| Literature DB >> 34886569 |
Matthew Armstrong1, Nicole K Halim1,2, Rebecca Raeside1, Si Si Jia1, Karice Hyun1,3, Farzaneh Boroumand1,3, Mariam Mandoh1, Anna C Singleton1, Philayrath Phongsavan2,4, Julie Redfern1,5, Stephanie R Partridge1,2,4.
Abstract
To evaluate the digital platforms most used by adolescents for healthy lifestyle information, perceived helpfulness of platform information, helpfulness for positive behaviour changes, and quality of platforms' lifestyle health information. Mixed-methods study including a cross-sectional online survey and content analysis. Eligible participants were 13-18-years; living in Australia; and had searched online for healthy lifestyle behaviour (nutrition, physical activity, weight management, sleep) information in the previous three months. Survey items examined the use of digital platforms, self-perceived helpfulness, usefulness for positive behaviour, and popular content. Data were analysed using descriptive statistics and ordinal logistic regression models. Content analysis was performed on popular digital content to evaluate expertise, objectivity, transparency, popularity, and relevance. In total, 297 participants completed the survey (62.3% female; 15.8 [SD1.5] years). Seventy-eight percent and 77% of participants reported using websites and social media, respectively, for seeking healthy lifestyle information. Websites and social media were rated as somewhat helpful by 43% and 46% of participants, respectively. Sixty-six percent and 53% of participants agreed/strongly agreed smartphone apps and social media were helpful for positive behaviour change, respectively. Helpfulness did not differ by age or gender. We evaluated 582 popular digital content; 38% were produced by a commercial company. Only 7% of content was from health organisations, 10% from health professionals and only 10% of content was objective, and 14% was transparent. Adolescents extensively utilise websites and social media for health information, yet popular content has limited objectivity and transparency. Governments and health organisations should consider creating age-appropriate digital information for healthy lifestyle behaviours.Entities:
Keywords: adolescents; chronic disease; nutrition; obesity; physical activity; prevention; smartphone applications; social media; streaming services; websites
Mesh:
Year: 2021 PMID: 34886569 PMCID: PMC8657837 DOI: 10.3390/ijerph182312844
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Demographic characteristics, healthy lifestyle behaviours and internet access, electronic devices, and digital platforms of participants (n = 297).
| Demographic Characteristics |
| % | |
|---|---|---|---|
| Age group (years) | 13–14 | 58 | 19.5 |
| 15–16 | 110 | 37.0 | |
| 17–18 | 129 | 43.4 | |
| Search frequency for lifestyle health information online | 1–2 times a month | 140 | 47.1 |
| Once a week | 78 | 26.3 | |
| A few times a week | 56 | 18.9 | |
| Once a day | 10 | 3.4 | |
| More than once a day | 13 | 4.4 | |
| Gender identity | Male | 105 | 35.4 |
| Female | 185 | 62.3 | |
| Other or prefer not to answer | 7 | 2.4 | |
| Geographical location 1 | Major city | 237 | 79.8 |
| Regional or remote | 56 | 18.9 | |
| Other 2 or prefer not to answer | 4 | 1.3 | |
| SEIFA quintile 3 | Low (quintiles 1 and 2) | 52 | 17.5 |
| Moderate (quintiles 3 and 4) | 113 | 38.0 | |
| High (quintile 5) | 127 | 42.8 | |
| Other 2 or prefer not to answer | 5 | 1.7 | |
| Language other than English spoken at home | No | 224 | 75.4 |
| Yes | 73 | 24.6 | |
| Parent(s)/guardian(s) education level | Some high school | 49 | 8.2 |
| Completed high school | 67 | 11.3 | |
| Studying for degree or diploma | 19 | 3.2 | |
| Trade or technical qualification | 51 | 8.6 | |
| Completed degree or diploma | 230 | 38.7 | |
| Post-graduate qualification | 143 | 24.1 | |
| Other, unknown, prefer not to answer | 35 | 5.8 | |
| Currently attending high school | No | 44 | 14.8 |
| Yes | 253 | 85.2 | |
| Current work or education situation | Working casual, part-time, or full-time | 23 | 7.7 |
| Enrolled in tertiary education course | 27 | 9.3 | |
| Age-specific BMI categories 4 | Underweight (BMI <18.5 kg/m2) | 47 | 15.8 |
| Healthy (BMI 18.5–24.9 kg/m2) | 165 | 55.6 | |
| Overweight (BMI 25.0–29.9 kg/m2) | 51 | 17.2 | |
| Obese (BMI ≥30.0 kg/m2) | 25 | 8.4 | |
| Prefer not to answer | 9 | 3.0 | |
| Chronic medical condition | No | 190 | 64.0 |
| Yes | 103 | 34.7 | |
| Prefer not to answer | 4 | 1.3 | |
| Vegetables (serves/day) 5 | <5 | 269 | 90.6 |
| ≥5 | 28 | 9.4 | |
| Fruits (serves/day) 5 | <2 | 102 | 34.3 |
| ≥2 | 195 | 65.7 | |
| Sugar sweetened beverages (cups/week) | 0 | 189 | 63.6 |
| 1–2 | 89 | 30.0 | |
| ≥3 | 19 | 6.4 | |
| Takeaway meals (meals/week) | Never/rarely | 41 | 13.8 |
| Less than 1 | 106 | 35.7 | |
| 1–2 | 120 | 40.4 | |
| 3–4 | 25 | 8.4 | |
| More than 4 | 5 | 1.7 | |
| Sleep (hours/day) 5 | <8 | 228 | 76.8 |
| ≥8 | 69 | 23.2 | |
| ≥60-min of moderate or vigorous physical activity (days/week) 5 | <7 | 270 | 90.9 |
| 7 | 27 | 9.1 | |
| Wi-Fi access at home | Yes | 297 | 100 |
| No | 0 | 0.0 | |
| Electronic device ownership | Smartphone | 277 | 93.3 |
| Wearable digital device | 100 | 33.7 | |
| Laptop or desktop computer | 261 | 87.9 | |
| Tablet device | 112 | 37.7 | |
| Mobile data plan (GB/month) 6 | 0 GB | 23 | 8.4 |
| ≤30 GB | 180 | 65.9 | |
| >30 GB | 48 | 17.6 | |
| Don’t know | 22 | 8.1 | |
| Online platforms utilised for health-related purposes | Internet websites | 232 | 78.1 |
| Social media | 228 | 76.8 | |
| Smartphone apps | 92 | 31.0 | |
| Streaming services | 86 | 29.0 |
1 Classified participant residential areas into five classes using postcode (major cities, inner regional, outer regional, remote, and very remote) were aggregated into two categories, major cities and regional/remote (inner regional, outer regional, remote, and very remote); 2 Postcode not listed to determine geographical location or SEIFA; 3 SEIFA provides measures of socioeconomic conditions by geographic area ranks areas in Australia according to relative socioeconomic disadvantage; 4 Determined using the defined ranges by the International Obesity Task Force; 5 Categories based on national recommendations for vegetables, fruit, physical activity, and sleep; 6 24 participants had no data plan BMI, Body Mass Index; GB, gigabyte; SEIFA, Socioeconomic Indexes For Areas.
Figure 1Survey items showing (A) Frequency of using digital platforms to access healthy lifestyle information; (B) Perceived helpfulness of digital platforms for accessing information and (C) Helpfulness of digital platforms for behaviour change.
Components, categories and attributes from the open-ended questions about helpfulness of digital platforms for behaviour change.
| Digital Platform | Category | Attributes | Verbatim Quote (Gender, Age) |
|---|---|---|---|
| Social media ( |
Changed body image ( | Positive body image, improvements to self-esteem and confidence | “There is an emerging drive for positive stigma around different body shapes and sizes. This has helped me feel very comfortable with who I am.” Female, 17 years |
|
Changed physical activity behaviours ( | Motivation, tips and ideas, free workouts | “Changed body workouts and structured the day into more organised and manageable loads.” Male, 15 years | |
|
Changed diet behaviours ( | Meal ideas, improved relationship with food | “I also love pages that post of quick healthy meal hacks.” Female, 17 years | |
|
Motivation by individuals ( | Following people’s journey’s, different types of people | “Seeing other people’s routines in regards to healthy eating and exercise has definitely influenced my lifestyle” Female, 18 years | |
| Websites ( |
Changed general knowledge ( | Well informed, facts, awareness | “Information on these sites allow me to be more well informed on what actions to take in order to pay better attention to my heath” Male, 18 years |
|
Changed diet behaviours ( | Healthier recipes, awareness of dietary behaviours | “More aware of what I’m consuming. Started cooking healthier meals because I had access to healthy recipes.” Female, 17 years | |
| Smartphone apps ( |
Change physical activity behaviours ( | Wellbeing, tracking, accountability notifications | “Mainly keep track of my steps. I do at least 10 k steps a day and maybe 3x a week I hit 15 k. It means I spend more time outside and had helped my happiness and [wellbeing]” Female, 14 years |
|
Changed diet behaviours ( | Notifications, tracking, accountability | “I can also access important information about sleep, nutrition and energy which helps me stick to a schedule.” Female, 18 years | |
| Streaming services ( |
Changed diet behaviours ( | Environmental impacts, vegetarian/vegan, less meat consumption | “Changed perception of meat and diary industry and how it is not very healthy” Male, 13 years |
Content analysis of popular pages, persons, apps, shows, or documentaries reported by participants.
| Category | Sub-Category | All Content | Websites | Social Media | Smartphone Apps | Streaming Services | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
| % |
| % |
| % |
| % |
| % | ||
| Expertise | Individual health professional | 59 | 10.1 | 4 | 2.6 | 55 * | 17.0 | 0 | 0.0 | 0 | 0.0 |
| Individual non-health professional | 158 | 27.1 | 4 | 2.6 | 154 | 47.5 | 0 | 0.0 | 0 | 0.0 | |
| Health organisation | 39 | 6.7 | 34 | 22.2 | 4 | 1.2 | 1 | 1.4 | 0 | 0.0 | |
| Non-health organisation | 4 | 0.7 | 0 | 0.0 | 4 | 1.2 | 0 | 0.0 | 0 | 0.0 | |
| Commercial company | 219 | 37.6 | 73 | 47.7 | 60 | 18.5 | 55 | 77.5 | 31 | 91.2 | |
| Other | 103 | 17.7 | 38 | 24.8 | 47 | 14.5 | 15 | 21.1 | 3 | 8.8 | |
| Objectivity | Commercial interests | 420 | 72.2 | 81 | 52.9 | 254 | 78.4 | 55 | 77.5 | 30 | 88.2 |
| No commercial interests | 57 | 9.8 | 32 | 20.9 | 23 | 7.1 | 1 | 1.4 | 1 | 2.9 | |
| Cannot determine | 105 | 18.0 | 40 | 26.1 | 47 | 14.5 | 15 | 21.1 | 3 | 8.8 | |
| Transparency | Disclosures | 83 | 14.3 | 54 | 35.3 | 14 | 4.3 | 12 | 16.9 | 3 | 8.8 |
| Non-disclosures | 397 | 68.2 | 59 | 38.6 | 263 | 81.2 | 44 | 62.0 | 31 | 91.2 | |
| Cannot determine | 105 | 18.0 | 40 | 26.1 | 47 | 14.5 | 15 | 21.1 | 3 | 8.8 | |
| Relevance | Nutrition | 329 | 56.5 | 97 | 63.4 | 168 | 51.9 | 37 | 52.1 | 27 | 79.4 |
| Physical activity | 369 | 63.4 | 113 | 73.9 | 169 | 52.2 | 56 | 78.9 | 31 | 91.2 | |
| Weight management | 268 | 46.0 | 86 | 56.2 | 126 | 38.9 | 40 | 56.3 | 16 | 47.1 | |
| Sleep | 92 | 15.8 | 54 | 35.3 | 20 | 6.2 | 15 | 21.1 | 3 | 8.8 | |
| Cannot determine | 64 | 11.0 | 40 | 26.1 | 6 | 1.9 | 15 | 21.1 | 3 | 8.8 | |
| Popularity | Content reported by ≥5 participants | 33 | 5.7 | 9 | 5.9 | 14 | 4.3 | 8 | 11.3 | 2 | 5.9 |
| Median | Range | Median | Range | Median | Range | Median | Range | Median | Range | ||
| Content frequency | 1 | 1–30 | 1 | 1–30 | 1 | 1–30 | 1 | 1–16 | 1 | 1–16 | |
| Number social media platforms for content with frequency ≥5 | - | - | - | - | 3 | 2–4 | - | - | - | - | |
| Number of followers across platforms for content with frequency ≥5 | - | - | - | - | 2,958,000 | 1,598,360–70,400,000 | - | - | - | - | |
* Inclusive of 35 accounts with expertise listed as ‘personal trainer’.