Traditional Islamic spiritual meditative practices: powerful psychotherapies for mental wellbeing
Bibliographic record
Abstract
The new millennium is witnessing a remarkable shift within the scientific community, to be increasingly understanding and accepting the impact of meditative, spiritual, and even religious practices, on health and wellbeing. This has been precipitated ironically, by cutting edge scientific studies. Rigorous empirical research in epigenomics and neuroscience is proving that religious and spiritual experiences impact psychology and physiology. Therapeutic and prophylactic benefits from spiritual meditative practices (SMPs) are now proven for a variety of chronic conditions, notably in mental health wellness. While all forms of SMPs are currently being investigated, those from the Islamic tradition are lagging behind interrogation of similar SMPs from other traditions, such as mindfulness. Traditional Islamic SMPs have remained largely hidden or misunderstood, and as yet poorly translated into the modern context. In this paper we situate Islamic SMPs in the context of how they impact mental health and wellbeing, explaining their breadth and depth. We highlight the efficacy of dhikr and Quran recitation therapies as treatments for addiction and anxiety, noting historic evidence, and discuss how they may be integrated into modern mental health treatments. A millennium and a half of historical data proves their efficacy as psychotherapy. Precedent for the use of Islamic SMPs to treat mental illness for all people regardless of faith exists, highlighting their potential for wide implementation today. Of the Islamic SMPs that can most easily be accessed by modern people, listening to Quranic recitation and forms of dhikr therapy are notable for their ease of administration and strikingly uniform positive results. More rigorous empirical studies are called for to better translate Islamic SMPs into modern complimentary and alternative medicine, as they hold great promise as universally adoptable cogent modern psychotherapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".