Dataset Information

Cross-sectional survey data on the socio-demographic characteristics associated with substance use among internal displaced persons in Maiduguri, Nigeria.

ABSTRACT: Regression analysis was carried out to examine the association between certain socio-demographic characteristics and substance use among internally displaced persons (IDPs). Using an adapted version of the Drug Use Disorder Identification Test (DUDIT) instrument, cross-sectional survey data were obtained from 520 IDPs living in three camps located in Maiduguri, Borno state of Nigeria. The data were analyzed using Statistical Package for Social Sciences software version 21.0. Specifically, this article provides data about the participants' demographic characteristics, the types of substances they use, reasons for using such substances, and the prevalence of substance use. This dataset can offer valuable multivariate information for future research agendas in similar, or closely related study populations. This cross-sectional dataset is also valuable for policymakers who are seeking ways to intervene in the substance use problem, as well as other associated social vices, affecting the vulnerable population of IDPs.

SUBMITTER: Aigbogun O

PROVIDER: S-EPMC10749230 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Cross-sectional survey data on the socio-demographic characteristics associated with substance use among internal displaced persons in Maiduguri, Nigeria.

Aigbogun Osaro O Aluh Deborah Oyine DO Okoro Roland Nnaemeka RN Yousefi Midya M Fawehinmi Olawole O Abdullahi Mohammed Sani MS

Data in brief 20231130

Regression analysis was carried out to examine the association between certain socio-demographic characteristics and substance use among internally displaced persons (IDPs). Using an adapted version of the Drug Use Disorder Identification Test (DUDIT) instrument, cross-sectional survey data were obtained from 520 IDPs living in three camps located in Maiduguri, Borno state of Nigeria. The data were analyzed using Statistical Package for Social Sciences software version 21.0. Specifically, this a ...[more]

PMID: 38146289

Similar Datasets

Project description:BackgroundNigeria, the most populous country in Africa and the 8th most populous in the world with a population of over 154 million, does not have current data on substance abuse treatment demand and treatment facilities; however, the country has the highest one-year prevalence rate of Cannabis use (14.3%) in Africa and ranks third in Africa with respect to the one-year prevalence rate of cocaine (0.7%) and Opioids (0.7%) use. This study aimed to determine the types, spread and characteristics of the substance abuse treatment centers in Nigeria.MethodsThe study was a cross sectional survey of substance abuse treatment centers in Nigeria. Thirty-one units were invited and participated in filling an online questionnaire, adapted from the European Treatment Unit/Program Form (June 1997 version).ResultsAll the units completed the online questionnaire. A large proportion (48%) was located in the South-West geopolitical zone of the country. Most (58%) were run by Non-Governmental Organizations. Half of them performed internal or external evaluation of treatment process or outcome. There were a total of 1043 for all categories of paid and volunteer staff, with an average of 33 staff per unit. Most of the funding came from charitable donations (30%). No unit provided drug substitution/maintenance therapy. The units had a total residential capacity of 566 beds. New client admissions in the past one year totalled 765 (mean = 48, median = 26.5, min = 0, max = 147) and 2478 clients received services in the non-residential units in the past year. No unit provided syringe exchange services.ConclusionsThe study revealed a dearth of substance abuse treatment units (and of funds for the available ones) in a country with a large population size and one of the highest prevalence rates of substance abuse in Africa. The available units were not networked and lacked a directory or an evaluation framework. To provide an environment for effective monitoring, funding and continuous quality improvement, the units need to be organized into a sustainable network.

Project description:Internally displaced persons (IDPs) are at high risk for COVID-19 transmission because of congested and unsanitary living conditions. COVID-19 vaccination is essential to build population immunity and prevent severe disease among this population. We determined the prevalence and factors associated with intention to accept COVID-19 vaccine among IDPs in Northeast Nigeria. This cross-sectional study, conducted during July-December 2022, included 1,537 unvaccinated IDPs from 18 IDPs camps. We performed a complex sample survey analysis and described participants' characteristics and vaccination intention with weighted descriptive statistics. We fitted weighted logistic regression models and computed adjusted odds ratios with 95% confidence intervals to identify factors associated with intention to accept COVID-19 vaccine. Of 1,537 IDPs, 55.4% were 18-39 years old, 82.6% were females, and 88.6% had no formal education. Among them, 63.5% (95% CI: 59.0-68.1) expressed intention to accept COVID-19 vaccine. Among the IDPs who intended to reject vaccine, 42.8% provided no reason, 35.3% had COVID-19 misconceptions, 9.5% reported vaccine safety concerns, and 7.4% felt no need. IDPs who perceived COVID-19 as severe (Adjusted Odds Ratio (AOR) = 2.31, [95% CI: 1.35-3.96]), perceived COVID-19 vaccine as effective (AOR = 4.28, [95% CI: 2.46-7.44]) and resided in official camps (AOR = 3.29, [95% CI: 1.94-5.56]) were more likely to accept COVID-19 vaccine. However, IDPs who resided 2 kilometers or farther from the nearest health facility (AOR = 0.34, [95% CI: 0.20-0.58]) were less likely to accept vaccine. Intention to accept COVID-19 vaccine among the IDPs was suboptimal. To improve vaccination acceptance among this population, health education and risk communication should be intensified to counter misinformation, strengthen vaccine confidence, and shape perception of COVID-19 severity, focusing on IDPs in unofficial camps. Appropriate interventions to deliver vaccines to remote households should be ramped up.

Project description:Questionnaires are among the most basic and widespread tools to assess the mental health of a population in epidemiological and public health studies. Their most obvious advantage (firsthand self-report) is also the source of their main problems: the raw data requires interpretation, and are a snapshot of the specific sample's status at a given time. Efforts to deal with both issues created a bi-dimensional space defined by two orthogonal axes, in which most of the quantitative mental health research can be located. Methods aimed to assure that mental health diagnoses are solidly grounded on existing raw data are part of the individual validity axis. Tools allowing the generalization of the results across the entire population compose the collective validity axis. This paper raises a different question. Since one goal of mental health assessments is to obtain results that can be generalized to some extent, an important question is how robust is a questionnaire result when applied to a different population or to the same population at a different time. In this case, there is deep uncertainty, without any a priori probabilistic information. The main claim of this paper is that this task requires the development of a new robustness to deep uncertainty axis, defining a three-dimensional research space. We demonstrate the analysis of deep uncertainty using the concept of robustness in info-gap decision theory. Based on data from questionnaires collected before and during the Covid-19 pandemic, we first locate a mental health assessment in the space defined by the individual validity axis and the collective validity axis. Then we develop a model of info-gap robustness to uncertainty in mental health assessment, showing how the robustness to deep uncertainty axis interacts with the other two axes, highlighting the contributions and the limitations of this approach. The ability to measure robustness to deep uncertainty in the mental health realm is important particularly in troubled and changing times. In this paper, we provide the basic methodological building blocks of the suggested approach using the outbreak of Covid-19 as a recent example.

Dataset Information

Cross-sectional survey data on the socio-demographic characteristics associated with substance use among internal displaced persons in Maiduguri, Nigeria.

Publications

Cross-sectional survey data on the socio-demographic characteristics associated with substance use among internal displaced persons in Maiduguri, Nigeria.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets