Evidence map›Paper›PMID 28183303›Full record

Trial reportBMC health services research2017

Usefulness of an educational lecture focusing on improvement in public awareness of and attitudes toward depression and its treatments.

Takashi Yakushi, Teizo Kuba, Yuzuru Nakamoto, Hiroshi Fukuhara, Munenaga Koda, Osamu Tanaka, Tsuyoshi Kondo

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Takashi YakushiDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, 207 Uehara, Nishihara-cho, Okinawa, 903-0215, Japan. yakushi3@hotmail.com.ORCID 0000-0002-2666-6332
Teizo KubaDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, 207 Uehara, Nishihara-cho, Okinawa, 903-0215, Japan.
Yuzuru NakamotoDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, 207 Uehara, Nishihara-cho, Okinawa, 903-0215, Japan.
Hiroshi FukuharaDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, 207 Uehara, Nishihara-cho, Okinawa, 903-0215, Japan.
Munenaga KodaDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, 207 Uehara, Nishihara-cho, Okinawa, 903-0215, Japan.
Osamu TanakaAomori Prefectural Center for Mental Health and Welfare, 353-92 Sannai Sawabe, Aomori, 038-0031, Japan.
Tsuyoshi KondoDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, 207 Uehara, Nishihara-cho, Okinawa, 903-0215, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is an urgent need to establish effective strategies for suicide prevention. Stigma against depression may be a potential anti-protective factor for suicide. Thus, we investigated baseline levels of awareness and attitudes toward depression and its treatment among the general population by our original 18-item questionnaire, which we aimed to validate in the present study. Next, we conducted two types of educational interventions and examined the results to clarify the difference in the quality of these lectures.

methodsSubjects were 834 citizens (245 males and 589 females) who received an anti-stigma-targeted (n = 467) or non-targeted lecture (n = 367). An 18-item questionnaire assessing levels of awareness and attitudes toward depression and its treatments was administered to each participant before and after the lecture. A chi-square test was used to investigate categorical variables for background data on the participants. Factor analysis of baseline scores was conducted on the 18 questionnaire items. Student's t-test was used for analysis of the gender effect. A two-way analysis of variance (ANOVA) was used for comparison among the 5 age groups and comparison of the effect of the two lectures. Multiple regression analysis was applied to examine the determinants of improved attitudes after intervention.

resultsPublic attitudes toward depression consisted of 4 distinct elements, which were disease-model attitudes, help-seeking behavior, negative affect toward depression, and non-medication solutions. Older participants had poorer disease-model attitudes and more negative affect toward depression, whereas younger participants showed poorer help-seeking behavior (p < 0.05). The anti-stigma-targeted lecture was superior to the non-targeted lecture in improving disease-model attitudes and non-medication solutions (p < 0.05). Multiple regression analyses revealed that each subscale score at post-lecture was strongly dependent on its own baseline subscale score (p < 0.01), and that baseline disease-model attitudes also affected post-lecture scores on negative affect toward depression and non-medication solutions (p < 0.01).

conclusionsThe educational intervention appears useful for acquiring accurate attitudes toward depression in a medical model. However, other strategies should be considered to enhance help-seeking behavior, especially in younger people.

Indexed as

Attitude to HealthSocial StigmaAdultAgedAge FactorsAnalysis of VarianceAwarenessDepressive DisorderFemaleHealth EducationHelp-Seeking BehaviorHumansMaleMiddle AgedPopulation GroupsPublic OpinionAnti-stigma-targeted lectureAttitudesAwarenessDepressionGeneral populationHelp-seekingMedical modelStigmaSuicide prevention

Identifiers

PMID28183303
PMCPMC5301371

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.