| Literature DB >> 30388824 |
Marco J Haenssgen1,2,3,4, Thipphaphone Xayavong5,6,7, Nutcha Charoenboon8, Penporn Warapikuptanun9, Yuzana Khine Zaw10.
Abstract
Education and awareness raising are the primary tools of global health policy to change public behaviour and tackle antimicrobial resistance. Considering the limitations of an awareness agenda, and the lack of social research to inform alternative approaches, our objective was to generate new empirical evidence on the consequences of antibiotic-related awareness raising in a low-income country context. We implemented an educational activity in two Lao villages to share general antibiotic-related messages and also to learn about people's conceptions and health behaviours. Two rounds of census survey data enabled us to assess the activity's outputs, its knowledge outcomes, and its immediate behavioural impacts in a difference-in-difference design. Our panel data covered 1130 adults over two rounds, including 58 activity participants and 208 villagers exposed indirectly via conversations in the village. We found that activity-related communication circulated among more privileged groups, which limited its indirect effects. Among participants, the educational activity influenced the awareness and understanding of "drug resistance", whereas the effects on attitudes were minor. The evidence on the behavioural impacts was sparse and mixed, but the range of possible consequences included a disproportionate uptake of antibiotics from formal healthcare providers. Our study casts doubt on the continued dominance of awareness raising as a behavioural tool to address antibiotic resistance.Entities:
Keywords: LMICs; Lao PDR; antibiotics; antimicrobial resistance; development studies; health behaviour; health education; rural; survey
Year: 2018 PMID: 30388824 PMCID: PMC6316454 DOI: 10.3390/antibiotics7040095
Source DB: PubMed Journal: Antibiotics (Basel) ISSN: 2079-6382
Figure 1Site map and research timeline in Lao PDR. Source: Authors, adapted from Google Inc. [18].
Characteristics of survey villages compared to the provincial average.
| Village Attributes | Village 1 | Village 2 | Salavan Average |
|---|---|---|---|
| Village Size | 1462 | 744 | 369 a |
| Household Size | 5.0 | 4.5 | 5.9 |
| Female Population Share | 48.8% | 53.1% | 50.1% |
| Dependency Ratio c | 0.68 | 0.63 | 0.64 b |
| Households Owning Mobile Phones | 96.0% | 89.9% | 81.6% |
Source: Primary survey data and Lao Statistics Bureau [19]. a Village numbers based on data from National Geospatial-Intelligence Agency [20]. b National average for rural areas. c Non-working-age population divided by working-age population (15–64 years).
Elements of the educational activity.
| Session & Duration | Description | Expected Outcomes | Main Message a | Direction of Communication |
|---|---|---|---|---|
|
| Ice breaking. | |||
|
| In groups, participants sketch a village map and mark down their own houses, important locations in the village, and draw lines to connect themselves with places as well as people they go to when sick. | Team learns about places, existing health networks, and health facilities within and nearby the village. | Participants | |
|
| Part (I): Participants sort medicines into 2 groups—those that they know and do not know. | Team gains overview of medicines and their purposes from participants’ perspective. | Participants | |
| Part (II): Participants free-sort pictures of common medicines into their own categories. | Team understands participants’ general conceptions around medicines and treatments. | Participants | ||
| Part (III): Participants sort medicines into two groups—over-the-counter medicines and prescription medicines. | Participants reflect on the ways to access medicines. | Only use antibiotics when prescribed by a certified health professional. | Team | |
|
| Participants pass a germ around in a circle. When the music stops, the person with the germ answers a right-or-wrong question about taking medicines. If incorrect, she/he are out of the game, the germ evolves, and the game continues. The last remaining person wins a prize. | Participants become familiar with the idea of bacteria evolving and resisting medicines. | (1) Germs can become “stronger” if treated inappropriately until the point that there is no medicine to treat them anymore. | Team |
|
| Break. | |||
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| A short skit performed by the team with a simple storyline around antibiotics and antibiotic resistance. | Participants gain a deeper understanding about drug resistance and their own part in the issue. | (1) Always follow health workers’ advice when using antibiotics. | Team |
|
| Participants simulate running a family business that produces goods and sells to the market. Each group (family) has different tools to make as much money as they can. Throughout the activity, family members are diagnosed randomly with a disease, provided with different treatment scenarios, and the rest of the family have to pay hospital fees to bring that sick member back. | Participants reflect on common illnesses and the various ways of treating them; the team gains an understanding of health decisions in the local context. | Only use antibiotics when prescribed by a certified health professional. | Team |
|
| Participants provide their reflections on the activities and lessons learned. | Participants understand the key messages from the activities, and express these to the group. | Participants | |
a Messages based on World Health Organization recommendations (WHO) (e.g., [22]).
Sample characteristics of two rounds of census surveys in two Lao villages.
| Variable | Survey Round I | Survey Round II | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean | Std. Dev. | Min | Max |
| Mean | Std. Dev. | Min | Max |
| ||
|
| % participated in educational activity: Throughout | n/a g | 0.05 | 0.21 | 0 | 1 | 1216 | ||||
| % participated in educational activity: Partly | n/a g | 0.00 | 0.06 | 0 | 1 | 1216 | |||||
| % heard about educational activity | n/a g | 0.22 | 0.41 | 0 | 1 | 1216 | |||||
|
| Sex (% female) | 0.55 | 0.50 | 0 | 1 | 1264 | 0.56 | 0.50 | 0 | 1 | 1216 |
| Age | 39.91 | 17.14 | 18 | 100 | 1264 | 40.04 | 17.02 | 18 | 100 | 1216 | |
| Completed years of formal education | 6.28 | 4.59 | 0 | 21 | 1264 | 6.22 | 4.56 | 0 | 21 | 1216 | |
| Wealth index (range: 0 to 1) a,b | 0.49 | 0.13 | 0.11 | 0.78 | 454 | 0.50 | 0.13 | 0.11 | 0.78 | 446 | |
| % speaking Lao | 1.00 | 0.00 | 1 | 1 | 1264 | 1.00 | 0.00 | 1 | 1 | 1216 | |
| Ethnic group: Lao Loum | 0.97 | 0.18 | 0 | 1 | 1264 | 0.96 | 0.19 | 0 | 1 | 1216 | |
| Ethnic group: Other | 0.01 | 0.10 | 0 | 1 | 1264 | 0.01 | 0.10 | 0 | 1 | 1216 | |
| Ethnic group: Don’t know/prefer not to say | 0.02 | 0.15 | 0 | 1 | 1264 | 0.03 | 0.16 | 0 | 1 | 1216 | |
|
| % have seen antibiotic capsules | 0.97 | 0.18 | 0 | 1 | 1264 | 0.96 | 0.19 | 0 | 1 | 1216 |
| % have heard of drug resistance (“due yah”) c | 0.39 | 0.49 | 0 | 1 | 1264 | 0.63 | 0.48 | 0 | 1 | 1216 | |
| % have heard of drug resistance (“lueng yah”) c | 0.79 | 0.40 | 0 | 1 | 1264 | 0.82 | 0.39 | 0 | 1 | 1216 | |
| % buy antibiotics over the counter (attitude) | 0.30 | 0.46 | 0 | 1 | 1264 | 0.27 | 0.44 | 0 | 1 | 1216 | |
| % prefer antibiotics over alternatives (attitude) | 0.29 | 0.45 | 0 | 1 | 1264 | 0.24 | 0.43 | 0 | 1 | 1216 | |
| % do not keep antibiotics for future use (knowledge) | 0.22 | 0.41 | 0 | 1 | 1264 | 0.27 | 0.44 | 0 | 1 | 1216 | |
| % antibiotic resistance can spread (knowledge) | 0.12 | 0.32 | 0 | 1 | 1264 | 0.02 | 0.15 | 0 | 1 | 1216 | |
| No. of desirable knowledge/attitude answers (0–4) | 0.93 | 0.93 | 0 | 4 | 1264 | 0.81 | 0.87 | 0 | 4 | 1216 | |
|
| % of illness episodes involving children | 0.39 | 0.49 | 0 | 1 | 512 | 0.35 | 0.48 | 0 | 1 | 284 |
| Self-rated severity (1 = mild, 2 = medium, 3 = severe) | 1.79 | 0.70 | 1 | 3 | 512 | 1.88 | 0.67 | 1 | 3 | 284 | |
| Average duration of illness episode (days) | 7.29 | 9.25 | 1 | 130 | 512 | 7.36 | 14.42 | 1 | 219 | 284 | |
| Average no. of medicines and treatments received f | 2.74 | 1.71 | 0 | 13 | 512 | 2.46 | 1.39 | 0 | 8 | 284 | |
| Average no. of antibiotics | 0.50 | 0.70 | 0 | 4 | 512 | 0.42 | 0.59 | 0 | 3 | 284 | |
| Average no. of antibiotics (incl. “uncertain” medicine) | 1.31 | 1.45 | 0 | 10 | 512 | 1.15 | 1.25 | 0 | 6 | 284 | |
| % public providers (health centres, hospitals) | 0.27 | 0.44 | 0 | 1 | 512 | 0.27 | 0.44 | 0 | 1 | 284 | |
| % private providers (clinics, hospitals, pharmacies) | 0.53 | 0.50 | 0 | 1 | 512 | 0.59 | 0.49 | 0 | 1 | 284 | |
| % informal providers (grocery stores, healers) | 0.02 | 0.14 | 0 | 1 | 512 | 0.05 | 0.22 | 0 | 1 | 284 | |
| % family and self-care | 0.97 | 0.18 | 0 | 1 | 512 | 1.00 | 0.06 | 0 | 1 | 284 | |
| % others | 0.06 | 0.25 | 0 | 1 | 512 | 0.07 | 0.26 | 0 | 1 | 284 | |
a Average of 17 household assets and amenities on scale from 0 to 1. b Household-level data. c The term “drug resistance” has two local expressions: “ດື້ຍາ” (“due yah”) is the formal translation of “drug resistance” and literally translates into “stubborn [to the effects of] medicine”. “ລຶ້ງຍາ” (“lueng yah”) is a colloquial but also broader expression that does not exclusively refer to drug resistance, meaning “[e.g., the body getting] used to medicine”. d Illness-level data. e Completed illnesses experienced by a respondent or a child under their supervision. f “Number of courses” as in, “how many types of medicine did you receive during step x of your illness?” g Educational activity took place after Survey Round I, therefore no exposure reported.
Evaluation framework for analysis of study outcomes.
| Framework Element | Outputs | Outcomes | Impacts |
|---|---|---|---|
| Level of Analysis | Individual | Individual | Illness |
| Indicators | Direct and indirect exposure to educational activity | Awareness and understanding of drug resistance a | Patterns of healthcare utilisation during acute illnesses c |
| Lessons and feedback from educational activity | “Desirability” of antibiotic-related attitudes and knowledge b | Sources of antibiotics during acute illnesses d |
a The term “drug resistance” has two local expressions: “ດື້ຍາ” (“due yah”) is the formal translation of “drug resistance” and literally translates into “stubborn [to the effects of] medicine”. “ລຶ້ງຍາ” (“lueng yah”) is a colloquial but also broader expression, meaning “[e.g., the body getting] used to medicine”. While “lueng yah” did not exclusively refer to drug resistance, it had arisen consistently as a theme during the questionnaire testing phase and, as can be seen in Results Section 3.2, it was commonly mentioned as an explanation for the formal term “due yah”. b See Table 3 for associated indicators. c Focusing especially on formal and informal healthcare providers. Formal providers included public hospitals and primary care units (public), and private clinics, private hospitals and pharmacies (private). Informal providers included traditional healers, grocery stores, retired doctors, and itinerant medicine traders. d Same as above, plus antibiotics stored at home and provided by family and friends as “informal” sources.
Characteristics of individuals by activity exposure.
| Variable | Direct Exposure (i.e., Participated in Activity) | Indirect Exposure (i.e., Talked About Activity) | Unexposed |
|---|---|---|---|
| Mean (Std. Dev) | Mean (Std. Dev) | Mean (Std. Dev) | |
| Sex (% female) | 0.71 (0.46) | 0.63 (0.49) | 0.54 (0.50) |
| Age | 44.76 (11.36) | 38.18 (14.91) | 40.85 (17.75) |
| Education | 7.10 (4.06) | 8.18 (4.99) | 5.67 (4.36) |
| Wealth index (range: 0 to 1) a | 0.51 (0.12) | 0.54 (0.11) | 0.50 (0.12) |
| Ethnic group: Lao Loum | 1.00 (0.00) | 0.99 (0.12) | 0.96 (0.20) |
| Ethnic group: Other | 0.00 (0.00) | 0.01 (0.10) | 0.01 (0.11) |
| Ethnic group: Don’t know/prefer not to say | 0.00 (0.00) | 0.00 (0.07) | 0.03 (0.16) |
Notes: “Endline” (R.2) data, using matched panel data. Groups are mutually exclusive, for example, the group “talked about activity” does not include participants of the activity (among whom 53 talked about the activity with other villagers). a Average of 17 household assets and amenities on scale from 0 to 1.
Figure 2Map and overview of educational activity exposure in case study villages. Notes: “Endline” (R.2) data, using matched panel data. n = 723 (Panel (a)), n = 407 (Panel (b)). Marker size adjusted to distinguish overlapping responses.
Figure 3Differences in communicated activity themes across participants and non-participants. Notes: “Endline” (R.2) data, using matched panel data.
Antibiotic-related attitudes and knowledge across survey rounds.
| Variable | Direct Exposure | Indirect Exposure | Unexposed | Difference-in-Difference | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Survey Round 1 | Survey Round 2 | Diffe-rence | Survey Round 1 | Survey Round 2 | Diffe-rence | Survey Round 1 | Survey Round 2 | Diffe-rence | Direct vs. Unexposed | Indirect vs. Unexposed | ||
|
|
| 27.6% | 91.4% | +63.8% | 49.0% | 75.0% | +26.0% | 36.2% | 58.8% | +22.6% | +41.2% | +3.4% |
| 1.7% | 3.5% | +1.7% | 5.3% | 1.0% | −4.3% | 3.7% | 2.4% | −1.3% | +3.0% | −3.1% | ||
| Medicine does not work | 6.9% | 17.2% | +10.3% | 15.9% | 15.9% | 0.0% | 12.6% | 10.0% | −2.7% | +13.0% | +2.7% | |
| Taking medicine wrongly (e.g., wrong type, too much) | 1.7% | 6.9% | +5.2% | 2.9% | 1.9% | −1.0% | 2.3% | 2.2% | −0.1% | +5.3% | −0.9% | |
| Stubborn patient, medicine restrictions/dislikes | 5.2% | 1.7% | −3.5% | 11.1% | 4.8% | −6.3% | 10.1% | 7.5% | −2.6% | −0.9% | −3.7% | |
| Addicted to or strong preference for medicine | 3.5% | 0.0% | −3.5% | 3.4% | 4.3% | +1.0% | 2.7% | 2.7% | 0.0% | −3.5% | +1.0% | |
| Side-effects, drug allergy, or a specific illness | 13.8% | 6.9% | −6.9% | 7.2% | 10.1% | +2.9% | 8.2% | 6.0% | −2.2% | −4.7% | +5.1% | |
| “Lueng yah” | 25.9% | 55.2% | +29.3% | 17.3% | 41.4% | +24.0% | 14.7% | 30.6% | +15.9% | +13.5% | +8.2% | |
| Other interpretation | 3.5% | 1.7% | −1.7% | 1.9% | 1.4% | −0.5% | 2.1% | 1.9% | −0.2% | −1.5% | −0.3% | |
| Don’t know / cannot or prefer not to answer | 37.9% | 6.9% | −31.0% | 35.1% | 19.2% | −15.9% | 43.6% | 36.8% | −6.8% | −24.2% | −9.1% | |
|
|
| 93.1% | 96.6% | +3.4% | 84.6% | 90.4% | +5.8% | 77.5% | 80.2% | +2.7% | +0.8% | +3.1% |
| 19.0% | 22.4% | +3.4% | 17.8% | 6.7% | −11.1% | 9.6% | 4.9% | −4.8% | +8.2% | −6.3% | ||
| Medicine does not work | 48.3% | 44.8% | −3.5% | 44.7% | 53.4% | +8.7% | 43.1% | 41.4% | −1.6% | −1.8% | +10.3% | |
| Taking medicine wrongly (e.g., wrong type, too much) | 3.5% | 6.9% | +3.5% | 2.9% | 1.9% | −1.0% | 2.2% | 5.8% | +3.6% | −0.1% | −4.6% | |
| Stubborn patient, medicine restrictions/dislikes | 0.0% | 0.0% | 0.0% | 1.0% | 1.0% | 0.0% | 1.3% | 1.0% | −0.2% | +0.2% | +0.2% | |
| Addicted to or strong preference for medicine | 20.7% | 10.3% | −10.4% | 21.6% | 24.0% | +2.4% | 20.8% | 23.2% | +2.3% | −12.7% | +0.1% | |
| Side-effects, drug allergy, or a specific illness | 1.7% | 3.5% | +1.7% | 0.5% | 0.0% | −0.5% | 1.4% | 1.6% | +0.2% | +1.5% | −0.7% | |
| Other interpretation | 3.5% | 6.9% | +3.5% | 2.4% | 3.4% | +1.0% | 4.3% | 3.7% | −0.6% | +4.0% | +1.6% | |
| Don’t know / cannot or prefer not to answer | 3.5% | 5.2% | +1.7% | 9.1% | 9.6% | +0.5% | 17.4% | 18.4% | +1.0% | +0.7% | −0.6% | |
|
|
| 1.22 | 1.33 | +0.10 | 0.96 | 0.82 | −0.14 | 0.90 | 0.79 | −0.11 | +0.22 | −0.03 |
| Would buy antibiotics over the counter | 48.3% | 55.2% | +6.9% | 32.2% | 32.7% | +0.5% | 28.5% | 24.7% | −3.8% | +10.7% | +4.3% | |
| Prefers antibiotics over alternatives | 32.8% | 31.0% | −1.7% | 29.8% | 20.2% | −9.6% | 28.0% | 25.5% | −2.5% | +0.8% | −7.1% | |
| Would not keep antibiotics for future use | 27.6% | 32.8% | +5.2% | 19.7% | 28.4% | +8.7% | 22.2% | 26.6% | +4.4% | +0.8% | +4.3% | |
| Thinks that antibiotic resistance can spread | 13.8% | 13.8% | 0.0% | 14.4% | 0.5% | −13.9% | 11.6% | 2.1% | −9.5% | +9.5% | −4.5% | |
Notes: Pooled data set, using matched panel data.
Figure 4Healthcare access and sources of antibiotics across survey rounds. Panel (a) Patterns of healthcare access by activity participation. Panel (b) Sources of antibiotics across survey rounds. Notes: Pooled data set, using complete survey data; repeated cross-sections of illness episodes (n = 727). Sub-sample sizes by survey round are: Round 1/direct exposure (n = 18)/indirect exposure (n = 89)/unexposed (n = 337); Round 2/direct exposure (n = 12)/indirect exposure (n = 59)/unexposed (n = 213). Multiple sources of antibiotic access per illness episode were possible. a “Antibiotics”, including confirmed and possible antibiotics, were based on reported medicines received during the illness, and respondent’s reported names and uses of antibiotics shown during the interview. b Includes public and private healthcare providers. c Includes traditional healers, grocery stores, retired doctors, itinerant medicine traders, and medicine stored at home and provided by family and friends.