Research Proposal Title
Studying the Effects of School Connectedness on Mental Health
in Students with Dyslexia after a School Transition
INTRODUCTION
This study seeks to examine the effects of school connectedness on mental health in students with dyslexia following the primary-secondary school transition in Singapore. Students with dyslexia—a medicalized disorder manifested by difficulties in conventional learning—are likely to face challenges in academic performance and social support, which can lead to poorer mental health outcomes. These challenges are likely amplified following a school transition, where all students, but particularly those with dyslexia, have to adapt to an entirely new academic and social environment not familiar with their specific needs.
It is thus vital to compare the perceived school connectedness and mental health between students with and without dyslexia before and after the school transition. This will reveal whether students with dyslexia are significantly more disadvantaged in their self-rated mental health, whether it can be attributed to school connectedness, and which aspects of school connectedness—belonging, participation, affirmation, judgment, fairness, access to help—are significant. Such findings will generate insights into adjustment difficulties for all students and inform recommendations on how schools, teachers, and allied educators can better respond to the unique challenges students with dyslexia face.
LIT REVIEW
Effects of School Connectedness on Mental Health
Shochet et al. (2006) found that school connectedness—measured by the extent students felt accepted, valued, respected, and included—predicted depressive symptoms for both genders, anxiety for girls, and general functioning for boys a year later. Prior mental health problems did not predict subsequent school connectedness. While there is gendered difference, it establishes a causal link between general social relations in schools and one’s overall mental health. McNeely and Falci (2004) distinguished the roles of teachers and peers in their conceptualization of school connectedness—measured by perceived teacher support and social belonging. Perceived fairness of the teacher is associated with lower initiation into risky health behaviours, while social belonging is unexpectedly not protective. This suggests that high connectedness may not necessarily produce better health behaviours and thus outcomes. Instead, its effect on risk behaviours is contingent on group norms.
Bond et al. (2007) distinguished between school and social connectedness in a three-wave longitudinal study. School connectedness is measured in terms of commitment to school, relations with teachers, relations with peers, opportunities to participate, and belonging, and social connectedness in terms of having someone to talk to, to depend on when angry or upset, and trust with private feelings and thoughts. They found that having high levels of both connectedness yielded the best outcomes, whereas having low school connectedness and high social connectedness was associated with a significantly higher risk of anxiety and depressive symptoms. The latter is surprising, as it suggests that emotional social support is an outlet for more negative mental health symptoms. However, this finding is weakened by the conflation of relations to school, teachers, and peers in the measurement of school connectedness, when each is likely to have very divergent effects.
School Transition as Stressful Life Event
Within the life course of the school is embedded various critical transitions. “Transitions, both normative and nonnormative, in combination with the skills and experiences individuals have and the adaptations they choose in the face of transitions, can serve as “turning points” and change life course trajectories.” (Benner & Graham, 2009, p. 357) In their eight-wave longitudinal study on multi-ethnic urban youth in the United States, transitions were found to pose immediate and persistent disruptions to both psychological functioning and grades. The transition was most challenging for the African-American and Latino minority groups, coinciding with the significant decline in their ethnic representation. The effects of this ethnic incongruence highlights how health outcomes emerge from the interactions between persons and contexts.
Trajectories in the domain of school are also intertwined with other domains of social life, thus transitions may reproduce disadvantages in one’s social background. Vaz et al. (2014) found that students from socially disadvantaged backgrounds scored lower for academic competence and mental health functioning than their counterparts before and after the primary-secondary transition. This highlights cumulative disadvantage, where “transitions and the ease with which individuals navigate transitions influence developmental outcomes in a cumulative fashion.” (Benner & Graham, 2009, p. 357-358) However, the effects of transitions are not only dependent on network factors, but also support factors. Stadler et al. (2010) found that school support provides an effective buffer against victimization for both males and females, with its importance increasing with age. They also found that parental support protects against maladjustment, especially in peer-victimized girls.
Dyslexia as Risk Factor
Students with dyslexia—”a disorder manifested by difficulty in learning to read, despite conventional instruction, adequate intelligence and sociocultural opportunity” (Critchley, 1999, p. 361)—are highly susceptible to negative health outcomes. A Canadian study (Wilson et al., 2009) found that those with self-reported learning difficulties are over “twice as likely to report high levels of distress, depression, anxiety disorders, suicidal thoughts, visits to mental health professionals, and poorer overall mental health.” (p. 24) These outcomes are particularly likely when making school transitions. Mortimore and Crozier (2006) found that the difficulties British students with dyslexia face in classrooms differed over the life course. In primary school, their main difficulties were reading, spelling, and handwriting. In higher education, their main difficulties were note-taking, organization of essays, and expressing ideas in writing. The outcomes for students with dyslexia across transitions are thus dependent on strong school support.
Such support is hardly limited to pedagogical assistance; dyslexia is not merely a physical condition, but a socially constructed role. Dyslexia is a medical label which is de-stigmatizing and beneficial from a system perspective. By ruling out stigmatized explanations for lower competence, such as low motivation or intellectual capacity, it can improve the individual’s self-esteem and also justify a greater allocation of school resources (Solvang, 2007). These can improve the academic competence of students with dyslexia, reducing stress. Yet this label also places certain individuals in a deviant role, where they may find themselves ostracized and bullied by classmates (Ingesson, 2007). Those with dyslexia are disposed to a conundrum of failure (Tanner, 2009), where public failure (humiliation via responses to speaking and writing problems), family failure (guilt to family), and personal failure (abiding fear) are all shaped by emergent social relations. Despite a charitable understanding of students with dyslexia, an incongruity in perceptions of help between provider and recipient (Shumaker & Brownell, 1984) may be a salient problem. Classmates may not be empathetic to the real needs of those with dyslexia, thus weakening the latter’s perceived access to social support.
Gaps in Literature
First, measures of school connectedness are often either too limited or not well-defined. Schools represent an ecology where social relations are dynamic and involve multiple parties whose roles should neither be ignored nor conflated. Second, while longitudinal studies have been conducted on students beginning before a school transition, the samples are inevitably spread across many schools and fail to account for transition supports that schools may be implementing (Benner & Graham, 2009). Even with network factors accounted for, such studies greatly underplay the role of school ecology in shaping social connectedness and mental health. Given that secondary schools constitute the site where students have to negotiate stressful transitions, it may be productive to control the sample at the secondary school level and rely on retrospective measures for tracing developments over time. Third, while many dyslexia studies have been done, research in Singapore is minimal. This is important because perceptions of dyslexia may significantly vary between Western and Asian countries like Singapore. Moreover, the recent surge in attention to students with special educational needs marks Singapore as an interesting case study.
SINGAPORE CONTEXT
Dyslexia appears to be gaining recognition in Singapore, with rising numbers of students seeking diagnosis and enrolling in the main literacy programme at the Dyslexia Association of Singapore (DAS) (Teng, 2016). According to DAS, about 20,000 primary and secondary students in Singapore have dyslexia (Lee, 2017). They are considered as having mild special educational needs (SEN) and mandated to attend mainstream schools. Since 2005, the Ministry of Education (MOE) has created a new para-professional role called the Allied Educator (Learning and Behavioural Support) (AED(LBS)) (Lim, Wong, & Tan, 2014, p. 125), designed to cater to the needs of students with mild SEN. Their tasks include providing in-class support, designing small-group interventions, working with school management to plan and execute school-wide SEN support programmes, and collaborating with parents and external agencies (MOE, 2017). These para-professionals undergo a one-year full-time diploma programme which provides them the specialized expertise to support those with learning difficulties. They number over 400 now, with at least one in each of the 190 primary schools and 69 secondary schools in Singapore (“The Big Read”, 2015). This promises to increase the perceived teacher support for students with dyslexia.
The number of regular teachers trained in special needs has also soared from 80 to 3,000 over a decade (“The Big Read”, 2015), but the proportion remains at around 10-20% of teachers in each primary and secondary school (Wong et al., 2013). There thus remains a great degree of role ambiguity for AED(LBS) professionals, who not only must deal with various stakeholders but do so in a low status and minority position, are expected to help with relief and administrative work, while also needing to pick up teaching skills and medical knowledge on their own (Lim, Wong, & Tan, 2014). The challenges they face are likely to impede their effectiveness in meeting the specific needs of students with mild SEN, the majority of which have either dyslexia or attention deficit hyperactivity disorder (ADHD). Moreover, the visibility of AED(LBS) professionals in the classroom makes the students’ conditions more apparent. The status inequality between teachers and these professionals may also produce emergent effects on how students with dyslexia are regarded and treated by their classmates, thus affecting their peer relations.
In a cross-sectional study on 99 Primary 3 students and 99 matched peers across 13 schools in Singapore, Yang (DAS, 2017; Lee, 2017) found that students with dyslexia are more prone to anxiety, depression, and low self-esteem. She identified academic performance, social support, and school belonging as significant protective factors to these mental health outcomes, which corroborates most research findings outside Singapore. She also reported that teachers rated students with dyslexia with significantly lower pro-social behaviours. However, such teacher-reported measures may be inaccurate due to their limited understanding of students with dyslexia. Moreover, having data only at one time interval means this research cannot draw causal relationships between these measures. It also does not complicate the role of school transitions as a stressful event exacerbating the challenges faced by students with dyslexia. Further research is thus needed to understand their difficulties even with the laudable efforts at integration.
RESEARCH QUESTION
How do the various aspects of school connectedness (SC) each influence mental health (MH) in students with dyslexia as a result of the primary-secondary school transition in Singapore?
METHOD
Population of Study
This will be a quantitative study conducted on the population of Secondary 1 students in Singapore. This population is chosen because they have just made the transition from primary school, following a national exam. It is also preferable to conducting research on older students, due to increasing attrition of the dyslexia student population and divergence of educational paths. Moreover, the presence of AED(LBS) professionals in secondary schools represents a huge opportunity for making recommendations that helps in changing outcomes when still highly achievable.
Conceptualization
Mental Health (MH)
There are two models which explain how social relationships affect health. The main effect model posits that social relationships are beneficial regardless of stress levels, whereas the stress-buffering model proposes that support is related to well-being only for those under stress (Cohen, Underwood, & Gottlieb, 2000; Kawachi & Berkman, 2001). It has been suggested that social networks work via main effects and social support work as buffers to stress. However, Shumaker and Brownell (1984) contend that social support influences health regardless of stress, albeit differently. It is thus vital for research on social support to measure not only stress levels, but also self-esteem, which indicates general mental health functioning regardless of stress levels.
School Connectedness (SC)
The proliferation of concepts like social support, social networks, social capital, and social participation has obfuscated the exact meanings of research findings (Shumaker & Brownell, 1984, p. 12). Berkman et al. (2000) provides a useful conceptual model to sort out these different levels of analysis. Social-structural conditions (macro)—culture, politics, social change, socioeconomic factors—condition the extent, shape, and nature of social networks (meso)—network structures and characteristics of ties—which provide opportunities for psychosocial mechanisms (micro)—social support, influence, engagement, access to resources—to influence health outcomes through behavioural, psychological, and physiological pathways (p. 847).
I take as a starting point this definition offered by Shumaker and Brownell (1984): “Social support is an exchange of resources between at least two individuals perceived by the provider or the recipient to be intended to enhance the well-being of the recipient.” (p. 13) While taxonomies of social support—e.g. emotional, instrumental, informational, and appraisal support (Berkman et al., 2000)—are useful, they are theoretical constructs based on the presumed knowledge of detached observers. As well-being is contingent on subjective views, it is more relevant to focus on how social support is perceived by the recipient, rather than the provider or researcher.
In the context of schools, social support can be differentiated into two main sources: peers and teachers (or allied educators). While some studies have divided it into school connectedness and social connectedness, these are not consistent and have yielded unnecessary conflation of actors, as in the case of Bond et al. (2007). For clarity, I will use the term ‘school connectedness’ to include various factors, which are to be analyzed not as a composite, but independently. These factors will be measured from the standpoint of students.
Operationalization
Mental Health (DV)
There are two main measures corresponding with the main effect and stress-buffering models: 1) self-esteem, and 2) stress. The ‘stress ‘measure will be divided into a) school work, and b) social environment, to reflect the dual nature of challenges that students with dyslexia likely face. Respondents will be asked to give ratings on a 7-point Likert scale (‘Strongly Disagree’ to ‘Strongly Agree’) for both their current experience in Secondary 1 (T2) and their experience 1 year ago in Primary 6 (T1).
School Connectedness (IV)
There are six measures, four of which pertain to relations with peers: 1) social belonging, 2) social participation, 3) social affirmation, 4) social judgment. The remaining measures pertain to relations with educators (both teachers and allied educators): 5) fairness, 6) access to help. All of these are self-rated measures, where respondents will be asked to give ratings on a 7-point Likert scale (‘Strongly Disagree’ to ‘Strongly Agree’) for their current experience in Secondary 1 (T2).
Control Variables
Other factors that may also affect mental health will be controlled, including physical health, household income, gender, race, perceived status of AED(LBS) professionals, and school prestige (tiered by minimum admission scores). The last two factors may predict aspects of school connectedness. Except the last factor, these data will be obtained from the students’ questionnaires due to limited resources. There is no control for academic performance, because grade structures and assessment rubrics likely vary across schools and classes, and it is prohibitive to obtain grade data across subjects. Instead, this factor is partially accounted for in the ‘stress’ measure, assuming a correlation of school performance and stress. Moreover, this measure reflects the standpoint of students, unlike grades.
Data Collection
Given the figures from news sources, the average population of students with diagnosed dyslexia in each primary and secondary school is about 75. As the actual numbers are likely to vary significantly across schools, I will seek data on the actual or estimated enrollment figures of students with dyslexia in secondary schools from the MOE or DAS. Only those schools with at least 60—an average of 15 per secondary school year—will be included in the sampling frame.
Using data on entry scores based on the nationwide Primary School Leaving Examination (PSLE) from the MOE, these secondary schools will be sorted into three tiers (Tier 1; Tier 2; Tier 3). Two schools will be randomly picked from each of these tiers, to study how experiences may vary across schools with varying academic climates. The principals of these selected schools will be contacted for express permission to conduct this quantitative research on Secondary 1 students. I will then obtain data on the physical classes these students attend, and pick a matched control group of students in the same classes with similar individual characteristics (i.e. gender/race). Research assistants will then administer surveys on all of these students midway into the school year, and be on hand to provide assistance when required.
The stratified sampling used in this study makes it possible to examine the effects of performance-based sorting on social connectedness. Furthermore, it is more productive to sample schools at the secondary level with retrospective measures, rather than at primary level in a longitudinal study. While a retrospective measure may be less accurate, it provides an instructive look at students’ own perceptions on school transitions. Furthermore, all Primary 6 students sit for the highly stressful PSLE, which serves as a control for their retrospective responses regardless of the primary school they studied in.
Data Analysis
Univariate
The data for each measure of MH can be compiled and processed to compute changes from before to after the school transition (T2–T1). They can then be analyzed for the presence of significant differences (p < 0.05) in the following measures:
- MH (T2–T1)
- MH in students with dyslexia vs MH in students without dyslexia (T2–T1)
- SC in students with dyslexia vs SC in students without dyslexia (T2)
Given the context of the PSLE, it is plausible that students with or without dyslexia may actually report more positive levels of mental health at T2 (1). Hence, it is more important to examine whether there is a significant difference in the average change (T2–T1) in mental health between those with and without dyslexia (2). As the control group is matched only at secondary school level, school connectedness will only be compared at T2 (3).
Bivariate
By examining the association between school connectedness at T2 and the change in mental health from T1 to T2, it is possible to attribute causality to school connectedness in the secondary school.
- SC (T2) x MH (T2–T1) in students with dyslexia
- SC (T2) x MH (T2–T1) in students with dyslexia (Tier 1; Tier 2; Tier 3)
- SC (T2) x MH (T2–T1) in students without dyslexia
- SC (T2) x MH (T2–T1) in students without dyslexia (Tier 1; Tier 2; Tier 3)
This can be first analyzed for the sample of students with dyslexia (4), and the sub-samples of students with dyslexia in each tier of schools sorted by academic entry points (5). As stated, mental health may not decrease. It is thus necessary to compare the results with the control group (6; 7), which may reveal more about the disadvantages faced by students with dyslexia across a school transition. The associations may not be positive either. These relationships will then need to be tested while controlling for other factors.
Multivariate
For each of the bivariate models, crosstabs can be performed with the insertion of categorical variables such as gender and race. Multivariate regression analysis can also be performed with the additional insertion of variables such as household income and academic tier.
CONTRIBUTION
The provision of support for students with dyslexia has largely been confined to individual families and individual schools in Singapore. Little attention is given to school transitions as a risk factor that may significantly worsen social and health outcomes for these students. This study will yield findings on whether students with dyslexia adapt significantly worse than students without dyslexia following a transition, and which aspects of social connectedness can be identified as causes. Such findings will generate generalizable insights into the nature of adjustment difficulties for students with or without dyslexia. Furthermore, by grouping schools into three tiers based on academic entry points, it is possible to examine diversity in school experiences, implicating relationships between academic competence, social connectedness, and mental health within specific school ecologies. This will inform recommendations on how schools, teachers, and allied educators can implement targeted interventions to meet the unique challenges students with dyslexia face within their specific academic climates. Finally, this study may serve as a productive model for future research in other cities, that can be more sensitive to school environments post-transition than longitudinal methods.
References
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