Amanda Ly, Emma Fisher, James P Dunham, Josefin Attermo Dufva, Kate Northstone, Abbie Jordan, Anthony E Pickering, Rachael Gooberman-Hill, Edmund Keogh, Rebecca M Pearson, Hannah Sallis
{"title":"雅芳父母与子女纵向研究》中有关疼痛和疼痛相关变量的总结。","authors":"Amanda Ly, Emma Fisher, James P Dunham, Josefin Attermo Dufva, Kate Northstone, Abbie Jordan, Anthony E Pickering, Rachael Gooberman-Hill, Edmund Keogh, Rebecca M Pearson, Hannah Sallis","doi":"10.12688/wellcomeopenres.22815.1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>To study pain, data on pain characteristics, possible triggers and consequences - such as the impact of pain on people's lives - need to be available. When not collated, described and/or organised in a systematic manner, it can be difficult to assess how useful an existing dataset may be for one's project. This data note describes and categorises the complex and multi-modal indices of pain available in the Avon Longitudinal Study of Parents and Children (ALSPAC).</p><p><strong>Methods: </strong>Data from two generations of the ALSPAC cohort; index child participants (Generation 1, G1), their mothers and fathers/mothers' partners (Generation 0, G0) were used. Search terms such as 'pain', 'ache', 'hurt', 'sore', specific pain conditions, labour pain and methods of pain relief were used to identify pain and pain-related variables. These data were extracted from all waves of data collection. We developed pain categories and subsequently categorised variables in an iterative process. Repeated measurements of the same variables over waves of data collection were also identified.</p><p><strong>Results: </strong>We identified 21 categories of pain variables, which were subsequently grouped into themes: pain characteristics, extended pain characteristics and causes, treatment for pain, pain interference and pain-related to specific events. Pain and pain-related data have been collected from G1 participants, G0 mothers, and G0 partners, although there are fewer data for the partners. There were some repeated measurements, most commonly, of pain location. As is typical with longitudinal birth cohort studies, maternal proxy-reports were used during participants' younger years and self-reports were utilised from adolescence onwards.</p><p><strong>Conclusions: </strong>Researchers interested in studying pain can feasibly do so in two generations of a regional UK population who have been followed up over 30 years. ALSPAC can be used to study pain from the early years through to young adulthood and in mothers from the perinatal period onwards.</p>","PeriodicalId":23677,"journal":{"name":"Wellcome Open Research","volume":"9 ","pages":"521"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11462121/pdf/","citationCount":"0","resultStr":"{\"title\":\"A summary of pain and pain-related variables in the Avon Longitudinal Study of Parents and Children.\",\"authors\":\"Amanda Ly, Emma Fisher, James P Dunham, Josefin Attermo Dufva, Kate Northstone, Abbie Jordan, Anthony E Pickering, Rachael Gooberman-Hill, Edmund Keogh, Rebecca M Pearson, Hannah Sallis\",\"doi\":\"10.12688/wellcomeopenres.22815.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>To study pain, data on pain characteristics, possible triggers and consequences - such as the impact of pain on people's lives - need to be available. When not collated, described and/or organised in a systematic manner, it can be difficult to assess how useful an existing dataset may be for one's project. This data note describes and categorises the complex and multi-modal indices of pain available in the Avon Longitudinal Study of Parents and Children (ALSPAC).</p><p><strong>Methods: </strong>Data from two generations of the ALSPAC cohort; index child participants (Generation 1, G1), their mothers and fathers/mothers' partners (Generation 0, G0) were used. Search terms such as 'pain', 'ache', 'hurt', 'sore', specific pain conditions, labour pain and methods of pain relief were used to identify pain and pain-related variables. These data were extracted from all waves of data collection. We developed pain categories and subsequently categorised variables in an iterative process. Repeated measurements of the same variables over waves of data collection were also identified.</p><p><strong>Results: </strong>We identified 21 categories of pain variables, which were subsequently grouped into themes: pain characteristics, extended pain characteristics and causes, treatment for pain, pain interference and pain-related to specific events. Pain and pain-related data have been collected from G1 participants, G0 mothers, and G0 partners, although there are fewer data for the partners. There were some repeated measurements, most commonly, of pain location. As is typical with longitudinal birth cohort studies, maternal proxy-reports were used during participants' younger years and self-reports were utilised from adolescence onwards.</p><p><strong>Conclusions: </strong>Researchers interested in studying pain can feasibly do so in two generations of a regional UK population who have been followed up over 30 years. ALSPAC can be used to study pain from the early years through to young adulthood and in mothers from the perinatal period onwards.</p>\",\"PeriodicalId\":23677,\"journal\":{\"name\":\"Wellcome Open Research\",\"volume\":\"9 \",\"pages\":\"521\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11462121/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wellcome Open Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12688/wellcomeopenres.22815.1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wellcome Open Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12688/wellcomeopenres.22815.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
A summary of pain and pain-related variables in the Avon Longitudinal Study of Parents and Children.
Background: To study pain, data on pain characteristics, possible triggers and consequences - such as the impact of pain on people's lives - need to be available. When not collated, described and/or organised in a systematic manner, it can be difficult to assess how useful an existing dataset may be for one's project. This data note describes and categorises the complex and multi-modal indices of pain available in the Avon Longitudinal Study of Parents and Children (ALSPAC).
Methods: Data from two generations of the ALSPAC cohort; index child participants (Generation 1, G1), their mothers and fathers/mothers' partners (Generation 0, G0) were used. Search terms such as 'pain', 'ache', 'hurt', 'sore', specific pain conditions, labour pain and methods of pain relief were used to identify pain and pain-related variables. These data were extracted from all waves of data collection. We developed pain categories and subsequently categorised variables in an iterative process. Repeated measurements of the same variables over waves of data collection were also identified.
Results: We identified 21 categories of pain variables, which were subsequently grouped into themes: pain characteristics, extended pain characteristics and causes, treatment for pain, pain interference and pain-related to specific events. Pain and pain-related data have been collected from G1 participants, G0 mothers, and G0 partners, although there are fewer data for the partners. There were some repeated measurements, most commonly, of pain location. As is typical with longitudinal birth cohort studies, maternal proxy-reports were used during participants' younger years and self-reports were utilised from adolescence onwards.
Conclusions: Researchers interested in studying pain can feasibly do so in two generations of a regional UK population who have been followed up over 30 years. ALSPAC can be used to study pain from the early years through to young adulthood and in mothers from the perinatal period onwards.
Wellcome Open ResearchBiochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
5.50
自引率
0.00%
发文量
426
审稿时长
1 weeks
期刊介绍:
Wellcome Open Research publishes scholarly articles reporting any basic scientific, translational and clinical research that has been funded (or co-funded) by Wellcome. Each publication must have at least one author who has been, or still is, a recipient of a Wellcome grant. Articles must be original (not duplications). All research, including clinical trials, systematic reviews, software tools, method articles, and many others, is welcome and will be published irrespective of the perceived level of interest or novelty; confirmatory and negative results, as well as null studies are all suitable. See the full list of article types here. All articles are published using a fully transparent, author-driven model: the authors are solely responsible for the content of their article. Invited peer review takes place openly after publication, and the authors play a crucial role in ensuring that the article is peer-reviewed by independent experts in a timely manner. Articles that pass peer review will be indexed in PubMed and elsewhere. Wellcome Open Research is an Open Research platform: all articles are published open access; the publishing and peer-review processes are fully transparent; and authors are asked to include detailed descriptions of methods and to provide full and easy access to source data underlying the results to improve reproducibility.