Abstract
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 multimodal 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.
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 multimodal 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.
Original language | English |
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Journal | Wellcome Open Research |
Early online date | 12 Sept 2024 |
DOIs | |
Publication status | E-pub ahead of print - 12 Sept 2024 |