| Literature DB >> 32134985 |
Tao Xu1,2, Sachi Tomokawa3,4, Ernesto R Gregorio5,6, Priya Mannava2, Mari Nagai2,7, Howard Sobel2.
Abstract
BACKGROUND: In the World Health Organization Western Pacific Region (WHO WPRO), most adolescents enroll in secondary school. Safe, healthy and nurturing school environments are critical for adolescent health and development. Yet, there were no systematic reviews found on the efficacy of school-based interventions among adolescents living in low and middle income countries (LMIC) in the Region. There is an urgent need to identify effective school-based interventions and facilitating factors for successful implementation in adolescent health in WPRO.Entities:
Mesh:
Year: 2020 PMID: 32134985 PMCID: PMC7058297 DOI: 10.1371/journal.pone.0230046
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Search and selection process of the articles.
Facilitating factors in implementing the interventions.
| Citation | Precondition | Stakeholder involvement | Approach | Content | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Policy & environment | High quality training for teacher | Include in curriculum | Community&parents | Teacher, principal, educational authorities | Health professionals | Peer education | Students participate | Repeated intervention | Skill based education | Culture and gender attention | |
| Aplasca et al., 1995 | ● | ● | ● | ● | ● | ● | ● | ● | |||
| Xu et al., 2000 | ● | ● | ● | ● | ● | ● | |||||
| Xia et al., 2004 | ● | ● | ● | ● | ● | ● | |||||
| Cartagena et al., 2006 | ● | ● | ● | ● | ● | ||||||
| Wen et al., 2010 | ● | ● | ● | ● | ● | ● | ● | ● | |||
| Chen et al., 2014 | ● | ● | ● | ● | ● | ● | |||||
| Jegannathan et al., 2014 | ● | ● | ● | ● | ● | ||||||
| Mohammed Nawi A et al., 2015 | ● | ● | ● | ||||||||
Summary of evidence.
| Citation | Country | Study design | Participants | Health topics | Intervention and | Outcome measures | Results |
|---|---|---|---|---|---|---|---|
| Aplasca et al., 1995 | Philippines | CRCT | 804 high school students (420 intervention, 384 control) | AIDS | AIDS-related knowledge, attitudes; sexual behaviors and alcohol and drug use. | The difference of changes in mean scores of AIDS knowledge is +0.45 (AIDS biology), +0.93 (transmission) and +0.41 (prevention), with P<0.01. There was no statistically significant overall effect on intended preventive behavior. | |
| Xu et al., 2000 | China | NRCT | 4063 intervention and 1050 control. | Deworming | Knowledge & behaviors; prevalence of helminth infection; environmental egg contamination, School policy and environment. | Knowledge passing rate increased from 10.9% to 82.7% (P<0.005); behavior (–); multi-parasitism rate decreased from 42.8% to 7.3% (P<0.01); egg contamination rate declining by 80.7% (P<0.01);policy (+); Environment(+) | |
| Xia et al., 2004 | China | NRCT | 4277 at baseline, 3346 at final evaluation. | Nutrition | Knowledge, attitudes & behaviors, school policy, school environment. | Knowledge of "nutrient-rich foods" increased from 36.0% to 59.6%(P<0.01).Awareness: the importance of eating three adequate meals each day increased from 50.0% to 86.6% (P<0.01).Washing hands before eating increased from 66.4% to 89.8% (P<0.01), "washing hands after using toilet" increased from 87.5% to 93.6% (P<0.01);policy (+);environment(+) | |
| Cartagenaet al., 2006 | Mongolia | NRCT | 320 interventions (M = 43%, F = 57%); 327 control (M = 43.5%, F = 56.5%). | HIV &SRH | Knowledge, attitudes, self-confidence & behaviors. | Small group peer education was more effective for knowledge (RI 5.03; 95% CI 3.08–8.21), attitude (RI 2.73; CI 95% 1.42–5.27), self-efficacy (RI 10.64,CI 8.59–13.19) and practice (OR 3.80, CI 95% 2.26–6.41) | |
| Wen et al., 2010 | China | NRCT | 2343 7th and 8th grade students, control (1004) and intervention (1339). Boys accounts for 52.1%, girls 45.9%. | Tobacco use | Knowledge, attitudes & behaviours (ever or regular smoker) | Knowledge increased, with the effect size being 0.32 in 7th cohort (P<0.001) and 0.41 in 8th cohort (P<0.001). Reduced the probability of baseline experimental smokers’ escalating to regular smoker (7.9 vs 18.3%; adjusted odds ratio (OR) 0.34, 95% CI = 0.12–0.97), but did not reduce the probability of baseline non-smokers’ initiating smoking (7.9 vs10.6%; adjusted OR 0.86, 95% CI = 0.54–1.38). Did not reduce the probability of smoking initiation (P>0.05). | |
| Chen et al., 2014 | China | CRCT | 709 Linzhi Tibetan (349 interventions, 360 controls) and 1098 Guangzhou Han (592 interventions, 506 controls). | Tobacco use | Knowledge, attitudes & behaviors, school policy, school environment. | Knowledge increased in Tibetan (β = 1.32, 95% CI (0.87–1.77) and Han groups (β = 0.47, 95% CI (0.11–0.83); attitudes toward smoking increased in Tibetan (β = 1.47, 95% CI (0.06–2.87)) but not in Han (β = −0.33, 95% CI (−1.68–1.01).Policy (+); environment (+). | |
| Jegannathan et al., 2014 | Cambodia | NRCT | 168 interventions (M = 92, F = 76); 131 control (M = 53, F = 78). | Suicide | Attitude, life skills development scale. | Among high-risk boys, a small to moderate effect size on depressed (ES = 0.40), attention problems (ES = 0.46), aggressive behaviour (ES = 0.48) and externalizing syndrome (ES = 0.64). Cohen's D: 0.2 = small effect, 0.5 = moderate effect, 0.8 = large effect | |
| Mohammed Nawi A et al., 2015 | Malaysia | CRCT | 47 intervention (M = 25, F = 22); 50 control (M = 30, F = 20). | Obesity | BMI, waist circumference, Body fat, quality of life score | No significant reduction in BMI, waist circumference, and the body fat percentage between the intervention and control groups. The effect sizes of the reduction were too small (0.09, 0.11, and 0.09 for BMI, waist circumference and body fat percentage). |
*CRCT = Cluster Randomized Controlled Trial, NRCT = Nonrandomized Controlled Trial.
Risk of bias evaluation table*.
| Citation | Selection bias | Performance bias | Detection bias | Attrition bias | Reporting bias | |
|---|---|---|---|---|---|---|
| Random sequence generation | Allocation concealment | Blinding of participants and personnel | Patient-reported outcomes | Long term (>6 wk) | Selecting reporting | |
| Aplasca et al., 1995 | – | – | – | ? | + | – |
| Xu et al., 2000 | + | + | ? | – | – | + |
| Xia et al., 2004 | + | + | ? | ? | – | – |
| Cartagena et al., 2006 | + | + | ? | ? | – | – |
| Wen et al., 2010 | + | + | – | ? | – | – |
| Chen et al., 2014 | – | – | – | ? | – | – |
| Jegannathan et al., 2014 | + | + | ? | ? | – | ? |
| Mohammed Nawi A et al., 2015 | – | – | ? | ? | – | – |
Categories for risk of bias are as follows: low risk of bias (–), unclear risk of bias (?), high risk of bias (+).