Kiuru, N., Lerkkanen, M., Niemi, P., Poskiparta, E., Ahonen, T. & Poikkeus, A. Et Al. (2013).

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Reading Research Quarterly, 48(4)pp. 349–368 | doi:10.1002/rrq.53 © 2013 International Reading Association

A B S T R A C T

This study examined the role of reading disability (RD) risk and environmen-tal protective factors in reading fluency in grade 4. The sample consisted of 538 Finnish-speaking students. Kindergarten measures included the students’ risk for RD based on poor achievement in phonological awareness and letter knowledge as well as information on the three control variables: nonver-bal ability, level of parental education, and gender. Measures in grades 1–3 included environmental protective factors: classmate reports of peer accep-tance; teacher reports of positive affect for the student; and mother, father, and teacher reports of partnership between the home and the school. The students were also tested on their reading fluency in grade 4. The results showed, first, that environmental protective factors, namely, high levels of peer acceptance and positive teacher affect, uniquely predicted students’ improved reading fluency in grade 4, after controlling for RD risk, nonverbal ability, level of parental education, and gender. Second, when controlling for the effects of single environmental protective factors, a higher overall number of environmental protective factors predicted students’ improved reading fluency in grade 4. Third, RD risk predicted lower peer acceptance, less positive teacher affect, and lower parent–teacher partnership in grades 1–3. Finally, the effect of RD risk on subsequent reading fluency was partially mediated through the overall number of protective factors in the student’s interpersonal environment.

In today’s society, f luent reading is a necessary skill for academic success as well as for garnering information from printed and elec-tronic sources (Zeffiro & Eden, 2000). Individuals with reading

disabilities (RD) not only have academic difficulties during their school years (Cunningham & Stanovich, 1998) but also typically man-ifest lower educational attainment and earnings in adulthood (Blackorby & Wagner, 1996; Savolainen, Ahonen, Aro, Tolvanen, & Holopainen, 2008). The transactional theory of risk and adaptation (Garmezy, Masten, & Tellegen, 1984; Rutter, 2007), and protective models of resilience (Fergus & Zimmerman, 2005) suggest that child outcomes are determined by the interplay between risk and protective factors rather than risk factors alone.

Risk for reading disability determined by familial background for dyslexia or by deficits in early language development has been shown to result in poor reading skills (e.g., Lyytinen et al., 2004; Pennington & Lef ly, 2001; Puolakanaho et al., 2007; Scarborough, 1990, 1998; Snowling, Gallagher, & Frith, 2003; Snowling, Muter, & Carroll, 2007; Torppa, Lyytinen, Erskine, Eklund, & Lyytinen, 2010). However, as not all children with this kind of risk end up with deficient literacy skills, it is important to ask whether protective factors could predict fluent reading despite the risk. Students lacking positive and

Noona Kiuru

Marja-Kristiina LerkkanenUniversity of Jyväskylä, Finland

Pekka Niemi

Elisa PoskipartaUniversity of Turku, Finland

Timo Ahonen

Anna-Maija Poikkeus

Jari-Erik NurmiUniversity of Jyväskylä, Finland

The Role of Reading Disability Risk and Environmental Protective Factors in Students’ Reading Fluency in Grade 4

350 | Reading Research Quarterly, 48(4)

supportive relationships with adults and peers are often at risk for academic problems (e.g., Goodenow, 1993; Ladd, Birch, & Buhs, 1999), whereas students with posi-tive relationships with teachers and peers in the early school years are more likely to show better school achievement (Furrer & Skinner, 2003).

Previous research has at least two limitations. First, most research has been conducted on general achieve-ment instead of specific academic skills, such as reading (for an exception, see T. Aro et al., 2009; Fleming, Cook, & Stone, 2002). Second, only a few of the studies focus-ing on academic outcomes have simultaneously investi-gated severa l environmental factors and their cumulative effects. These studies have mainly involved adolescents rather than young students (e.g., Rosenfeld, Richman, & Bowen, 2000) or relied on student self-reports on their social relations (e.g., Laursen, Furman, & Mooney, 2006; Wentzel, 1998). The aims of the pres-ent study were threefold:

1. To investigate the extent to which three specific environmental protective factors (i.e., peer accep-tance, teachers’ positive affect for the student, partnership between home and school) have unique and cumulative effects on students’ read-ing fluency in grade 4

2. To investigate the extent to which a student’s early risk for RD predicts the three environmental pro-tective factors

3. To investigate the extent to which the association of early risk for RD with subsequent reading flu-ency is mediated via the three environmental pro-tective factors

Students’ Reading Fluency and RDFluent reading is the ability to read with accuracy, speed, and proper expression (Kuhn & Stahl, 2003; National Institute of Child Health and Human Development, 2000). Recent definitions of f luent read-ing skill also include comprehension (e.g., Rasinski, 2004). In sum, the definition of f luency comprises the whole reading process, from word decoding to word meaning and the construction of phrase- and passage-level meaning. Phillips and Torgesen (2006), however, argue that individual differences in reading speed can theoretically influence overall reading fluency and that it is reasonable, therefore, to use a somewhat narrower definition of fluency, such as rate and accuracy in read-ing. For example, Jenkins, Fuchs, van den Broek, Espin, and Deno (2003) showed that fluency in word recogni-tion explained individual differences in text reading f luency in fourth grade. Reading rate has also been

shown to correlate highly with reading comprehension (e.g., Fuchs, Fuchs, Hosp, & Jenkins, 2001) and to be one of the most reliably measured aspects of f luency (e.g., Wolf & Katzir-Cohen, 2001).

Reading disabilities is typically defined as difficul-ties in word decoding (Lyon, Shaywitz, & Shaywitz, 2003); however, especially in the later phases of reading acquisition, RD are manifested as slow, dysfluent, and inaccurate reading. In particular, studies in more trans-parent orthographies than English have shown that the primary problem for RD is f luency rather than word reading accuracy (e.g., M. Aro & Wimmer, 2003; de Jong & van der Leij, 2003; Wimmer & Mayringer, 2002). The proportion of children at risk for RD has been reported to be as high as 17–20% (Grigorenko, 2001).

Other factors, such as gender, parental education, and general ability, have also been shown to be associ-ated with reading fluency. Gender differences favoring girls have been reported in literacy tasks in the early school years (e.g., Chatterji, 2006; Robinson & Lubienski, 2011) and been explained by boys’ lower interest in read-ing, boys’ lower frequency of reading activities (Logan & Johnson 2009), girls’ better verbal abilities, and different gender role expectations (Gambell & Hunter, 1999). Previous research also indicates that parents’ level of education predicts children’s reading f luency (e.g., Lewis, 2000; McClelland & Morrison, 2003) and is a stronger predictor than family income or socioeconom-ic status (see Melhuis, 2010).

One explanation for the link between parental edu-cation and children’s reading fluency is the association that has been observed between low parental education and low levels of cognitive and learning stimulation at home (e.g., literacy resources, shared reading, parental teaching of reading; Guo & Harris, 2000; Lee & Croninger, 1994). Lower cognitive and learning stimula-tion at home, in turn, has been shown to be linked to poorer vocabulary and language development, thereby also affecting literacy development (Scarborough & Dobrich, 1994; Torppa et al., 2007). In addition, general ability has been shown to be linked with reading skills (e.g., Ferrer, Shaywitz, Holahan, Marchione, & Shaywitz, 2010). In this study, we used nonverbal reasoning as a measure of ability.

This study was conducted in Finland, where compul-sory education begins in the year of the child’s seventh birthday. Six-year-olds are entitled to kindergarten education for one year before embarking on their nine-year comprehensive school career. Finnish kinder-garten education focuses on learning through play, and instruction is not divided into subject area lessons. Although students’ development in phonological awareness and letter knowledge is supported in kinder-garten, systematic instruction of decoding does not begin before grade 1, when students move to primary school.

The Role of Reading Disability Risk and Environmental Protective Factors in Students’ Reading Fluency in Grade 4 | 351

Reading instruction leans heavily on phonics and blend-ing sound–spelling patterns. Compared with many other languages, learning to read in Finnish is relatively easy because it has a highly regular orthography and simple syllabic structure (Seymour, Aro, & Erskine, 2003). However, even a highly consistent orthography does not guarantee that literacy acquisition will be smooth for all students. In Finnish, RD are typically identified in flu-ency rather than accuracy (e.g., Holopainen, Ahonen, & Lyytinen, 2001), as has also been reported in other ortho-graphically consistent languages (e.g., van Daal & van der Leij, 1999; Wimmer, 1993).

Environmental Protective Factors and Reading SkillsIn the previous literature, protective factors have been conceptualized as factors that serve to ameliorate or modify the effects of risk (Garmezy et al., 1984; Luthar, 1993; Masten et al., 1988; Rutter, 1987). According to Vitaro, Brendgen, Larose, and Tremblay (2005), variables that interact with an early risk factor may be considered protective factors if they mitigate the link between this risk factor and the outcome in question, but they may be considered compensatory factors if they exert main effects that counteract the risk factor, thus reducing the overall risk. Gutman, Sameroff, and Cole (2003) have drawn a distinction between protective factors and pro-motive factors: Protective factors are linked with more positive outcomes in a high-risk sample but not in a low-risk sample, whereas promotive factors contribute to bet-ter outcomes for all students. Typically, protective factors are identified on the basis of their nature rather than their effects. This feature differentiates them from the interactive concept of resilience that, according to Rutter (2012), refers to reduced vulnerability to environmental risk experiences or overcoming an adversity, and needs to be inferred by analyzing the outcomes of individuals who have experienced a similar adversity.

Protective factors can be related to the individual (e.g., good cognitive skills, easy temperament) or to the environment (e.g., degree of environmental support; for a review, see Masten & Coatsworth, 1998; Motti-Stefanidi, Asendorpf, & Masten, 2012). In the present study, the focus is on environmental protective factors operationalized as peer acceptance, positive teacher affect, and partnership between home and school. These factors were chosen based on their previous identifica-tion as key supportive factors of early school adjustment (e.g., Christenson, 2004; Ladd et al., 1999) and, hence, can be assumed to promote optimal reading develop-ment during the first years of primary school.

Theories on social motivation (Deci & Ryan, 2000; Eccles, Wigfield, & Schiefele, 1998; Goodenow, 1993;

Skinner, Kindermann, Connell, & Wellborn, 2009; Wentzel, 1998) suggest that supportive interpersonal relationships serve as a resource for promoting students’ academic skills, including reading fluency. It has been suggested that students are more likely to internalize positive school-related values and attitudes in a develop-mental context characterized by support and warmth (Baumeister & Leary, 1995; Wentzel, 2002). It has also been proposed that social interactions and affective experiences in relationships are internalized as relation-al schemata (for a review, see Hartup & Laursen, 1999) that help the individual orient to, evaluate, and address environmental demands, including learning demands at school. Supportive relationships at school can also promote students’ learning via stress reduction (Boulton, Trueman, & Murray, 2008; Ladd et al., 1999). In addition, supportive relationships have been found to increase a sense of relatedness, which in turn predicts stronger engagement and achievement at school (Furrer & Skinner, 2003; Zimmer-Gembeck, Chipuer, Hanisch, Creed, & McGregor, 2006).

Acceptance by classroom peers is a key supportive factor in the classroom context (Ladd et al., 1999). Peer acceptance is defined as experiences of being liked or accepted by the members of one’s peer group (Bukowski & Hoza, 1989). It includes companionship and having a sense of connection to the larger peer group (Ladd & Kochenderfer, 1996). Peer acceptance enables students to engage in rather than withdraw from classroom learning and activities (Buhs & Ladd, 2001; Ladd, Kochenderfer, & Coleman, 1997; Lubbers, Van Der Werf, Snijders, Creemers, & Kuyper, 2006) and gives them access to group activities and collaborative learn-ing experiences (Buhs & Ladd, 2001; Ladd et al., 1999), which promote their academic achievement. A wealth of evidence indicates that students benefit from being accepted by their peer group in regard to their academic competence (e.g., Buhs, Ladd, & Herald, 2006; Flook, Repetti, & Ullman, 2005; Guay, Boivin, & Hodges, 1999; Ollendick, Weist, Borden, & Greene, 1992; O’Neil, Welsh, Parke, Wang, & Strand, 1997; Wood, 2007), but less is known about the associations of peer acceptance with the development of specific skills, such as reading (for exceptions, see Li, 1985). The recent results by Morgan, Farkas, and Wu (2012) suggest that the topic deserves attention.

Another important supportive factor in the class-room context is the quality of the teacher–student relationship. According to the extended attachment the-ory, teacher–student relationships can be conceptualized as secondary attachment bonds because they have many of the properties and functions of parent–child attach-ment relationships (Howes, 1999; Pianta, 1999). A posi-tive relationship with a teacher, characterized by high degrees of warmth, support, and sensitivity, provides a


safe context for the development of academic compe-tences, including reading skills (Birch & Ladd, 1997; Connor, Morrison, & Katch, 2004; Perry, Donohue, & Weinstein, 2007). Previous studies have indicated that close and supportive relations between teachers and stu-dents are linked to high overall academic achievement (e.g., Hamre & Pianta, 2001; O’Connor & McCartney, 2007; Osterman, 2000; Pianta, La Paro, Payne, Cox, & Bradley, 2002). Students have also been reported to show more rapid language and literacy skill development (Curby, Rimm-Kaufman, & Ponitz, 2009; Hughes, & Kwok, 2007; Kiuru, Aunola, et al., 2012; National Institute of Child Health and Human Development Early Child Care Research Network, 2000) when the quality of the teacher–student relationship is good.

Cooperation between the child’s parents and teach-ers is also important for students’ academic develop-ment (Christenson, 2004). The collaborative aspect of parent–teacher relationships has been referred to by terms such as trust (Adams & Christenson, 2000), home–school involvement (Epstein & Dauber, 1991; Fantuzzo, Tighe, & Childs, 2000), family–professional partnership (Summers et al., 2005), and parent–school connection (Copple & Bredekamp, 2009; see also Powell, Son, File, & San Juan, 2010). Parent–teacher relations have been shown to be at their most beneficial for stu-dents’ academic development when they represent a genuine partnership, including mutual respect, trust, and two-way communication between parent and teacher, along with shared values and expectations about how to support the child (Christenson, 2004; Epstein & Sanders, 2002; Foot, Howe, Cheyne, Terras, & Rattray, 2002; Keen, 2007; Keyes, 2002; Lerkkanen, Kikas, Pakarinen, Poikonen, & Nurmi, 2013; Souto-Manning & Swick, 2006; Vickers & Minke, 1995). Previous research has shown that parents’ school-based involvement (e.g., presence at parent–teacher confer-ences) in kindergarten predicted better literacy skills in the subsequent primary school years (e.g., Dearing, Kreider, Simpkins, & Weiss, 2006; Miedel & Reynolds, 1999). However, not all studies have found a similar effect of parental school involvement on reading skills (e.g., see Powell et al., 2010).

In line with the transactional models of child devel-opment (Sameroff & Fiese, 2000; Sameroff & MacKenzie, 2003), accumulation of environmental risk or protective factors might have effects on students’ literacy acquisi-tion (T. Aro et al., 2009; Gutman et al., 2003; Sameroff, Seifer, Barocas, Zax, & Greenspan, 1987). Scholars who take an expansive view of the interpersonal context of development argue that students’ academic outcomes are a function of support received across a variety of relationships at school (e.g., Furrer & Skinner, 2003; Laursen & Mooney, 2008). In addition to additive effects (i.e., unique effects of different environmental

protective factors; Ladd & Burgess. 2001), different envi-ronmental protective factors may also have cumulative effects (cf. Deater-Deckard, Dodge, Bates, & Pettit, 1998), meaning that a higher overall number of protec-tive factors might predict better reading f luency over and above the effects of single protective factors.

Previous empirical research on adolescents has revealed that individuals embedded in a network of rela-tionships that are uniformly supportive are better adjust-ed (Laursen et al., 2006; Scholte, van Lieshout, & van Aken, 2001), have better grades (Rosenfeld et al., 2000), and higher academic motivation (Ryan, Stiller, & Lynch, 1994) than do adolescents embedded in a network of rela-tionships that are low in support. Yet, some studies have failed to demonstrate any cumulative effects (e.g., Wentzel, 1998). As far as we know, the present study is among the very first attempts to investigate whether sev-eral protective environmental protective factors together could promote primary school students’ reading fluency.

Whereas most studies have focused on the impacts of interpersonal relationships on students’ academic skills, these skills may equally well have an impact on children’s relationships with significant others. The transactional perspective on child development sug-gests that a child can both shape and be shaped by the context (Sameroff & Fiese, 2000; Sameroff & MacKenzie, 2003). Child characteristics, such as academic difficul-ties, evoke various responses from significant others that can have far-reaching consequences for students’ further achievement and school careers. Research has shown that students with reading difficulties (Gadeyne, Ghesquière, & Onghena, 2004; Kiuru, Poikkeus, et al., 2012) have more difficulties than other students do in gaining peer group acceptance. There is some evidence to suggest that teachers provide more individual learn-ing support for students who are struggling with learn-ing literacy or math (Nurmi, Viljaranta, Tolvanen, & Aunola, 2012) and that parents typically have more fre-quent teacher contact when their children are doing poorly in school (Izzo, Weissberg, Kasprow, & Fendrich, 1999). However, despite providing increased learning support, teachers have been found to report more nega-tive affect and less closeness in their relationships with low-achieving students (for a review, see Nurmi, 2012).

Research Questions and HypothesesThe present study examined the following three research questions (see Figure 1):

1. To what extent do environmental protective fac-tors (i.e., peer acceptance, positive teacher affect, partnership between home and school) predict


students’ reading fluency in grade 4 when control-ling for RD risk, gender, parental education, and nonverbal ability measured in kindergarten? First, it was expected (hypothesis 1a) that high levels of peer acceptance (e.g., Flook et al., 2005; O’Neil et al., 1997), positive teacher affect (e.g., Connor, Son, Hindman, & Morrison, 2005; Hughes, & Kwok, 2007), and partnership between home and school during grades 1–3 (e.g., Dearing et al., 2006) would promote reading fluency in grade 4. Second, it was also assumed that different envi-ronmental protective factors would have a cumu-lative effect, so the presence of a higher number of environmental protective factors would predict better reading fluency (hypothesis 1b; Rosenfeld et al., 2000).

2. To what extent does RD risk measured in kinder-garten predict protective factors in students’ interpersonal environment (i.e., peer acceptance, having a supportive teacher, a close partnership between home and school) during grades 1–3? It

was expected (hypothesis 2a) that RD risk would predict low subsequent peer acceptance (e.g., Gadeyne et al., 2004; Kiuru, Poikkeus, et al., 2012) and low positive teacher affect (e.g., Nurmi, 2012). It was also expected (hypothesis 2b) that the over-all number of environmental protective factors would be lower among students at risk for RD than those not at risk (Fleming et al., 2002).

3. To what extent does risk for RD measured in kin-dergarten predict students’ reading f luency in grade 4? To what extent is the effect of RD risk on subsequent reading fluency mediated via protec-tive factors in students’ interpersonal environ-ment? First, it was expected that reading disability risk would predict students’ lower reading fluency in grade 4 (hypothesis 3a; Gallagher, Frith, & Snowling, 2000; Lyytinen et al., 2004; Snowling et al., 2007). Second, it was expected that the effect of RD risk on subsequent reading fluency would be partly mediated through protective factors in the student’s interpersonal environment: RD risk

FIGURE 1Theoretical Model

Grade 4

Environmental protective factors• Peer acceptance

• Positive teacher affect for the student• Home–school partnership

Kindergarten Grades 1–3

Nonverbal ability

Gender

Risk for readingdisabilities Reading fluency

Level ofparental education


was expected to predict a lower number of protec-tive factors in the student’s interpersonal environ-ment, which in turn was expected to predict lower subsequent reading fluency (hypothesis 3b).

MethodParticipants and ProcedureThis study is part of the extensive longitudinal First Steps study (Lerkkanen, Niemi, et al., 2006), in which a community sample of Finnish students (n = 1,880) have been followed up from kindergarten to grade 4. The aims of the follow-up are to investigate the develop-ment of academic skills and motivation of students by taking into account the transactional effects of teachers’ and parents’ beliefs and practices, students’ disabilities, and the support provided in the classroom by teacher– student and peer relationships. The participants in this study were 538 students (230 girls, 308 boys) and their parents (466 mothers, 327 fathers) and teachers (n = 130–136) resident in three medium-sized towns and one municipality: two in Central Finland, one in Western Finland, and one in Eastern Finland. At the beginning of the study, the children’s parents and teach-ers were asked for their written consent to participate. By signing the consent, they also agreed that the mate-rial collected could be used for scientific research, including publications.

Originally, the sample consisted of a more intensive-ly followed subsample of 608 students drawn from the whole sample of 1,880 students (mean number of study participants per classroom across grades 1–4 = 3.21, SD = 0.12). To be included in the present study, informa-tion on reading fluency in grade 4 had to be available. Application of these criteria led to a final sample of 538 students. The number of schools and classrooms from which the target students were drawn varied across grade (kindergarten: 117 schools, 191 classrooms; grade 1: 97 schools, 157 classrooms; grade 2: 75 schools, 168 classrooms; grade 3: 76 schools, 172 classrooms; grade 4: 76 schools, 174 classrooms). The students’ average age was 73.97 months (SD = 3.53 months, median = ~6 years) prior to the study (fall of kindergar-ten). The sample was fairly representative of the Finnish population (Statistics Finland, 2007). In 6% of the fami-lies (6% in general population), the parents had not been educated beyond comprehensive school, 30% had completed a secondary education (30% in general popu-lation), 36% had a bachelor’s degree or vocational college degree (35% in general population), and 28% had a master’s degree or higher (29% in general population).

Attrition analyses were carried out to compare stu-dents for whom information on reading f luency in grade 4 was available (i.e., participants in the study,

n = 538) with students for whom information in kinder-garten was available but who had dropped out by grade 4 (n = 70). The results revealed that those who stayed in the study had a higher level of nonverbal ability (M = 13.92, SD = 3.45, as assessed by spatial relations task in kindergarten) than dropouts did (M = 12.90, SD = 3.03, t(601) = -3.16, p = .002, Cohen’s d = .37). Furthermore, students with RD risk were overrepre-sented among dropouts (39%) compared with partici-pants (22%,χ2(1, n = 606) = 9.58, p = .002, Cramer’s V = .13). However, students who stayed in the study and those who dropped out did not differ by gender or parental education. The bias of the study sample in grade 4 toward students with higher nonverbal ability and students without RD risk is likely to have a conser-vative effect on the associations found.

MeasuresData on students’ reading disability risk, based on letter knowledge, phonological awareness, and control factors (i.e., nonverbal ability, parents’ education, gender), were obtained during the spring of kindergarten (March 2007). Data on environmental protective factors (i.e., peer acceptance, teachers’ positive affect for the student, partnership between home and school) were gathered in grades 1 (March 2008), 2 (March 2009), and 3 (March 2010), and the outcome variable, reading f luency, was measured in grade 4 (March 2011).

Risk for RDThe risk for later RD was determined on the basis of initial phoneme identification (indicator of phonologi-cal awareness) and letter knowledge subtests drawn from the ARMI test battery (Lerkkanen, Poikkeus, & Ketonen, 2006). Initial phoneme identification and let-ter knowledge have consistently been identified as the best predictors in the early identification of RD risk in the highly transparent Finnish orthography (Lerkkanen, Ahonen, & Poikkeus, 2011). In the initial phoneme iden-tification task, the students were presented with four pictures of objects and their names. The students were instructed as follows: “Here are pictures of omena, suk-ka, reppu, and lintu [an apple, sock, bag, and bird]. Listen carefully. Which word starts with the sound /o/: omena, sukka, reppu, lintu?” The sum score was based on the number of correct items (maximum value of 10, Kuder–Richardson reliability = .74). Letter knowledge was evaluated by asking the students to name 29 letters shown in random order. One point was given for each correct response (maximum 29 points, Kuder–Richardson reliability = .95).

Risk for RD was defined as joint occurrence of low phonological awareness (i.e., scored clearly below age level in initial phoneme identification, ≤15th percentile)


and poor letter knowledge (≤15th percentile; Kiuru, Poikkeus, et al., 2012; Lerkkanen et al., 2011; see also Lyytinen et al., 2004). The cutoff point was the 15th per-centile, which is close to 1 standard deviation below the mean in a normal distribution and close to common knowledge in Finnish primary school that about 10–15% of school entrants show a relative delay in their reading acquisition. For their kindergarten data, Poskiparta, Niemi, and Vauras (1999) used the lowest quartile, which resulted in half of the putative at-risk students being false positives in no need of remedial instruction. Niemi et al. (2011) used the cutoff point of -1 standard deviation for the above reading-related skills at the beginning of grade 1. In the spring of grade 1, these at-risk students scored 3.3 standard deviations below the mean on the measure of word reading.

Control VariablesFirst, parents were asked about their level of vocational education (1 = no further qualification after compre-hensive school; 7 = licentiate or doctoral degree). The highest parental educational level (mother’s or father’s) was used in the analyses. Second, gender was coded as 1 = girl and 2 = boy. Third, nonverbal ability (i.e., non-verbal reasoning) was measured in kindergarten with the spatial relations task from the Woodcock and Johnson (1977) test battery. The test requires identifying the subset of pieces needed to form a complete shape, with multiple-point scored items (i.e., “Two of these pieces (a, b, c, d) go together to make this (e). Tell me which two pieces.”). This test measures the ability to use spatial visualization (i.e., to apprehend spatial forms or shapes and rotate or manipulate them in the imagina-tion). A maximum of 31 tasks can be attempted within the three-minute time limit (maximum score: 31, Kuder–Richardson reliability = .72).

Peer Acceptance in the ClassroomStudents’ peer acceptance was measured in grades 1–3 by using a sociometric nomination procedure. Students were asked to circle (from a list of all the students in the class) the names of those with whom they most like to spend time during breaks (Poikkeus, 2008). The num-ber of permitted nominations varied by class size. If the number of students in the class was 12 or greater, then three nominations were permitted. If the number of stu-dents in the class was 8–11, then two nominations were permitted. If the number of students in the class was less than eight, then one nomination was permitted. Peer acceptance represents the number of nominations each student received, standardized by class size. Sociometric nominations provide valid, stable, and reliable assess-ments of peer acceptance during early childhood (Bukowski, Cillessen, & Velasquez, 2012). Because our

focus was on students’ overall peer acceptance across grades 1–3, a mean was calculated from the peer accep-tance scores in those grades. The Cronbach’s a reliabil-ity was .63.

Teachers’ Positive Affect for the StudentThe teachers rated their affect for the target students on a 5-point scale (1 = not at all, 5 = very often) in grades 1–3. Teachers’ positive affect was measured with four items:

1. “When you teach this child, how often do you feel satisfied?”

2. “When you teach this child, how often do you feel joy?”

3. “When you teach this child, how often do you feel helpless?”

4. “When you teach this child, how often do you feel stress and frustration?”

The two negatively worded items were reverse scored. Teacher report of positive emotions toward a student has been found to be closely related to sensitive teaching practices and the closeness of the teacher–student rela-tionship (Spilt & Koomen, 2009). Individual average scores were computed at each time point (grade 1 Cronbach’s a = .84, grade 2 Cronbach’s a = .85, grade 3 Cronbach’s a = .87). Because our focus was on over-all positive teacher affect for the student across grades 1–3, a mean was calculated from the positive teacher affect scores in those grades. The Cronbach’s a reliabil-ity was .77.

Partnership Between Home and SchoolThe home–school partnership was evaluated from the perspectives of the child’s mother, father, and teacher using two scales assessing central aspects of partner-ship: the Trust Scale (Adams & Christenson, 2000) and the Family Involvement Scale (Fantuzzo et al., 2000). First, parents’ trust in their child’s teacher was assessed using the short version of the Trust Scale (for the valid-ity of the short scale, see Lerkkanen et al., 2013). Parents rated six items on their trust in their child’s teacher (e.g., “I am confident that my child’s teacher does a good job of encouraging my child’s sense of self-esteem.”; “[…] does a good job of encouraging my child to have a posi-tive attitude toward learning.”; “[…] is receptive to my input and suggestions.”) on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).

Second, parents’ involvement was assessed by the short version of the Family Involvement Questionnaire by Fantuzzo et al. (2000), focusing on activities and behaviors that parents engage in at school with their


children. Such behavior includes volunteering in the classroom, going on class trips, and meeting with other parents in or outside of school to plan some activities, events, or fund-raising. This kind of cooperation between teacher and parents is also encouraged in the Finnish national curriculum. Parents rated seven items (e.g., “I participate in the planning of some classroom activities with the teacher.”; “I talk with my child’s teacher about how I can support my child with school assignments.”) on a 5-point Likert scale (1 = not at all, 5 = very often; mothers: grade 1 Cronbach’s a = .83, grade 2 Cronbach’s a = .82, grade 3 Cronbach’s a = .80; fathers: grade 1 Cronbach’s a = .85, grade 2 Cronbach’s a = .84, grade 3 Cronbach’s a = .84).

In turn, teachers were asked to evaluate their part-nership with students’ parents using the short version of the Family Involvement Scale by Fantuzzo et al. (2000), which was adapted for use with teachers. Teachers rated seven items on their involvement with parents (e.g., “Parents participate in planning some classroom activi-ties with me.”; “I talk with parents about how they can support their child with school assignments.”) on a 5-point Likert scale (1 = not at all, 5 = very often; grade 1 Cronbach’s a = .66, grade 2 Cronbach’s a = .69, grade 3 Cronbach’s a = .71). Because our focus was on the overall home–school partnership during grades 1–3, a mean was calculated from the mothers’, fathers’, and teachers’ reports in those grades. The Cronbach’s a reli-ability was .71.

Cumulative Environmental SupportA variable tapping cumulative environmental support was calculated as follows. First, dichotomous variables were created by using the highest 25th percentile (~0.75 SD) as a cutoff point to indicate whether students have each of the three types of protective factors (i.e., high peer acceptance, high positive teacher affect, high part-nership between home and school). Each participant was then classified into one of the following groups on the basis of the number of protective factors identified as high in support: 0 = no environmental protective fac-tors, 1 = one environmental protective factor, 2 = two environmental protective factors, or 3 = three environ-mental protective factors.

Reading FluencyStudents’ reading fluency in grade 4 was measured with three different reading tests. The first test was a group-administered subtest of the nationally normed reading test battery ALLU—Ala-asteen lukutesti (ALLU—Reading Test for Primary School; Lindeman, 1998). In this speeded test, a maximum of 80 items can be attempted within the two-minute time limit. Each item includes a picture and four phonologically similar words

(e.g., työ, myös, vyö, syö). The task is to draw a line between the picture and the word that semantically matches it. The number of correct responses was used to measure achievement in this word reading task (Kuder–Richardson reliability = .95).

In the second test (the Word Chain Test; Nevala & Lyytinen, 2000; see also Lyytinen et al., 2004), the students were instructed to recognize the words in a total of 10 word chains, including four to six words written together, and mark the word boundary with a vertical line. The time limit for accomplishing the task in grade 4 was one minute and five seconds. A student received 1 point for each correctly separated word (maximum 40 points). The number of correct respons-es was used to measure achievement in this reading task (test reliability = .78).

The third test was the Test of Sentence Reading Efficiency and Comprehension (Wagner, Torgesen, Rashotte, & Pearson, 2009; for the Finnish version, see Lerkkanen & Poikkeus, 2009). In this speeded test, a maximum of 60 sentences can be attempted within the three-minute time limit. Students were instructed to read the sentences one by one and evaluate whether they are true or false by circling the correct alternative. The number of correct responses (maximum 60 points) was used to measure achievement in this reading task (Kuder–Richardson reliability = .94).

A reading fluency composite score, tapping reading skills in grade 4, was formed as follows. First, the scales of the three reading tests were standardized. Then, a mean score was calculated from the scores of all three tests. The Cronbach’s a for the reading skills composite score was .84.

Analysis StrategyThe research questions were examined using path modeling. All models were estimated using the Type = Complex approach (Muthén & Muthén, 1998–2013). This method estimates the models at the level of the whole sample, correcting distortions of standard errors and χ2-values in the estimation caused by cluster-ing of observations (classroom differences). The analy-ses were carried out along the following steps. First, descriptive information was inspected. Second, to investigate the impacts of RD risk and environmental protective factors on reading fluency in grade 4 and the evocative effects of RD risk on environmental factors, a path model corresponding to the theoretical model pre-sented in Figure 1 was estimated. This model also included the control variables (i.e., nonverbal ability, parental education, gender). Third, a variable measur-ing cumulative environmental support was added into the previous model to investigate whether the overall number of environmental protective factors uniquely


promotes reading fluency in grade 4 when controlling for the effects of the single environmental protective factors (for a similar procedure that can be used in investigating cumulative risks, see T. Aro et al., 2009). One-tailed significance testing was applied for testing the hypothetized associations.

The analyses were carried out using the Mplus pro-gram (Version 7; Muthén & Muthén, 1998–2013). Assuming missingness at random, the parameters of the models were estimated using the full-information maximum likelihood estimation with standard errors that are robust against nonnormal distributions (Muthén & Muthén, 1998–2013). The proportions of missing data ranged from 0% to 9% (M = 3.46%, SD = 0.03), and the covariance coverage of the data ranged from 86% to 100% (M = 95%, SD = 4%). Little’s (1988) MCAR test indicated that data were missing completely at random: χ2(69) = 84.49, p > .05. The good-ness of fit of the estimated path models was evaluated

according to the following four indicators: (1) chi-square test, (2) comparative fit index (CFI), (3) root mean square error of approximation (RMSEA), and (4) stan-dardized root mean square esidual (SRMR). A model fits the data well when the p-value associated with the χ2 test is nonsignificant. RMSEA values below .06, SRMR values below .08, and CFI values of close to .95 indicate a relatively good fit between the hypothesized model and the observed data (see also Hu & Bentler, 1999).

ResultsDescriptivesTable 1 shows the means and standard deviations of the observed variables separately for the students with and without RD risk. Table 2 presents the correlations between the predictor and outcome variables. Compared with the students not at risk for RD, the at-risk students

TABLE 1Descriptive Information Separately for Students With and Without Risk of Reading Disabilities (RD; N = 538)

Variable

RD risk (22%) No RD risk (78%)

t df Cohen’s dM SD M SD

Reading fluency (grade 4)

Reading Test for Primary Schoola 30.36 8.23 36.18 8.83 6.40*** 534 .68

Word Chain Testb 11.64 5.14 17.07 7.23 7.61*** 534 .88

Test of Sentence Reading Efficiency and Comprehensionc

39.33 9.14 45.10 9.26 5.98*** 534 .63

Composite reading fluency −0.68 0.73 −0.01 0.85 7.78*** 534 .85

Protective social factor (grades 1–3)

Peer acceptance −0.24 0.68 −0.04 0.73 2.64** 499 .28

Positive teacher affect for the student

3.78 0.70 4.12 0.68 4.64*** 506 .49

Home–school partnership 3.01 0.30 3.08 0.32 2.12* 519 .23

Cumulative environmental support 0.33 0.60 0.60 0.76 3.26** 471 .40

Control variable (kindergarten)

Nonverbal ability 12.89 2.77 14.21 2.27 5.26*** 533 .52

Parents’ education 3.95 1.54 4.36 1.44 2.54* 489 .28

Gender

Girls 14% at risk: χ2(1) = 16.11, p < .001, Cramer’s V = .17

Boys 28% at risk

aLindeman, J. (1998). ALLU—Ala-asteen lukutesti [ALLU—Reading Test for Primary School]. The Center for Learning Research, University of Turku, Finland.bNevala, J., & Lyytinen, H. (2004). Sanaketjutesti [Word Chain Test]. Jyväskylä, Finland: Niilo Mäki Instituutti & Jyväskylän yliopiston Lapsitutkimuskeskus.cWagner, R.K., Torgesen, J.K., Rashotte, C.A., & Pearson, N.A. (2009). TOSREC: Test of Sentence Reading Efficiency and Comprehension. Austin, TX: Pro-Ed.*p < .05. **p < .01. ***p < .001.


in kindergarten had substantially poorer reading f lu-ency in grade 4. Further, the RD-risk students were gen-erally less accepted in their peer group, their teacher showed less positive affect toward them, the quality of the partnership between their parents and teachers was lower, and they generally had fewer environmental pro-tective factors. In turn, peer acceptance, teachers’ posi-tive affect for the student, and higher cumulative environmental support were related to better reading f luency in grade 4. In addition, the different environ-mental protective factors were positively correlated with each other: r (peer acceptance, home–school partner-ship) = .11, p = .01), r (positive teacher affect, home–school partnership = .13, p = .01, and r (positive teacher affect, peer acceptance) = .29, p < .001.

RD Risk, Environmental Protective Factors, and Later Reading FluencyNext, the path model corresponding to the theoretical model (see Figure 1) for RD risk, environmental protec-tive factors, and later reading fluency was estimated. The final model, containing statistically significant paths only, fit the data well: χ2(4, N = 538) = 1.67, p = .80, CFI = 1, RMSEA = .00, SRMR = .01. First, the results (see Figure 2) showed that RD risk in kindergarten predicted poorer reading fluency in grade 4 when controlling for the effects of the control variables (i.e., nonverbal ability, parental

education, gender) and those of the environmental pro-tective factors. Furthermore, peer acceptance and teach-ers’ positive affect for the student also predicted grade 4 reading fluency when controlling for RD risk, nonverbal ability, parental education, and gender. The more accept-ed a student generally was in his or her peer group and the more positive affect teachers reported toward a student during grades 1–3, the better student’s reading fluency was in grade 4. Partnership between home and school did not have any unique effect on reading fluency.

In the next step, the variable cumulative environmen-tal support (i.e., number of protective factors a student had) was added to the previous model. The results showed that when controlling for the effects of RD risk, nonverbal ability, parental education, gender, and the single environ-mental factors, cumulative environmental support con-tributed further to students’ reading fluency in grade 4 (standardized β = .16, p = .0035). In other words, the more environmental protective factors a student had during grades 1–3 (irrespective of the relationship domain), the better his or her reading fluency in grade 4 was.

The results presented in Figure 2 showed further that RD risk has some evocative effects on the school environment–related protective factors. RD risk nega-tively predicted peer acceptance, teachers’ positive affect, and partnership between home and school, when controlling for nonverbal ability, parental education, and gender: The RD students were less accepted, their

TABLE 2Correlations Between Predictors and Outcomes (N = 538)

Explanatory variable

Outcome variable

Peer acceptance (grades 1–3)

Positive teacher affect (grades 1–3)

Home–school partnership (grades 1–3)

Cumulative support

(grades 1–3)

Reading fluency

(grade 4)

Control variable (kindergarten)

Nonverbal ability .15*** .23*** .001 .13** .33***

Parents’ education .13** .19*** .13* .18** .17***

Gendera −.05 −.42*** .01 −.13* −.26***

Risk factor (kindergarten)

Risk for reading disabilities −.17** −.27*** −.13* −.24** −.45***

Protective social factor (grades 1–3)

Peer acceptance — — — — .22***

Positive teacher affect — — — — .33**

Home–school partnership — — — — .06

Cumulative environmental support

— — — — .28***

Note. When calculating the correlations, dichotomous variables were defined as categorical variables, and the other variables were defined as continuous.a1 = girl; 2 = boy.*p < .05. **p < .01. ***p < .001.


teacher showed less positive affect, and the quality of the partnership between their home and school was lower than among the students without RD risk. When the variable cumulative environmental support (i.e., num-ber of protective factors that a student has) was included in the model, the results showed that when controlling for the effects of the control variables, RD risk predicted a lower number of protective factors in the student’s interpersonal environment (standardized β = .11, p = .0095). In other words, problems in interpersonal relationships seemed to accumulate among RD-risk students.

Finally, we examined the extent to which the effects of RD risk in kindergarten on reading fluency in grade 4 are mediated via environmental protective factors. Figure 2 shows the results of the overall mediation mod-el regarding the direct path from RD risk to later read-ing fluency (x Æ y), as well as the paths from RD risk to

the environmental protective factors (x Æ m) and the paths from the environmental protective factors to later reading fluency (m Æ y). The results of the tests for sta-tistical significance of the indirect effects (x Æ m Æ y) carried out within the overall mediation model showed first that the effect of RD risk in kindergarten on subse-quent reading fluency was partially mediated through teachers’ positive affect for the student during grades 1–3 (estimate = −.03, SE = .02, p = .036): RD risk pre-dicted teachers’ lower reports of positive affect for the student, which in turn predicted poorer reading fluency in grade 4. Furthermore, when the variable cumulative environmental support (i.e., number of protective fac-tors that a student has) was included in the model, the results revealed that the effect of RD risk in kindergar-ten on subsequent reading fluency was partially medi-ated through cumulative environmental support during grades 1–3 (estimate = −.04, SE = .02, p = .0335): RD risk

Note. Paths are presented as standardized estimates.a1 = girl; 2 = boy.*p < .05. **p < .01. ***p < .001. +p < .10.

FIGURE 2Complex Model for Risk of Reading Disabilities, Grade 4 Reading Fluency, and Environmental Protective Factors

Nonverbal ability(kindergarten)

Gendera

Risk for readingdisabilities

(kindergarten)

Reading fluency(grade 4, R2 = .24)

Level of parental education

.21*** −.11**

−.20***

.11**.15***

Peer acceptance (grades 1-3, R2 = .04)

Positive teacher affect for the student

(grades 1–3, R2 = .19)

Home–school partnership

(grades 1–3, R2 = .03)

−.10**−.30***.17***

.13*

−.08*

.16***

.12*

.10*

.07+

−.08*


predicted a lower number of protective factors in the student’s interpersonal environment, which in turn pre-dicted poorer reading fluency in grade 4.

We also carried out multigroup analyses to examine whether RD risk moderates the effects of environmental protective factors on subsequent reading f luency. The results revealed, however, that the model fits did not sig-nificantly decrease (p > .05) when the paths were con-strained to be equal between the students with and without RD risk. In other words, the effects of environ-mental protective factors on subsequent reading fluency did not significantly differ between the students with and without RD risk.

DiscussionOnly a few attempts have been made to simultaneously examine the role of several environmental protective factors and their cumulative effects on students’ reading f luency. The results of the present study showed that two environmental factors (high levels of peer accep-tance and teachers’ positive affect for the student) con-tributed uniquely to reading f luency after controlling for previous RD risk and other control variables. Moreover, environmental protective factors had a cumulative effect on subsequent reading f luency: The more environmental protective factors a student had, the better his or her later reading f luency was. Furthermore, some evidence for evocative effects of RD risk was found: RD risk predicted lower peer accep-tance, lower teacher ratings of positive affect for the stu-dent, and poorer home–school partnership during the early grades of primary school. Finally, the effect of RD risk in kindergarten on later reading fluency was partly mediated through cumulative environmental support: RD risk predicted a lower number of environmental protective factors, which then predicted lower subse-quent reading fluency.

Environmental Protective Factors and Later Reading SkillsTheoretical perspectives on social motivation (e.g., Deci & Ryan, 2000; Eccles et al., 1998; Skinner et al., 2009) suggest that supportive interpersonal relationships can serve as a resource for promoting students’ academic skills. In accordance with theories related to social motivation, and our hypothesis 1a, our results showed that high peer acceptance (see also Flook et al., 2005; O’Neil et al., 1997) in grades 1–3 promoted good read-ing fluency in grade 4. Our finding on peer acceptance is in line with previous research on the predictive asso-ciation between peer acceptance and students’ general academic achievement (Buhs, 2005; Buhs et al., 2006;

Guay et al., 1999; Wood, 2007) but broadens it by show-ing that this association also holds for students’ reading skills.

Several mechanisms may underlie the result. First, because peer acceptance includes companionship and a sense of connection to a larger peer group, it provides stu-dents with a psychological connection to the school envi-ronment that empowers them to engage in rather than withdraw from classroom learning and activities (Buhs & Ladd, 2001; Ladd et al., 1997; Lubbers et al., 2006). This view is supported by previous evidence showing that stu-dents’ experiences of peer support and acceptance pro-mote their act ive classroom engagement and participation, further boosting their academic achieve-ment (Buhs et al., 2006; Furrer & Skinner, 2003; Ladd et al., 1999). Second, peer group acceptance may provide students with greater access to group activities and col-laborative learning experiences (Buhs & Ladd, 2001; Ladd et al., 1999), thereby promoting their reading skills.

Again, in accordance with theories related to social motivation and our hypothesis 1a (see also Connor et al., 2005; Hughes & Kwok, 2007), our results showed that teachers’ positive affect in grades 1–3 promoted good reading fluency in grade 4. There are several pos-sible explanations for this association. One relates to the attachment theory (Ainsworth, Blehar, Waters, & Wall, 1978; Bowlby, 1982). A warm and supportive teacher–student relationship during the first grades of primary school may provide students with emotional security in the classroom (Howes, 1999), thereby facilitating full concentration on learning. Second, teachers’ positive affect may also provide students with the kind of social support (e.g., Pianta, 1999) needed to remain motivated and engaged in learning tasks. A third possibility is that when the teacher–student relationship is positive, teach-ers show more sensitivity toward students’ individual learning needs in reading tasks. Some previous research indicates that high sensitivity shown by teachers toward their students’ individual needs promotes students’ reading development (Connor et al., 2004; Morrison & Connor, 2009). Future work on the role of teachers in students’ reading skills would profit from a more detailed investigation of aspects other than affection alone in teacher–student relationships, such as the extent of behavioral control and instructional support.

Contrary to hypothesis 1a, one of the three environ-mental protective factors (i.e., the level of the partnership between home and school) had no unique effects on grade 4 reading skills when controlling for the other fac-tors in the model. The results are inconsistent with those of Dearing and colleagues (2006), who found predictive associations between parents’ school-based involvement and children’s literacy skills. The results also differ from the theoretical notions of Pomerantz, Moorman, and Litwack (2007), according to which high quality of the


home–school partnership would highlight the value of school to students, thereby promoting learning at school. The results, however, are consistent with some recent evidence (e.g., Powell et al., 2010) indicating that the home–school partnership may have stronger predictive power on social than academic outcomes. Future studies are needed to clarify these associations.

Cumulative Effects of Environmental Protective Factors on Subsequent Reading FluencyIn accordance with the transactional perspectives (Gutman et al., 2003; Sameroff & MacKenzie, 2003) and our hypothesis 1b, the results of the present study showed further that cumulative support from multiple social relationships has a positive effect on a student’s reading skills over and above the effects of single sourc-es of support. The results indicated that a higher num-ber of protective factors in a student’s interpersonal environment predicted better reading skills over and above single protective factors. The results broaden the previous cumulative risk models (Deater-Deckard et al., 1998; Sameroff, 1993) by showing that different simulta-neous protective factors can also have a cumulative impact on students’ academic performance. The find-ings also extend previous research by showing that hav-ing a supportive network of interpersonal relationships promotes not only the school adjustment of adolescents (e.g., Rosenfeld et al., 2000; Ryan et al., 1994) but also reading skills (fluency) in primary school. In sum, our results suggest that it is not only the quality of single interpersonal protective factors in the student’s school environment that matters but also the accumulation of multiple environmental protective factors.

One possible explanation for these results is that higher overall support from different relationships is related to the fulfillment of children’s basic psychologi-cal needs of social relatedness (Zimmer-Gembeck et al., 2006). When this need is properly met in the school environment, students feel safe and well connected to school, which in turn fosters their motivation and engagement in learning to read. When students are engaged with their school environment, they are likely to build skills that promote positive reading experienc-es. An important implication of the present findings is that in order to optimize learning to read among stu-dents, it is important to make an effort to support their teacher and peer relationships in the school context.

RD Risk, Environmental Protective Factors, and Later Reading FluencyIn accordance with the evocative models of child char-acteristics (e.g., Rutter, 1997), we also examined whether

RD risk in kindergarten contributes to the environmen-tal protective factors that a student has in the later school years. The results supported the evocative model and our hypothesis 2a (e.g., Gadeyne et al., 2004; Nurmi, 2012) by showing that RD risk predicted low subsequent peer acceptance, lack of positive teacher affect for the student, and a low-quality home–school partnership. These results are in accordance with some previous findings. First, they are consistent with the notion that forming positive peer relationships is a more difficult task for students with learning difficulties than for oth-er students (Frederickson & Furnham, 2001).

One possible reason for this is that students with learning disabilities often have attention, language, and communication difficulties (Luciano & Savage, 2007; Willcutt et al., 2007), which make it more difficult for them to perceive social cues accurately, follow social rules, and communicate in socially acceptable ways (Herbert-Myers, Guttentag, Swank, Smith, & Landry, 2006). A further explanation relates to the academic reputation of RD-risk students. Classmates are aware of one another’s academic skills, perhaps as a consequence of the public display of work done in the class, teachers’ public feedback, and the sharing of information between peers (see Stipek & MacIver, 1989). Consequently, it is possible that better-achieving peers perceive at-risk stu-dents’ learning as inferior and are therefore less willing to accept these students into their peer groups.

Second, the finding that RD risk in kindergarten contributed to low positive teacher affect toward a stu-dent during the first years of primary school is in line with prior research suggesting that aside from increased learning support for students who have academic diffi-culties, teachers report more negative affect and less closeness in their relationships with low-achieving stu-dents (for a review, see Nurmi, 2012). Earlier research has also indicated that primary school teachers tend to perceive students with learning disabilities as lacking ability more often than others in the class (Woodcock & Vialle, 2011).

The “Pygmalion in the classroom” paradigm (Rosenthal & Jacobson, 1968; for a review, see Babad, 1993) provides one potential explanation for these results. A key notion of this paradigm is that teachers give more attention and display positive affect to stu-dents whom they expect to perform well than to those whom they expect to perform poorly. Moreover, research on teachers’ affects has shown that the major source of teachers’ positive emotions, such as satisfac-tion, is students’ good learning outcomes and progress (Emmer, Oakland & Good, 1974; Hargreaves, 1998). Consequently, it is possible that despite attempts to be positive, teachers may experience less joy and more stress when teaching students for whom learning is very challenging and slow. The second possibility is that


students at risk for RD experience negative affects in the face of academic challenges (see Pomerantz et al., 2007), in turn leading teachers to become less positive (i.e., transfer of negative affects from students to teachers). It is noteworthy that in the present study, we investigated the effect of RD risk instead of diagnosed RD.

Third, RD risk in kindergarten was found to predict a less close partnership between home and school dur-ing the first grades of primary school. Although there is some evidence that parents typically have heightened contact with teachers when children are doing poorly in school (Izzo et al., 1999), our results suggest that the partnership between parents and teachers of at-risk stu-dents is not necessarily close and trustful. One possible explanation for this finding is that if RD students’ skills continue to lag behind those of other students, parents may increasingly start to worry about their child’s per-formance and feel unsure about whether their child is receiving sufficient support at school. This may then lead to lack of partnership formation with the classroom teacher. Another possibility is that the child’s parents have experienced learning difficulties at school, nega-tive memories of which are brought to mind when they witness their child struggling with academic tasks. Parents’ distance-taking from school-related activities may then also be reflected in a low-quality partnership with the teacher. It is notable, however, that the effect of RD risk on the home–school partnership was small after controlling for gender, nonverbal ability, and par-ents’ education.

In support of hypothesis 2b, the results also revealed that aside from the fact that RD risk predicted lower support in each type of relationship, RD risk also gener-ally predicted a smaller number of environmental pro-tective factors. In other words, problems in interpersonal relationships tended to accumulate among students at risk for RD. This result parallels those of Fleming and colleagues (2002), who found that having a learning dis-ability predicted students’ negative perceptions of dif-ferent social relations. A possible reason is that the poor reading achievement of the RD-risk students may have evoked similar negative reactions across different types of relationships, hindering the formation of supportive relationships.

Finally, consistent with hypothesis 3a (see also Lyytinen et al., 2004; Snowling et al., 2007), the results showed that RD risk had a relatively strong and negative effect on subsequent reading skills. When controlling for the effects of gender, nonverbal ability, and parental education, RD risk measured in kindergarten continued to predict poorer reading skills in grade 4. This finding is in line with previous longitudinal evidence showing that students who struggle with reading initially are likely to continue struggling throughout their later school years (Juel, 1988; Stanovich, 1986). Yet, the fact

that the association between RD risk and reading skills four years later was only moderately strong leaves room for other relevant factors, such as environmental protec-tive factors.

Interestingly, the results of the present study showed further that the effect of RD risk on subsequent reading fluency was partially mediated by cumulative environ-mental support. RD risk predicted a smaller number of environmental protective factors, which then predicted lower subsequent reading fluency. These results were in accordance with hypothesis 3b. Overall, the findings of the present study suggest not only that students are influenced by their interpersonal environments but also that children’s characteristics, in this case RD risk, have an evocative impact on other people’s affections and responses (see also Rutter, 1997; Scarr & McCartney, 1983). Taken together with the results showing that environmental protective factors contribute to positive development of reading f luency, these results suggest that child characteristics (poor or good reading skills) and relationships in the classroom form transactional patterns that are likely to accumulate across time (Sameroff, 2009). However, as the analyses were correla-tional, causal inferences cannot be drawn. Clearly, these links deserve further study.

LimitationsThis study also has its limitations. First, teacher affec-tion was measured by teacher reports only. In future studies, observational data would provide information about interaction between teachers and students in actual classroom situations. Second, although the read-ing fluency measure used in this study tapped accuracy and speed on the word and sentence levels, the measure did not tap the reading comprehension aspect of fluen-cy. Therefore, future studies are needed to investigate the role of environmental protective factors in students’ text reading fluency and comprehension.

Third, our focus was on overall environmental support across grades 1–3. Although there is evidence to suggest that low peer acceptance (e.g., Ladd, 2006) and low positive teacher affect (e.g., Jerome, Hamre, & Pianta, 2009) tend to persist from grade to grade, perhaps due to reputational bias or child-related characteristics to which peers and teachers react, it would also be important to investigate changes in the quality of interpersonal rela-tionships and their impacts on the development of students’ reading skills. Fourth, the present study focused only on the risk for reading disability and subsequent reading skills. Although RD are often related with learn-ing disabilities (Beitchman & Young, 1997), the learning disabilities population is known to be heterogeneous (Kavale & Forness, 2000). Consequently, it would be important to investigate in more detail whether the


interpersonal processes studied here are any different for different subtypes of RD, such as RD with and without comorbid problems in other skills (e.g., math), self- regulation, and attention.

Fifth, although not directly addressed in the present study, teacher effectiveness in facilitating reading devel-opment could also have a role in supporting a student with RD. Sixth, recent research suggests that the boot-strap method might be more optimal than regular maximum likelihood estimation in evaluating the statistical significance of indirect effects (MacKinnon, Lockwood, & Williams, 2004). The current version of Mplus software, however, does not enable bootstrap analysis in conjunction with the complex method that was used in the present study.

Finally, the present study was carried out in a particu-lar cultural and educational environment, Finland, which differs at least in two respects from many other countries. First, Finnish children enter grade 1 at the age of 7—that is, one to two years later than in many other countries. Second, Finnish is a language with a highly transparent orthography, unlike, for example, the orthography of English, which is highly op aque (Seymour et al., 2003). Consequently, the results would need to be replicated in other languages and educational contexts.

ConclusionsThe results of the present study indicate that students at risk for RD need more support from the environment because they need to invest a high effort in practicing reading to obtain good learning results. We found not only that RD risk in kindergarten predicts poor reading fluency in grade 4 but also that RD-risk students are less accepted in the classroom by their peers, their teachers report less positive affects toward them, and their parents and teachers cooperate less actively. Our results indicated that RD-risk students have to learn reading skills in less positive classroom and school contexts, which in turn has detrimental effects on their reading fluency.

Yet, our findings further suggested that there are reasons to believe that it is possible to change this pessimistic scenario. A key finding of the present study was that supportive relations with the teacher and peers promoted reading fluency both among students with and without risk for RD. The results suggest that suc-cessful interventions to guide teachers’ affects, atti-tudes, and behaviors toward risk students in a more positive direction and help students integrate with their peers in the classroom can optimally support the devel-opment of students’ reading skills.

NOTESThis study was funded by a grant from the Academy of Finland to the Finnish Centre of Excellence in Learning and Motivation

Research (213486) and other grants from the same funding agency to Noona Kiuru (7133146), Marja-Kristiina Lerkkanen (125811), Anna-Maija Poikkeus (263891), and Jari-Erik Nurmi (252304). Funding sources have had no role in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

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Submitted March 19, 2013Final revision received June 3, 2013

Accepted June 5, 2013

NOONA KIURU (corresponding author) is an adjunct professor in the Department of Psychology and MARJA KRISTIINA LERKKANEN an adjunct professor in the Department of Teacher Education at the University of Jyväskylä, Finland; e-mail [email protected] and [email protected].

PEKKA NIEMI is a professor and ELISA POSKIPARTA a senior researcher in the Department of Psychology at the University of Turku, Finland; e-mail [email protected] and [email protected].

TIMO AHONEN is a professor in the Department of Psychology, ANNA-MAIJA POIKKEUS a professor in the Department of Teacher Education, and JARI-ERIK NURMI a professor in the Department of Psychology at the University of Jyväskylä, Finland; email [email protected], [email protected], and [email protected].

Kiuru, N., Lerkkanen, M., Niemi, P., Poskiparta, E., Ahonen, T. & Poikkeus, A. Et Al. (2013).

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