Designing for interrupted reading.

Fast, fragmented, contextual

Mobile news consumption is fast, fragmented and highly dependent on context. Users may read deeply when time allows, but often engage with content in short, interrupted moments throughout the day.

This project explores how a mobile news experience can better support both immediate and time-constrained reading behaviours by improving content structure, enabling users to resume articles after interruption, and guiding them toward what to read next. Using The Journal app as a case study, I analysed the current experience and designed a set of improvements focused on continuity, discoverability and engagement.

How The Journal works today

The Journal app delivers breaking news through a continuously updating "Latest" feed, prioritising speed and recency of content.

Articles are presented in chronological order, and while content is tagged by topic, navigation is largely driven by recency rather than structured browsing or reading continuity.

As a result, the app is effective at delivering news quickly, but does not support how users actually read it, particularly when sessions are interrupted or when users are deciding what to read next.

Optimised for recency, not consumption

The "Latest" feed presents a continuous stream of articles with minimal structure, making it difficult for users to scan, prioritise or re-find content. While this ensures up-to-date coverage, it does not support how users browse under different time constraints.

At the same time, key behaviours such as saving articles, resuming reading and continuing into new content are either unsupported or weakly surfaced.

The app does not provide a way to save articles for later, meaning users must rely on memory to return to content they're interested in. Tag-based navigation allows exploring related topics, but requires deliberate interaction and isn't positioned as part of a clear continuation flow.

As a result, users are left to decide what to do next without clear guidance, increasing the likelihood that sessions end prematurely.

Survey, interviews & usability testing

To understand how users engage with mobile news, I combined qualitative and evaluative methods: a survey (10 participants) on general reading habits; interviews (4 users) to explore behaviour in depth; usability testing (3 sessions) on key tasks in The Journal app; and a competitive analysis of BBC, RTÉ and The Irish Times.

Survey insights, users consistently reported reading in short sessions throughout the day, being interrupted mid-article, forgetting to return to articles they intended to finish, and seeing value in saving content but lacking support for it in some apps.

Interviews, behaviour varied by context: when users had time they read immediately; when time was limited they scanned headlines and deferred reading. Without a way to capture intent or return easily, those articles were often lost.

Usability testing, across three tasks (finding an article, returning to a previously viewed article, and continuing after finishing one) users struggled to re-find previously viewed content, found the chronological feed hard to scan and prioritise, had no clear way to continue after an article, and relied on manual scrolling or memory rather than system support.

Grounding the findings

To synthesise findings, I organised observations into an affinity diagram, grouping insights across reading behaviour, interruptions and context, scanning behaviour, intent and saving, and navigation and structure.

This helped identify repeated behavioural patterns and ensured design decisions were grounded in consistent evidence rather than isolated observations.

Six patterns that shaped the design

01, Reading sessions are frequently interrupted. Users begin with the intention to finish but are interrupted by real-world context; without a reliable way to resume, articles are abandoned.

02, Reading behaviour depends on available time. Users switch between scanning and reading depending on context, and without a way to capture intent, deferred content is often lost.

03, The feed does not support efficient scanning. A purely chronological list makes it hard to assess relevance or priority quickly.

04, Users lack a reliable way to return to content. Without saving or automatic tracking, they rely on memory or manual scrolling to re-find articles.

05, There is no clear path for what to read next. Tags restrict continuation to similar topics; broader pathways like trending or latest aren't surfaced.

06, Sessions often end after a single article. Due to lack of guidance and friction in discovery, many users don't continue even when willing to.

Aoife, 29, office worker in Dublin

Aoife reads the news in short, in-between moments throughout her day, typically during her commute or while waiting. These sessions are rarely uninterrupted, often cut short by arriving at her stop, notifications, or needing to switch attention quickly.

She frequently starts articles intending to finish them later, but without a clear way to track progress or return to where she left off, many are abandoned.

Frustrations, losing her place when interrupted; not knowing how long an article will take; dropping off mid-article and not returning; forgetting or losing track of articles she meant to finish.

Goals, stay informed quickly during limited windows; dip into longer articles when time allows; easily return to unfinished content.

Where the current experience breaks

1. Opens app, quickly scans headlines to find something relevant. 2. Starts reading an article, engages, but is unsure how long it will take. 3. Gets interrupted, stops due to external factors (e.g. the commute ending).

4. Attempts to return, has no clear way to resume from where she left off. 5. Drops off, either abandons the article or restarts and loses context.

The breakdown: interruption leads directly to drop-off.

Principles & focus areas

Design principles, design for interruption, not ideal reading conditions; reduce reliance on memory; support both scanning and deep reading; surface next steps at natural decision points.

I focused on improving the experience across three key areas: (1) reading continuity, (2) feed structure and intent capture, and (3) content continuation.

Testing structure before detail

These sketches explore different ways of addressing the key issues, reading continuity, content discovery and navigation clarity. I focused on quickly testing structural ideas rather than visual detail: how users might resume reading, move between articles, and discover more after finishing one.

Several directions were explored, such as integrating "Continue Reading" into the main feed versus a dedicated space, and different approaches to progressing between articles. These explorations identified which patterns felt intuitive before moving into refined wireframes.

Refining layout & hierarchy

The wireframes refine layout, hierarchy and interaction patterns based on the most promising concepts. Key decisions: separating "Continue Reading" into its own dedicated space to support interrupted sessions; simplifying the main feed to improve scanning; and introducing clearer pathways for continuing into new content.

The article experience was refined for longer reading sessions, clearer metadata, improved hierarchy, and a vertical progress indicator to help users understand their position within an article. The focus was ensuring the structure supported both quick scanning and deeper reading while reducing friction in moving between articles.

Feed improvements

The existing feed is difficult to scan and doesn't support quick decision-making or capturing intent.

Key decisions, clear section hierarchy improves scannability and helps users understand content structure; visual grouping reduces the cognitive load of scanning a continuous list; and articles can be saved directly from the feed, supporting quick, low-commitment decisions.

Outcome, users can more easily identify relevant content and capture articles to return to later. (After, left; before, right.)

Reading continuity

Users are frequently interrupted mid-article and have no reliable way to return, leading to abandoned sessions.

Key decisions, in-progress articles are surfaced automatically, removing the need to manually save; a progress indicator reflects how much has been read; reading position is preserved so users resume exactly where they left off; and progress is based on editorial content only, excluding content beneath the article.

Outcome, users can seamlessly resume articles without relying on memory or manual navigation.

Content continuation

After finishing an article, users aren't clearly guided toward what to read next, leading to session drop-off.

Key decisions, a recommended category ("In this section", "Most read", "Latest") at the end of an article provides different ways to continue; content is surfaced at the natural end of reading; familiar patterns (e.g. swipe to next article) make continuation intuitive; and tag-based exploration is retained but no longer the primary mechanism.

Outcome, encourages multi-article sessions and reduces drop-off after a single read. (Before, left; after, right.)

A supportive reading system

The redesigned experience shifts the app from a passive feed into a more supportive reading system: users can resume articles after interruption, content is easier to scan and navigate, articles can be saved without friction, and users are guided toward what to read next.

This reduces reliance on memory, shortens the time to resume reading, and creates clearer pathways for continued engagement.

What I'd do next

Designing for both scanning and reading required balancing different behaviours depending on time and context. A key challenge was supporting interruption without introducing additional complexity or requiring user effort. I also explored horizontal interaction patterns early on, but removed them in favour of more familiar vertical structures to align with user expectations in news apps.

Given more time, I'd validate the continuation patterns and placement decisions through further usability testing.

Where it goes from here

Personalised recommendations based on reading behaviour; offline reading support; and smarter notifications for saved or partially read content.