Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability

Abstract Background Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection platform was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal. Methods Mothers (15–25 years old) with infants (< 12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews were conducted to understand mothers’ experiences and perceptions of passive data collection. Results Of the 782 women approached, 320 met eligibility criteria and 38 mothers (11 depressed, 27 non-depressed) were enrolled. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Across all participants, 5,579 of the hour-long data collection windows had at least one audio recording [mean (M) = 57.4% of the total possible hour-long recording windows per participant; median (Mdn) = 62.6%], 5,001 activity readings (M = 50.6%; Mdn = 63.2%), 4,168 proximity readings (M = 41.1%; Mdn = 47.6%), and 3,482 GPS readings (M = 35.4%; Mdn = 39.2%). Feasibility challenges were phone battery charging, data usage exceeding prepaid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors increasing acceptability and reducing gaps in data collection. Conclusion Per sensor type, approximately half of the hour-long collection windows had at least one reading. Feasibility challenges for passive sensing on mobile devices can be addressed by providing alternative phone charging options, reverse billing for the app, and replacing mobile phones with smartwatches. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration International Registered Report Identifier (IRRID): DERR1-10.2196/14734

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Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability

10.21203/rs.3.rs-22755/v2 ◽

2020 ◽

Author(s):

Sujen Man Maharjan ◽

Anubhuti Poudyal ◽

Alastair van Heerden ◽

Prabin Byanjankar ◽

Ada Thapa ◽

...

Keyword(s):

Data Collection ◽

Health Services ◽

Mobile Devices ◽

Family Involvement ◽

Mobile Phones ◽

Young Mothers ◽

Low Resource Settings ◽

Low Resource ◽

Passive Sensing ◽

Passive Data

Abstract Background: Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal.Methods: Mothers (15-25 years old) with infants (<12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews (n=31) were conducted to understand mothers’ experiences and perceptions of passive data collection. Results: 782 women were approached and 320 met eligibility criteria. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Of 9,605 possible readings per sensor, 5,579 audio recordings [mean (M)=57.4%; median (Mdn)=62.6%], 5,001 activity readings (M=50.6%; Mdn=63.2%), 4,168 proximity readings (M=41.1%; Mdn=47.6%), and 3,482 GPS readings (M=35.4%; Mdn=39.2%) were obtained. Feasibility challenges were phone battery charging, data usage exceeding pre-paid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors to increase acceptability and reduce gaps in data collection. Conclusion: Approximately half of all possible passive data readings were collected. Feasibility challenges can be addressed by providing alternative phone charging options, setting up reverse billing for the app, and exploring smartwatches as a replacement for mobile phones. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration: International Registered Report Identifier (IRRID): DERR1-10.2196/14734

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Passive Sensing Data Collection with Adolescent Mothers and Their Infants to Improve Mental Health Services in Low-Resource Settings: A Feasibility and Acceptability Study in Rural Nepal

10.21203/rs.3.rs-22755/v1 ◽

2020 ◽

Author(s):

Sujen Man Maharjan ◽

Anubhuti Poudyal ◽

Alastair van Heerden ◽

Prabin Byanjankar ◽

Ada Thapa ◽

...

Keyword(s):

Data Collection ◽

Health Services ◽

Family Involvement ◽

Mobile Phones ◽

Qualitative Interviews ◽

Low Resource Settings ◽

Sensing Data ◽

Passive Sensing ◽

Passive Data ◽

Rural Nepal

Abstract Background: Passive sensor data from mobile phones can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. Our Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) study assessed feasibility and acceptability of passive data collection with young mothers, including mothers experiencing postpartum depression, in rural Nepal.Methods: Mothers between 15-25 years of age with infants less than 12 months old were recruited from vaccination clinics in rural Nepal. They were provided with a mobile smartphone and passive Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. End-line qualitative interviews (n=31) were conducted to understand mothers’ experiences and perceptions of passive data collection.Results: 782 women were approached and 320 met eligibility criteria. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Of 9,602 possible readings per sensor, 57.4% of audio (5,579 recordings), 50.6% of activity (5,001 readings), 41.1% of proximity (4,168 readings), and 35.4% of GPS (3,482 readings) were obtained. The percentage of data collection was comparable for depressed and non-depressed mothers. Qualitative interviews revealed mobile charging, excessive data usage, and burden of carrying mobile phones as feasibility challenges. Concerns for privacy and family involvement were acceptability challenges. Overall, study team engagement and education of family members on technology contributed to mothers’ comfort participating in passive data collection. Conclusion: Approximately half of all possible passive data were collected. Feasibility challenges can be addressed by providing alternative phone charging options, setting up reverse billing for the app, and exploring smartwatches as replacement for mobile phones. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing data collection for psychological treatments and other health services. Registration: International Registered Report Identifier (IRRID): DERR1-10.2196/14734

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Procedures to Select Digital Sensing Technologies for Passive Data Collection With Children and Their Caregivers: Qualitative Cultural Assessment in South Africa and Nepal (Preprint)

10.2196/preprints.12366 ◽

2018 ◽

Author(s):

Brandon A Kohrt ◽

Sauharda Rai ◽

Khanya Vilakazi ◽

Kiran Thapa ◽

Anvita Bhardwaj ◽

...

Keyword(s):

South Africa ◽

Data Collection ◽

Community Health ◽

Health Workers ◽

Time Lapse ◽

Home Based ◽

Passive Sensing ◽

Passive Data ◽

Environmental Sensor ◽

Cultural Assessment

BACKGROUND Populations in low-resource settings with high childhood morbidity and mortality increasingly are being selected as beneficiaries for interventions using passive sensing data collection through digital technologies. However, these populations often have limited familiarity with the processes and implications of passive data collection. Therefore, methods are needed to identify cultural norms and family preferences influencing the uptake of new technologies. OBJECTIVE Before introducing a new device or a passive data collection approach, it is important to determine what will be culturally acceptable and feasible. The objective of this study was to develop a systematic approach to determine acceptability and perceived utility of potential passive data collection technologies to inform selection and piloting of a device. To achieve this, we developed the Qualitative Cultural Assessment of Passive Data collection Technology (QualCAPDT). This approach is built upon structured elicitation tasks used in cultural anthropology. METHODS We piloted QualCAPDT using focus group discussions (FGDs), video demonstrations of simulated technology use, attribute rating with anchoring vignettes, and card ranking procedures. The procedure was used to select passive sensing technologies to evaluate child development and caregiver mental health in KwaZulu-Natal, South Africa, and Kathmandu, Nepal. Videos were produced in South Africa and Nepal to demonstrate the technologies and their potential local application. Structured elicitation tasks were administered in FGDs after showing the videos. Using QualCAPDT, we evaluated the following 5 technologies: home-based video recording, mobile device capture of audio, a wearable time-lapse camera attached to the child, proximity detection through a wearable passive Bluetooth beacon attached to the child, and an indoor environmental sensor measuring air quality. RESULTS In South Africa, 38 community health workers, health organization leaders, and caregivers participated in interviews and FGDs with structured elicitation tasks. We refined the procedure after South Africa to make the process more accessible for low-literacy populations in Nepal. In addition, the refined procedure reduced misconceptions about the tools being evaluated. In Nepal, 69 community health workers and caregivers participated in a refined QualCAPDT. In both countries, the child’s wearable time-lapse camera achieved many of the target attributes. Participants in Nepal also highly ranked a home-based environmental sensor and a proximity beacon worn by the child. CONCLUSIONS The QualCAPDT procedure can be used to identify community norms and preferences to facilitate the selection of potential passive data collection strategies and devices. QualCAPDT is an important first step before selecting devices and piloting passive data collection in a community. It is especially important for work with caregivers and young children for whom cultural beliefs and shared family environments strongly determine behavior and potential uptake of new technology.

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What Does Social Support Sound Like? Challenges and Opportunities for Using Passive Episodic Audio Collection to Assess the Social Environment

Frontiers in Public Health ◽

10.3389/fpubh.2021.633606 ◽

2021 ◽

Vol 9 ◽

Cited By ~ 1

Author(s):

Anubhuti Poudyal ◽

Alastair van Heerden ◽

Ashley Hagaman ◽

Celia Islam ◽

Ada Thapa ◽

...

Keyword(s):

Mental Health ◽

Social Support ◽

Data Collection ◽

Social Interactions ◽

Social Environment ◽

Mobile Phones ◽

Qualitative Interviews ◽

Young Mothers ◽

The Social ◽

Audio Data

Background: The social environment, comprised of social support, social burden, and quality of interactions, influences a range of health outcomes, including mental health. Passive audio data collection on mobile phones (e.g., episodic recording of the auditory environment without requiring any active input from the phone user) enables new opportunities to understand the social environment. We evaluated the use of passive audio collection on mobile phones as a window into the social environment while conducting a study of mental health among adolescent and young mothers in Nepal.Methods: We enrolled 23 adolescent and young mothers who first participated in qualitative interviews to describe their social support and identify sounds potentially associated with that support. Then, episodic recordings were collected for 2 weeks from the mothers using an app to record 30 s of audio every 15 min from 4 A.M. to 9 P.M. Audio data were processed and classified using a pretrained model. Each classification category was accompanied by an estimated accuracy score. Manual validation of the machine-predicted speech and non-speech categories was done for accuracy.Results: In qualitative interviews, mothers described a range of positive and negative social interactions and the sounds that accompanied these. Potential positive sounds included adult speech and laughter, infant babbling and laughter, and sounds from baby toys. Sounds characterizing negative stimuli included yelling, crying, screaming by adults and crying by infants. Sounds associated with social isolation included silence and TV or radio noises. Speech comprised 43% of all passively recorded audio clips (n = 7,725). Manual validation showed a 23% false positive rate and 62% false-negative rate for speech, demonstrating potential underestimation of speech exposure. Other common sounds were music and vehicular noises.Conclusions: Passively capturing audio has the potential to improve understanding of the social environment. However, a pre-trained model had the limited accuracy for identifying speech and lacked categories allowing distinction between positive and negative social interactions. To improve the contribution of passive audio collection to understanding the social environment, future work should improve the accuracy of audio categorization, code for constellations of sounds, and combine audio with other smartphone data collection such as location and activity.

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Smart Phones As a Viable Data Collection Tool in Low-resource Settings: Case Study of Rwandan Community Health Workers

Neuroscience and Biomedical Engineering ◽

10.2174/2213385204666160711155116 ◽

2016 ◽

Vol 4 (2) ◽

pp. 132-139 ◽

Cited By ~ 2

Author(s):

Suzana Brown ◽

Alan Mickelson

Keyword(s):

Data Collection ◽

Community Health ◽

Community Health Workers ◽

Health Workers ◽

Smart Phones ◽

Data Collection Tool ◽

Low Resource Settings ◽

Low Resource

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Habilidades do Enfermeiro no Diagnóstico e Cuidado ao Portador de Depressão / Nursing Skills in Diagnosis and Care For Patients With Depression

REVISTA CIÊNCIAS EM SAÚDE ◽

10.21876/rcsfmit.v5i4.402 ◽

1970 ◽

Vol 5 (4) ◽

pp. 13-19

Author(s):

Cristiane Rosa Guedes ◽

Bianca Del Ducca Alvarenga ◽

Isabella Rotella ◽

Débora Vitória Alexandrina Lisboa Vilella

Keyword(s):

Data Collection ◽

Family Involvement ◽

Nursing Care ◽

Direct Contact ◽

Descriptive Study ◽

Structured Interview ◽

Qualitative Approach ◽

Patient Relationship ◽

The Subject ◽

The City

RESUMOObjetivo: Identificar o significado para o enfermeiro em prestar cuidados para pacientes com Depressão. Materiais e métodos: Estudo exploratório e descritivo com abordagem qualitativa, a amostra foi de 12 enfermeiras, o cenário de estudo foram Unidades Básicas de Saúde e Estratégias de Saúde da Família, urbanas da cidade de Itajubá-MG. A coleta de dados foi por meio do roteiro de entrevista semiestruturada composta por questionário contendo uma pergunta inerente ao assunto. Resultados: Encontramos oito categorias como estigma da depressão, suicídio, dificuldade em lidar, tempo escasso, envolvimento familiar, aceitação da doença, acolhimento e dar medicamento, de acordo com os discursos dos sujeitos coletados na entrevista. Conclusão: Os enfermeiros não estão em contato direto com portadores de depressão no seu trabalho, não entendem que é sua tarefa identificar e encaminha-los para tratamento especializado. Sugerimos que outros estudos sejam desenvolvidos sobre essa temática.Palavras-chave: Depressão. Relação Enfermeiro-Paciente. Assistência de Enfermagem. ABSTRACTObjective: To identify the meaning for nurses when providing care for patients with depression. Materials and Methods: exploratory and descriptive study with qualitative approach, the sample consisted of 12 nurses, the study scenario was the urban Unidades Básicas de Saúde e Estrategia de Saúde da Família, in the city of Itajubá. Data collection was done through semi-structured interview guides consisting of a questionnaire containing a question related to the subject. Results and Discussion: we found eight categories as stigma of depression, suicide, coping difficulties, scarce time, family involvement, acceptance of the disease, host and give medicine, according to the speeches of the subjects collected in the interview. Conclusion: nurses are not in direct contact with individuals with depression in their work, do not understand that it is their job to identify and refer them to specialized treatment. We suggest that other studies be developed on this theme.Keywords: Depression, Nurse-patient Relationship, Nursing care.

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Conducting Population Health Research during the COVID-19 Pandemic: Impacts and Recommendations

Sustainability ◽

10.3390/su13063320 ◽

2021 ◽

Vol 13 (6) ◽

pp. 3320

Author(s):

Amy R. Villarosa ◽

Lucie M. Ramjan ◽

Della Maneze ◽

Ajesh George

Keyword(s):

Data Collection ◽

Health Services ◽

Data Quality ◽

Population Health ◽

Health Research ◽

Alternative Methods ◽

Residential Aged Care ◽

Recruitment Methods ◽

Face To Face ◽

The Impact

The COVID-19 pandemic has resulted in many changes, including restrictions on indoor gatherings and visitation to residential aged care facilities, hospitals and certain communities. Coupled with potential restrictions imposed by health services and academic institutions, these changes may significantly impact the conduct of population health research. However, the continuance of population health research is beneficial for the provision of health services and sometimes imperative. This paper discusses the impact of COVID-19 restrictions on the conduct of population health research. This discussion unveils important ethical considerations, as well as potential impacts on recruitment methods, face-to-face data collection, data quality and validity. In addition, this paper explores potential recruitment and data collection methods that could replace face-to-face methods. The discussion is accompanied by reflections on the challenges experienced by the authors in their own research at an oral health service during the COVID-19 pandemic and alternative methods that were utilised in place of face-to-face methods. This paper concludes that, although COVID-19 presents challenges to the conduct of population health research, there is a range of alternative methods to face-to-face recruitment and data collection. These alternative methods should be considered in light of project aims to ensure data quality is not compromised.

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Research on the Use of Mobile Devices and Headphones on Pedestrian Crossings—Pilot Case Study from Slovakia

Safety ◽

10.3390/safety7010017 ◽

2021 ◽

Vol 7 (1) ◽

pp. 17

Author(s):

Miroslava Mikusova ◽

Joanna Wachnicka ◽

Joanna Zukowska

Keyword(s):

Mobile Phone ◽

Mobile Devices ◽

Mobile Phones ◽

Slovak Republic ◽

Pedestrian Behavior ◽

The Road ◽

Phone Calls ◽

Lack Of Information ◽

Interaction Factor ◽

Future Work

The topic of the use of mobile devices and headphones on pedestrian crossings is much less explored in comparison to the use of the mobile phone while driving. Recent years have seen many discussions on this issue, especially in foreign countries. The Slovak Republic, however, has not been giving it enough attention (and it is not mentioned in the National Road Safety Plan for the Slovak Republic from 2011 to 2020). This paper aims to draw attention to this issue. It presents basic outputs of a pilot study on pedestrian safety, with a focus on the use of mobile devices and headphones at selected non-signalized pedestrian crossings in three Slovak cities. Overall, 9% of pedestrians used headphones or mobile devices at observed pedestrian crossings (4% of them used headphones, 1% used headphones and at same time used their mobile phone, 2% made phone calls and 2% used their mobile phones). While these numbers can be considered relatively low, the study proved that during weekdays every 2 min someone was using the crossing without fully focusing on crossing the road safely. Another main finding was that although the safety risk at pedestrian crossings is increased by factors such as rush hour traffic or reduced visibility, pedestrian behavior related to the use of mobile phones and headphones does not change. A safety assessment was also carried out at the crossings. The results show that pedestrian behavior is not affected by the level of safety of the crossing (e.g., visibility of the crossing for drivers). The results of the presented analysis suggest that action is needed to change that. Due to the lack of information about accidents involving pedestrians using mobile phones and headsets when crossing the road, no relevant statistical data could be analyzed. The dataset collected can be used as a basis for further investigation or comparisons with other countries of the relevant indicators. In future work, we would like to include a pedestrian–driver interaction factor focusing on driver speed behavior in relation to pedestrians (who are on or are about to step onto a pedestrian crossing) and identify critical situations caused by improper behavior of drivers and/or pedestrians. This will help to understand speed adjustment problems related to pedestrian crossings.

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How to increase the value of self-reported health service data by using data linkage: a case study

European Journal of Public Health ◽

10.1093/eurpub/ckaa165.1279 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

W Peng ◽

J Maguire ◽

A Hayen ◽

J Adams ◽

D Sibbritt

Keyword(s):

Data Collection ◽

Health Service ◽

Health Services ◽

Stroke Prevention ◽

Data Linkage ◽

Recurrent Stroke ◽

Service Planning ◽

Stroke Survivors ◽

Reported Data

Abstract Background This is a case study for recurrent stroke prevention. Lifestyle factors account for about 80% of the risk of recurrent stroke. Most health services studies examining stroke prevention rely on stroke survivors' self-reported lifestyle behaviour data. How can researchers increase the value of collected self-reported data to provide additional information for more comprehensive assessments? Methods 45 and Up Study is the largest ongoing study in the Southern Hemisphere focusing on the health of people aged 45 years and older living in NSW, Australia. This case study linked self-reported longitudinal lifestyle data in the 45 and Up Study, with corresponding mortality data (i.e. NSW Registry of Births, Deaths and Marriages & NSW Cause of Death Unit Record File) and hospital data (i.e. NSW Admitted Patient Data Collection) via the Centre for Health Record Linkage (CHeReL). The main outcome measures are health services, clinical outcomes, and mortality rates for stroke care. The analyses will include descriptive analysis, multivariate regression analysis, and survival analysis. Results A total of 8410 stroke survivors who participated in the 45 and Up Study were included in this data linkage study. From January 2006 to December 2015, 99249 hospital claims (mean: 13 times admission to hospital per person) and 2656 death registration records have been linked to these participants. The mean age of the stroke survivors was 72 (SD = 11) years, with 56% being males. These results are preliminary and more analyses will be conducted by using quality of life status, clinical diagnosis, comorbidities, and procedures. Conclusions Data linkage enables researchers to generate comprehensive findings on health services studies and gain a more holistic understanding of the determinants and outcomes of stroke prevention with lower data collection costs and less burden on participants. Key messages Data linkage brings about a new opportunity for self-reported data on health services utilisation. It is a cost-effective way to enhance existing self-reported data via the data linkage approach to increase its usefulness for informing health service planning.

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