomes in the short and long-term, appropriate teacher training, educating healthcare professionals, best practices for delivering homebound services, and H/H student performance and engagement in online and non-online environments need further exploration_msocom_1 [15, 25, 54]. Additionally, we have little understanding of the affordances and challenges associated with learning in an online environment for H/H students, which likely vary considerably based upon the unique needs of the child. Nonetheless, this study is one of the first projects to bridge these streams of literature and illustrate that H/H students have educational success with online schooling. Healthcare providers may find that online school can serve as a permanent intervention that comes alongside students in ways other interventions have fallen short.

10 Dec 2021

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Rong Zhu, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In ethics statement in the manuscript and in the online submission form, please provide additional information about the records used in your retrospective study. Specifically, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent. If patients provided informed written consent to have data from their medical or educational records used in research, please include this information.

3. Thank you for stating the following financial disclosure:

"The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

At this time, please address the following queries:

a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution.

b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

c) If any authors received a salary from any of your funders, please state which authors and which funders.

d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

4. Thank you for stating the following in the Competing Interests section:

"April Fleetwood is employed by Florida Virtual School."

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests).  If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

5. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability.

Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

6. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study compared the performance of hospital homebound students with regular students enrolled in an online learning school. The topic of this study is definitely worth investigating, as very little evidence exists on the academic performance of hospital homebound students in education – especially in online educational courses – compared against a cohort of regular students. That being said, the topic of this study is of relevance to a broad international field of researchers and may contribute significant findings to the field. However, the current version of the manuscript lacks several important aspects such as (a) a documentation of the data analysis in the methods section, (b) a clear inclusion criteria section of how the samples were drawn and (d) a description of the online school. Not every reader will be aware of the online school and thus, it should be described in more detail (a separate section). Based on these key aspects, it is difficult to interpret the findings currently. Finally, the current version of the manuscript misses some important contributions regarding online learning systems which may be cited in a revised version of the manuscript.

Introduction:

The introduction is well-written, and I have only a few comments here.

Typo page 2:

The sentence: “Meeting the educational needs…” appears to miss some words at the end. I recognized some more typos while reading the manuscript. The authors should proof read the manuscript.

The author may want to provide an overview or “the present study” section at the end of the introduction, which helps the reader to grasp an overview of what this study is about.

Methods:

Online schools and Online Courses:

The online school should be described in more detail. No information at all in provided on which courses are offered, for which age/grade level, which subjects, etc. It should also be noted whether students receive feedback or how students get learning materials assigned. At the current version of the manuscript, no information at all is provided on how an “online course” looks like or what is meant by and “online course”.

Inclusion criteria:

A separate inclusion criteria section which describes the inclusion process may help the reader to grasp the inclusion process of the two cohorts better.

Data Analysis:

The data analysis and the motivation behind the data analysis is not described at all. Currently, the manuscript lacks any description of why the analyzes were conducted. Why did the authors examine these analyses and not others? Or were other analyzes performed but did not reach significance and were thus not reported? The motivation of why the dependent/independent variables were selected should be noted.

The statistical software the analyzes were carried out with should be noted.

Results:

The authors should provide more descriptive variables on the data. What was the mean number of courses students enrolled in (range of enrolled courses)? How long does one course take? How many sessions does one course include (range)? How many different courses exist in this online school? Were all courses analyzed? More information here is needed.

Online courses in general vary heavily and information on this is necessary to compare this study with others describing performance outcomes in online courses.

Non-significant findings cannot be interpreted as support for no differences between groups! The authors should note this and may want to carry out a Bayesian Analysis to support their point or compute a Bayes Factor for their findings.

Discussion:

The authors analyzed whether students remained enrolled or not. They may want to hint towards recent attempts addressing this by means of survival analyzes. The lack of a systematic and persistent usage of online courses is one of the main problems of online courses and attempts on how to increase the enrollment for longer periods of time is one of the most challenging future questions in the field of online courses (Bacca-Acosta & Avila-Garzon, 2021; Grutzmacher et al., 2019; Plank et al., 2008; Spitzer et al., 2021; Villano et al., 2018).

The authors note the boom in online learning courses around the world due to the COVID-19 pandemic. They may want to bolster this argument by adding some more references to it providing evidence that several online learning environments experienced a usage boom since march 2020 (Meeter, 2021; Spitzer et al., 2021; Tomasik et al., 2020; Velde et al., 2021).

The authors may want to note that they did not control for any behavioral variables in their analysis such as time on task, number of problem sets, or repetition attempts students may have used. Future research may investigate differences in usage patterns between the two cohorts.

References

Bacca-Acosta, J., & Avila-Garzon, C. (2021). Student engagement with mobile-based assessment systems: A survival analysis. Journal of Computer Assisted Learning, 37(1), 158–171. https://doi.org/10.1111/jcal.12475

Grutzmacher, S. K., Munger, A. L., Speirs, K. E., Vafai, Y., Hilberg, E., Duru, E. B., Worthington, L., & Lachenmayr, L. (2019). Predicting attrition in a text-based nutrition education program: Survival analysis of Text2bhealthy. JMIR MHealth and UHealth, 7(1), 1–10. https://doi.org/10.2196/mhealth.9967

Meeter, M. (2021). Primary school mathematics during Covid-19: No evidence of learning gaps in adaptive practicing results. Trends in Neuroscience and Education, 25(October), 100163. https://doi.org/10.1016/j.tine.2021.100163

Plank, S. B., DeLuca, S., & Estacion, A. (2008). High school dropout and the role of career and technical education: A survival analysis of surviving high school. Sociology of Education, 81(4), 345–370. https://doi.org/10.1177/003804070808100402

Spitzer, M. W. H., Gutsfeld, R., Wirzberger, M., & Moeller, K. (2021). Evaluating students ’ engagement with an online learning environment during and after COVID-19 related school closures : A survival analysis approach. Trends in Neuroscience and Education, 25, 100168.

Tomasik, M. J., Helbling, L. A., & Moser, U. (2020). Educational gains of in-person vs. distance learning in primary and secondary schools: A natural experiment during the COVID-19 pandemic school closures in Switzerland. International Journal of Psychology, 56(4), 566–576. https://doi.org/10.1002/ijop.12728

Velde, M. van der, Sense, F., Spijkers, R., Meeter, M., & ... (2021). Lockdown Learning: Changes in Online Study Activity and Performance of Dutch Secondary School Students during the COVID-19 Pandemic. https://psyarxiv.com/fr2v8/

Villano, R., Harrison, S., Lynch, G., & Chen, G. (2018). Linking early alert systems and student retention: a survival analysis approach. Higher Education, 76(5), 903–920. https://doi.org/10.1007/s10734-018-0249-y

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

23 Jan 2022

To the Editor and Reviewers,

I am pleased to submit this revised manuscript, Hospital Homebound Students and K-12 Online Schooling, for review. I appreciate the insightful suggestions made by the editor and reviewers, we have worked to address each suggestion to the best of our ability. The authors received no specific funding for this work.

In response to a comment by the editor, we have included a more detailed explanation of data availability. Importantly, our ability to provide access to the data is limited by Florida law. Family Educational Rights and Privacy Act (FERPA), 20 U.S.C. § 1232g; 34 C.F.R Part 99; and chapter 119 and section 1002.22, Florida Statutes states: Individuals and organizations that receive data through the research request process have strict obligations to protect that data and must meet the requirements of both federal and state laws in their usage and handling of that data. The parties receiving this data have separate obligations based on these provisions and must protect the confidentiality and privacy of this information and may not disclose this information to others.

The Florida Department of Education requires all requests to comply with the Family Educational Rights and Privacy Act’s (FERPA’s) research exception (34 CFR Part 99.31[6][i]), which requires that the disclosure of information be limited to organizations conducting studies for, or on behalf of, educational agencies. In addition, the research must meet one of the following three allowable purposes: 1) to improve instruction; 2) to develop, validate or administer predictive tests; or 3) to administer student aid programs. Requests must meet one of these criteria to be approved.

In sum, the data is available via public request via Florida’s Government-in-the-Sunshine law. This provides the right of access to governmental documents at the state and local level. Data access can be facilitated using the Florida Department of Education External Research Data Request Process: https://www.fldoe.org/accountability/accountability-reporting/external-research-requests/. While this is not standard, we feel that this does not alter our adherence to PLOS ONE policies on sharing data and materials.

I have attached a table (see uploaded revision letter) that lists each suggestion, along with our response, inclusive of page numbers where the narrative addressing the response can be found.

Submitted filename: revisionletter.doc

Click here for additional data file.

18 Feb 2022

Hospital Homebound Students and K-12 Online Schooling

PONE-D-21-36433R1

Dear Dr. Black,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Rong Zhu, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors addressed all of my comments and I see no major flaws. Major parts of the manuscripts have been revised in great detail and all major points I previously raised have been addressed. Congrats!

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

15 Mar 2022

PONE-D-21-36433R1

Hospital Homebound Students and K-12 Online Schooling

Dear Dr. Black:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Rong Zhu

Academic Editor

PLOS ONE