Primary Origins of Sleep Disorders and Attention Deficit Hyperactivity Disorder: Common Symptoms and Implications for Diagnosis and Treatment
Bibliographic record
Abstract
Abstract: There have been many recent studies set up to examine the characteristics of Attention Deficit Hyperactivity Disorder (ADHD) and Sleeping Disorders (SDO), some separately and others to determine whether or not there is a link between them. To control behavior, medication is the most frequent method of treatment for ADHD, even though there is not yet an understanding of long-term effects of chemical intervention. The pharmaceutical industry funds most of these studies on ADHD, beginning with a hypothesis to determine a deficit in character, assigning a label, and proceeding to correct with a prescription. The diagnosis of ADHD is generally based on parent and caregiver's reports of child behavior and has been steadily increasing over the past several decades. Thus far, there have been few studies that explore the relationships and environmental contributions to the problem behaviors identified in both conditions. This paper suggests that ADHD and SDO have relational implications that originate prior to and during the birth process. This paper explores recent studies that have identified the symptoms common of ADHD and SDO and question the validity of the diagnosis and the use of medication to treat the symptoms. Keywords: ADHD, Attention Deficit Hyperactivity Disorder, SDO, Sleep Disorders Introduction Attention Deficit Hyper-Activity Disorder is a relatively new term used to describe children's behavior and is frequently used as a label and a diagnosis. Diagnosis of ADHD in children has increased over the past decades (Prosser, 2006, Robinson, Sciar, Skaer & Galin, 1999). Prosser, a researcher and educator in Australia, suggests that ADHD is the most commonly diagnosed psychiatric disorder among schoolaged children (Posser, 2006, p. 2). The reason for this trend is not clear, but some studies attempt to provide evidence that supports a crossgenerational link, whether through family patterns, social constructs, or genetic transmissions. More recent studies explore the neurological aspects of ADHD to identify areas of the brain that are affected (Owens, 2008). Concurrent studies focus on sleep disorders (SDO) and are recognizing common patterns in children suffering from sleep disorders and children diagnosed with ADHD (Stuart, 2007). The common characteristics of Attention Deficit-Hyperactivity Disorder (ADHD) are behaviors of inattention, impulsivity, and hyperactivity that interfere with academic and social functioning. However, to consider the behaviors characteristic of ADHD and SDO as psychiatric disorders may be misguided dogma that eludes humane treatment and ignores the intrinsic needs of the child. Identifying characteristics such as attention span and activity levels and attributing these personality traits to be out of the range of typical developmental may say more about professional interests and beliefs than the experiences of the children. Professionals and researchers are committed to share and apply their knowledge, which is often biased and focused on a single question that has limited parameters. The current development of research regarding ADHD tends to focus on establishing that a link between symptoms and the neurobiology of brain function exists and can be corrected or changed with a chemically derived substitute. Incidence of children diagnosed with ADHD is a growing phenomenon. The Centers for Disease Control and Prevention statistics, reviewed in May 2010, indicate parents reported children diagnosed with ADHD increased by 22% between 2003 and 2007. A Canadian population health study published in 2005, states that 338,400 or 6.4% of children aged five to seventeen are labeled as having ADHD (Waddell, Shepherd, & McLauchlin, 2007, p. 45). An Australian study finds that three to six percent of school-aged children are diagnosed with ADHD (Prosser, 2006, p. 2). An earlier study found that the number of doctor office-based visits, documenting a diagnosis of ADHD increased from 1. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".