Dataset Information

Content analysis of 4 to 8 year-old children's dream reports.

ABSTRACT: The role of dreaming in childhood and in adulthood are still equally enigmatic fields yet to be fully explored. However, while there is a consensus at least about the typical content and formal characteristics of adult dream reports, these features are still a matter of debate in the case of young children. Longitudinal developmental laboratory studies concluded that preschoolers' dreams usually depict static images about mostly animals and body states of the dreamer but they basically lack the active representation of the self, human characters, social interactions, dream emotions and motion imagery. Due to methodological arguments these results became the reference points in the literature of developmental dream research, in spite of the significantly different results of numerous recent and relevant studies using extra-laboratory settings. This study aims to establish a methodologically well-controlled and valid way to collect children's dreams for a representative period of time in a familiar home setting to serve as a comparison to the laboratory method. Pre trained parents acted as interviewers in the course of a 6 week-period of dream collection upon morning awakenings. Our results suggest that even preschoolers are likely to represent their own self in an active role (70%) in their mostly kinematic (82%) dream narratives. Their dream reports contain more human, than animal characters (70 and 7% of all dream characters respectively), and social interactions, self-initiated actions, and emotions are usual part of these dreams. These results are rather similar to those of recent extra-laboratory studies, suggesting that methodological issues may strongly interfere with research outcomes especially in the case of preschoolers' dream narratives. We suggest that nighttime awakenings in the laboratory setting could be crucial in understanding the contradictory results of dream studies in case of young children.

SUBMITTER: Sandor P

PROVIDER: S-EPMC4415323 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Content analysis of 4 to 8 year-old children's dream reports.

Sándor Piroska P Szakadát Sára S Kertész Katinka K Bódizs Róbert R Bódizs Róbert R

Frontiers in psychology 20150430

The role of dreaming in childhood and in adulthood are still equally enigmatic fields yet to be fully explored. However, while there is a consensus at least about the typical content and formal characteristics of adult dream reports, these features are still a matter of debate in the case of young children. Longitudinal developmental laboratory studies concluded that preschoolers' dreams usually depict static images about mostly animals and body states of the dreamer but they basically lack the ...[more]

PMID: 25983708

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Project description:Can dreams reveal insight into our cognitive abilities and aptitudes (i.e., "human intelligence")? The relationship between dream production and trait-like cognitive abilities is the foundation of several long-standing theories on the neurocognitive and cognitive-psychological basis of dreaming. However, direct experimental evidence is sparse and remains contentious. On the other hand, recent research has provided compelling evidence demonstrating a link between dream content and new learning, suggesting that dreams reflect memory processing during sleep. It remains to be investigated whether the extent of learning-related dream incorporation (i.e., the semantic similarity between waking experiences and dream content) is related to inter-individual differences in cognitive abilities. The relationship between pre-post sleep memory performance improvements and learning-related dream incorporation was investigated (N = 24) to determine if this relationship could be explained by inter-individual differences in intellectual abilities (e.g., reasoning, short term memory (STM), and verbal abilities). The extent of dream incorporation using a novel and objective method of dream content analysis, employed a computational linguistic approach to measure the semantic relatedness between verbal reports describing the experience on a spatial (e.g., maze navigation) or a motor memory task (e.g., tennis simulator) with subsequent hypnagogic reverie dream reports and waking "daydream" reports, obtained during a daytime nap opportunity. Consistent with previous studies, the extent to which something new was learned was related (r = 0.47) to how richly these novel experiences were incorporated into the content of dreams. This was significant for early (the first 4 dream reports) but not late dreams (the last 4 dream reports). Notably, here, we show for the first time that the extent of this incorporation for early dreams was related (r = 0.41) to inter-individual differences in reasoning abilities. On the other hand, late dream incorporation was related (r = 0.46) to inter-individual differences in verbal abilities. There was no relationship between performance improvements and intellectual abilities, and thus, inter-individual differences in cognitive abilities did not mediate the relationship between performance improvements and dream incorporation; suggesting a direct relationship between reasoning abilities and dream incorporation. This study provides the first evidence that learning-related dream production is related to inter-individual differences in cognitive abilities.

Project description:BackgroundSocial media is often used for health communication and can facilitate fast information exchange. Despite its increasing use, little is known about child health information sharing and engagement over social media.ObjectiveThe primary objectives of this study are to systematically describe the content of social media posts about child pain and sleep and identify the level of research evidence in these posts. The secondary objective is to examine user engagement with information shared over social media.MethodsTwitter, Instagram, and Facebook were searched by members of the research team over a 2-week period using a comprehensive search strategy. Codes were used to categorize the content of posts to identify the frequency of content categories shared over social media platforms. Posts were evaluated by content experts to determine the frequency of posts consistent with existing research evidence. User engagement was analyzed using Netlytic, a social network analysis program, to examine visual networks illustrating the level of user engagement.ResultsFrom the 2-week period, nearly 1500 pain-related and 3800 sleep-related posts were identified and analyzed. Twitter was used most often to share knowledge about child pain (639/1133, 56.40% of posts), and personal experiences for child sleep (2255/3008, 75.00% of posts). For both topics, Instagram posts shared personal experiences (53/68, 78% pain; 413/478, 86.4% sleep), Facebook group posts shared personal experiences (30/49, 61% pain; 230/345, 66.7% sleep) and Facebook pages shared knowledge (68/198, 34.3% pain; 452/1026, 44.05% sleep). Across platforms, research evidence was shared in 21.96% (318/1448) of pain- and 9.16% (445/4857) of sleep-related posts; 5.38% (61/1133) of all pain posts and 2.82% (85/3008) of all sleep posts shared information inconsistent with the evidence, while the rest were absent of evidence. User interactions were indirect, with mostly one-way, rather than reciprocal conversations.ConclusionsSocial media is commonly used to discuss child health, yet the majority of posts do not contain research evidence, and user engagement is primarily one-way. These findings represent an opportunity to expand engagement through open conversations with credible sources. Research and health care communities can benefit from incorporating specific information about evidence within social media posts to improve communication with the public and empower users to distinguish evidence-based content better. Together, these findings have identified potential gaps in social media communication that may be informative targets to guide future strategies for improving the translation of child health evidence over social media.

Dataset Information

Content analysis of 4 to 8 year-old children's dream reports.

Publications

Content analysis of 4 to 8 year-old children's dream reports.

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