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Table 2 Data extraction table

From: Protocol for a systematic literature review of smartphone apps to support the self-management of rheumatic and musculoskeletal diseases: development strategies, theoretical underpinnings and barriers to engagement

Summary of publication

Name of intervention

 

Study title

 

Author(s)

 

Year

 

DOI or URL

 

Protocol available online? (Provide link)

 

Prior feasibility and pilot testing? Y/N

 

Study design (e.g. RCT, observational, case–control study, feasibility, pilot)

 

Methods (quantitative, qualitative, mixed methods)

 

Aims/purpose of study

 

Location/setting (e.g. country, number of participating centres, primary/secondary care, specialty)

 

Demographics of population

Mean age (SD)

 

Female: # (%)

 

Population: Condition(s)

 

Inclusion/exclusion criteria (copy and paste)

 

Mean duration of symptoms/time since diagnosis

 

Integration of appropriate theory

Has a published/validated development framework been cited? Y/N (if yes, please specify, e.g. intervention mapping, person-based approach, Centre for eHealth Research and Disease Management (CeHRes) development approach)

 

Targeted health behaviour(s)

 

Consideration of motivational/behaviour change theory to promote self-management behaviour? Y/N (if yes, please specify theory used, e.g. self-efficacy theory, self-determination theory, MoVo process model, COM-B model of behaviour)

 

Specification of BCTs utilised and proposed mechanism(s) of action? Y/N (if yes, please list BCTs + corresponding conceptual MoAs; requires conscious acknowledgement of techniques used and conceptual frameworks by which they promote behaviour change, e.g. an app may display autonomy-supportive language, but not have considered how or why this promotes behaviour change, or the motivational framework supporting its use)

 

Consideration of theoretical frameworks to promote app engagement? Y/N (if yes, please specify theory or framework used, e.g. persuasive systems design, self-determination theory-based taxonomy of app features)

 

Intervention development

aTransparency regarding funder

 

aTransparency on data ownership

 

aAdherence to data protection and regulatory frameworks

 

Acknowledgement of alignment with clinical guidelines

 

Stage of development (e.g. pilot/feasibility testing, deployed)

 

Strategies of development (copy overview of methodology if available)

 

aCo-design with patients? Y/N

 

aCo-design with HCPs? Y/N (if yes, please specify professions)

 

Co-design with others? (Y/N) (if yes, please specify, e.g. stakeholder committee, behavioural scientists, HCI researchers)

 

Is any training/education provided to the patients on using the technology?

 

Is any training/education provided to the HCP on using the technology?

 

Self-management intervention content (please specify details, list developed using guidance from EULAR (Nikiphorou et al., 2021) [26] and patient organisations [NASS, NRAS, versus arthritis])

aEvidence-based, up-to-date, scientifically justifiable content

 

Disease education

 

Flare management

 

Coping with pain

 

Coping with fatigue

 

Managing sleep

 

Medication education

 

Medication management (e.g. reminders)

 

Joint decision-making

 

Psychological support (e.g. cognitive behavioural therapy)

 

Mental health assessment

 

Physical activity/ stretching

 

Physiotherapy techniques guided or created by a physiotherapist

 

Occupational health (work-related) guidance

 

Smoking

 

Alcohol intake

 

Nutrition

 

Other lifestyle advice and support (please specify)

 

Social support

 

Clinical action plans

 

Problem-solving

 

Signposting to patient organisations

 

Signposting to advice line/HCP contacts

 

Signposting to other resources (please specify)

 

aTailoring/personalisation

 

Other

 

APP features, according to SDT motivational taxonomy (Villalobos-Zúñiga et al., 2020) — Y/N

Reminders

 

Goal setting

 

Motivational messages

 

Pre-commitment

 

Activity feedback

 

History (e.g. progress graph)

 

Log/self-monitoring

 

Rewards

 

Performance sharing

 

Peer challenging

 

Messaging (peer to peer)

 

Messaging (to HCPs — please specify asynchronous/synchronous + purpose)

 

aCommunication moderation

 

Others (please specify)

 

Operating system (i.e. iOS or Android)

 

Barriers/facilitators to engagement

Barriers to engagement with digital intervention

 

Barriers to engagement with self-management behaviours

 

Facilitators of engagement with digital intervention

 

Facilitators of self-management behaviours

 

Measures of effectiveness

Self-management support measures, e.g. patient activation, self-efficacy

 

What objective outcomes are used (e.g. accelerometer data, spinal mobility?

 

What clinician-reported outcome measures (ClinROs), diaries, or other tools are used?

 

What patient-reported outcome measures (PROMs) are used?

 

What is used to measure intervention adherence?

 

What is used to measure intervention acceptability?

 

What is used to measure intervention usability?

 

At what time points are outcomes assessed?

 

Results/description of effectiveness

Was the intervention effective (qualitative)?

 

Was the intervention effective (quantitative)?

 

Adherence?

 

Acceptability?

 

aUsability? (Across all ages, abilities)

 

aCost-effectiveness?

 

Contextual influences on intervention success (economic factors, available resources, local healthcare system structure) [53]

 

Conclusions, clinical implications, future directions?

 

Limitations (of the intervention)

 

Methodological strengths/limitations for evaluation of effectiveness

Study design

 

Strengths (of the study design)

 

Limitations (of the study design)

 
  1. NASS National Axial Spondyloarthritis Society, NRAS National Rheumatoid Arthritis Society
  2. aFrom EULAR points to consider for the development, evaluation and implementation of mobile health applications aiding self-management in people living with RMDs [31]