A 10-day experience sampling dataset on subjective experiences of middle and upper secondary school students in 2022

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Forsman" }, { "@type": "Person", "name": "Patrik Söderberg" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": "This data note presents a dataset collected within a 10-day experience sampling survey study among middle and upper secondary students in Finland during autumn 2022. The dataset encompasses a brief start-up survey in addition to 40 momentary assessments, allowing for the analysis of both inter- and intraindividual processes. The start-up survey includes validated measures on students’ perceptions of school-related support from family, peers, and teachers, general self-efficacy, and academic self-efficacy, as well as items on school enjoyment, and school absenteeism. The experience sampling data includes items related to positive and negative emotions, lecture characteristics, perceived teacher style, peer relationships, as well as sleep quality, breakfast, school readiness, and school day satisfaction. Data were collected using the “RealLife Exp” mobile app. Multiple procedures were undertaken to validate and confirm the reliability of the dataset, as presented in this data note. The methodological approach utilized for gathering the data featured in this dataset allows for a nuanced analysis of individual and contextual influences along with lagged effects on school well-being, with the potential to discover previously overlooked patterns and trends." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/13-1522", "name": "A 10-day experience sampling dataset on subjective experiences of..." } } ] } Home Browse A 10-day experience sampling dataset on subjective experiences of... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Mölsä M, Forsman AK and Söderberg P. A 10-day experience sampling dataset on subjective experiences of middle and upper secondary school students in 2022 [version 1; peer review: awaiting peer review] . F1000Research 2024, 13 :1522 ( https://doi.org/10.12688/f1000research.157148.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Data Note A 10-day experience sampling dataset on subjective experiences of middle and upper secondary school students in 2022 [version 1; peer review: awaiting peer review] Martina Mölsä https://orcid.org/0000-0001-8936-1168 1 , Anna K. Forsman 2 , Patrik Söderberg 1 Martina Mölsä https://orcid.org/0000-0001-8936-1168 1 , Anna K. Forsman 2 , Patrik Söderberg 1 PUBLISHED 16 Dec 2024 Author details Author details 1 Department of Developmental Psychology, Åbo Akademi University, Vaasa, Finland 2 Department of Health Sciences, Åbo Akademi University, Vaasa, Finland Martina Mölsä Roles: Formal Analysis, Funding Acquisition, Investigation, Methodology, Writing – Original Draft Preparation Anna K. Forsman Roles: Writing – Review & Editing Patrik Söderberg Roles: Conceptualization, Data Curation, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Writing – Review & Editing OPEN PEER REVIEW REVIEWER STATUS AWAITING PEER REVIEW This article is included in the Data: Use and Reuse collection. Abstract This data note presents a dataset collected within a 10-day experience sampling survey study among middle and upper secondary students in Finland during autumn 2022. The dataset encompasses a brief start-up survey in addition to 40 momentary assessments, allowing for the analysis of both inter- and intraindividual processes. The start-up survey includes validated measures on students’ perceptions of school-related support from family, peers, and teachers, general self-efficacy, and academic self-efficacy, as well as items on school enjoyment, and school absenteeism. The experience sampling data includes items related to positive and negative emotions, lecture characteristics, perceived teacher style, peer relationships, as well as sleep quality, breakfast, school readiness, and school day satisfaction. Data were collected using the “RealLife Exp” mobile app. Multiple procedures were undertaken to validate and confirm the reliability of the dataset, as presented in this data note. The methodological approach utilized for gathering the data featured in this dataset allows for a nuanced analysis of individual and contextual influences along with lagged effects on school well-being, with the potential to discover previously overlooked patterns and trends. READ ALL READ LESS Keywords experience sampling, school well-being, social support, self-efficacy, emotions Corresponding Author(s) Martina Mölsä ( [email protected] ) Close Corresponding author: Martina Mölsä Competing interests: No competing interests were disclosed. Grant information: The research was funded by the Högskolestiftelsen i Österbotten and the Gösta Branders Research Fund, Åbo Akademi University Foundation (Gösta Branders forskningsfond, Stiftelsen för Åbo Akademi). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2024 Mölsä M 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 work is properly cited. How to cite: Mölsä M, Forsman AK and Söderberg P. A 10-day experience sampling dataset on subjective experiences of middle and upper secondary school students in 2022 [version 1; peer review: awaiting peer review] . F1000Research 2024, 13 :1522 ( https://doi.org/10.12688/f1000research.157148.1 ) First published: 16 Dec 2024, 13 :1522 ( https://doi.org/10.12688/f1000research.157148.1 ) Latest published: 16 Dec 2024, 13 :1522 ( https://doi.org/10.12688/f1000research.157148.1 ) Introduction The purpose of this data note is to describe an experience sampling dataset concerned with subjective emotional experiences of Finnish school students collected in 2022. The dataset was gathered as part of a research project at Åbo Akademi University (ÅAU). Specifically, it provides a summary of the raw dataset, comprising both baseline and momentary self-report ratings on self-efficacy, social support, and positive and negative affect. These self-reports were submitted by middle and upper secondary school students. This dataset is currently being utilized in several ongoing research studies. Traditionally, research on student school-related well-being has predominantly adopted between-person approaches such as cross-sectional research designs, overlooking the dynamic nature of adolescents’ daily experiences in the school setting. Unlike cross-sectional surveys, which typically asks respondents to rate their overall experiences in retrospect, the experience sampling method (ESM; Larson & Csikszentmihalyi, 1983 ) is an intensive longitudinal design approach that allows respondents to report their experiences in real-time and on multiple occasions over time. This enables the capture of ecologically valid data within the natural school environment ( Zirkel et al., 2015 ). Although ESM is increasingly popular for exploring both intra- and interindividual processes related to student behaviors, thoughts, and emotions, few ESM datasets have addressed social dimensions within the school setting. Collecting data for such studies can be challenging due to the significant time and resource commitment required from both researchers and participants. With both baseline and momentary data included, this dataset allows for comprehensive analyses of individual and contextual influences, as well as lagged effects. Thus, the ESM employed enriches this dataset by providing the means to assess students’ within-person processes or situational factors, including the antecedents and consequences of various psychological states in students daily school life. Consequently, this methodological approach offers the potential to discover patterns and trends in school well-being that may otherwise go unnoticed. Methods Sample The dataset was generated from a sample of middle and upper secondary school students in Finland in fall 2022. The dataset comprises a start-up survey as well as momentary self-reports from students over a period of 10 weekdays. Initially, 358 participants completed the start-up survey. Of these, 324 participants participated in the 10-day ESM period. Participants who did not provide consent or did not complete at least three ESM assessments, along with students who had not yet turned 15, were excluded from the dataset, leading to an analytic sample of 302 participants. To note, the raw data file contains approximately 8,260 rows for these 302 participants due to the data’s long format, where each row represents an individual measurement point. For the purpose of participant anonymity, background variables such as age, socio-economic status, school or municipality are not included at the individual level in the dataset available for open access. For the same reason, gender response options “other” and “I don’t want to reply” were collapsed into missing data. Procedure Data was collected using the “RealLife Exp” app, developed by LifeData (accessible at https://www.lifedatacorp.com/ ). During start-up sessions at schools, participants were in large groups with teachers present given instructions on how to download the app “RealLife Exp” on their own mobile phones, including instructions on how to start the survey. The participants were given the possibility to ask any questions related to the data collection and the research project during the start-up sessions. While LifeData operates as a Software as a Service (SaaS) platform and does not issue traditional copyright licenses, our use of the app is fully compliant with their terms of service. Measured variables The public dataset described in this data note comprises both baseline and momentary data ( Söderberg & Mölsä, 2024 ). Start-up survey The start-up survey includes measures on (a) academic self-efficacy (ASE, a subscale within the Self-Efficacy Questionnaire for Children, SEQ-C; Muris, 2001 ), (b) school-related social support from peers (Peer Support at School; PSS), teachers (Teachers-Student Relationship; TSR), and family (Family Support for Learning; FSL) (from SEI; Appleton et al., 2006 ), and (c) general self-efficacy (from S-GSE; Schwarzer & Jerusalem, 1995 ). To note, a modified version of the S-GSE with a Swedish translation by Koskinen-Hagman et al. (1999) was used. In addition, there is a single item measuring school enjoyment (self-designed), and another item assessing school absenteeism (self-designed). Regarding academic self-efficacy, four out of the original eight items in the ASE subscale ( Muris, 2001 ) were selected for inclusion in this dataset. Similarly, not all the original 35 items in the SEI ( Appleton et al., 2006 ) were used; instead, the measurement instrument was modified to contain a total of 19 items, distributed across the three subscales. Moreover, from the original S-GSE scale ( Schwarzer & Jerusalem, 1995 ) of ten items, five items of the S-GSE were selected to be included in this dataset. Additionally, for the S-SGE scale, the response scale was modified from a 4-point to a 5-point scale. Apart from the item on school absenteeism, all baseline items were chosen to be rated on a slider scale with two end points, ranging from 1 (“No, not at all”) to 5 (“Yes, absolutely”). The survey item measuring school absenteeism (“Have you been absent from school in the past two weeks?”) consists of three response options: (a) No, (b) Yes, once, and (c) Yes, several times. Experience Sampling Measures (ESM) The ESM part was designed to include three blocks of inquiries: a morning block, a pre-and afternoon block, and an evening block. The morning block (Block A) encompassed three items: (i) “Good morning. Did you sleep well last night?”, (ii) “Have you eaten (or will you eat) breakfast this morning?”, and (iii) “Do you feel okay about going to school today?”. The pre- and afternoon block (Block B) aimed to assess the respondent’s current emotional state with the query (i) “How are you feeling right now?” (8 items), (ii) perceptions of the most recent lecture with the query “The recent lecture was …” (6 items), and (iii) an assessment of their enjoyment during peer interactions with the query “Did you have a good time with your classmates in the morning/in the afternoon?” (1 item). Lastly, the evening block (Block C) was designed to assess overall school day satisfaction with a single query: “What rating would you give for the overall school day?”. The first query within Block B includes items based on both positive and negative emotions following the PANAS framework ( Watson & Clark, 1994 ; Watson et al., 1988 ). All other ESM items were designed by the project. All ESM items were selected to be rated on a 5-point slider scale (1: No, not at all, 5: Yes, absolutely), except for the item within Block C, which was rated on a 10-point slider scale. Translation of items In addition to utilizing existing modified versions of scales with Swedish translations, such as the S-SGE scale, all items within the dataset were translated into Swedish for the data collection. The translations were refined within the research group and confirmed by the project leader. Prior to data collection, the translated items underwent testing through a series of pilot studies conducted among secondary school students, with participant numbers ranging from three to fifteen for each test. ESM protocol The ESM protocol encompasses four measurement points per day during a period of 10 school days across two weeks (Monday-Friday), resulting in a total of 40 measurement points. The ESM surveys were administered at three designated fixed intervals (07:15 a.m., 09:45 a.m., 01:05 p.m.) and one randomized interval (07:00–10:00 p.m.), with a 1.5-hour response window provided for each prompt. Respondents had the option to skip any question but could not revisit or modify their response. To mitigate potential reporting fatigue, the assessment scales were kept brief. Additionally, a planned missingness approach was implemented for the PANAS items to mitigate systematic non-response effects. Specifically, one item (in block B: “I enjoy being at school”) was consistently included, while each of the other PANAS items was intentionally omitted on one out of seven prompts. Furthermore, additional signals with random questions unrelated to the dataset, were prompted once every afternoon to add variety. Respondents were regularly notified of their progress throughout the data collection period by means of in-app information. As external motivation, respondents who participated in both the baseline survey and the ESM period were rewarded with a 20 € gift card. See Table 1 for an overview of the ESM protocol designed for this dataset. Table 1. The ESM protocol for the dataset. Prompt 07:15 a.m. 09:45 a.m. 01:05 p.m. 07:00–10:00 p.m. Block A (i) Sleep quality 1 item (ii) Breakfast 1 item (iii) School readiness 1 item Block B (i) PANAS 1 item + 6 out of 7 items 1 item + 6 out of 7 items (ii) Lecture characteristics 6 items 6 items (iii) Peer relationships 1 item 1 item Block C (i) School day satisfaction 1 item Total items per prompt 3 items 14 items 14 items 1 item Dataset validation Pilot studies To ensure face validity and to assess participant burden, a series of four pilot studies were conducted among secondary school students prior to the main data collection. The sample sizes for each pilot ranged from three to 15. As part of these pilot studies, participants were prompted at the end of the ESM session to answer a few questions about their experiences with the study. Additionally, a subset of the participants agreed to participate in brief (10-minute) online video interviews to provide more detailed feedback on their experiences. The overall feedback from the pilots indicated that participants thought that participation in this type of study was meaningful, especially when compared to other types of studies such as cross-sectional surveys commonly conducted within schools. The pilot studies also confirmed that participants understood the items as intended, thus affirming the face validity of the measures. Factor analysis To assess construct validity, a confirmatory factor analysis (CFA) was performed using the SEQ-C, SEI, and S-GSE scales from the baseline survey. Prior to the CFAs, the KMO values indicated adequate sampling adequacy for all scales: SEQ-C (KMO = 0.736), SEI (KMO = 0.902), and S-GSE (KMO = 0.843), as recommended by Kaiser (1974) . Additionally, Bartlett’s Test of Sphericity (BTS) was significant for each scale ( p < 0.001), indicating that the variables were significantly correlated and justifying the use of the factor analytic model. Maximum Likelihood (ML) estimation was employed for the CFA of all scales, except for the SEI scale, where robust Maximum Likelihood (MLR) was used due to high kurtosis (>3) in one of the items. The individual CFAs indicated an overall adequate model fit, though the RMSEA for the SEQ-C scale fell outside the acceptable range. For detailed goodness-of-fit statistics, see Table 2 . The analyses of KMO and BTS were conducted using IBM SPSS Statistics 29, while the CFAs were performed using MPlus Version 8.8. Table 2. Recommended goodness-of-fit statistics with CFA-derived dataset values. Fit indices Good Acceptable SEQ-C SEI S-GSE X 2 /df <3.0 <5.0 4.63 2.42 2.76 RMSEA 0.95 >0.90 0.976 0.922 0.984 TLI >0.95 >0.90 0.929 0.911 0.969 Dataset reliability To evaluate how consistently the items within each scale measured the same underlying construct, i.e. between-person reliability, internal consistency checks for this dataset were performed using Cronbach’s alpha ( Cronbach, 1951 ). Sufficient internal consistency was displayed for the three sub-scales within the SEI, with α = 0.88 (PSS), α = 0.92 (TSR), and α = 0.89 (FSL), for the S-GSE scale (α = 0.84), and for the SEQ-C scale (α = 0.76). Limitations Firstly, as the dataset relies on self-report measures, there is always a potential for response bias or social desirability effects. However, measures were taken to minimize these biases through anonymous data collection, clear instructions provided to respondents as well as a planned missingness design. Secondly, while the sample size of the dataset can be considered sufficient for many analyses, a larger sample size would allow for more robust and generalizable results. Ethical considerations The data collection was conducted in compliance with the ethical guidelines of the Declaration of Helsinki ( World Medical Association, 2001 ) and the guidelines for ethical review in human sciences ( Finnish National Board on Research Integrity, TENK, 2019 ). In Finland, all research with human participants must comply with the guidelines of TENK. The guidelines do not cover medical research as defined by law ( Medical Research Act 488/1999 ) or other research designs where ethical review is a separate obligation laid down by law. According to the TENK guidelines, research is to be conducted in such a way that the dignity and autonomy of human research participants is respected, and the research does not cause significant risks, damage or harm to research participants, communities or other subjects of research. Further, the guidelines state that ethical review is to be carried out prior to gathering data, if the research contains one or more of the following factors: 1. Participation in the research deviates from the principle of informed consent. Participation is not, for example, voluntary, or the subject is not given sufficient or correct information about the research. 2. The research involves intervening in the physical integrity of research participants. 3. The focus of the research is on minors under the age of fifteen, without separate consent from a parent or carer, or without informing a parent or carer in a way that would enable them to prevent the child’s participation in the research. 4. Research that exposes participants to exceptionally strong stimuli. 5. Research that involves a risk of causing mental harm that exceeds the limits of normal daily life to the research participants or their family members or others closest to them. 6. Conducting the research could involve a threat to the safety of participants or researchers or their family members or others closest to them. If none of the above factors are met, ethical review is not required. In Finland, neither legislation nor TENK’s guidelines require ethical review by an ethics committee for research based purely on public and published data, registry and documentary data, or archive data. Approval to perform the study was sought and granted from the board of each of the participating schools. Given that the target population was 15 years and older, active parental consent was not required according to the TENK guidelines, but parents were informed in writing about the study in collaboration with the participating schools and had the option to contact the project if they did not want their teenager to participate in the study (passive parental consent). For participants, information about the study and the management of data, were provided both orally and in writing via the app “RealLife Exp” at the beginning of the start-up session. Participant written consent for study participation, as well as for data collection and management, was obtained via the app before participants could proceed to the items in the start-up survey. The respondents were informed of their right to withdraw from the study at any time. Upon completion of data collection, all data were retrieved from LifeData’s servers, anonymized, and securely stored on the university’s password-protected servers. Data availability Zenodo: A 10-day experience sampling dataset on subjective experiences of middle and secondary school students in 2022. https://doi.org/10.5281/zenodo.13332148 ( Söderberg & Mölsä, 2024 ). The project contains the following underlying data: • ESM_repository_2022.sav Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Acknowledgements The authors express their gratitude to the involved school principals and education boards, and all study participants. The authors also thank the research foundation Högskolestiftelsen i Österbotten for financial support for the project as well as Åbo Akademi University for supporting the doctoral studies of the first author, Mölsä. Additionally, the authors acknowledge the funding provided by the Gösta Branders Research Fund for the APC pool. References Appleton JJ, Christenson SL, Kim D, et al. : Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument. J. Sch. Psychol. 2006; 44 (5): 427–445. Publisher Full Text Cronbach LJ: Coefficient alpha and the internal structure of tests. Psychometrika. 1951; 16 : 297–334. Publisher Full Text Finnish National Board on Research Integrity, TENK: Ethical principles of research with human participants and ethical review in the human sciences in Finland (Publication No. 3/2019).2019. Reference Source Kaiser HF: An index of factorial simplicity. Psychometrika. 1974; 39 : 31–36. Publisher Full Text Koskinen-Hagman M, Schwarzer R, Jerusalem M: Swedish version of the General Self-Efficacy Scale.1999. Reference Source Larson R, Csikszentmihalyi M: The Experience Sampling Method. New Directions for Methodology of Social & Behavioral Science. 1983; 15 : 41–56. Medical Research Act 488: 1999. Reference Source Muris P: A brief questionnaire for measuring self-efficacy in youths. J. Psychopathol. Behav. Assess. 2001; 23 (3): 145–149. Publisher Full Text Schwarzer R, Jerusalem M: General self-efficacy scale (GSE) [Database record]. APA PsycTests. 1995. Publisher Full Text Söderberg P, Mölsä ME: A 10-day experience sampling dataset on subjective experiences of middle and secondary school students in 2022. [Dataset]. Zenodo. 2024. Publisher Full Text Watson D, Clark LA: The PANAS-X: Manual for the Positive and Negative Affect Schedule - Expanded Form. University of Iowa; 1994. Publisher Full Text Watson D, Clark LA, Tellegen A: Development and validation of brief measures of positive and negative affect: The PANAS scales. J. Pers. Soc. Psychol. 1988; 54 (6): 1063–1070. PubMed Abstract | Publisher Full Text World Medical Association: World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. Bull. World Health Organ. 2001; 79 (4): 373–374. World Health Organization. Reference Source Xia Y, Yang Y: RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Behav. Res. Methods. 2019; 51 (1): 409–428. PubMed Abstract | Publisher Full Text Zirkel S, Garcia JA, Murphy MC: Experience-sampling research methods and their potential for education research. Educ. Res. 2015; 44 (1): 7–16. Publisher Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 16 Dec 2024 ADD YOUR COMMENT Comment Author details Author details 1 Department of Developmental Psychology, Åbo Akademi University, Vaasa, Finland 2 Department of Health Sciences, Åbo Akademi University, Vaasa, Finland Martina Mölsä Roles: Formal Analysis, Funding Acquisition, Investigation, Methodology, Writing – Original Draft Preparation Anna K. Forsman Roles: Writing – Review & Editing Patrik Söderberg Roles: Conceptualization, Data Curation, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The research was funded by the Högskolestiftelsen i Österbotten and the Gösta Branders Research Fund, Åbo Akademi University Foundation (Gösta Branders forskningsfond, Stiftelsen för Åbo Akademi). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (1) version 1 Published: 16 Dec 2024, 13:1522 https://doi.org/10.12688/f1000research.157148.1 Copyright © 2024 Mölsä M 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 work is properly cited. 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Register $(document).ready(function () { signIn.createSignInAsRow($("#sign-in-form-gfb-popup")); $(".target-field").each(function () { var uris = $(this).val().split("/"); if (uris.pop() === "login") { $(this).val(uris.toString().replace(",","/")); } }); });