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Record W2794641809 · doi:10.1093/schbul/sby016.437

T161. HEARING VOICES AMONG INDIGENOUS MAASAI WOMEN IN TANZANIA: IMPLICATIONS FOR GLOBAL MENTAL HEALTH

2018· article· en· W2794641809 on OpenAlexaff
Neely Myers, Luca Pauselli, Michael T. Compton

Bibliographic record

VenueSchizophrenia Bulletin · 2018
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsColumbia College
Fundersnot available
KeywordsMaasaiTanzaniaMental healthIndigenousPopulationHearing lossPsychologyPsychiatryMedicineClinical psychologyEnvironmental healthSocioeconomicsAudiologySociology

Abstract

fetched live from OpenAlex

Studies of the health of indigenous and tribal people can shed light on health inequalities with implications for global mental health. Almost no previous studies of mental health among the Maasai in Kenya or Tanzania or even pastoralist groups in general are available, with the exception of one mentioning the stress of rural-to-urban migration. While engaged in ethnographic research in 2013, Myers interviewed 13 Maasai women in northern Tanzania about their everyday lives. Interested in the phenomenology of voice-hearing, she also asked them if they heard voices. Eleven of the women (85%) reported regularly hearing voices that they found to be distressing. Myers returned in 2015 to collect data from a larger sample, which has resulted in this report. For this study, we used a convenience sample (n=73) of females taken from a broader study whose eligibility criteria included being a Maasai person living in the Arusha Region of Tanzania and over the age of 18. We excluded people who reported being psychiatric patients or family members of patients being seen by the local mental health coordinator to create a nonclinical community sample. This project conducted an initial survey to: 1) estimate the community prevalence of voice-hearing, or auditory verbal hallucinations (AVHs) in this specific population; and, 2) examine any demographic correlates and two specific hypothesized correlates based on previous literature about voice-hearing (e.g., psychological stress and potentially traumatic events). The prevalence of AVHs in this community sample was quite high compared to other studies in sub-Saharan Africa, at 34.3%. There were no differences between participants who did and did not experience AVHs in terms of demographics, but those experiencing AVHs had a statistically significantly higher level of psychological distress (30.1, SD=6.0, compared to 25.1, SD=6.0), with a Cohen’s d effect size of .87. Even though a numerical difference was observed in terms of potentially traumatic events (4.6, SD=2.1, compared to 3.8, SD=2.3), this difference was not statistically significant (d=.38). Hearing distressing voices may be an indicator of mental ill health that is easily recognizable to community health workers and brings much-needed attention to communities in need. Maasai women face tremendous social adversity in this time of rapid social, economic, and climate change in the region. Evidence for a link between stressful life events, social disadvantage, and the development of psychotic symptoms is strong in Europe, but not as well-developed in this region. The high level of psychosocial stress and AVHs in our sample may also be indicative of extreme social adversity. Maasai women have been historically disenfranchised since the advent of colonial and postcolonial policies favoring men. Women in this region also experiences extreme states of deprivation, including a 21.5 year gap in life expectancy at birth compared to the local population (for all Maasai), 81% severe food insecurity, and a rate of 59% for the stunted growth of children (as compared to their neighbors, the Meru, with 21% of children with stunted growth). Due to local livelihood insecurity, the age of first marriage has been decreasing, resulting in increased pressure on women. This analysis contextualizes these findings and calls for further research on the epidemiology of voice-hearing in this region, as well as further work on the phenomenology of these AVHs so that we can best understand how to address them and improve mental health outcomes for this marginalized group.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.013
GPT teacher head0.294
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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