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Object Control Profiles and Gender Differences in Preschoolers: A 2-Year Latent Transition Analysis

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Title: Object Control Profiles and Gender Differences in Preschoolers: A 2-Year Latent Transition Analysis
Language: English
Authors: Hang Zhang, Yueyue Zhou, Qiaoling Li (ORCID 0000-0003-0278-303X), Guoxiang Zhao
Source: SAGE Open. 2025 15(3).
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 12
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Preschool Children, Gender Differences, Student Characteristics, Psychomotor Skills, Motor Development, Foreign Countries
Geographic Terms: China
Assessment and Survey Identifiers: Test of Gross Motor Development
DOI: 10.1177/21582440251381164
ISSN: 2158-2440
Abstract: Based on dynamic systems theory, the longitudinal study tracked 120 kindergarten children 2 years to examine the differentiation and transition of object control profiles among preschool children aged 3 to 6. Latent profile analysis (LPA) and latent transition analysis (LTA) were employed to identify development profiles and transitions, as well as to examine gender differences within these profiles. The findings indicated that: (1) Children's object control abilities were classified into three profiles: low, medium, and high, with the medium profile accounting for the largest proportion at both time points. (2) From T1 to T2, children in low and medium profiles at T1 were more likely transition to the high profile at T2, while those in the high profile at T1 showed a higher probability of transitioning to the medium profile at T2. (3) At T2, significant gender differences emerged, with boys being more likely than girls to belong to the medium profile. These findings provide empirical insights to guide kindergarten educational practices in supporting children's developmental trajectories.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1487278
Database: ERIC
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  Value: <anid>AN0188424263;[kbz6]01jul.25;2025Oct07.03:06;v2.2.500</anid> <title id="AN0188424263-1">Object Control Profiles and Gender Differences in Preschoolers: A 2-Year Latent Transition Analysis </title> <p>Based on dynamic systems theory, the longitudinal study tracked 120 kindergarten children 2 years to examine the differentiation and transition of object control profiles among preschool children aged 3 to 6. Latent profile analysis (LPA) and latent transition analysis (LTA) were employed to identify development profiles and transitions, as well as to examine gender differences within these profiles. The findings indicated that: (<reflink idref="bib1" id="ref1">1</reflink>) Children's object control abilities were classified into three profiles: low, medium, and high, with the medium profile accounting for the largest proportion at both time points. (<reflink idref="bib2" id="ref2">2</reflink>) From T1 to T2, children in low and medium profiles at T1 were more likely transition to the high profile at T2, while those in the high profile at T1 showed a higher probability of transitioning to the medium profile at T2. (<reflink idref="bib3" id="ref3">3</reflink>) At T2, significant gender differences emerged, with boys being more likely than girls to belong to the medium profile. These findings provide empirical insights to guide kindergarten educational practices in supporting children's developmental trajectories.</p> <p>Plain Language Summary: Object control profiles in preschoolers The longitudinal study tracked 120 kindergarten children 2 years to examine the differentiation and transition of object control profiles among preschool children aged 3 to 6. These findings provide empirical insights in supporting children's developmental trajectories.</p> <p>Keywords: object control; latent profile analysis; latent transition analysis; preschool children</p> <hd id="AN0188424263-2">Introduction</hd> <p>Object control ability is a fundamental component of the gross motor development in preschool children, encompassing their capacity to manipulate and control objects such as balls. Within the framework of the Test of Gross Motor Development (TGMD-2), this ability is assessed through six core movements: striking a stationary ball, stationary dribbling, kicking, underhand rolling, catching, and overhand throwing. These activities are designed to evaluate and enhance the children's proficiency in handling and directing objects, which is essential for their overall physical development ([<reflink idref="bib35" id="ref4">35</reflink>]). In recent years, although the importance of children's motor development has gained widespread attention, challenges remain in translating theoretical recommendations into effective educational practices ([<reflink idref="bib45" id="ref5">45</reflink>]).</p> <p>According to China's newly released <emph>Exercise Guidelines for Preschool Children (3–6 years old)</emph>, one of the primary causes of physical health problems in children and adolescents—such as the increase in overweight and obesity, is insufficient physical exercise during early childhood ([<reflink idref="bib9" id="ref6">9</reflink>]). The preschool period represents a sensitive phase for the development of gross motor skills. Robust motor development not only enhances children's physical abilities and promotes a healthy physical fitness levels but also exerts a profound influence on their cognitive and emotional capabilities ([<reflink idref="bib3" id="ref7">3</reflink>]; [<reflink idref="bib17" id="ref8">17</reflink>]; [<reflink idref="bib25" id="ref9">25</reflink>]). Therefore, exploring the characteristics and patterns of children's motor development carries significant theoretical and practical implications for guiding subsequent educational practices.</p> <p>Researchers have conducted studies to assess the gross motor development of children aged 3 to 4, finding that while children in this age group are generally capable of mastering displacement skills such as running and jumping, they often encounter greater challenges with object control skills, particularly those related to ball handling ([<reflink idref="bib39" id="ref10">39</reflink>]). This insight underscores that object control skills, as advanced components of gross motor development, necessitate longitudinal investigations spanning sufficient developmental periods to elucidate their dynamic transition patterns in early childhood. Unfortunately, the academic community currently lacks a unified explanation for this phenomenon ([<reflink idref="bib1" id="ref11">1</reflink>]; [<reflink idref="bib7" id="ref12">7</reflink>]; [<reflink idref="bib29" id="ref13">29</reflink>]; [<reflink idref="bib30" id="ref14">30</reflink>]).</p> <p>The development of children's object control ability is fundamentally a self-organizing process driven by the dynamic coupling of neural, biomechanical, and environmental constraints. Dynamic systems theory (DST) provides the core explanatory framework for this phenomenon ([<reflink idref="bib28" id="ref15">28</reflink>]). This theoretical perspective emphasizes that movement patterns emerge through real-time interactions among <emph>organismic constraints</emph> (e.g., corticocerebellar myelination rates during the 4 to 6-year critical period), <emph>task constraints</emph> (e.g., object weight/target distance gradients in throwing actions), and <emph>environmental constraints</emph> (e.g., equipment accessibility and instructional frequency in preschool settings; [<reflink idref="bib12" id="ref16">12</reflink>]; [<reflink idref="bib34" id="ref17">34</reflink>]). These interactions produce phase-stable behavioral states whose characteristic nonlinear phase transitions challenge conventional linear developmental models. Although cross-sectional studies have identified group-level differences in object control proficiency, they have failed to elucidate how constraint parameters drive the differentiation and transformation of individual developmental trajectories ([<reflink idref="bib10" id="ref18">10</reflink>]). To address this gap, our longitudinal study employs Latent Profile Analysis (LPA) to identify distinct profiles of object control competence in young children, complemented by Latent Transition Analysis (LTA) to delineate developmental trajectories. This approach advances the field from descriptive characterization to mechanism-informed intervention.</p> <p>The contradictory findings regarding gender differences in object control skills among 3 to 6-year-olds ([<reflink idref="bib11" id="ref19">11</reflink>]; [<reflink idref="bib26" id="ref20">26</reflink>]; [<reflink idref="bib42" id="ref21">42</reflink>]) highlight significant limitations in current research paradigms. While scholars have attempted to explain these disparities through both biological factors (e.g., neuromuscular maturation differences, hormonal influences) and sociological perspectives (e.g., gender role socialization, parenting styles; [<reflink idref="bib14" id="ref22">14</reflink>]; [<reflink idref="bib42" id="ref23">42</reflink>]), neither theoretical framework has sufficiently elucidated the dynamic mechanisms underlying these developmental differences, nor have they provided clear guidance for educational intervention practices. Particularly noteworthy is the striking paucity of empirical research examining how systematic curricular interventions at the preschool level might mitigate these gender disparities. Addressing this critical gap, the present longitudinal study employs latent profile analysis to examine gender differences across developmental subgroups, an approach that not only reveals the temporal dynamics of gender-based skill differentiation but also provides an evidence-based foundation for designing targeted, gender-sensitive object control skill interventions in early childhood education settings.</p> <p>The three-grade structure of Chinese kindergartens provides a standardized yet developmentally sensitive framework for tracking motor skill progression during this critical period of early childhood. Therefore, this study specifically investigates the development of object control skills in children aged 3 to 6 years, utilizing a 2-year longitudinal design that tracks children from the junior kindergarten class (aged 3–4 years) through their transition to the senior class (aged 5–6 years), while employing person-centered analytical approaches to capture individual developmental trajectories within this critical early childhood period. The primary aim is to identify the divergent patterns developmental transitions and gender difference in children's object control. Additionally, this study seeks to propose developmental recommendations for enhancing motor development education in early childhood.</p> <hd id="AN0188424263-3">Latent Profiles and Developmental Transitions in Children's Object Control</hd> <p>Over the past few years, psychological scholars have predominantly concentrated their research on developmental variations in object control skills as children grow, aiming to identify age-specific traits of object control ([<reflink idref="bib38" id="ref24">38</reflink>]). This research methodology often treats children of the same age as a uniform cohort, presupposing that individuals within the same age range follow identical development trajectories in object control. However, from a holistic perspective of perso-environment interaction, individual differences arise from a variety of factors, including internal characteristics and environmental complexities. These differences, however, do not indicate chaotic or arbitrary development. On the contrary they lead to the formation of groups of individuals who share similar psychological and behavioral traits. This process results in pattern characterized by intra-profile homogeneity and inter-profile heterogeneity ([<reflink idref="bib23" id="ref25">23</reflink>]). While traditional research methods are effective for analyzing certain aspects of age-related characteristics in object control, they often failed to fully consider the comprehensive level of individual object control development as well as the categorical features and developmental transitions involved. Examining object control development from a categorical perspective provides an innovative and insightful approach for the educators and practitioners. Such an approach enables them to better understand the characteristics and trends of object control development in a more intuitive and dynamical manner.</p> <p>Regrettably, current research predominantly adopts a variable-centered perspective, focusing on reflecting, the heterogeneous developmental characteristics of object control in children aged 3 to 6 ([<reflink idref="bib17" id="ref26">17</reflink>]; [<reflink idref="bib18" id="ref27">18</reflink>]). Although limited findings indicate the existence of distinct profiles in the gross motor development of preschool children ([<reflink idref="bib4" id="ref28">4</reflink>]; [<reflink idref="bib33" id="ref29">33</reflink>]), latent profile research on children's motor development, which relies solely on scale-based measurements, falls short of offering targeted recommendations for motor development based on motion tests. Therefore, the primary aim of this study is to explore the potential profiles of object control among preschool children, elucidate the diverse development patterns in their object control abilities, and provide theoretical support for future educational practices and intervention strategies.</p> <p>In recent years, an increasing number of researchers have adopted individual-centered analysis methods to explore the heterogeneity in children's motor development. Latent profile analysis (LPA) is a statistical method that emphasizes an individual-centered approach. Unlike traditional variable-centered methods such as mean division and cluster analysis, LPA identifies latent profiles within variables to explain relationships between external continuous variables, thereby achieving relative independence of manifest variables in specific local areas ([<reflink idref="bib21" id="ref30">21</reflink>]; [<reflink idref="bib22" id="ref31">22</reflink>]; [<reflink idref="bib24" id="ref32">24</reflink>]). Building on this, latent transition analysis (LTA) focuses on exploring the dynamic trends of latent profile development in longitudinal data, placing greater emphasis on transitions of individuals between categories. LTA enables researchers to more accurately discern specific differences and developmental trends among individuals ([<reflink idref="bib19" id="ref33">19</reflink>]). The development of object control in preschool children is in a dynamic and evolving process, characterized by significant plasticity. Uncovering the overall state of object control development in preschool children, as well as its diverse developmental characteristics, and exploring the stable or transitional patterns among different profiles of children represent pressing academic issues. In light of this, the present study will examine the latent differentiation patterns and developmental transition patterns of object control in preschool children, focusing on six measured indicators of object control.</p> <hd id="AN0188424263-4">Gender Differences</hd> <p>The presence of gender differences in children's motor development and their specific manifestations has consistently been a significant focus of academic research. Drawing upon Dynamic Systems Theory (DST), gender differences in motor development fundamentally represent emergent properties arising from nonlinear interactions among biological, environmental, and sociocultural constraints. Regarding biological constraints, boys' contemporaneous advantages in upper-limb strength and trunk rotation efficiency confer performance advantages in ball-related activities during early childhood ([<reflink idref="bib32" id="ref34">32</reflink>]). Simultaneously, environmental and sociocultural constraints manifest when societal expectations systematically channel boys toward ball sports ([<reflink idref="bib8" id="ref35">8</reflink>]), establishing a self-fulfilling dynamic whereby elevated expectations amplify motor performance outcomes. Research has indicated that among children aged 3 to 6, girls exhibit higher levels of displacement ability and body perception ability ([<reflink idref="bib26" id="ref36">26</reflink>]). In contrast, other researchers have found no significant gender differences in displacement ability for this age group. However, in terms of object control ability, boys significantly outperform girls, and this advantage becomes more pronounced as they age ([<reflink idref="bib11" id="ref37">11</reflink>]; [<reflink idref="bib42" id="ref38">42</reflink>]). Object control is regarded as a higher-level ability within the development of gross motor skills. Current research on gender differences in object control remains inconclusive, with few studies exploring differentiation patterns and gender disparities between profiles from a longitudinal developmental perspective. In response to this gap, the present study aims to further investigate the gender differences among profiles of children's object control.</p> <p>In summary, this study adopts a 2-year longitudinal design with children aged 3 to 6 as participants. Using latent profile analysis and latent transition analysis, it explores the profiles and transition patterns of object control in preschool children. Additionally, the study examines the gender differences that exist between different profiles. Drawing on existing theoretical and empirical research findings, this study hypothesizes that: (<reflink idref="bib1" id="ref39">1</reflink>) There is heterogeneity in the object control of preschool children, which can be differentiated into distinct profiles based on various characteristics. (<reflink idref="bib2" id="ref40">2</reflink>) The object control of preschool children in different profiles will undergo changes over time; (<reflink idref="bib3" id="ref41">3</reflink>) There are gender differences in the profiles of object control among preschool children.</p> <hd id="AN0188424263-5">Methods</hd> <p></p> <hd id="AN0188424263-6">Participants</hd> <p>We conducted an a priori power analysis using G*Power 3.1 to determine the required sample size for this study. The analysis was configured for a <emph>t</emph>-test of the difference between two dependent means (matched pairs), with a two-tailed test. Input parameters included an effect size <emph>d</emph><subs>z</subs> = 0.25, α error probability =.05, and Power (1 −β error probability) =.80. Results indicated that a minimum sample size of 101 participants was required.</p> <p>Nonprobability sampling strategies are any methods of sampling that do not utilize some form of random selection. By far the most common nonprobability sampling strategy used within developmental science is convenience sampling ([<reflink idref="bib2" id="ref42">2</reflink>]). Convenience sampling was employed for this study, with data collection conducted at two Provincial Model Kindergartens in a prefecture-level city in China. Within each kindergarten, two junior classes were randomly selected, resulting in a total of 120 children as research participants. A 2-year longitudinal study was conducted, with 63 boys (52.50%) and 57 girls (47.50%) included in the sample. The first assessment was completed in May 2021, and the second assessment was conducted in May 2023. After excluding data with missing values, 126 children were tested at time point T1, and 120 children remained at time point T2, resulting in a dropout rate of approximately 4.76%.</p> <p>Attrition analysis was conducted using independent samples <emph>t</emph>-tests. Results indicated no statistically significant differences in object control skills between participants who completed the study and those lost to follow-up, <emph>t</emph> (<reflink idref="bib124" id="ref43">124</reflink>) = 0.248, <emph>p</emph> =.804. All participants exhibited normal development in intelligence, vision, and hearing, and informed consent was obtained from the guardians of all participants before the study.</p> <hd id="AN0188424263-7">Measures</hd> <p>The Test of Gross Motor Development-2 (TGMD-2) was employed to assess object control, including six specific object control movements: striking a stationary ball, stationary dribbling, kicking, underhand rolling, catching, and overhand throwing. Each movement includes 3 to 5 evaluation criteria, with participants receiving 1 point for meeting each criterion and 0 points otherwise. The test was conducted twice for each participant, and the final score was calculated based on the total points across all movements. Higher scores reflect better object control development in children.</p> <hd id="AN0188424263-8">Procedures</hd> <p>After obtaining informed consent from the children's parents or guardians, the same group of participants underwent two rounds of testing, in May 2021 and May 2023. The testers were graduate students majoring in psychology and physical education, who received training on the standards for the six object control movements and the testing procedures prior to the formal assessment. To ensure scoring consistency, each gross motor skill assessment was simultaneously scored by two trained postgraduate researchers for every participant, with all sessions video-recorded. In cases of scoring discrepancies (e.g., one rater scoring 1 and the other scoring 0 for a specific skill criterion), the raters reviewed the video recording together to reassess the child's performance against the standardized criteria. The final score was determined through consensus-based resolution and recorded on the scoring sheet. This rigorous protocol enhanced the inter-rater reliability of our assessments.</p> <p>All procedures used preschool-adapted safety measures (soft equipment, reduced distances) during routine activities. Benefits included targeted development of children's motor skills and evidence-based guidelines for kindergartens.</p> <hd id="AN0188424263-9">Ethical Considerations</hd> <p>This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Henan University (ID: YB-JFZX-2022-06). Informed consent was obtained from all the guardians of the children involved in the study. The privacy of the participant was fully respected and protected.</p> <hd id="AN0188424263-10">Data Analysis</hd> <p>Data analysis was conducted in two main stages. First, SPSS 24.0 was utilized for data entry and management, followed by descriptive statistical analysis, paired sample <emph>t</emph>-tests, and multiple logistic regression analyses. Subsequently, latent profile analysis and latent transition analysis were performed using Mplus 8.3. This study rigorously adheres to methodological standards for latent profile analysis (LPA) and latent transition analysis (LTA), implementing a four-phase validation framework to ensure statistical robustness. Primarily grounded in simulation research by [<reflink idref="bib27" id="ref44">27</reflink>], the Bootstrap Likelihood Ratio Test (BLRT) was established as the principal determinant for profile enumeration due to its consistently minimal Type I error rates under sample variability. This approach was supplemented by a hierarchical verification system for information criteria, prioritizing the sample-size adjusted Bayesian Information Criterion (aBIC) based on [<reflink idref="bib40" id="ref45">40</reflink>] empirical demonstration of its superior classification accuracy (provided each latent category contains at least 50 participants), while traditional BIC and AIC served as secondary reference metrics. [<reflink idref="bib6" id="ref46">6</reflink>] advised evaluating a range of information criteria, including the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and adjusted Bayesian Information Criterion (aBIC). Smaller values for these criteria indicate a better model fit ([<reflink idref="bib6" id="ref47">6</reflink>]). Additionally, the entropy value, ranging from 0 to 1, reflects classification accuracy, with values closer to "1" indicating more precise classification. An entropy value of 0.8 or higher suggests that over 90% of cases are correctly classified, which indicates that the model is acceptable ([<reflink idref="bib20" id="ref48">20</reflink>]). Additionally, the profile probabilities represent the proportion of individuals within each profile. If the proportion of a specific profile is too small (e.g., less than 5%), it suggests that the profile may not be valid. To further investigate gender differences among object control profiles, multiple logistic regression analysis was conducted using SPSS 24.0.</p> <hd id="AN0188424263-11">Results</hd> <p></p> <hd id="AN0188424263-12">Descriptive Statistics</hd> <p>Consistent with prior validation protocols ([<reflink idref="bib16" id="ref49">16</reflink>]), the structural validity of TGMD-2 was established through item-total correlation analysis. As presented in Table 1, all subtests demonstrated statistically significant correlations with the total score (<emph>r</emph> =.42 to.66, <emph>p</emph> <.01), confirming moderate-to-strong coherence between individual motor skill components and the global construct.</p> <p>Table 1. Correlations Among Object Control Indicators and the Total Score.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /></colgroup><thead><tr><th align="left">Variables</th><th align="center">Correlation coefficient</th></tr></thead><tbody><tr><td>Stationary dribbling</td><td>.66<xref ref-type="table-fn" rid="tfn1">**</xref></td></tr><tr><td>Kicking</td><td>.51<xref ref-type="table-fn" rid="tfn1">**</xref></td></tr><tr><td>Underhand rolling</td><td>.42<xref ref-type="table-fn" rid="tfn1">**</xref></td></tr><tr><td>Catching</td><td>.54<xref ref-type="table-fn" rid="tfn1">**</xref></td></tr><tr><td>Striking a stationary ball</td><td>.65<xref ref-type="table-fn" rid="tfn1">**</xref></td></tr><tr><td>Overhand throwing</td><td>.52<xref ref-type="table-fn" rid="tfn1">**</xref></td></tr></tbody></table> </ephtml> </p> <p>1 <emph>p</emph> <.01.</p> <p>The correlations between all study variables, are reported in Table 2.</p> <p>Table 2. Descriptive Statistics and Correlations Among Object Control Indicators.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Variables</th><th align="center">1</th><th align="center">2</th><th align="center">3</th><th align="center">4</th><th align="center">5</th><th align="center">6</th><th align="center">7</th><th align="center">8</th><th align="center">9</th><th align="center">10</th><th align="center">11</th><th align="center">12</th></tr></thead><tbody><tr><td>1</td><td align="center">—</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>2</td><td>.21<xref ref-type="table-fn" rid="tfn3">*</xref></td><td align="center">—</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>3</td><td>.12</td><td>.16</td><td align="center">—</td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>4</td><td>.30<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.25<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.14</td><td align="center">—</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>5</td><td>.27<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.14</td><td>.19<xref ref-type="table-fn" rid="tfn3">*</xref></td><td>.18<xref ref-type="table-fn" rid="tfn3">*</xref></td><td align="center">—</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>6</td><td>.11</td><td>.16</td><td>.07</td><td>.03</td><td>.33<xref ref-type="table-fn" rid="tfn3">**</xref></td><td align="center">—</td><td /><td /><td /><td /><td /><td /></tr><tr><td>7</td><td>.32<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.24<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.17</td><td>.20<xref ref-type="table-fn" rid="tfn3">*</xref></td><td>.09</td><td>.15</td><td align="center">—</td><td /><td /><td /><td /><td /></tr><tr><td>8</td><td>.03</td><td>−.04</td><td>.10</td><td>.20<xref ref-type="table-fn" rid="tfn3">*</xref></td><td>−.08</td><td>.08</td><td>.03</td><td align="center">—</td><td /><td /><td /><td /></tr><tr><td>9</td><td>.06</td><td>−.01</td><td>−.03</td><td>−.05</td><td>.12</td><td>.28<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.04</td><td>−.04</td><td align="center">—</td><td /><td /><td /></tr><tr><td>10</td><td>.10</td><td>.17</td><td>−.08</td><td>.05</td><td>.05</td><td>.05</td><td>.03</td><td>−.10</td><td>−.13</td><td align="center">—</td><td /><td /></tr><tr><td>11</td><td>.06</td><td>.04</td><td>.15</td><td>.07</td><td>−.01</td><td>.00</td><td>.15</td><td>.07</td><td>−.10</td><td>.07</td><td align="center">—</td><td /></tr><tr><td>12</td><td>.02<xref ref-type="table-fn" rid="tfn3">*</xref></td><td>.09</td><td>.04</td><td>.04</td><td>.01</td><td>.00</td><td>.10</td><td>.05</td><td>−.06</td><td>−.01</td><td>.10</td><td align="center">—</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 <emph>Note</emph>. 1–6, 7–12 respectively refer to T1, T2's stationary dribbling, kicking, underhand rolling, catching, striking a stationary ball, and overhand throwing.</item> <item>3 <emph>p</emph> <.05. **<emph>p</emph> <.01</item> </ulist> <p>Table 3 presents the means and standard deviations of the main study variables from the two measurements. Paired sample <emph>t</emph>-tests were conducted to examine the differences in the main variables across the two time points. The results indicate significant differences in the six object control indicators between the two time points.</p> <p>Table 3. Descriptive Statistical Analysis and Paired Sample t -Test.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Variables</th><th align="center">T1 <italic>M</italic> (<italic>SD</italic>)</th><th align="center">T2 <italic>M</italic> (<italic>SD</italic>)</th><th align="center"><italic>t</italic></th></tr></thead><tbody><tr><td>Stationary dribbling</td><td>3.092 (1.85)</td><td>5.73 (1.28)</td><td>−15.30<xref ref-type="table-fn" rid="tfn4">***</xref></td></tr><tr><td>Kicking</td><td>7.07 (1.35)</td><td>7.67 (0.75)</td><td>−4.19<xref ref-type="table-fn" rid="tfn4">***</xref></td></tr><tr><td>Underhand rolling</td><td>4.96 (1.21)</td><td>6.40 (1.24)</td><td>−8.99<xref ref-type="table-fn" rid="tfn4">***</xref></td></tr><tr><td>Catching</td><td>4.43 (1.29)</td><td>5.25 (0.87)</td><td>−5.88<xref ref-type="table-fn" rid="tfn4">***</xref></td></tr><tr><td>Striking a stationary ball</td><td>6.57 (1.85)</td><td>8.10 (1.37)</td><td>−7.26<xref ref-type="table-fn" rid="tfn4">***</xref></td></tr><tr><td>Overhand throwing</td><td>4.77 (1.69)</td><td>7.43 (1.08)</td><td>−14.49<xref ref-type="table-fn" rid="tfn4">***</xref></td></tr></tbody></table> </ephtml> </p> <p>4 <emph>p</emph> <.01.</p> <hd id="AN0188424263-13">Latent Profile Analysis of Object Control</hd> <p>To investigate the profiles of children's object control, latent profile analysis (LPA) was conducted using scores from six object control movements as indicators.</p> <p>Table 4 presents the fit indices for varying numbers of profiles in the LPA of children's object control at the two time points. As shown in Table 4 (As indicated by the bolded values, these profile data represent the most favorable results in the analysis), the minimum sample size of the smallest profile in the four-profile model at T1 is less than 5%, indicating that this profile is not valid. The AIC and aBIC values for the three-profile model are lower, and the results for LMR (<emph>p</emph> <.01) and BLRT (<emph>p</emph> <.001) further indicate that the three-profile model outperforms the two-profile model. Therefore, after careful consideration, the three-profile model is determined to be the best-fitting model for T1. For T2, the AIC, BIC, and aBIC values also decrease as the number profiles increases, and the entropy values suggest that the four-profile solution is preferable. However, the LMR value for the four-profile model is not significant. Thus, considering both model fit and simplicity, the three-profile model is identified as the best-fitting model for T2.</p> <p>Table 4. LPA of Objective Control at T1 and T2.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Time</th><th align="center">Profiles</th><th align="center">AIC</th><th align="center">BIC</th><th align="center">aBIC</th><th align="center">Entropy</th><th align="center"><italic>p-</italic>LMR</th><th align="center"><italic>p-</italic>BLRT</th><th align="center">Profile probabilities</th></tr></thead><tbody><tr><td>T1</td><td>1</td><td>2,661.28</td><td>2,694.73</td><td>2,656.79</td><td>1</td><td align="center">—</td><td align="center">—</td><td>1</td></tr><tr><td /><td>2</td><td>2,592.37</td><td>2,645.33</td><td>2,585.26</td><td>0.991</td><td>0.057</td><td><0.001</td><td>0.63/0.37</td></tr><tr><td /><td>3</td><td>2,582.82</td><td>2,655.29</td><td>2,573.09</td><td>0.939</td><td>0.004</td><td><0.001</td><td>0.37/0.55/0.08</td></tr><tr><td /><td>4</td><td>2,572.94</td><td>2,664.93</td><td>2,560.60</td><td>0.951</td><td>0.003</td><td><0.05</td><td>0.35/0.02/0.55/0.08</td></tr><tr><td>T2</td><td>1</td><td>2,165.18</td><td>2,198.63</td><td>2,160.69</td><td>1</td><td align="center">—</td><td align="center">—</td><td>1</td></tr><tr><td /><td>2</td><td>2,091.90</td><td>2,144.87</td><td>2,084.80</td><td>0.991</td><td>0.043</td><td><0.001</td><td>0.82/0.18</td></tr><tr><td /><td>3</td><td>2,015.08</td><td>2,087.56</td><td>2,005.36</td><td>0.992</td><td>0.047</td><td><0.001</td><td>0.22/0.72/0.07</td></tr><tr><td /><td>4</td><td>1,860.35</td><td>1,952.34</td><td>1,848.01</td><td>1</td><td>0.662</td><td><0.001</td><td>0.72/0.11/0.11/0.07</td></tr></tbody></table> </ephtml> </p> <p>Analyzing the results of the latent profile analysis models at the two time points allows for description and categorization of distinct profiles. First, based on the score characteristics of the three profiles at T1 across the six indicators (see Figure 1), the profiles are designated according to their levels of object control development as follows: Profile1: Low—Characterized by the lowest scores across all six indicators among the three profiles. Profile 2: Medium—Characterized by scores in the middle range for all six indicators. Profile 3: High—Characterized by the highest scores across all six indicators. The distribution of children in each profile comprises 37%, 55%, and 8% of the total sample, respectively. Second, based on the score characteristics of the three profiles at T2 across the six indicators (see Figure 2), the profiles are categorized as follows: Profile1: Low—Characterized by the lowest scores in all indicators except for overhand throwing. Profile2: Medium—Characterized by the highest scores in striking a stationary ball and the overhand throwing, with middle-range scores for the other four indicators. Profile 3: High—Characterized by the highest scores in all indicators except for striking a stationary ball and the overhand throwing. The distribution of children in each profile comprises 22%, 72%, and 7% of the total sample, respectively.</p> <p>Graph: Figure 1. Latent profiles at T1.</p> <p>Graph: Figure 2. Latent profiles at T2.</p> <hd id="AN0188424263-14">Latent Transition Analysis of Object Control</hd> <p>Given that the three-profile model was identified as the most optimal solution for both T1 and T2 in the latent profile analyses, a latent transition analysis was conducted to examine profile transitions between these two time points. Table 5 delineates the probabilities of children in each profile at T1 either remaining in their initial profile or transitioning to a different profile at T2. The results reveal significant shifts in the developmental levels of object control from T1 to T2. Among the three profiles, the Medium profile exhibits the greatest likelihood of remaining stable, with 12.1% of participants maintaining their status. However, Children in the Medium profile at T1 demonstrate a higher probability (87.9%) of progressing to the high profile at T2. Moreover, children initially classified in the Low profile at T1 show a tendency for upward transitions, advancing to either the Medium profile (18.5%) or the High profile (81.5%) at T2. On the other hand, children in the High profile at T1 predominantly transition to the Medium profile at T2, indicating a decline in developmental level.</p> <p>Table 5. Transition Probabilities</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th /><th align="center">T2 low</th><th align="center">T2 medium</th><th align="center">T2 high</th></tr></thead><tbody><tr><td>T1 low</td><td>0</td><td>0.185</td><td>0.815</td></tr><tr><td>T1 medium</td><td>0</td><td>0.121</td><td>0.879</td></tr><tr><td>T1 high</td><td>0</td><td>1</td><td>0</td></tr></tbody></table> </ephtml> </p> <hd id="AN0188424263-15">Gender Differences</hd> <p>To explore gender differences in children's object control, the Low profiles at T1 and T2 were used as reference groups in a multivariate logistic regression analysis, with gender as the predictor variable. The analysis produced odds ratios (OR), representing the probability ratio of a child being classified into the Medium or High profile compared to the Low profile. The results are summarized in Table 6. Gender was coded as 1 (male) and 2 (female), with statistical significance levels set at <emph>p</emph> < 0.05 (significant) and <emph>p</emph> < 0.01 (highly significant).</p> <p>Table 6. The Results of Logistic Regression Analysis on the Effects of Gender on Latent Profiles of Object Control.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /></colgroup><thead><tr><th align="left" rowspan="3">T1 IV</th><th align="center" colspan="8"><italic>Control group</italic>: Low (T1)</th></tr><tr><th align="center" colspan="4">Medium (T1)</th><th align="center" colspan="4">High (T1)</th></tr><tr><th align="left">OR</th><th align="center"><italic>p</italic></th><th align="center" colspan="2">95% CI</th><th align="center">OR</th><th align="center"><italic>p</italic></th><th align="center" colspan="2">95% CI</th></tr></thead><tbody><tr><td>Gender</td><td>1.45</td><td>.39</td><td>0.62</td><td>3.39</td><td>2.41</td><td>.06</td><td>0.96</td><td>6.07</td></tr><tr><th align="left" rowspan="3">T2 IV</th><th align="center" colspan="8"><italic>Control group</italic>: Low (T2)</th></tr><tr><th align="center" colspan="4">Medium (T2)</th><th align="center" colspan="4">Medium (T2)</th></tr><tr><th align="left">OR</th><th align="center"><italic>p</italic></th><th align="center" colspan="2">95% CI</th><th align="center">OR</th><th align="center"><italic>p</italic></th><th align="center" colspan="2">95% CI</th></tr><tr><td>Gender</td><td>3.96</td><td><.01</td><td>1.50</td><td>10.40</td><td>4.52</td><td>.08</td><td>0.85</td><td>24.11</td></tr></tbody></table> </ephtml> </p> <p>At T1, with the Low profile serving as the reference category, no significant gender differences were observed across the profiles (OR = 1.45; OR = 2.41). However, at T2, when the Low profile remained the reference category, the findings indicate that boys were more likely than girls to transition into the Medium profile (OR = 3.96).</p> <hd id="AN0188424263-16">Discussion</hd> <p>Dynamic Systems Theory (DST) fundamentally posits that the development of young children's object control abilities constitutes a self-organizing process emerging from the nonlinear coupling of neural, task, and environmental constraints. While previous studies have examined age and gender differences along with developmental trends, research remains notably lacking in adopting a person-centered approach to investigate the underlying mechanisms of longitudinal profile differentiation, transition patterns, and gender effects in children aged 3 to 6 years ([<reflink idref="bib5" id="ref50">5</reflink>]; [<reflink idref="bib31" id="ref51">31</reflink>]; [<reflink idref="bib42" id="ref52">42</reflink>]). The findings of this study reveal that at both T1 and T2, children's object control abilities can be categorized into three distinct profiles: Low, Medium, and High. Children within each profile display varying levels of stability and distinct transition patterns over time. Additionally, this study identified gender differences within the profiles, providing a deeper understanding of the developmental trajectories of object control abilities in early childhood and highlighting the role of gender in shaping these developmental patterns.</p> <p>This study reveals the hierarchical differentiation of children's object control abilities based on latent profile analysis, which can be interpreted from the perspective of dynamic systems theory as the multistable representation of individual developmental trajectories at the psychobehavioral level. At both T1 and T2, children's object control abilities were consistently categorized into three distinct profiles: Profile 1 (Low), Profile 2 (Medium), and Profile 3 (High), this reflects the differential adaptation states that children develop through the interplay of neurophysiological maturation, cumulative motor experience, and environmental task demands. Each profile exhibited varying degrees of developmental progress across the two time points. These findings align with the dynamic growth patterns typical of early childhood, reinforcing the preschool period as a critical and sensitive phase for motor development, and a peak period for overall growth and maturation ([<reflink idref="bib13" id="ref53">13</reflink>]). Notably, the Medium profile consistently represented the largest proportion of children at both time points, while the High profile accounted for the smallest proportion. These findings suggest that most children exhibit average motor skills development, followed by below-average levels, with only a minority achieving advanced proficiency ([<reflink idref="bib15" id="ref54">15</reflink>]).</p> <p>Furthermore, over time, all three profiles demonstrated significant developmental progress. By T2, scores for five out of six motor skills began to converge, although disparities persisted in overhand throw. This divergence could stem from the relative simplicity of kicking movements compared to the more complex overhand throw, a finding consistent with previous research ([<reflink idref="bib15" id="ref55">15</reflink>]). A possible explanation for this disparity is the limited exposure to throwing activities, as nearly 98% of children have minimal opportunities to practice such movements in their daily lives ([<reflink idref="bib44" id="ref56">44</reflink>]). The lack of experience, compounded by reduced practice during the predominantly home-based environment between assessments, likely contributed to slower mastery and even a decline in overhand throwing performance among children in the High profile at T2. On the other hand, variations in home environments and physical activity frequency further amplify these differences beyond initial biological predispositions.</p> <p>To chart development trajectories, latent transition analysis was conducted to examine profile transitions from early to later kindergarten years. The transition matrix revealed substantial movement between profiles, driven by the rapid growth characteristic of the preschool period. Children in the Low and Medium profile at T1 were more likely to progress to the High profile at T2, suggesting accelerated improvement in object control skill among these groups. Conversely, children in the High profile at T1 exhibited a tendency to transition to the Medium profile at T2, possibly reflecting a convergence of scores across most motor skills. By T2, scores for five motor skills aligned more closely, with the exception of the overhand throw, where the Medium profile demonstrated greater proficiency than the high profile. According to the pyramid model of gross motor skill development, 60% of children reach the mature stage of fundamental motor skill development before the age of 10, with object control abilities typically maturing with age and reaching near-completion before elementary school ([<reflink idref="bib37" id="ref57">37</reflink>]). This trend explains the convergence of motor skill scores in the later kindergarten year (T2). Children aged 2 to 7 are in a critical window for the development of fundamental motor skills, which primarily involve gross motor movements. Proficiency in these skills not only provides a foundation for fine motor development but also supports the maturation of the nervous system and brain centers ([<reflink idref="bib41" id="ref58">41</reflink>]; [<reflink idref="bib43" id="ref59">43</reflink>]). Thus, it is essential to promote balanced motor skill development, while addressing disparities in specific skills through consistent support and intervention.</p> <p>The gender differentiation pattern revealed in this study is essentially the result of the dynamic coupling between neurobiological constraints and sociocultural constraints. At T1, no significant gender differences were found among younger kindergarten children. However, at T2, boys in the older kindergarten group were significantly more likely than girls to be in the Medium profile. The Medium profile at T2 displayed scores in stationary dribbling and kicking comparable to those of the High profile, and scores in striking a stationary ball and overhand throwing that exceeded those of the High profile, indicating above-average object control abilities. Empirical evidence suggests that gender differences in throwing movements are negligible among children aged 3 to 5 but become pronounced between aged 5 and 6 ([<reflink idref="bib43" id="ref60">43</reflink>]). Although girls tend to outperform boys in displacement movements during the early years, boys' greater engagement in physical activities over time likely enables them to achieve higher levels of gross motor skill sophistication and balance as they grow older ([<reflink idref="bib36" id="ref61">36</reflink>]). From a dynamic systems perspective, the biomechanical traits early evident in boys (such as upper limb strength gains) synergize adaptively with ball-related tasks in kindergarten. When neural maturation enters a sensitive period at ages 5 to 6 ([<reflink idref="bib32" id="ref62">32</reflink>]), their trunk rotation efficiency confers corresponding advantages in throwing/striking actions. Within sociocultural constraints, social expectations direct boys' attentional resources toward ball games ([<reflink idref="bib8" id="ref63">8</reflink>]), further confirming that developmental trajectories are dominated by real-time constraint interactions.</p> <hd id="AN0188424263-17">Implications</hd> <p>This study adopts an individual-centered approach and conducts a 2-year longitudinal design to investigate the stratification, temporal dynamics, and gender disparities in object control among 3 to 6 year-old children in China. By illuminating the developmental nuances of object control in this age group, the findings contribute to a deeper understanding of object control development and provide a foundation for cross-regional and cross-cultural analyses and serving as a valuable reference for educational practices in kindergartens.</p> <p>Firstly, kindergartens should establish developmentally inclusive motor environments by implementing targeted intervention curricula aligned with object control developmental stages across three grade levels. This includes facilitating daily mixed-age and mixed-gender collaborative games (e.g., older children guiding younger peers in throwing/catching activities) to disrupt ability stratification, while administrators conduct monthly spatial optimization based on equipment utilization patterns. Secondly, educators should develop developmental observation frameworks to identify critical motor breakthroughs (e.g., three consecutive successful throws), implementing customized guidance: (<reflink idref="bib1" id="ref64">1</reflink>) For cautious learners: Scaffolded approaches (gradually increasing throwing distances). (<reflink idref="bib2" id="ref65">2</reflink>) For risk-taking learners: Rule-bound challenges ("step backward after hitting target"). (<reflink idref="bib3" id="ref66">3</reflink>) Gender-balanced participation: Role rotation systems and group incentives ("three attempts per child"). Finally, parents should engage in 10-minute daily gamified training within designated safe home movement zones, establishing concurrent home-school monitoring of each child's developmental trajectory.</p> <hd id="AN0188424263-18">Conclusion</hd> <p>This study reveals three key insights into children's object control development: (<reflink idref="bib1" id="ref67">1</reflink>) Three distinct proficiency profiles (Low, Medium, High) were identified across time points, with Medium being most prevalent; (<reflink idref="bib2" id="ref68">2</reflink>) Children in initial Low/Medium profiles showed greater likelihood of transitioning to High profile, while High profile children tended to regress toward Medium profile; (<reflink idref="bib3" id="ref69">3</reflink>) Gender differences emerged at T2, with boys more likely classified as Medium profile. These findings extend developmental trajectory models by demonstrating nonlinear progression patterns in motor skills. Future research should examine contextual factors influencing these transition dynamics to optimize skill development interventions.</p> <hd id="AN0188424263-19">Limitations</hd> <p>The study acknowledges several limitations that warrant further exploration in future research. Firstly, the study developmental transitions in children's object control abilities at only two time points. Future research could adopt a longitudinal tracking design with more frequent measurements to capture finer-grained developmental trajectories. Additionally, the current study does not delve into the precursors of children's object control abilities. Future research could explore the multifaceted influences on object control development, such as family dynamics, socioeconomic status, environmental factors, and parental involvement.</p> <ref id="AN0188424263-20"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref2" type="bt">2</bibl> <bibtext> Qiaoling Li</bibtext> </blist> <blist> <bibtext>Graph https://orcid.org/0000-0003-0278-303X</bibtext> </blist> <blist> <bibl id="bib3" idref="ref3" type="bt">3</bibl> <bibtext> This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Henan University (ID: 20231110007).</bibtext> </blist> <blist> <bibl id="bib4" idref="ref28" type="bt">4</bibl> <bibtext> Informed consent was obtained from all subjects involved in the study.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref50" type="bt">5</bibl> <bibtext> Informed consent for publication of participant data was obtained from all subjects involved in the study.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref46" type="bt">6</bibl> <bibtext> The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Teaching Reform Research and Practice Project of Henan University (No. YB-JFZX-2022-06).</bibtext> </blist> <blist> <bibl id="bib7" idref="ref12" type="bt">7</bibl> <bibtext> The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref35" type="bt">8</bibl> <bibtext> The data presented in this study are available on request from the corresponding author. 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  Data: Object Control Profiles and Gender Differences in Preschoolers: A 2-Year Latent Transition Analysis
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  Data: <searchLink fieldCode="AR" term="%22Hang+Zhang%22">Hang Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Yueyue+Zhou%22">Yueyue Zhou</searchLink><br /><searchLink fieldCode="AR" term="%22Qiaoling+Li%22">Qiaoling Li</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0278-303X">0000-0003-0278-303X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Guoxiang+Zhao%22">Guoxiang Zhao</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22SAGE+Open%22"><i>SAGE Open</i></searchLink>. 2025 15(3).
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  Data: <searchLink fieldCode="DE" term="%22Preschool+Children%22">Preschool Children</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Psychomotor+Skills%22">Psychomotor Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Motor+Development%22">Motor Development</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
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  Data: Based on dynamic systems theory, the longitudinal study tracked 120 kindergarten children 2 years to examine the differentiation and transition of object control profiles among preschool children aged 3 to 6. Latent profile analysis (LPA) and latent transition analysis (LTA) were employed to identify development profiles and transitions, as well as to examine gender differences within these profiles. The findings indicated that: (1) Children's object control abilities were classified into three profiles: low, medium, and high, with the medium profile accounting for the largest proportion at both time points. (2) From T1 to T2, children in low and medium profiles at T1 were more likely transition to the high profile at T2, while those in the high profile at T1 showed a higher probability of transitioning to the medium profile at T2. (3) At T2, significant gender differences emerged, with boys being more likely than girls to belong to the medium profile. These findings provide empirical insights to guide kindergarten educational practices in supporting children's developmental trajectories.
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      – TitleFull: Object Control Profiles and Gender Differences in Preschoolers: A 2-Year Latent Transition Analysis
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