Paper based and mobile application based self-monitoring tool for healthy dietary intake, Development and Applicability: A non-randomized trial

doi:10.21203/rs.3.rs-3341567/v1

Download PDF

Research Article

Paper based and mobile application based self-monitoring tool for healthy dietary intake, Development and Applicability: A non-randomized trial

https://doi.org/10.21203/rs.3.rs-3341567/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background and objectives Unhealthy diet is a key risk factor for Non-Communicable Diseases (NCD) that contribute to increased morbidity and premature mortality. With increased computer literacy and mobile phone penetration there is a high opportunity for mobile application-based interventions. Therefore, the study was conducted to develop a mobile application for self-monitoring of dietary intake and assess it acceptability and effectiveness in diet control

Materials and methods Mobile application was developed based on research evidence and opinions of local experts. Mobile application was introduced to a selected group of participants (who were in preparation, action, maintenance stages of TTM) and a paper-based intervention was used as the comparison. Socio demographic data was collected through a self-administered questionnaire and participants were followed up for three months for adherence and effectiveness of interventions was assessed at the end comparing progressive change in stage of change and changed to healthy dietary intake between two groups as primary and secondary outcomes respectively. The study was registered in Sri Lankan Clinical Trail Registry (Registration no - SLCTR/2020/025)

Results Among 123 office workers participated in the study 19.5% preferred the mobile intervention over the paper-based intervention. Younger, not married office workers with no child had higher acceptance for the mobile intervention (p<0.05). There was no difference of adherence (in all three months) and outcome between two groups of intervention.

Discussion As office workers used to do paper works, they might have preferred the paper-based intervention while increased usage of smart phones in younger population might have contributed to higher acceptance in younger age group.

Conclusion and recommendations Mobile application-based interventions are better accepted among young age group and further studies are recommended to explore the applicability

Trial registration The study was registered in Sri Lankan Clinical Trail Registry (Registration no - SLCTR/2020/025 Date 15^th December 2020)

Non-Communicable Diseases (NCD) have accounted for 73·4% (95% uncertainty interval [UI] 72·5–74·1) of the deaths around the world to become “the number one killer” in the year 2017(1) and cardiovascular and cerebrovascular diseases accounted for 16.1% of the total Disability Adjusted Life Years (DALY) in 2016 (2). Alarmingly major contributions to deaths and DALY were from low- and middle-income countries (2). Among four key risk factors (smoking, alcohol consumption, unhealthy diet, and physical inactivity) which have repeatedly shown associations with the development of NCD, an unhealthy or suboptimal diet has a significant and well-established impact on the development of NCD as well as its complications. It was highlighted that an unhealthy and suboptimal diet accounted for 11 million deaths and 225 million DALY in 2017 (3). Similarly, both mortality and DALY burden are higher in the local context as well. Ischemic heart disease, stroke, and diabetes are the top three contributors to deaths and DALY due to NCD among Sri Lankans (4). Though alcohol and tobacco use were higher among males (45.7% and 34.8% respectively), unhealthy diet and physical inactivity were prevalent in both males and females (5).

As behavioral risk factors have contributed to the development of NCD and its complications, even a small change in such behaviors can have a significant impact on the health of an individual or a community (6). Therefore, it is essential to aim at behavior changes to reduce NCD burden. Human behavior and its change do not occur at random. There are mechanisms of action by which a behavior change can occur. Behavior change theories generally describe the mechanisms of action (mediators), moderators of behavior change, and assumptions regarding behavior change (7). There has been a plethora of behavior change theories that explained human behaviour and have been used in different type of interventions (7).

TTM is well-known to be effective in interventions for smoking cessation and its effectiveness in intervention for other behaviour changes was evident in recent studies. It was shown to be effective in changing dietary behaviour, physical activity, and suicide prevention as well (8,9). With the recent increase of studies aiming at risk factors for chronic non-communicable diseases, TTM has been widely used in interventions aimed at changing dietary behaviour (9). Recent reviews based on newer studies conclude that interventions based on TTM have been successful and effective in changing physical activity, dietary behaviour, smoking and opioid addiction prevention, and dental hygiene improvement (10). Dietary interventions targeted on reducing dietary fat intake and improving fruit and vegetable consumption or general healthy dietary intake have been successful according to a very recent review of 14 studies based on TTM (11).

Behaviour Change Techniques (BTC) are the smallest active ingredient of an intervention, and they are designed based on behaviour change theories (12). Number of systematic reviews and meta-analysis have been conducted to assess the effectiveness of BCT and concluded that goal setting, self-monitoring and provide information through credible sources (subject specialists) were more effective BCTs among various BCTs used in behaviour change interventions (12–14).

With the advancement and increased usage of mobile phones and devices, health interventions through such devices have come into the picture and number of studies and reviews have claimed the effectiveness of mobile health interventions over conventional health interventions (15–17). Usage of BCT within the mobile application and adopting behaviour change theories or models have been found to be associated with the overall application quality and functionality of the application (17). Further, BCTs like providing instructions, feedback on behaviour, contingency rewards and the ability for self-monitoring were commonly used in mobile apps for health interventions (18). Among BCTs, self-monitoring was found to be more effective in mobile apps compared to other methods of self-monitoring (19,20).

Workforce participation of the population above 15 years of age in Sri Lanka was 52.3% in 2019 that is nearly three forth of males (73%) and one third of females (34.1%) (21). Around 25% of the workforce are employed in the public sector (government and semi-government) and it is around 1.1 million excluding tri-forces (22). When considering International Classification of Occupations 57.6% of the Sri Lankan working population is comprised of professionals, technical and associate workers, and clerks (22). Most of them perform office-based duties except in the Departments of Health and Education (22). Because of the nature of their work, they are less physically active during working hours and are at a higher risk for developing NCD. At the same time a study conducted in public sector offices in Colombo district showed higher prevalence of NCD risk factors among office workers like physical inactivity, excessive carbohydrate and sugar intake, high Body Mass Index (BMI) and high waist to hip ratio (23). As a group of individuals with similar risk factors gathered in one place and considering the feasibility of implementation office setting is an ideal setting for health promotion interventions and it was found to be effective for such interventions (24).

While Sri Lanka is claiming high mobile phone penetration (25) with nearly 47% smartphone usage among the public (26), more than 70% of office workers are with computer literacy and 56% of them are accessing internet (22). Therefore, there is a higher potential for mobile app-based health interventions in office settings and there is higher need of intervention for this specific population when considering their high risk of developing NCDs.

Thus, the current study aimed to develop a mobile application for self-monitoring of dietary intake and assess it acceptability and effectiveness in diet control compared to a paper-based diet monitoring tool.

The study was conducted in two phases as design phase and implementation phase. During the designing phase extensive literature survey was conducted to identify appropriate theory/ theories for behaviour change and BCTs to incorporate into diet monitoring tools (mobile app and paper-based tool). It was done through search applications including Google scholar, Medline, PubMed and Mendeley for studies available online and Post-Graduate Institute of Medicine (PGIM) library repository for theses and dissertations using key words diet, dietary intake, behaviour change theory, behaviour change interventions and mobile app-based interventions. Following the literate review experts in the fields of behavioural science, nutrition and mobile health interventions was consulted for their opinion on the layout of diet monitoring tools and operationalization of dietary portions and servings. Combining findings from the literate review and experts’ opinion the layout for diet monitoring tools was formed and mobile app layout was discussed with the software development team. Then the mobile application was developed, and further discussions was conducted with experts on the operationalization of the application. When it comes to a consensus mobile application was pre-tested at a public sector office (Chief secretariat – Southern province) which was not included in the proper study and piloted at an office in Matara district (Divisional Secretariat – Welipitiya).

The implementation phase was conducted as a non-randomized experimental trial.

Study setting

Study was conducted 10 selected government offices in Galle districts.

Study population

Development officers (DO), Management assistants (MA) and administrative and management officers were selected for the study. Workers who are involving with any of physical exertion during their duty and those who on special dietary plans were excluded from the study.

Sample size sampling

Sample size was calculated for the main study (CRT) assuming a 50% improvement of dietary practices. Proportion of people consuming recommended number of fruit and vegetable servings (reported by steps survey 2016) (5) was considered as the baseline and 50% improvement was estimated in the intervention group. Five percent alpha error and 20% beta error were allowed in sample size calculation. As cluster sampling was done design effect of 1.58 was also incorporated for the sample size as well

Multistage cluster sampling was used to recruit the participants. Cluster was defined as an office with at least 30 clerical type workers. Clusters were selected purposefully depending on the number of workers and nature of work carried out in the office. The participants within the clusters were selected randomly, using a series of random numbers.

Data collection and data collection tools

Two-point data collection was conducted at the baseline and at the intervention. Data collection tools comprised of three parts which included a self-administered (survey) questionnaire, a staging algorithm and 24-hour dietary recall. Self-administered (survey) questionnaire was used to assess basic socio-demographic data, general health status, and dietary behaviours. Weight and hight of participants were measured according to standard procedures described in European Health Examination Survey (EHES) (27). Four question staging algorithm was used to ascertain the stage of change for healthy behaviour change. 24-hour dietary recall by a trained data collector was used for assessment of dietary intake. It was assisted with a picture guide to determine the unit of measurement and amount of food that a measuring unit will contain, and it was further assisted with a computer software to calculate the number of serving taken from each food group. basic socio-demographic data and general health status data was collected only at the baseline and assessment of dietary intake and stage of change was done at the baseline and post intervention as well. Healthy diet was defined as adherence to the numbers of servings recommended in FBDG for Sri Lankans for more than three food groups including cereal and cereal based foods, fruits, and vegetables, with the consumption of one or no unhealthy food per day

Intervention

A daily serving counter was introduced to participants who are planning to start or already started a dietary behaviour change (preparation, action and maintenance stage as described in TTM)

Mobile based intervention (intervention group) – a simple mobile application was developed as to mark daily intake of servings by adding to numbers of serving for each food groups described in Food Based Dietary Guidelines for Sri Lankans (FBDG) (28). In the main user interface, the serving counter was displayed for each food groups (cereal and cereal based foods, vegetables, fruits, fish meat and pulses, dairy products, nuts and seeds and unhealthy foods). Recommended numbers of servings were indicated in green colour. When exceeding or not meeting the recommended number the indicator turns in to red colour indicating the unhealthy eating. A serving guide customized to local foods was included as an additional interface and a link to the serving guide was included in the main interface.

Paper based intervention (comparison group) – A paper-based serving counter with a serving guide was also prepared with the same colour coding for the numbers of serving in each food group.

Principal investigator introduced serving counter (both paper-based and mobile based) to the participants at the beginning of the intervention and they were allowed to choose the type of the serving counter they want. Marking of the serving counter was assessed monthly by inspecting marked papers and observing the summery of marking of the mobile based serving counter. Application was configured to record a summary of marking for last 30 days. If a participant had missed more than two days of marking per any week, it was considered as poor adherence to the serving counter.

Intervention was conducted for three months, and post-intervention assessment of dietary intake and stage of change were conducted at the end of the third month. Progressive (forward) change in stage of change was considered as the primary outcome whereas change from unhealthy diet to a healthy diet was considered as the secondary outcome.

Statistical analysis

Sample characteristics were described in relation to socio-demographic, health and work-related factors. Acceptance rate and adherence to the intervention was described using percentages.

All participants were included in the post-intervention analysis considering the initial group despite their adherence to practice intention-to-treat analysis. However, it was not possible for the monthly adherence assessment. Therefore, those who had not turned up for the assessment of adherence were categorized as non-adherent participants.

Pre and post comparison in stage of change and healthy dietary intake was done within and between mobile application and paper-based groups using Mcnemar test to check the statistical significance. paired t-test, Mann Whitney U test was used to check differences of means and medians while 0.05 was considered as the cut off for the significance. Intention to treat analysis was implemented and all participants initially selected either mobile app or paper-based serving counter included in the post-intervention assessment.

Ethical and administrative clearance

Ethical approval for the study was obtained from the Ethical Review Committee, Faculty of Medicine, University of Ruhuna (Registration no. − 2020/P/105) and the trial was registered in Sri Lanka Clinical Trial Registry (Registration no - SLCTR/2020/025). Administrative approval was obtained by all relevant authorities (District Secretariate Galle District, Provincial Ministry of Local Government, Regional Director of Health Services – Galle District). Informed written consent was obtained from all office workers prior to data collection. Workers identified with problems were referred to Teaching Hospital Karapitiya, Base Hospital Udugama, Elpitiya or Balapitiya.

Study was conducted while adhering to the World Medical Association Declaration of Helsinki on ethical principles for medical research involving human subjects.

One hundred and twenty-three participants who were in preparation, action and maintenance stages of TTM was invited to have either mobile application or paper-based intervention and the response rate was 100%. Mean age of the sample was 40 years (SD 8.04) and median age was 39 (IQR 14). A vast majority had educated up to G. C. E. advanced level or higher, majority were married and most of them were from clerical and supportive workers group where the category if DOs and MAs belongs. Table 1 summarizes socio-demographic characteristics of the study sample.

Table 1

Socio-demographic characteristics of the study sample
Characteristic	Number	Percentage
Sex
Male	25	24.4
Female	98	75.6
Education
Grade 6–11	2	1.6
Passed O/L	6	4.9
Passed A/L	42	34.1
Tertiary education	73	59.3
Marital status
Unmarried	24	19.5
Living together	1	0.8
Married	96	78
Divorced	2	1.6
Current post
Managerial	17	13.8
Professionals	2	1.6
Technical and associate officers	12	9.8
Clerical and supportive worker	92	74.8
Number of children
No children	37	30.1
1	26	21.1
2	39	31.7
3	17	13.8
4	4	3.3
Travel time
Less than 30 minutes	57	46.3
30 minutes – 1hour	50	40.7
More than 1 hour	16	13
Travel method
Walking	3	2.4
Public transport	65	52.8
Private vehicle (own/shared)	55	44.7

Acceptance of the intervention

Majority of the sample (99/123, 80.5%) has preferred the paper-based intervention while (24/123) 19.5% preferred mobile application. Younger age, being unmarried and not having children were associated with acceptance of mobile application over the paper-based intervention. Table 2 summarizes factors associated with the acceptance of mobile application as the method of intervention.

Table 2

Factors associated with the acceptance of mobile application
Characteristic	Mobile application accepted Number (%)	Mobile application not accepted Number (%)	Chi square value	p value
Sex
Male	4 (16.0)	21 (84.0)	0.25	0.62
Female	20 (20.4)	78 (79.6)
Having tertiary education
Yes	18 (24.7)	55 (75.3)	3.03	0.08
No	6 (12.0)	44 (88.0)
Married
Yes	14 (14.1)	85 (85.9)	9.32	0.02
No	10 (41.7)	14 (58.3)
Post held
DO/ MA	19 (20.7)	73 (79.3)	0.30	0.58
Other categories	5 (16.1)	26 (83.9)
Having children
Yes	11 (12.8)	75 (87.2)	8.22	0.04
No	13 (35.1)	24 (35.1)
Travel time
Less than 30 minutes	11 (19.3)	46 (80.7)	0.70	0.71
30 minutes – 1hour	11 (22.0)	39 (88.0)
More than 1 hour	2 (12.5)	14 (87.5)
Travel method
Walking	0 (0.0)	3 (100.0)	4.17	0.13
Public transport	9 (13.8)	56 (86.2)
Private vehicle (own/shared)	15 (27.3)	40 (72.7)
Age
Mean (SD)*	34.3 (7.3)	41.0 (7.6)	-	< 0.001
*Independent sample t-test used to compare mean age between two groups

Figure 1 illustrates flow of participants at different levels of the intervention.

Adherence and outcome of the intervention

Adherence to the intervention was higher in all three months (75.6%, 77.2% and 81.3% respectively). Method of intervention (mobile application or paper-based) was not associated significantly with adherence in any month. Though majority (67.5%) has not achieved a progressive change in stage of change, nearly half of the whole intervention group (47.2%) has achieved a change to healthy dietary intake. But none of the adherence or outcomes showed a significant association with mode of intervention. Table 3 summarizes associations of adherence and outcomes with the mode of intervention.

Table 3

**Associations of adherence and outcomes with the mode of intervention**.
Adherence/ Outcome	Mobile application Number (%)	Paper based intervention Number (%)	Chi square value	p value
Adherence I
Yes	16 (17.2)	77 (82.8)	1.30	0.26
No	8 (26.7)	22 (73.3)
Adherence II
Yes	16 (16.8)	79 (83.2)	1.90	0.17
No	8 (28.6)	20 (71.4)
Adherence III
Yes	20 (20.0)	80 (80.0)	0.80	0.78
No	4 (17.4)	19 (82.6)
Progressive change in stage of change
Yes	7 (17.5)	33 (82.5)	0.15	0.70
No	17 (20.5)	66 (79.5)
Change to a healthy diet
Yes	12 (20.7)	46 (79.3)	0.10	0.76
No	12 (18.5)	53 (81.5)

Most of the sample characteristics were compatible with data from the labour force data except in the gender distribution. Labour force data report has also highlighted that composition of the work force will change sector to sector as well as office to office (22). Further gender distribution of the current study is compatible with a previous study conducted in an office setup (23).

Acceptance of the mobile application was low (19.5%) among office workers despite higher computer literacy (70%) and internet using (56%) among office workers. Further acceptance of mobile application was associated with younger age, not having children and unmarried state. This clearly shows that mobile application was more accepted among young workers who have had experience in mobile applications. According to a report from the department of census and statistics digital literacy is higher among young population and reduced among older population (29). However, the older people have preferred the paper-based intervention as they have not been exposed much to mobile applications.

None of the adherence or outcome related factors was associated with the acceptance of mobile application as the intervention. This can be due to selection bias as participants were allowed to use the method of intervention they want. As they have chosen the method that is more comfortable for them adherence has been good. However, even though all the participants were in a stage of planning or having healthy diet, achievement of intended outcome was not high. There are other factors that can influence a behavioural change contributing to this controversy.

Strengths and limitations

The study sample is representing whole district and generalization of the study finding is more accurate. The study design of non-randomized experimental trials contained it inherent drawbacks as the inability to give a clear comparison between two groups.

Mobile applications-based interventions can reach the younger generation and it can be used to achieve behaviour changes. Study recommends further studies to explore the possibility and effectiveness of mobile health interventions.

Ethics approval and consent to participate

Authors declare that Ethical approval for the study was obtained from the Ethical Review Committee, Faculty of Medicine, University of Ruhuna (Registration no. - 2020/P/105) and the trial was registered in Sri Lanka Clinical Trial Registry (Registration no - SLCTR/2020/025). Administrative approval was obtained by all relevant authorities (District Secretariate Galle District, Provincial Ministry of Local Government, Regional Director of Health Services – Galle District). Informed written consent was obtained from all office workers prior to data collection. Workers identified with problems were referred to Teaching Hospital Karapitiya, Base Hospital Udugama, Elpitiya or Balapitiya Study was conducted while adhering to the World Medical Association Declaration of Helsinki on ethical principles for medical research involving human subjects.

Consent for publication

In the current study consent for publication is not applicable because no individual level data with identification was not included in the manuscript.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the following link, https://drive.google.com/drive/folders/1LQZnbvIT7uoc0AcTsYi52bO-3FM2v2br?usp=sharing with permission from the corresponding author on request.

Competing interests

The authors declare that they have no competing interests.

Funding

The study has been self-funded by the corresponding author.

Authors' contributions

As for author contribution CW and SW was involved in technical guidance and supervising the research project while JG did the planning the research project, data collection analysis and report writing.

Authors acknowledge District Secretary – Galle District and Chief Secretary – Sothern Province for granting administrative approval for the study and all Divisional Secretaries and Heads of local authorities for supporting the project. Dr Rajith Hathamuna and Mr. Kasun Vithanage are acknowledged for technical support for computer and mobile application creation and operationalization. Dr Sithara Kulathunga, Dr Sulekha Peellage and Dr Isuri Sandunika are acknowledged for their contribution in data collection.

Roth GA, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet [Internet]. 2018 Nov 10 [cited 2022 Jan 31];392(10159):1736. Available from: /pmc/articles/PMC6227606/
Hay SI, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, et al. Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet [Internet]. 2017 Sep 16 [cited 2022 Jan 31];390(10100):1260. Available from: /pmc/articles/PMC5605707/
Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet [Internet]. 2019 May 11 [cited 2022 Feb 1];393(10184):1958. Available from: /pmc/articles/PMC6899507/
Institute for Health Metrics and Evaluation. Sri Lanka Institute for Health Metrics and Evaluation [Internet]. 2020 [cited 2022 Feb 7]. Available from: https://www.healthdata.org/sri-lanka
Ministry of Health Nutrition and Indigenous Medicine. Non Communicable Disease Risk Factor Survey Sri Lanka 2015 [Internet]. 1st ed. Colombo: Ministry of Health, Nutrition and Indigeneous Medicine; 2017. Available from: https://www.who.int/ncds/surveillance/steps/STEPS-report-2015-Sri-Lanka.pdf
Swann C, Carmona C, Ryan M, Raynor M, Barış E, Dunsdon S, et al. Health systems and health-related behaviour change: a review of primary and secondary evidence. Citeseer [Internet]. 2010 [cited 2022 Jul 27]; Available from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.302.2422&rep=rep1&type=pdf
Davis R, Campbell R, Hildon Z, Hobbs L, Michie S. Theories of behaviour and behaviour change across the social and behavioural sciences: a scoping review. Health Psychol Rev [Internet]. 2015 Aug 7 [cited 2022 Feb 12];9(3):323. Available from: /pmc/articles/PMC4566873/
Coleman MT, Pasternak RH. Effective strategies for behavior change. Prim Care [Internet]. 2012 Jun [cited 2022 Mar 4];39(2):281–305. Available from: https://pubmed.ncbi.nlm.nih.gov/22608867/
Spahn JM, Reeves RS, Keim KS, Laquatra I, Kellogg M, Jortberg B, et al. State of the evidence regarding behavior change theories and strategies in nutrition counseling to facilitate health and food behavior change. J Am Diet Assoc [Internet]. 2010 Jun [cited 2022 Feb 10];110(6):879–91. Available from: https://pubmed.ncbi.nlm.nih.gov/20497777/
Hashemzadeh M, Rahimi A, Zare-Farashbandi F, Alavi-Naeini A, Daei A. Transtheoretical Model of Health Behavioral Change: A Systematic Review. Iran J Nurs Midwifery Res [Internet]. 2019 Mar 1 [cited 2022 Feb 11];24(2):83. Available from: /pmc/articles/PMC6390443/
Nakabayashi J, Melo GR isa, Toral N. Transtheoretical model-based nutritional interventions in adolescents: a systematic review. BMC Public Health [Internet]. 2020 Dec 1 [cited 2022 Feb 15];20(1). Available from: https://pubmed.ncbi.nlm.nih.gov/33054748/
Samdal GB, Eide GE, Barth T, Williams G, Meland E. Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses. Int J Behav Nutr Phys Act [Internet]. 2017 Mar 28 [cited 2022 Mar 16];14(1):42. Available from: /pmc/articles/PMC5370453/
Cradock KA, ÓLaighin G, Finucane FM, Gainforth HL, Quinlan LR, Ginis KAM. Behaviour change techniques targeting both diet and physical activity in type 2 diabetes: A systematic review and meta-analysis. Int J Behav Nutr Phys Act [Internet]. 2017 Feb 8 [cited 2022 Mar 16];14(1). Available from: /pmc/articles/PMC5299734/
Hartmann-Boyce J, Johns DJ, Jebb SA, Aveyard P, Ogden J, Onakpoya I, et al. Effect of behavioural techniques and delivery mode on effectiveness of weight management: systematic review, meta-analysis and meta-regression. Obesity Reviews [Internet]. 2014 [cited 2022 Mar 16];15(7):598. Available from: /pmc/articles/PMC4237119/
Lee M, Lee H, Kim Y, Kim J, Cho M, Jang J, et al. Mobile App-Based Health Promotion Programs: A Systematic Review of the Literature. Int J Environ Res Public Health [Internet]. 2018 Dec 13 [cited 2023 May 5];15(12). Available from: /pmc/articles/PMC6313530/
DiFilippo KN, Huang WH, Andrade JE, Chapman-Novakofski KM. The use of mobile apps to improve nutrition outcomes: A systematic literature review. J Telemed Telecare [Internet]. 2015 Jul 11 [cited 2023 May 5];21(5):243–53. Available from: https://pubmed.ncbi.nlm.nih.gov/25680388/
Schoeppe S, Alley S, Rebar AL, Hayman M, Bray NA, Van Lippevelde W, et al. Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques. Int J Behav Nutr Phys Act [Internet]. 2017 Jun 24 [cited 2023 May 5];14(1). Available from: /pmc/articles/PMC5483249/
Schoeppe S, Alley S, Rebar AL, Hayman M, Bray NA, Van Lippevelde W, et al. Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques. Int J Behav Nutr Phys Act [Internet]. 2017 Jun 24 [cited 2023 May 5];14(1). Available from: /pmc/articles/PMC5483249/
Patel ML, Hopkins CM, Brooks TL, Bennett GG. Comparing Self-Monitoring Strategies for Weight Loss in a Smartphone App: Randomized Controlled Trial. JMIR Mhealth Uhealth [Internet]. 2019 Feb 1 [cited 2023 May 5];7(2). Available from: /pmc/articles/PMC6416539/
Lieffers JRL, Hanning RM. Dietary assessment and self-monitoring with nutrition applications for mobile devices. Can J Diet Pract Res [Internet]. 2012 Sep [cited 2023 May 5];73(3). Available from: https://pubmed.ncbi.nlm.nih.gov/22958633/
Department of Census, Statistics. labour force data [Internet]. Department of Census and Statistics, Battaramulla: Department of Census and Statistics; 2020. Available from: http://www.statistics.gov.lk/samplesurvey/LFS_Annual%20Report_2017.pdf
Department of Census, Statistics. Census of Public and Semi Government Sector Employment – 2016. Department of Census and Statistics, Ministry of National Policies and Economic Affairs; 2016.
Swarnamali AKSH, Jayasinghe MVTN, Katulanda P. IDENTIFICATION OF RISK FACTORS FOR SELECTED NON COMMUNICABLE DISEASES AMONG PUBLIC SECTOR OFFICE EMPLOYEES, SRI LANKA. Lijhls [Internet]. 2017 May;1(2):12–24. Available from: https://grdspublishing.org/index.php/life/article/view/26
Chandrasiri A, Dissanayake A, De Silva V. Health promotion in workplaces strategy for modification of risk factors for Non Communicable Diseases (NCDs): A practical example from Sri Lanka. Work. 2016 Jan 1;55(2):281–4.
Telecommunication Regulatory Commission of Sri Lanka. Telecommunication Regulatory Commission of Sri Lanka - Annual Report 2020. 2021.
Perera A, Wattegama Ch. Seven new facts we learnt about mobile and internet use in Sri Lanka. Daily FT [Internet]. 2019 Jul 5 [cited 2023 May 3]; Available from: https://www.ft.lk/Columnists/Seven-new-facts-we-learnt-about-mobile-and-internet-use-in-Sri-Lanka/4-681306
Tolonen Hanna, editor. EHES Manual. Part B. Fieldwork procedures. 2nd ed. National Institute for Health and Welfare; 2016.
Nutrition Division Ministry of Health. Food Based Dietary guidelines for Sri Lankans. 2nd ed. Nutrition Division Ministry of Health; 2011.
Department of Census and Statistics. Computer Literacy Statistics 2021 [Internet]. Colombo; 2021 [cited 2023 May 18]. Available from: http://www.statistics.gov.lk/ComputerLiteracy/StaticalInformation/Bulletins/2021-Annual

No competing interests reported.

Download PDF

Editorial decision: Major revision
14 Sep, 2023
Editor assigned by journal
14 Sep, 2023
Submission checks completed at journal
13 Sep, 2023
First submitted to journal
10 Sep, 2023

You are reading this latest preprint version

Paper based and mobile application based self-monitoring tool for healthy dietary intake, Development and Applicability: A non-randomized trial

Status:

Version 1

Abstract

Figures

Background

Methods

Study setting

Study population

Sample size sampling

Data collection and data collection tools

Intervention

Statistical analysis

Ethical and administrative clearance

Results

Acceptance of the intervention

Adherence and outcome of the intervention

Discussion

Strengths and limitations

Conclusion and recommendations

Declarations

References

Additional Declarations

Status:

Version 1