https://orcid.org/0000-0001-5342-493X
Figures
Abstract
Self-regulation, which encompasses cognitive, behavioural, and emotional domains, poses challenges in consistent measurement due to diverse definitions and conceptual complexities. In recognition of its profound impact on long-term mental health and wellbeing in children, this systematic review examined available self-regulation measures for children and young people between 1 and 18 years of age. The systematic review followed the COSMIN taxonomy and reported on the measurement tools’ characteristics and psychometric properties. The methodology and reporting were guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and checklist. The protocol for this review was registered with PROSPERO (Number CRD42020155809). A search of six databases (Embase, MEDLINE, PsycINFO, Scopus, CINAHL and ERIC) was performed, and grey literature was searched to identify studies on the psychometric properties of measures assessing all three domains (cognitive, behavioural, and emotional) of self-regulation. The types of psychometric properties were examined against the COSMIN taxonomy of measurement properties. A total of 15,583 studies were identified, and 48 of these met the criteria that reported psychometric properties of 23 self-regulation measures assessing all three domains of self-regulation. Most measures relied on self-reports for ages 11–17, and all had limited psychometric evaluation. The Emotion Regulation Checklist was the most studied measure. Notably, none of the studies evaluated measurement error. The content validity was inadequately evaluated, particularly in terms of comprehensiveness and comprehensibility. Future research should focus on developing measures for young children, evaluating measurement error, and enhancing content validity for comprehensive understanding and effective intervention.
Citation: Chen Y-WR, Janicaud N, Littlefair D, Graham P, Soler N, Wilkes-Gillan S, et al. (2024) A systematic review of self-regulation measures in children: Exploring characteristics and psychometric properties. PLoS ONE 19(9): e0309895. https://doi.org/10.1371/journal.pone.0309895
Editor: Leona Cilar Budler, University of Maribor, SLOVENIA
Received: December 18, 2023; Accepted: August 20, 2024; Published: September 19, 2024
Copyright: © 2024 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Self-regulation is a central facet of human functioning [1,2], encompassing a person’s ability to control their behaviour, emotions, thoughts and attention to attain specific goals [3,4]. Previous researchers found that self-regulation is positively associated with school achievement [1,5–7], wellbeing and mental health [1,5]. Without proficient self-regulation skills, building lasting friendships, engaging in healthy romantic relationships and participating in appropriate social roles would be almost unattainable [6,8]. Indeed, children need to develop and apply self-regulation skills successfully across multiple aspects of life [1,9].
However, contrasting perspectives and various disciplinary specialisations have resulted in multiple conceptual meanings for self-regulation [10]. Although conceptually, there are related and overlapping terms for self-regulation (e.g., emotional regulation), inconsistency and incongruency in terminology have led to complexity in defining self-regulation [10,11]. Further, the term self-regulation encompasses varying concepts and consists of multiple facets with no exact indicator of what constitutes self-regulation, further complicating the measurement of its construct [10]. These discrepancies in terminology and definitions of constructs being measured resulted in difficulties in integrating research findings across studies and disciplines.
In addition, timely and effective assessment and identification of self-regulation difficulties are crucial to ensure the implementation of appropriate early interventions to prevent long-term mental health and wellbeing difficulties associated with poor self-regulation [12]. Measuring the outcome of service provision is imperative to discern the value and impact of treatment, regardless of population and practice area [13]. Validated, sensitive and reliable self-regulation measures to assess treatment efficiency in children and adolescents are necessary for clinical use.
To date, very few studies have reviewed self-regulation measures for children. For example, Philpott-Robinson, Johnson [11] conducted a recent scoping review to identify self-regulation assessment tools in 67 studies, highlighting inconsistencies in the measures and constructs used for assessing self-regulation in pre-school and elementary-aged children. Similarly, Solé-Ferrer, Mumbardó Adam [14] systematically reviewed 37 self-regulation measures from 50 studies for children and adolescents, revealing considerable diversity in the measures used, which often attributed to the lack of consensus in the definition of the self-regulation construct. Although a range of self-regulation measures have been identified in these reviews, there was a lack of a well-defined concept of self-regulation for guiding the selection of measurement tools. This, coupled with the omission of reviews of psychometric properties, particularly the critical consideration of content validity [15], hinders the practical and research application of these findings.
There is an urgent need for a systematic review to adopt a universal definition of self-regulation, identify and outline the characteristics of self-regulation measures, and evaluate their psychometric properties. In contemporary literature, self-regulation is a multi-dimensional construct encompassing three specific domains: cognitive, emotional, and behavioural regulation [10,16–18]. Therefore, our study presents a unique perspective compared to previous reviews, focusing on assessing self-regulation across all three domains. Specifically, cognitive regulation involves mental functions such as attention, memory, flexibility and the management of thoughts [16,19,20]. Emotional regulation pertains to managing and influencing emotions, including their expression and experience [21,22]. Behavioural regulation encompasses controlling actions, including the ability to inhibit or initiate behaviours and manage impulses [20]. Thus, our systematic review aimed to: (a) identify the available self-regulation measures used in paediatric populations (0–18 years) from the studies investigating their psychometric properties, (b) summarise the characteristics of the measures and included studies, and (c) evaluate the psychometric properties of these measures, including their development and content validity. The evaluation of psychometric properties follows the terminology and definitions outlined in the COSMIN (COnsensus-based Standards for the selection of health Measurement INstrument) taxonomy [23].
Methods
This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines [24]. The ten items of the A MeaSurement Tool to Assess systematic Reviews 2 (AMSTAR 2) Field [25] were also used. The protocol for this review was registered with PROSPERO (Number CRD42020155809).
[The PRISMA checklist is provided as Supporting Information].
Eligibility criteria
The eligibility criteria for this review encompassed published articles or manuals that provided information on the study of the psychometric properties of measures designed to assess self-regulation. Given the multitude of terms with similar definitions closely related to self-regulation, articles were considered for inclusion if they explicitly claimed to measure any of the terms associated with self-regulation, such as self-regulation, emotion regulation, effortful control, behaviour regulation, or emotional competence. Additionally, articles were included if the measurement tools were applied to populations with an average age below 18 years. However, articles were excluded if the primary focus was not on the measurement of self-regulation but instead utilised the tool to develop another measurement instrument. For instance, an article would be excluded if the self-regulation measure was used solely to establish the criterion validity of another tool not related to self-regulation. In addition, articles were excluded if it was impossible to separate the measurement of self-regulation from other constructs; for example, if a measurement tool claimed to assess both self-regulation and social skills, it would be excluded. Articles written in languages other than English were excluded. Further, conference abstracts, theses, presentations and articles where the measurement tool was unavailable were excluded. We did not restrict the publication date to capture a comprehensive range of measurement tools for our review.
Information sources
A systematic literature search was performed using medical subject headings (MeSH) or Thesaurus terms and free text on the following online databases: Embase, MEDLINE, PsycINFO, Scopus, CINAHL and ERIC. These databases were selected to cover the wide array of disciplines concerned with self-regulation, such as psychology, education, health sciences and medicine. To identify articles in the databases, we used a combination of different search terms in the following areas: “self-regulation’, ’psychometric properties’, ’assessment’ and ’children’. The original search was performed in February 2023 and updated in March 2024. Grey literature was searched for using Google Scholar. A complete list of search terms and strategies is available in S1 File.
Study selection
We used Endnote to remove duplicate entries from the systematic literature search across the six databases. We then created the Excel spreadsheet to include the titles and abstracts of the articles retrieved for screening. The second author, who had also provided training to the other reviewer (TM) regarding the eligibility criteria for article inclusion and exclusion, independently reviewed all the titles and abstracts of the retrieved articles against the inclusion criteria. The other reviewer independently evaluated a randomly selected 20% of the article abstracts to ensure rating accuracy. Inter-rater reliability for the screening between the two reviewers was assessed based on weighted Kappa calculations of 0.86 (95% CI = 0.80–0.93). Where disagreements occurred between the reviewers, a third reviewer (YRC) was involved in determining an article’s eligibility for inclusion until a consensus was reached. Due to the high inter-rater reliability achieved [25], the second author screened the remaining articles. In the secondary stage screening, the full-text articles and assessment items were screened against the definitions of the three domains of self-regulation by consensus ratings of the first, second and last authors to ensure the tools satisfied the criteria measuring all three domains (i.e., cognitive regulation [thoughts], emotion regulation [feelings], and behavioural regulation [emotions]). Grey literature was searched using Google Scholar, and reference lists of included studies were searched to identify any articles that were not identified in the systematic literature search.
Methodological quality of the studies
The methodological quality of each study was systematically assessed using standard quality assessment criteria for evaluating primary research [26]. The Kmet checklist offers a quantifiable measure for evaluating the quality of studies using a 3-point ordinal scale (2 = yes, 1 = partial, 0 = no) applied to 14 criteria, including sampling strategy, justification of analytic methods, and reporting of results. To derive the quality percentage score, the total score is divided by the maximum score, omitting non-applicable criteria. Subsequent classification of methodological quality is then based on the calculated percentage, with scores exceeding 80% classified as strong, those falling within the range of 70–79% classified as good, those between 50–69% classified as fair, and scores below 50% classified as poor.
Data synthesis
At this stage of analysis, all articles for each of the measurement tools of self-regulation were scrutinised as guided by the Cochrane Handbook for Systematic Reviews [27] and the Systematic Reviews Centre for Reviews and Dissemination [28]. The COSMIN taxonomy [23] was used to identify which psychometric properties have been studied and reported on for each of the measurement tools. We particularly examined the content validity due to its recognised importance as the most psychometric property for investigation in a measurement tool [15]. Comprehensive data forms were developed and populated for the following information:
- Measurement tool characteristics–including the purpose, measurement type, recall period, scale titles and number of items, response options, number of scales and range of scores, and the interpretation of scores.
- Study characteristics–including the purpose of the study, sample size, population characteristics, the age ranges captured in each study and the methodological quality of each study.
- Psychometric properties–reporting on whether a study has been conducted on each of the properties detailed in COSMIN: internal consistency, reliability, measurement error, content validity, structural validity, hypothesis testing, measurement invariance/ cross-cultural validity and criterion validity. The examination of responsiveness was excluded in this study because investigating it requires reviewing studies that have employed the identified measures as an outcome assessment.
- Content validity–reporting on three aspects of the content of an instrument: (a) relevance (i.e., the degree to which all items of a measurement tool are relevant for the construct of interest within a target population and purpose of use), (b) comprehensiveness (i.e., the degree to which all key concepts of the construct are included in a measurement tool), and (c) comprehensibility (i.e., the degree to which items of a measurement tool are easy to understand by respondents) [15].
Results
Results of search
The systematic literature search from the six databases produced 15,583 articles. After removing 5,078 duplicates, a total of 10,505 articles were retrieved for screening using the inclusion and exclusion criteria. An additional nine articles were located in total, six via grey literature searching on Google Scholar and three from reference list searching. After screening for titles and abstracts, 237 records were identified for full-text screening, with 48 studies meeting the final eligibility criteria for this review. Fig 1 shows the PRISMA flowchart that illustrates the process of study selection.
Characteristics of measurement tools
A summary of the characteristics of the identified measurement tools is presented in Table 1. Fourteen of 23 measurement tools were self-report measures, including interviews with the child, where participants were expected to answer questions relating to their self-regulation. The measures used Likert scales, asking participants to rate either how much they agreed that a statement related to them or the frequency of a particular behaviour, thought, or feeling. The scales used were a 5-point (n = 11) or 4-point Likert scale (n = 3). Five measurement tools were parent/carer/teacher reports, where a parent, carer or teacher was asked to answer questions about their child’s self-regulation. Likert scales on the frequency of particular behaviours were used for four measures, while one measure used interviews with parents or carers for assessment. Four measurement tools used observer reports, which were not necessarily from a parent or carer. These measures used Likert scales asking about the degree to which the observer agrees about a child’s behaviour (Pre-school Situational Self-Regulation Toolkit assessment [PRSIST]; Response to Challenge Scale [RCS]) or frequency of behaviours (Pre-school Self-Regulation Assessment [PSRA]; Emotion Regulation Checklist [ERC]). The PSRA also record the latency of a behaviour, levels of waiting on a 4-point Likert scale, and levels of sharing on a 2-point Likert scale. It should be noted that the Difficulties in Emotion Regulation Scale (DERS) was included in the present study in its original form, as well as five other variants where different items were omitted for purposes of validating shortened versions. While all measures except the Adolescent Anger Rating Scale (AARS) were not commercially published, researchers and clinicians must contact the developers for cost information and obtain a copy of the measure.
The age distribution for the available assessment tools was skewed toward older age ranges, with a substantial abundance of measurement tools for ages 12 and above (Table 2). Twelve years of age was the most well-represented category, featuring 16 measurement tools. In contrast, ages 0–2 years had only one measurement tool. The intermediate age groups fell between 3 and 11 years, comprising between 5 and 10 measurement tools. Notably, self-report measurement tools were predominantly used for individuals aged 12 and older, while observational measures were more prevalent for the 3–7 age group. Moreover, parent or carer reports were less frequently utilised across all age ranges.
Characteristics of studies
All of the studies were conducted from 2000 onwards, except for one developmental study related to the ERC in 1997 (Table 3). Of the 48 studies, 33 were conducted within the most recent 10-year period (2014–2023), while the remaining 15 distinct studies were carried out before 2014. The sample sizes of child participants varied from 10 to 2,124, with 23 studies involving more than 500 participants. Most participants were from the USA (n = 18), followed by European countries (n = 17). The remaining participants were from Turkey (n = 5), Asian countries (n = 5), South America (n = 2), and Australia (n = 1). All studies except Jamal, Dzulkarnain [29] have good to strong methodological quality ratings. The most common risks of bias identified in studies rated as fair to good include unclear reporting on participant selection methods and insufficient information on participant characteristics.
Psychometric properties of measurement tools
The ERC is the most extensively studied tool, with nine studies conducted between 1997 and 2022, followed by the DERS and PRSA, which have been the subject of five studies, respectively (Table 3). Table 4 provides an overview of the psychometric properties examined in the included measurement tools. Regarding reliability, internal consistency has been assessed for 18 out of 23 measurement tools. However, both inter-rater and test-retest reliability were only examined for ERC and PSRA. Measurement error was not investigated for any of the tools.
In terms of validity, the structural validity of all measurement tools except for Early Development of Emotional Competence (EDEC) has been evaluated primarily through factor analysis. Hypothesis testing was conducted for all tools except Difficulties in Emotion Regulation Scale 16 (DERS-16) and EDEC. Eleven measurement tools have been examined for cross-cultural validity in different languages. ERC is the most widely used in cross-cultural studies, spanning six different countries in addition to the USA. Furthermore, measurement invariance, which is the other aspect of cross-cultural validity (e.g., differences across age groups or client populations), was explored in ten measures. The criterion validity of other versions of DERS was examined against the original DERS.
Concerning content validity, most measurement tools have been examined for their relevance, with each tool being developed based on a stated definition of the self-regulation construct (Table 5). However, it remains unclear whether the development of the construct in the PRSIS was based on a specific theory, conceptual framework, or model. Additionally, the target population for which the development was intended was not clearly disclosed in four measurement tools (Child Self-Report of Emotional Experience [CSREE], DERS-8, DERS-18, Emotional Skills & Competence Questionnaire [ESCQ]). Only six tools included cognitive interview studies or pilot testing as part of their development process. Furthermore, only three studies reported on comprehensibility (DERS-16, Emotional Competence Assessment Questionnaire [ECAQ], PSRA) and three on comprehensiveness (Adolescent Emotion Regulation Strategies Questionnaire [AERSC], ECAQ, PSRA) of the measurement tools from the client’s perspectives.
Discussion
This systematic review aimed to identify self-regulation measures applicable to infants, children, and young people aged 0 to 18 years, identifying 23 measures from 48 studies. The findings reveal significant gaps, particularly the scarcity of measures suitable for young children. Additionally, the study highlights that most measures have been insufficiently evaluated for psychometric properties. Overall, the findings provide a comprehensive overview of currently available measures, offering valuable insights for clinicians in selecting appropriate self-regulation assessments and recognising the limitations of existing tools.
One of the main findings concerns the availability of measures for different age cohorts. First, there is a significant scarcity of measures suitable for young children, which presents clinical challenges in early intervention, especially during the critical period when addressing self-regulation difficulties is paramount [77]. This scarcity underscores the need for well-developed and ecologically valid measures to assess self-regulation in preschool-age children, given its predictive nature for social and academic skills throughout childhood [78]. In addition, the majority of measures identified are self-report, particularly prevalent among adolescents aged 11–17 years. While self-report measures offer time efficiency for clinicians, their suitability may be limited for younger or neurodiverse children who are still developing their self-awareness and the ability to process, understand and communicate their emotions and experiences [79].
Another significant finding underscores the insufficient examination of psychometric properties across measures, with most studies only including 1–2 evaluations per measure. In addition, the majority of investigations were conducted by the developers of measures, resulting in a lack of independent evaluations. In contrast to other measures, the ERC was the most extensively evaluated, with nine studies exploring various psychometric properties. Given that the median age of children reported in a recent systematic review of self-regulation interventions was six years [80], the ERC emerges as the most researched measure for clinicians working with children aged 3–12 years who commonly require intervention for self-regulation. For clinicians supporting older children and young people, the DERS and its brief version (11–17 years) and ESCQ (12–17 years) were the most extensively researched measures (both self-report), each with four or more studies evaluating psychometric properties.
Of note, measurement error was not evaluated for any of the 23 measures, which raises concerns given its importance in reliability assessment. Measurement error estimates systematic and random errors in a client’s score that are not attributed to true changes in the measured construct [23]. This is particularly crucial when assessing pre- to post-intervention change.
However, most measures had been assessed for validity, including structural validity, hypothesis testing, internal consistency, and cross-cultural validity. Notably, content validity was inadequately assessed for most measures despite its significance in ensuring that the measure adequately reflects the construct of interest. Content validity involves both item generation and cognitive interview/pilot testing to ensure relevance, comprehensiveness and comprehensibility [15]. While many measures included the construct’s definition and conceptual framework, they fell short in evaluating comprehensiveness and comprehensibility. This is particularly concerning, given the prevalence of self-report measures. Although these measures allow individuals to self-report against included items, very few measures conducted cognitive interviews or other pilot tests on a sample representing the target population or sought feedback on the comprehensibility or comprehensiveness of the measurement tools. This approach hampers the understanding and interpretation of items by respondents, which may lead to capturing data that does not encapsulate the construct of self-regulation. Finally, although the included measures evaluated all three domains of self-regulation, most measures had a particular focus on emotional regulation, which is reflected in the names of many measures.
Limitations
While aiming for the rigour of this systematic review, several limitations should be considered when interpreting the results. Firstly, due to the absence of a universally agreed-upon definition for the construct of self-regulation and its domains, we relied on each domain’s shared understanding to review each measure’s items and determine the measures for inclusion in our review. Secondly, we assessed whether each type of psychometric property was examined for each measure but did not rate the quality of the psychometric properties of the reported information about the instruments. Future studies should utilise the COSMIN risk of bias [23] to evaluate the methodological quality of each psychometric article and the quality of the various psychometric properties to guide assessment and treatment planning decisions. Further, assessing responsiveness as a psychometric property was beyond the scope of this systematic review, as it would require a different search strategy. Subsequent studies could explore whether the measures included in this review have been employed as outcome measures and evaluate their responsiveness to changes in self-regulation. Lastly, this review only included full-text English studies, potentially overlooking measures developed in languages other than English.
Conclusion
This systematic review identified 48 studies that reported evidence of the psychometric properties of 23 self-regulation measures used with infants, children, and young people aged 0 to 18 years. Most measures had limited investigation of psychometric properties, except the ERC, the most extensively evaluated measure. Despite the critical role of self-regulation in the clinical assessment and treatment of children, this review underscores the need for more research examining the psychometric properties of self-regulation measures used with children. Directions for future research can be considered in terms of the continued evaluation of existing measures or the development of new measures. Notably, one avenue for future research is the development of measures for young children, particularly those aged three years and younger. Such measures should consider parent and teacher reports as well as observational assessments across home and other care contexts. Another avenue for further research is evaluating measurement errors in existing measures. Additionally, more parent- and teacher-report and observational assessments are needed to evaluate self-regulation measures for older children and young people.
Supporting information
S3 File. List of identified studies for the full-text review.
https://doi.org/10.1371/journal.pone.0309895.s003
(PDF)
S4 File. Quality assessment of includqed studies.
https://doi.org/10.1371/journal.pone.0309895.s004
(PDF)
Acknowledgments
We would like to thank Elaine Tam, the former Academic Liaison Librarian of Occupational Therapy at the University of Sydney, for generously contributing her time and expertise in guiding the formulation of search terms and training the second author in search procedures.
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